What Is Gemini Spark?

Gemini Spark represents Google's vision of a proactive, autonomous AI assistant that can execute workflows spanning multiple apps and services. Unlike the conversational Gemini chatbot, Spark is built to perform tasks with minimal user intervention. It leverages a suite of Connected Apps—including Google Workspace (Gmail, Calendar, Docs, Sheets, Slides, Drive, Keep, Tasks), Search, Personal Intelligence, a remote web browser, code execution capabilities, Canvas, and location data—to accomplish user-defined goals.

The system introduces three core components: Tasks, Skills, and Schedules. A Task is the high-level objective, such as planning a business trip or compiling a report. A Skill is a reusable set of instructions paired with additional context—for example, a "Travel Booking" skill that knows your preferred airlines and hotel chains. A Schedule is an automated trigger based on time or conditions, such as sending a notification when a flight is delayed and proposing an updated itinerary.

Users can have up to 15 tasks running concurrently, and Spark adheres to the same compute-based usage limits that apply to other Gemini features. This design ensures that even complex, multi-step operations remain manageable without overwhelming the system.

Expanded Workspace Integration

Since its debut with AI Ultra, Google has significantly enhanced Spark's integration with its productivity suite. The agent can now interact with Calendar, Gmail, Docs, Sheets, Slides, Drive, Keep, and Tasks in more sophisticated ways. Below are the key capabilities for each service.

Calendar

Spark can manage schedules by checking calendar availability, RSVPing to invitations, and scheduling new events. It can also reschedule meetings, change locations, or cancel events. A smart scheduling feature allows it to check participants' calendars and suggest open slots that fit everyone's availability, reducing the back-and-forth of finding a meeting time.

Gmail

The agent can search across email threads to find specific topics or summarize conversations. It can draft and reply to emails, forward messages, and organize the inbox using labels. This functionality is particularly useful for users who receive a high volume of correspondence and need quick summaries or automated responses.

Docs, Sheets, Slides, and Drive

Spark can search, read, and manage files in Google Drive. It can create, edit, and format documents, spreadsheets, and presentations. For shared documents, users must review and confirm edits before they are applied, ensuring collaborative integrity. The agent can also read comments on documents, spreadsheets, and presentations, and add images from prompts to documents or slides.

Important: To edit shared files, Spark requires explicit user confirmation before changes are made. This safeguard prevents accidental modifications to collaborative work.

Google Keep

The agent can find, retrieve, and create notes and lists within Google Keep. This allows users to quickly capture ideas or retrieve saved information without manually searching through the app.

Google Tasks

Spark can search for reminders and tasks, as well as add, update, and delete them. Notably, the agent can perform bulk actions on private tasks without requiring additional confirmation. Google advises users to carefully review their requests before submitting them to avoid unintended changes.

How Gemini Spark Differs from Other AI Agents

Google's approach with Spark is part of a broader industry trend toward autonomous AI agents. Unlike Microsoft's Copilot, which primarily assists within Office apps, Spark aims to orchestrate workflows across Google's ecosystem and beyond. Its use of Personal Intelligence—which can access user preferences, location, and browsing history—allows it to personalize tasks without constant prompting.

The remote web browser and code execution capabilities enable Spark to interact with websites and run scripts, making it suitable for data extraction, form filling, and other online tasks. The Canvas feature provides a visual workspace for planning and organizing tasks, while location data can trigger location-based automations, such as sending a reminder when leaving a certain area.

Practical Use Cases

Consider a user planning a business trip to London. With Spark, they can create a single Task: "Plan and manage my business trip to London." The agent then breaks this down into subtasks—booking flights, reserving a hotel, creating a schedule of meetings, and preparing travel documents. It can use a Travel Booking skill to search for flights and hotels according to stored preferences, and a Gmail Writing skill to draft confirmation emails. If a flight is delayed, a Schedule will trigger a notification and propose an updated itinerary.

Another example involves monthly reporting. A user can schedule a recurring Task that extracts data from Google Sheets, summarizes it in a Docs report, and emails the PDF to stakeholders—all without manual intervention. The ability to have 15 tasks running simultaneously means users can automate multiple workflows in parallel.

Availability and Future Outlook

Currently, Gemini Spark is available to AI Pro subscribers in the United States via the Gemini web app and mobile apps. Google has not announced pricing changes—Spark is included in the existing AI Pro subscription, which costs $19.99 per month and also provides access to AI Ultra for advanced reasoning. The company has promised broader international availability soon.

Analysts see Spark as a key differentiator for Google's AI offerings, especially as competition heats up with OpenAI's ChatGPT plugins and Microsoft Copilot. By tightly integrating with its own ecosystem and providing robust automation capabilities, Google aims to attract power users who rely heavily on Workspace products. However, the compute-based usage limits may constrain heavy users, and the requirement for explicit confirmation on shared document edits could slow down collaborative workflows.

Looking ahead, Google is expected to continue expanding Spark's skills library and supporting more third-party apps through the Connected Apps framework. The agent may also gain the ability to learn from user feedback and adapt its behavior over time, moving closer to a truly personalized AI assistant. For now, US-based AI Pro subscribers can start experimenting with Spark's task automation, while users in other regions await the global rollout.

Source: 9to5Google News

Lil’ Finder Guy, a small, anthropomorphic figure with a simple rounded body and expressive face, was heavily featured throughout the MacBook Neo campaign. Apple showcased the character in a livestream event and a series of TikTok videos, where it interacted with the laptop’s features and even “measured exactly one apple tall.” The character quickly became an internet sensation, inspiring fan-made artwork, wallpapers, 3D-printable models, and countless memes across social media platforms. Its popularity extended beyond the campaign: an easter egg appearance in a WWDC 2026 session delighted developers, and attendees received custom enamel pins featuring the mascot in their swag bags.

Coelho’s now-deleted post credited the colleagues who worked with her on the campaign, which was shortlisted for a Cannes Lions award. She described leading the character’s visual design and concept as a “dream design project.” The images she shared included studies of Lil’ Finder Guy’s expressions, proportions, and overall shape, alongside what appeared to be an airbrushed physical prototype. These artifacts offer a fascinating look at how Apple’s design team moves from concept to final product, even for a secondary character in a marketing campaign.

Early sketches and prototype

The sketches showed multiple iterations of the character, with subtle changes in head size, eye placement, and limb proportions. Coelho’s work emphasized a friendly, approachable aesthetic that would appeal to a broad audience, from creative professionals to everyday consumers. The physical prototype, likely 3D-printed and hand-painted, allowed the team to test how the character would appear in three dimensions and interact with the MacBook Neo’s design language. This tangible model helped refine the final look that would appear in videos and print materials.

The character’s name, “Lil’ Finder Guy,” is a playful reference to the classic Finder icon on macOS—a smiling face. It also nods to the MacBook Neo’s positioning as a premium, lightweight laptop for power users. By anthropomorphizing the Finder, Apple created an emotional hook that made technical specifications feel more human and relatable. The campaign’s success in generating user-generated content and viral buzz underscores Apple’s ability to blend design, marketing, and cultural relevance.

Behind the scenes of the campaign

According to Coelho’s post, the character’s development was part of a larger push by Apple to engage younger audiences on platforms like TikTok. The MacBook Neo itself was launched as a successor to the MacBook Air, targeting students and freelancers who need portability without sacrificing performance. The campaign featured Lil’ Finder Guy performing everyday tasks—loading apps, organizing files, and even dancing to popular songs—creating a viral loop that boosted the laptop’s visibility. The character’s simplicity made it easy to animate and adapt for multiple platforms, from high-res video to small social media clips.

The Cannes Lions shortlist recognition highlights the campaign’s creative impact. Apple has a history of award-winning advertising, but assigning a human-like personality to a system tool was a fresh approach. Coelho’s team collaborated with Apple’s internal design group, external agency partners, and even the software engineering team to ensure the character’s movements and interactions with macOS were authentic. The result was a cohesive campaign that felt both playful and deeply rooted in Apple’s product identity.

Sofia Coelho’s role at Apple

Sofia Coelho is an accomplished art director who has been with Apple for several years, working on a range of projects from product launch keynotes to retail store visuals. Her portfolio includes work on the iPhone 15 series, the Apple Watch, and various software interfaces. Prior to joining Apple, she held design roles at major tech companies and advertising agencies, where she honed her skills in branding and user experience. Her leadership on the Lil’ Finder Guy project demonstrates her ability to merge whimsy with functional design, a hallmark of Apple’s marketing approach.

The deletion of Coelho’s LinkedIn post on July 24 adds a layer of mystery to the reveal. Apple often keeps its design process under wraps, and internal sharing of behind-the-scenes material is sometimes restricted. It’s possible that the post violated Apple’s social media guidelines or that the company wanted to maintain control over the character’s narrative. Regardless, the images had already been circulated and shared by fans before removal, ensuring that the design community got a rare look at Apple’s creative work.

Lil’ Finder Guy’s cultural impact

Since its debut, Lil’ Finder Guy has become more than just a mascot. It has been featured in fan animations, cosplay at tech conferences, and even parody accounts on social media. Some developers created interactive versions of the character for macOS, while others designed custom wallpapers and icons. The character’s widespread appeal can be attributed to its universal design: a simple, smiley face that transcends language barriers. In an era where brands increasingly use virtual influencers and mascots to connect with audiences, Lil’ Finder Guy stands out for its authenticity and lack of commercial agenda.

The character also appeared in a WWDC 2026 session as a hidden easter egg, surprising attendees who spotted it in a demo of the latest macOS features. Apple later sold limited-edition enamel pins featuring Lil’ Finder Guy at the conference, which quickly sold out. The pins became coveted collectibles, with some appearing on resale platforms at elevated prices. This blend of digital and physical merchandise is a strategy Apple has used before, but the organic viral spread of Lil’ Finder Guy made it particularly effective.

As Apple continues to refine its marketing for new products, the lessons from the MacBook Neo campaign may influence future mascots. The combination of clever design, social media optimization, and a strong emotional hook proved that even a small character can make a big impact. For now, the sketches and prototype shared by Coelho—though now deleted—remain a testament to the creativity and meticulous planning behind one of Apple’s most delightful recent campaigns.

For those interested in the technical side, the character’s proportions were carefully calibrated to match the MacBook Neo’s form factor. In one sketch, notes indicated that Lil’ Finder Guy “measures exactly one apple tall,” a reference to the Apple logo on the laptop’s lid. The prototype’s airbrushed finish gave it a soft, matte appearance that aligned with the laptop’s aluminum body. These details, while small, reflect Apple’s obsession with consistency across products and marketing.

The MacBook Neo itself has been well-received, praised for its lightweight design, improved battery life, and powerful M4 chip. The campaign arguably helped drive sales among younger demographics who appreciated the playful tone. It also reinforced Apple’s image as a company that takes design seriously—even when designing a mascot that looks like a smiling blob. The fact that the post was deleted only adds to the allure, making fans more eager to see what Apple’s design team will dream up next.

Source: 9to5Mac News

OpenAI originally began piloting its ChatGPT Health feature in January 2026. Early feedback reported lackluster results, which likely explains the months-long silence surrounding the feature. Users found that the initial version struggled to provide meaningful insights from health data, leading to limited adoption among the pilot group. However, OpenAI has used this period to refine the system, addressing user concerns and enhancing the underlying AI models.

Today, OpenAI is reintroducing ChatGPT Health and expanding access beyond the initial wave of testers. The new version is available to logged-in ChatGPT users aged 18 and older in the United States, spanning web and iOS platforms across Free, Go, Plus, and Pro plans. Users can begin by selecting “Health” from the sidebar in ChatGPT to activate the feature. This broader rollout signals OpenAI’s commitment to making health-related AI tools more accessible, while also ensuring that user privacy remains a priority.

“Health in ChatGPT is launching to U.S. users,” OpenAI announced. “You can choose to securely connect Apple Health and supported medical records so ChatGPT can help you understand your information in context, keep track of what has changed, and have more informed, personalized conversations.” This emphasis on security and personalization is central to the feature’s redesign, as OpenAI aims to build trust with users who may be hesitant to share sensitive health data.

OpenAI says the new version builds on feedback from the initial round of testing. During the pilot, users expressed a desire for more contextual analysis and clearer comparisons over time. In response, the company has improved ChatGPT’s ability to draw on relevant information from connected health records. “With your permission, ChatGPT can now draw on relevant information you’ve connected in Health to help you compare a new result with prior tests, summarize changes since your last appointment, or explore how sleep, activity, and workouts relate to your routine,” OpenAI adds. This capability transforms raw health data into actionable insights, such as tracking trends in blood pressure, glucose levels, or fitness metrics.

ChatGPT Health should also benefit from OpenAI’s continuous improvement of its frontier models since the start of the year. The company has released several updates to its GPT series, enhancing natural language understanding, reasoning, and data analysis. These improvements allow ChatGPT to process complex health data more accurately and provide more coherent summaries. For instance, the model can now distinguish between normal variations in health metrics and potential anomalies, offering users a clearer picture of their overall well-being.

The feature integrates directly with Apple Health, which aggregates data from the iPhone, Apple Watch, and third-party apps. Users can connect data such as heart rate, steps, sleep patterns, and nutrition, as well as medical records from healthcare providers. By granting ChatGPT access, users can ask questions like “How has my sleep quality changed this month?” or “What might explain the recent increase in resting heart rate?” The AI then generates responses based on the user’s specific data, offering personalized guidance without replacing professional medical advice.

OpenAI has emphasized that the feature is designed to complement, not replace, traditional healthcare. The company advises users to consult with their doctors for medical decisions. Nonetheless, ChatGPT Health aims to empower individuals with a deeper understanding of their health data, potentially improving engagement with wellness routines and chronic condition management. This aligns with broader trends in digital health, where AI is increasingly used to bridge the gap between raw data and actionable knowledge.

The relaunch also comes at a time when OpenAI is expanding its enterprise and consumer offerings. The company has been aggressively pursuing partnerships in healthcare, education, and productivity. By integrating with Apple Health, OpenAI gains a foothold in the consumer health market, which is dominated by Apple’s ecosystem. Apple Health currently supports millions of users worldwide, and the integration allows ChatGPT to tap into this vast user base. However, the feature is limited to the United States initially, with potential global expansion depending on regulatory approvals and demand.

Security and privacy remain critical considerations. OpenAI states that all health data is encrypted and processed in compliance with HIPAA standards, although the feature is not yet available in Codex, the company’s more restricted environment for sensitive data. Users retain full control over data sharing; they can disconnect Apple Health at any time and delete chat history. OpenAI also clarifies that health data will not be used for model training without explicit consent. This approach mirrors best practices in the industry, where companies like Apple and Google have set high bars for data protection.

The initial feedback for the relaunched feature has been positive. Early adopters have praised the improved accuracy of health summaries and the ability to track changes over time. For example, one user reported using ChatGPT to review blood test results from two different dates, and the AI correctly identified a slight improvement in cholesterol levels while noting an increase in vitamin D deficiency. Another user used the feature to correlate sleep patterns with daily step counts, discovering that low activity days often preceded poor sleep. Such insights, while simple, demonstrate the potential of combining AI with personal health data.

Despite the enthusiasm, challenges remain. Some users have expressed concerns about data security, especially given recent high-profile data breaches in the tech industry. OpenAI has responded by publishing a detailed privacy policy specific to Health in ChatGPT, explaining data flow and retention policies. Additionally, the feature is limited to U.S. users due to varying health privacy laws in other countries. OpenAI has indicated plans to expand to additional regions, but no timeline has been provided.

The relaunch of ChatGPT Health also highlights the evolving role of AI in healthcare. While earlier attempts at AI-powered health tools were often criticized for being too generic or unreliable, recent advances in large language models have opened new possibilities. OpenAI’s competitors, including Google and Microsoft, are also exploring similar integrations. Google’s AI assistant can already access health data via Google Fit, and Microsoft has partnered with healthcare systems to deploy AI for clinical decision support. OpenAI’s move positions it as a strong contender in the consumer-facing AI health space.

Looking ahead, OpenAI may expand ChatGPT Health to include integrations with other health platforms, such as Google Fit or Samsung Health. The company could also add features like medication reminders, diet tracking, or even mental health support, leveraging its conversational AI to create a holistic health assistant. However, any expansion will require careful navigation of regulatory landscapes, particularly in the European Union and Asia, where data protection laws are stringent.

In summary, the relaunch of ChatGPT Health with expanded access represents a major step forward for OpenAI in the healthcare domain. By incorporating user feedback and leveraging improved AI models, the company has addressed many of the shortcomings of the initial pilot. The feature offers U.S. users a secure way to make sense of their health data, providing personalized insights that can help them make informed decisions. As AI continues to permeate every aspect of life, its integration with health management is likely to become increasingly common, and OpenAI’s latest effort signals that the technology is maturing rapidly.

Source: 9to5Mac News

I consider myself a casual AI user. I do not build apps with machine learning, I have no interest in benchmarking models, and my primary use is as a smarter search engine. I suspect this places me squarely in the average iPhone user category. AI is a useful tool, but I am neither a passionate enthusiast nor someone who fears every new development labeled ‘artificial intelligence.’ With that perspective, my early testing of iOS 27 has been extremely positive. The new Siri does exactly what I have been wanting from a personal assistant for years.

Everyone has their own wishlist for Siri, but my personal top three priorities before iOS 27 were: world knowledge, a conversational user interface, and consistent, integrated behavior across all Apple devices. So far, Siri AI has delivered on all three fronts. Let me break down how each of these upgrades manifests in the real world.

World Knowledge

The old Siri was notoriously limited in its knowledge domains. It could tell you about sports scores, movie times, or the weather, but ask about a niche historical event, a complex scientific concept, or the latest news from a specific industry, and it often drew a blank. With iOS 27, that has changed dramatically. Siri AI can now answer questions about just about anything. It leverages a vast internal knowledge base that appears to be updated in real time. For example, I asked Siri about the impact of quantum computing on cryptography, and it provided a detailed, accurate explanation with context and examples. I then followed up with a question about the latest developments in fusion energy, and it gave me a concise summary of recent breakthroughs from research labs around the world. This level of world knowledge is transformative. It turns Siri from a limited assistant into a genuine research tool.

Conversational UI

One of my biggest frustrations with the old Siri was its inability to maintain a coherent conversation. If I asked a follow-up question, it often treated it as a completely new command without any context. The new Siri, however, features a dedicated Siri app that serves as a home for conversations. This interface is a game-changer. When I ask a question, I can see the full history of our exchange, ask clarifying follow-ups, and even revisit past chats with ease. The conversational flow feels natural. For instance, I asked Siri to recommend a good Italian restaurant in my area. It provided several options with ratings and reviews. I then said, “What about something cheaper?” and it understood the context, narrowing the list to more affordable choices. This level of discourse is exactly what I wanted from a truly conversational UI. The Siri app also allows me to save important conversations or revisit them later, making it a persistent, intelligent notebook.

Consistent and Integrated Across Apple Devices

Another major pain point was the fragmented nature of Siri across different Apple devices. The old Siri on iPhone might have different capabilities than on Mac or Apple Watch, and the experience on HomePod was even more limited. With iOS 27, Apple has designed Siri AI to be consistent across all platforms. The same intelligence and knowledge bases are available whether you are on your iPhone, Mac, Apple Watch, iPad, or even Apple TV and HomePod. This means you can start a conversation on your Mac, pick it up on your iPhone while commuting, and later review it on your iPad at home. The integration is seamless. Moreover, Siri is deeply integrated with Apple’s own apps and services. It can offer personalized assistance based on your messages, notes, email, calendar events, and more. For example, Siri can proactively remind you of a task from your notes without you even asking, based on the time and location context. This level of cross-app integration is something that competitors like Google Assistant or Amazon Alexa find hard to match because they lack the deep system-level access that Apple has. The consistency also means that the Siri you interact with on your HomePod has the same intelligence as on your phone, making the smart speaker experience far more capable.

Apple first announced its intention to upgrade Siri with AI capabilities back in 2024. The AI landscape has changed dramatically since then, with the rise of large language models from OpenAI, Google, Meta, and others. Many wondered if Apple’s effort would fall behind. But early signs indicate that for the average iPhone user, iOS 27’s new Siri could prove well worth the wait. The company has clearly invested in making Siri not just smarter, but also more reliable and more integrated into the user’s digital life. It is no longer just a voice interface; it is an intelligent companion that learns from your behavior and adapts to your needs.

Beyond these core upgrades, Siri AI also brings improvements in speed, accuracy, and privacy. Apple has emphasized that AI processing is done on-device as much as possible, with opt-in cloud assistance for more complex queries. This approach reassures privacy-conscious users. In my testing, most queries were answered almost instantly, with no noticeable lag. The new Siri also seems better at understanding natural language quirks, slang, and even incomplete sentences. I found myself speaking more naturally rather than having to phrase commands as if talking to a robot.

Another notable addition is the integration of Siri into third-party apps. Developers can now use the SiriKit APIs to make their apps respond to Siri commands with AI-generated actions. For example, a note-taking app could have Siri summarize a long document or create a new entry based on a spoken description. This opens up a world of possibilities for productivity and creativity. Early adopters of the beta report that the integration is smooth and consistent across apps that have implemented the new APIs.

What about the accessories? The article also lists some best iPhone accessories, but in the context of Siri, these accessories now benefit from the improved assistant. For instance, the AirPods Pro 3, which integrate seamlessly with Siri, now offer hands-free access to the new conversational interface. The MagSafe car mount works with iPhone’s new Siri-focused driving mode, which uses the smart assistant to manage calls, messages, and navigation without distraction. And the AirTag 2, with its enhanced precision finding, leverages Siri for locating lost items through voice commands. All these accessories become more powerful because of the unified Siri experience.

In summary, iOS 27’s new Siri is a landmark update. It addresses the three biggest complaints that users have had for years: limited knowledge, poor conversational flow, and inconsistent behavior across devices. The implementation is thoughtful and polished, and for the casual user like me, it delivers exactly what I hoped for. The AI upgrade feels natural and helpful, not gimmicky. It makes the iPhone a smarter, more capable device that anticipates your needs and assists you proactively. I am excited to see how developers will further extend Siri’s capabilities. For now, I can confidently say that the new Siri is the best version we have ever seen, and it sets a new standard for what a personal assistant should be.

Source: 9to5Mac News

1: Maxed Out Battery Life

Battery life consistently ranks as one of the top priorities for iPhone users. The desire for longer-lasting devices drives both consumer expectations and engineering decisions at Apple. The iPhone 17 Pro and Pro Max already saw notable improvements in battery longevity, thanks to a combination of efficient A17 Pro chipset and optimized software. However, rumors indicate that Apple plans to push battery performance even further with the iPhone 18 Pro.

The expected gains stem from multiple efficiency improvements across the hardware stack. First, an upgraded LTPO+ display technology will allow for more granular refresh rate management, reducing power consumption when static content is displayed. Second, the A20 Pro chip, built on a cutting-edge 2nm process, promises substantial performance-per-watt gains over the current 3nm architecture. This process shrink typically delivers a 10-15% improvement in energy efficiency, directly extending battery life. Third, Apple may introduce its first in-house designed C2 cellular modem, which could offer better power efficiency compared to the Qualcomm modems used in previous generations.

Recent leaks also point to larger physical battery cells in both the iPhone 18 Pro and iPhone 18 Pro Max. Reports from supply chain sources suggest that Apple is increasing battery capacity by up to 10% in the standard Pro model, with the Pro Max receiving even more significant gains. Considering that the iPhone 17 Pro Max already offered exceptional battery life—often lasting well over a day under moderate use—these improvements could make the iPhone 18 Pro Max a multi-day device for many users. The combination of hardware efficiency and larger batteries means that even heavy users may find themselves charging less frequently.

For perspective, the iPhone 15 Pro Max introduced a battery life that many reviewers praised as all-day even with intensive usage. The iPhone 17 Pro improved upon that, and the 18 Pro aims to set a new benchmark. If you often find yourself reaching for a charger by mid-afternoon, the iPhone 18 Pro's battery upgrades could be the single most compelling reason to upgrade from the 17 Pro. Efficiency gains also benefit overall device heat management, reducing thermal throttling during demanding tasks like gaming or video editing.

2: Big Camera Improvements

Apple's camera systems have long been a highlight of each new iPhone generation, and the iPhone 18 Pro is rumored to deliver what Mark Gurman describes as 'the biggest leap in camera hardware' in years. This is particularly noteworthy given that the iPhone 17 Pro already featured an impressive triple-camera array with a 48MP main sensor, 12MP ultra-wide, and 12MP telephoto lens with 3x optical zoom. So what exactly will make the 18 Pro stand out?

According to multiple leaks, the primary focus will be on the Main and Telephoto cameras. The main camera is expected to adopt a variable aperture system, similar to what some Android flagships have offered in the past. This would allow the lens to physically adjust its aperture size—from f/1.4 to f/2.8, for example—giving users more control over depth of field and low-light performance. In bright conditions, a smaller aperture can improve sharpness and reduce overexposure, while in dim light, a wider aperture lets in more light, reducing noise and improving detail. This feature would be a first for any iPhone and could dramatically enhance photography versatility.

The Telephoto camera is also getting a major upgrade, with a larger aperture that will improve light capture and potentially enable better optical zoom capabilities. Some rumors suggest that the Telephoto lens could shift from 3x to a 5x or even 6x optical zoom, bringing it closer to the capabilities of the iPhone 17 Pro Max's tetraprism lens. A Weibo leaker known as Fixed Focus Digital recently stated that the camera bump on the iPhone 18 Pro will be 2mm thicker than its predecessor, attributing this to an enlarged main camera module. Physical changes of this magnitude indicate not just sensor upgrades but also possibly larger lens elements and improved image stabilization hardware.

Beyond still photography, video recording may also see benefits. The variable aperture could allow for more cinematic depth-of-field effects in real time, and the larger sensors could improve low-light video quality. Computational photography features like Deep Fusion, Smart HDR, and Night mode will likely receive algorithmic updates to take advantage of the new hardware. For photography enthusiasts who use their iPhone as a primary camera, these upgrades represent a significant step forward. Even casual users will notice sharper images, better portrait effects, and enhanced low-light performance. If you regularly take photos in challenging lighting conditions or value professional-grade creative control, the iPhone 18 Pro's camera system could justify the upgrade from the 17 Pro.

3: Revised Design

Design plays a crucial role in upgrade decisions, especially for those who own a recent model. If a new iPhone looks virtually identical to the one already in your pocket, the appeal of upgrading diminishes. Apple seems to recognize this and is preparing several design refinements for the iPhone 18 Pro, even if the overall silhouette remains familiar.

Three specific design updates have been rumored: new color options, a smaller Dynamic Island, and a unified rear glass and aluminum construction. Let's examine each. First, color options. Current rumors point to Dark Cherry, Light Blue, and Silver, with a possible Black or Space Gray variant also in the mix. These colors would replace the Titanium Desert (from iPhone 16 Pro) and Natural Titanium (from iPhone 17 Pro), offering a fresh palette that may attract users looking for a change.

Second, the Dynamic Island is expected to shrink by approximately 35% compared to the iPhone 17 Pro's implementation. Introduced with the iPhone 14 Pro, the Dynamic Island has been a controversial design element, taking up notable screen real estate at the top of the display. Reducing its size would not only provide a modern look but also free up usable screen area for content and notifications. A smaller cutout could also make the display appear more edge-to-edge, bringing the iPhone closer to the all-screen design seen on many Android competitors.

Third, Apple is reportedly moving away from the two-tone rear color scheme that divided opinions last year. Instead, the iPhone 18 Pro will feature a unified appearance, with a single-color rear glass and an aluminum frame that blends seamlessly. This change could give the device a more premium and cohesive aesthetic, similar to the iPhone 4 or the current iPad Pro. The switch to a unified design may also improve durability, as the glass and aluminum construction would be more integrated.

These design updates, while not radical, collectively refresh the iPhone 18 Pro's identity. The smaller Dynamic Island alone could make the device feel significantly more modern. Combined with new colors and a cleaner back, the 18 Pro will likely stand out from the iPhone 17 Pro in hand. For users who prioritize aesthetics and enjoy having the latest look, these changes are a strong incentive to upgrade. Moreover, a refreshed design often maintains or improves resale value, which can offset some of the financial cost of upgrading annually.

Beyond these three main reasons, there are other factors that might sway potential upgraders—such as improved display technology (possibly a brighter panel with better HDR performance), faster charging capabilities, or new software features that require the A20 Pro chip. However, battery life, camera hardware, and design will likely be the headline features driving most purchase decisions. As with any pre-launch rumors, it's important to temper expectations until official specifications are announced. But the overall picture suggests that the iPhone 18 Pro will offer meaningful, tangible improvements over its predecessor, making the upgrade path more compelling than usual.

Source: 9to5Mac News

The decision comes at a critical juncture for Facebook. While the platform remains the most popular social network globally by total users, its growth has stagnated, and its dominance is being challenged on multiple fronts. In the first quarter of 2026, Meta reported a collective loss of 20 million users across all its platforms, a stark indicator that the company’s core demographic is drifting away. TikTok, by contrast, passed 1 billion monthly active users just three years after its global launch—a milestone that took Facebook nearly a decade to achieve. YouTube is also a close second in popularity, and its short-form video feature, Shorts, is thriving.

The TikTok Threat and Facebook’s Response

For years, Facebook executives downplayed TikTok’s threat. In 2022, Alison told The Verge that he saw “TikTok chasing Facebook,” not the other way around. But the data tells a different story. Facebook’s user engagement, especially among younger audiences, has been steadily declining. Teenagers and young adults increasingly prefer TikTok’s algorithmically curated, entertainment-first feed over Facebook’s traditional mix of posts from friends, groups, and pages.

Meta’s first direct response to TikTok was Reels, launched on Instagram in 2020. Reels was a moderately successful attempt to bring short-form video to the photo-sharing app. Now, Meta is applying the same strategy to Facebook, but with a much more aggressive twist: turning the entire app into a video-first experience. The experimental full-screen interface will initially roll out to countries where video consumption is notably higher, such as India and parts of Southeast Asia, with a possible expansion to the United States next year.

The shift is driven by a fundamental change in how people use social media. “Video is where conversations are happening, communities are forming, and even commerce is starting to take place,” Alison said in a statement. By forcing users into a TikTok-like feed, Facebook hopes to increase time spent on the platform and boost ad revenue. But critics argue that such a drastic move could alienate longtime users who still prefer text-based updates and photo albums.

Emulating Competitors: Reddit and Craigslist

Facebook’s transformation doesn’t stop with video. The company has been steadily borrowing features from other successful platforms to keep its ecosystem sticky. This year, it launched the Forum app, a dedicated space for interacting with Facebook Groups. Forum is designed to mimic subreddit communities on Reddit, offering threaded discussions, upvoting, and topic-based channels. The goal is to create deeper, more engaging conversations that rival Reddit’s user-generated content model.

Additionally, Facebook today announced the launch of Seller, a new app tailored for Marketplace merchants. Seller acts as a dedicated hub for sellers to track performance, manage listings, and communicate with buyers—essentially a Craigslist-style experience but with the convenience of integrated payment and shipping options. This move comes as Facebook Marketplace has grown into a massive e-commerce platform, but it still lacks the dedicated tools that power sellers on Amazon or eBay. By creating a standalone Seller app, Facebook aims to attract more professional merchants and compete directly with platforms like Craigslist, which remains popular for local classifieds.

Free Verification Badges: A Shift in Trust Strategy

Another noticeable change is the introduction of a free verified badge for users. Previously, verification on Facebook required a paid subscription to Meta Verified, which costs $11.99 per month. Now, users can obtain a blue checkmark by completing a simple selfie verification process. The goal is to help users know that a profile is linked to a real person, thereby improving trust and reducing impersonation.

This move is partly a response to criticism that paid verification erodes the meaning of the badge. Twitter (now X) faced similar backlash when it launched paid blue checks under Elon Musk. By offering a free alternative, Facebook hopes to restore some credibility while still keeping the paid tier for additional perks like account support and enhanced visibility. The free badge will likely become a baseline requirement for joining groups or participating in marketplace transactions, further integrating verification into the platform’s core experience.

The Broader Strategy: A Super-App Ambition?

Facebook’s evolution over the years has turned it into a hodgepodge of social and commerce services. It started as a simple network for college students, then added photo sharing, news feed, gaming, messaging (Messenger), marketplaces, dating, job listings, and now dedicated apps for groups and sellers. The company is effectively trying to become a “super app”—similar to WeChat in China—where users can do everything from chatting to shopping to booking appointments without leaving the ecosystem.

But the super-app model has proven difficult to replicate in the West. WeChat succeeded in China because of a lack of alternative services and deep integration with daily life. In the US and Europe, users are more fragmented and privacy-conscious. Facebook’s attempts to bundle services have often led to clutter and user fatigue. The addition of a full-screen video feed could be the final straw for users who remember the platform as a simple way to share photos and stay in touch with friends.

Meta is also facing regulatory headwinds. Antitrust investigations in the EU and US have scrutinized the company’s dominance and its practices of copying competitors. The new video interface and standalone apps may draw further attention from regulators who argue that Meta uses its size to crush smaller rivals. However, Meta argues that these changes are pro-competitive because they offer users more choices within the Facebook ecosystem.

What This Means for Users

For the average Facebook user, the upcoming changes could be jarring. Those who open the app expecting to see updates from friends and family might instead be greeted with a TikTok-style feed of viral videos, recommended based on their viewing habits. Facebook says it will initially test this experience with a small group of users and gather feedback before a wider rollout. But the direction is clear: Facebook is betting that video is the future of social interaction.

For content creators, the shift could be a boon. A dedicated video feed rewards engaging, short-form content, which could help creators build larger audiences on Facebook. However, it also means increased competition, as the algorithm will favor viral videos over personal updates. Businesses may need to rethink their advertising strategies, investing more in video production to capture user attention.

The introduction of the Seller and Forum apps also signals that Facebook wants to become a more modular platform. Instead of trying to do everything in one app, Meta is spinning off specific functions into standalone experiences. This could reduce clutter in the main Facebook app while still keeping users within the Meta ecosystem. It’s a strategy reminiscent of messaging: Messenger was separated from Facebook years ago, and both apps remain popular.

Historical Context: Facebook’s Previous Pivots

Facebook has undergone several major transformations before. In 2012, it pivoted to mobile and launched the News Feed algorithm. In 2016, it shifted its focus to video, heavily promoting Facebook Live and even paying publishers to create Video content. In 2018, following the Cambridge Analytica scandal, it prioritized privacy and introduced features like “Clear History.” Each pivot was met with skepticism but ultimately helped Facebook maintain relevance.

However, the current pivot is arguably the most risky. TikTok’s success is not just about the format—it’s about the algorithm. TikTok’s “For You” feed is incredibly good at surfacing content that users didn’t know they wanted. Facebook’s recommendation engine, by contrast, has historically been based on social connections and group membership. Retooling the algorithm to compete with TikTok’s is a massive engineering challenge. If Facebook fails to match TikTok’s dopamine hit, users could quickly abandon the new interface.

Moreover, Facebook’s user base is older and more established. Many users depend on the platform for news, community groups, and business networking. Forcing a video-first experience on them could lead to a backlash, as seen when Instagram users protested the proliferation of Reels and suggested algorithms. Meta learned from that experience: Instagram eventually allowed users to toggle between a standard and a Reels-heavy feed. Facebook may offer similar opt-out options, but the long-term goal remains to shift everyone toward video.

The Competitive Landscape

Facebook is not the only platform scrambling to imitate TikTok. YouTube Shorts, Instagram Reels, Snapchat Spotlight, and even LinkedIn have introduced short-form video features. TikTok itself is expanding into longer videos, e-commerce, and group chats. The social media landscape is becoming increasingly homogeneous, with everyone copying everyone else. In this environment, differentiation becomes harder. Facebook’s bet is that its massive user base and data on social relationships will give it an edge—if it can execute.

Meanwhile, the rise of decentralized platforms like Mastodon and Bluesky poses a different kind of threat. These platforms offer users more control over their data and algorithms, appealing to those tired of corporate social media. Facebook’s moves toward centralization (by making the app more addictive) could accelerate the exodus of privacy-conscious users. However, the scale of these alternative platforms remains tiny compared to Facebook’s billions.

Conclusion-free Endnote

As Facebook experiments with a TikTok-like interface, launches Reddit and Craigslist clones, and offers free verification, one thing is clear: the company is willing to radically change its identity to survive. Whether these changes will attract new users or drive away old ones remains to be seen. The next few years will be decisive for Facebook’s future as it tries to balance innovation with user loyalty. The results of the full-screen video test, expected by early 2027, will likely shape the next chapter of the platform that once defined social media itself.

Source: The Verge News

For decades, American science was largely directed by government agencies like the National Science Foundation (NSF) and the National Institutes of Health (NIH), with academic peer review guiding funding decisions. But a noticeable shift is underway. Increasingly, the language of venture capital—terms like "moonshot\

Source: The Verge News

This crackdown follows backlash about large pop-up ads for McAfee antivirus and LG’s own apps appearing on Windows 11 PCs after being connected to LG monitors. Upon connection, a Windows driver update was silently installing LG driver updates and the LG Monitor App Installer without explicit permission from the user — with reports about the auto-installing issue dating back to 2024.

The problem stemmed from the way Windows Update works. When a user connected an LG monitor, Windows Update would automatically fetch and install the latest drivers provided by the manufacturer. In this case, LG had bundled its Monitor App Installer — which included an optional McAfee trial — as part of those drivers. Users reported that even if they declined the McAfee installation during the initial setup, the pop-up notifications for the trial would still reappear periodically, urging them to activate or renew the antivirus software. This practice is often referred to as bloatware or crapware, where manufacturers include unwanted software to generate additional revenue through partnerships.

The issue gained significant traction on social media and forums like Reddit, where users shared screenshots of the intrusive notifications. Many expressed frustration that a simple monitor connection could trigger such unwanted behavior, especially on a premium platform like Windows 11. Some users reported that the pop-ups appeared even after they had uninstalled the LG Monitor App Installer, suggesting that residual services or scheduled tasks continued to run. This led to concerns about the lack of user control over system updates and the transparency of Microsoft’s driver distribution ecosystem.

LG defended its behavior in a long, uncredited statement sent to Windows Latest that seems to miss the point entirely: “LG Electronics reiterates that McAfee is not installed automatically and is never installed without the user’s explicit consent. The LG Monitor App Installer is distributed through Microsoft’s official Windows distribution process, which included McAfee as an option. McAfee will be installed only if a user actively chooses to proceed with the installation and provides consent. Under no circumstances is McAfee installed automatically or without user authorization. The LG Monitor App Installer does not access, collect, or transmit any customer personal data.”

Despite this defense, the user experience told a different story. The pop-up advertisements themselves were unwanted, regardless of whether the full McAfee software was installed. The notifications appeared as Windows system notifications, making them feel like official alerts rather than marketing materials. This blurred the line between system messages and advertisements, a practice that has drawn criticism from privacy advocates and usability experts. The situation highlights a broader industry trend where hardware manufacturers leverage Windows Update as a distribution channel for their own software, often without clear user consent.

LG isn’t the only company that pushes automatic installation features. Tom Warren had previously noted that Dell had similarly auto-installed the Alienware Command Center app on Windows when connected to Alienware monitors. However, Dell’s Frank Cestone says in a statement that “As of February 2025, Alienware moved to an opt-in installation process for Alienware Command Center (AWCC) that requires explicit user consent.” This shift by Dell suggests that the industry is slowly recognizing the need for more transparent installation practices. Dell’s move came after similar complaints from Alienware monitor users, who discovered that the Command Center software was being installed without their explicit approval during Windows Update.

The Dell case is instructive because it shows that manufacturers can change their approach when pressured. Alienware’s initial installation method was similar to LG’s: the software was distributed via Windows Update as a driver or optional component. After feedback, Dell redesigned the process so that users must actively click to install AWCC, rather than having it automatically downloaded and installed. This opt-in model is considered best practice by many in the software community, as it respects user autonomy and reduces unwanted system clutter.

In addition to monitor issues, LG has also faced criticism for pushing annoying ad notifications on its TVs at startup. Users of LG’s webOS platform have reported seeing advertisements for LG’s own content services or third-party apps when turning on their televisions. While these ads can sometimes be dismissed, they cannot be permanently disabled without changing network settings or using third-party workarounds. This behavior has led to accusations that LG is increasingly prioritizing advertising revenue over user experience across its product lines.

Microsoft’s intervention in the McAfee pop-up case is significant because it shows the company is willing to hold its partners accountable for poor behavior. Windows Update is a critical system service, and any abuse of that channel can undermine user trust in Microsoft’s platform. By publicly stating that LG has agreed to disable the pop-ups, Microsoft sends a message that such practices will not be tolerated. However, this reactive approach may not be sufficient to prevent future occurrences. Some industry analysts argue that Microsoft should implement stricter policies for driver distribution, such as requiring all bundled software to be opt-in and clearly labeled as third-party offerings.

The technical aspects of how the LG Monitor App Installer ended up on users’ systems are worth examining. When a monitor is connected, Windows Update checks for driver updates from the manufacturer’s Windows Hardware Dev Center dashboard. Manufacturers can submit driver packages that include not only critical display drivers but also additional software components. These packages are then signed by Microsoft to ensure they come from a trusted source. In LG’s case, the driver package included the LG Monitor App Installer as a legacy component. Once the driver was installed, a post-install script would launch the installer, which then presented the McAfee offer. Users who clicked through the installer without reading carefully could inadvertently agree to install McAfee, and even those who declined would still see reminder pop-ups designed to encourage later installation.

The history of such bloatware on Windows is long and checkered. Since the early days of Windows XP, PC manufacturers (OEMs) have pre-installed trial software, toolbars, and other utilities to subsidize hardware costs. Over time, Microsoft has made efforts to reduce this “crapware” through programs like “Signature Edition” PCs and the “Windows 10 S” mode, which restricts software installation to the Microsoft Store. However, the LG case shows that bloatware can still enter the system through the driver update pipeline, a channel that is often overlooked by users.

The McAfee pop-up issue also raises questions about the role of antivirus software in the modern computing landscape. While McAfee once dominated the consumer antivirus market, its reputation has suffered due to aggressive marketing tactics and resource-heavy software. Many users now rely on Windows Defender, which comes built-in with Windows 11 and provides adequate protection for most users. The push for third-party antivirus trials like McAfee is often seen as unnecessary and intrusive, especially when the software can cause performance degradation or compatibility issues.

For LG, the agreement to disable the pop-ups is a welcome change, but it remains to be seen whether the company will fully reform its practices. The LG Monitor App Installer may still be bundled with future driver updates, even if the McAfee notifications are removed. Users who have already installed the app may need to uninstall it manually to prevent any residual background processes. Microsoft has not disclosed whether it will audit other manufacturers for similar behavior, but the precedent set by this case could lead to broader scrutiny.

From a consumer perspective, the best defense against unwanted software is to stay informed. Users should regularly check their installed applications and review optional Windows Update components before installing. They can also delay driver updates from Windows Update and instead download only necessary drivers from the manufacturer’s website. For enterprise environments, IT administrators can use group policies to block automatic driver installations from Windows Update entirely. These measures can help prevent unwanted software from reaching user systems in the first place.

Ultimately, the LG McAfee incident highlights the delicate balance between convenience and user control in modern operating systems. While automatic driver updates are essential for security and stability, they should not be used as a backdoor for advertising or unwanted software. Microsoft’s intervention is a positive step, but it also reveals a vulnerability in the ecosystem that requires ongoing vigilance. As the lines between hardware, software, and services continue to blur, users must remain proactive in protecting their digital experience from the encroachment of commercial interests.

Source: The Verge News

Initially, Meta had announced that starting in the coming months, users would need to pay a $20 monthly subscription to access Conversation Focus. Even paying subscribers would be limited to 15 hours of use per month, a restriction the company justified by citing the costs of running the service. However, independent tests quickly disproved that claim: the feature works even when the glasses are disconnected from the internet, proving it is locally processed. This revelation ignited a firestorm of criticism, with many accusing Meta of attempting to monetize a basic hardware function under the guise of operational costs.

What was planned?

The subscription model was part of a broader strategy to convert Meta’s Ray-Ban smart glasses into a recurring revenue stream. Under the original plan, Conversation Focus would join other “premium features” behind a paywall. The company even introduced the concept of “rate limits,” capping usage hours for paid subscribers—a move that many saw as an artificial scarcity tactic. Meta’s spokesperson, Tyler Yee, confirmed to reporters that the company is not abandoning the idea of subscriptions; rather, it is pausing the test for Conversation Focus specifically.

“We’re still exploring all our options for the best approach,” Yee said in a statement. “Conversation focus will remain available for free through our Early Access Program for early testers while we work on a better approach.”

Why the backlash?

The backlash was driven by several factors. First, the feature is undeniably local—it does not use cloud processing, meaning Meta’s only ongoing cost would be minimal support and updates. Charging a monthly fee for a feature that works offline felt like a cash grab. Second, the rate limit of 15 hours per month seemed arbitrary and punitive, especially since many users rely on the glasses for daily communication. Third, the announcement came at a time when consumers are increasingly skeptical of subscription fatigue, with everyone from Adobe to Peloton facing similar criticism.

Technology journalists and critics quickly highlighted the disconnect between Meta’s rhetoric and reality. One writer demonstrated that after disconnecting the glasses from the internet, Conversation Focus continued to function perfectly, debunking the company’s alleged cost justification. This forced Meta to backtrack, at least temporarily.

Meta's broader strategy

Meta has been under immense pressure to monetize its hardware division, which includes the Quest VR headsets and the Ray-Ban smart glasses. The smart glasses, co-developed with EssilorLuxottica, have been praised for their design and functionality, but sales have been modest. By introducing subscriptions, Meta hopes to offset the hardware subsidies that keep the glasses at an accessible price point—$299 for the standard model.

“We sell hardware at accessible prices to get AI glasses into the hands of as many people as possible and they pack a lot of value for free, so some premium features will be subscription-based over time,” Yee explained. “Charging power users for expanded use of premium features is how we sustain this strategy and keep investing in breakthrough capabilities.” This rationale echoes similar moves by other hardware companies, such as Microsoft’s Xbox Game Pass or Amazon’s various free-with-ads tiers. However, the key difference is that those subscriptions often add real value, whereas Conversation Focus is a basic accessibility tool.

What happens next?

For now, Conversation Focus remains freely available to early testers through the Early Access Program. Meta has not set a new timeline for introducing a subscription, and it is unclear whether the company will ultimately abandon the idea entirely or simply revise the pricing and limits. The company’s statements suggest it is still committed to subscriptions for some features, but it may be more cautious about which ones.

The pause also highlights a growing tension in the smart glasses market: consumers expect premium devices to come with premium software support, but they are increasingly resistant to paying ongoing fees for features that should be included. Apple, Samsung, and Google all face similar challenges with their smartwatch and earbud ecosystems. Meta’s experiment will be watched closely as a bellwether for the entire industry.

Moreover, the incident underscores a public relations misstep. Meta has a history of announcing controversial features and then backtracking under pressure—recent examples include changes to its privacy policies and AI moderation tools. The company’s ability to communicate effectively with its user base remains a work in progress.

Technical details and implications

Conversation Focus uses advanced beamforming and audio algorithms to isolate a speaker’s voice from ambient noise. Because the processing is done on the glasses’ onboard chip, it does not consume additional server resources. This is in contrast to cloud-dependent features like real-time translation or AI image recognition, which do incur ongoing costs. By targeting a local feature for monetization, Meta risked alienating early adopters who had already paid $299 for the hardware.

The rate limit, if implemented, would have forced power users to choose between paying $20 per month or losing access to a core functionality. For people with hearing difficulties or those who rely on the glasses for work, the monthly fee would have been a significant barrier. Accessibility advocates were particularly vocal, arguing that Meta was effectively charging for a basic accommodation.

Meta’s decision to pause the plan is likely a strategic retreat, not a surrender. The company may reintroduce a subscription for Conversation Focus after a cooling-off period, perhaps with a lower price or a different usage cap. Alternatively, Meta might bundle it with other premium features to make the offer more palatable. Early testers will continue to enjoy free access, which gives Meta time to refine its approach.

In the meantime, the smart glasses market continues to evolve. Competitors like Amazon (with its Echo Frames) and startups like Brilliant Labs are also exploring subscription models. The key will be to find a balance between monetization and customer satisfaction. For now, Meta has bought itself some goodwill by listening to feedback, but whether that goodwill will last depends on its next move.

The incident also raises questions about the sustainability of hardware subsidization. If Meta cannot convince users to pay for software features, it may have to raise the upfront price of the glasses, making them less competitive. This is a classic dilemma for tech companies: low prices drive adoption, but long-term profitability requires recurrent revenue. Meta’s gamble is that users will eventually accept subscriptions for valuable AI-driven features, but the backlash suggests that acceptance is not guaranteed.

As the company continues to develop its smart glasses platform, it will have to tread carefully. The pause in rate limits is a step toward de-escalating tensions, but it is not a permanent solution. The coming months will reveal whether Meta can find a way to monetize without alienating its most loyal customers. For now, the Conversation Focus feature remains free, and users can continue to enjoy it without worrying about metered usage.

Source: The Verge News

The model is called TESSERA, an acronym that stands for Transformer for Earth Surface and Environmental Representation and Analysis. Its design borrows from large language models. Where an LLM learns from text, TESSERA learns from space. It ingests years of imagery from the European Space Agency’s Sentinel satellites, both radar and optical, the team announced. It then compresses each 10-metre square of the planet’s land into a compact 128-number “fingerprint,” or embedding.

That may sound abstract, but the payoff is concrete. Normally, mapping crops, forests, or floods from satellite data means building a bespoke model and hand-labelling thousands of examples for each task. With TESSERA’s fingerprints already computed, researchers can build those tools with far less data, often on an ordinary CPU. The team says it needs about 30 times less labelled data than starting from raw imagery. For instance, a farmer monitoring crop health might only need a handful of annotated satellite images to calibrate a yield prediction model, rather than thousands. This reduction in data requirements is a game-changer for regions where expertise and computing resources are scarce.

Training and inference on AMD hardware

The more unusual part of the project is what it ran on. Cambridge’s Energy and Environment group trained TESSERA on 16 AMD Instinct MI300X GPUs, using roughly 6,200 GPU-hours and AMD’s open ROCm software stack. Training a model is the easy bit. Running it across every 10-metre pixel on Earth—about 1.5 trillion a year—is the hard part. For that, the team turned to Vultr, an independent cloud firm that sponsored the compute, using six of its bare-metal servers. Each server packs eight AMD Instinct MI325X GPUs. Together they churn out roughly three terabytes of compressed data a day. The researchers liken that to covering the landmass of Italy, daily. A single year of global coverage takes months of continuous processing.

The use of AMD hardware is significant because it challenges the conventional wisdom that serious AI workloads require Nvidia’s CUDA ecosystem. AMD’s ROCm is an open-source alternative that has historically lagged in software maturity and community support. But projects like TESSERA show that with enough engineering effort, AMD GPUs can perform comparably for large-scale geospatial AI tasks. The team noted that they had to optimize the training pipeline for ROCm, but the performance was sufficient to train a frontier-scale model on a modest budget.

Applications across agriculture, conservation, and energy

The point of TESSERA is openness. Cambridge is releasing the embeddings free under a Creative Commons licence, alongside the full training recipe. Any government, researcher, or startup can build on them. Professor Anil Madhavapeddy, who leads the work, says the goal is to “democratise access to planetary-scale environmental monitoring.” The uses are concrete.

Farmers can track crop health and forecast yields at 10-metre resolution, a boon for smallholders in developing regions. For example, in sub-Saharan Africa, where ground-based surveys are expensive and infrequent, TESSERA’s embeddings could allow local agricultural offices to detect pest outbreaks or water stress weeks sooner than traditional methods. Conservationists can watch habitats shift, from tropical forests to the UK hedgerows that shelter hedgehogs. Energy planners can map solar and wind sites to guide the transition. All of it runs off the same shared fingerprints.

Moreover, TESSERA’s pre-computed embeddings enable rapid experimentation. Researchers can run a random forest or simple neural network on the embeddings to classify land cover types, rather than training a deep learning model from scratch on raw pixels. That lowers the barrier to entry for scientists in disciplines like ecology or urban planning who may not have deep AI expertise.

Broader context: the AI hardware landscape

TESSERA is a small story with a large subtext. A public university built a frontier-scale AI model, made it free, and did it on the hardware everyone says you cannot use. The field is convinced that serious AI means Nvidia GPUs and private labs. A planet’s worth of embeddings, trained on AMD and given away, is a quiet rebuttal. The development also highlights the growing importance of open-source AI stacks. As concerns mount over vendor lock-in and the environmental cost of training massive models, initiatives like TESSERA demonstrate that alternative paths are viable.

Cambridge’s choice of AMD was not merely ideological. The team considered Nvidia options but found that AMD offered better price-to-performance for their specific workload—large-scale matrix multiplications on high-resolution satellite data. Additionally, because ROCm is open source, the team could inspect and modify the driver-level code to optimize memory usage for the 10-metre pixel processing pipeline. This level of customization is harder to achieve with Nvidia’s proprietary CUDA ecosystem.

The implications extend beyond Earth observation. If AMD’s Instinct line can handle planetary-scale geospatial AI, it may also be suitable for other data-intensive fields like climate modeling, genomics, and physics simulation. The success of TESSERA could encourage other research groups to explore AMD hardware, potentially fostering a more competitive and diverse AI hardware market. That, in turn, could lower costs and accelerate innovation across the board.

Looking ahead, the Cambridge team plans to extend TESSERA to include time-series forecasting—predicting crop yields or deforestation months in advance based on the embeddings. They are also exploring partnerships with humanitarian organizations to deploy TESSERA-based tools for disaster response. For instance, after a flood, the embeddings could be used to quickly map inundated areas without needing manual annotation of new satellite imagery. The team emphasizes that all future work will remain open-source, ensuring that the benefits are widely shared.

In a field often dominated by billion-dollar corporate labs, TESSERA stands as a reminder that public research institutions can still punch above their weight. By choosing AMD and an open licence, Cambridge has not only advanced geospatial AI but also sent a message that the future of AI need not be locked into a single vendor.

Source: TNW | Artificial-Intelligence News

At its Advancing AI event in San Francisco, AMD unveiled a comprehensive lineup of new hardware designed to challenge Nvidia’s stranglehold on the data center AI market. The announcements included the MI455X AI accelerator, the Helios server rack—a system that packs 72 of those chips into a single interconnected unit—and the Venice generation of Epyc server processors, which AMD claims will set new performance benchmarks for both AI training and inference. The event was a clear signal that AMD is moving beyond selling individual components to offering end-to-end data center solutions, mirroring Nvidia’s own strategy.

The MI455X is the latest in AMD’s Instinct series of AI accelerators, optimized for the massive parallelism required by large language models (LLMs). Although AMD did not disclose specific performance figures, the company asserts that the MI455X will outperform Nvidia’s H100 and the upcoming B100 in both training and inference workloads, primarily due to its enhanced memory bandwidth and a new high-bandwidth interconnect that allows chips within the Helios rack to communicate with near-zero latency. The Helios rack itself is a marvel of engineering: it integrates 72 MI455X accelerators, each with dedicated high-bandwidth memory, connected through AMD’s Infinity Fabric, effectively creating a single massive GPU-equivalent system. This architecture is directly comparable to Nvidia’s DGX SuperPOD, but AMD claims it offers superior performance per watt and a lower total cost of ownership.

Venice Epyc: The Next-Gen Server CPU

Alongside the accelerators, AMD announced the Venice generation of Epyc server processors, built on TSMC’s advanced two-nanometer process. This node shrink allows AMD to pack more cores, increase clock speeds, and reduce power consumption compared to previous generations. The Venice chips are designed to handle both general-purpose compute and AI inference tasks, blurring the line between CPUs and accelerators. AMD positioned Venice as a direct competitor to Nvidia’s Vera CPU, which Nvidia recently integrated into its own data center platforms. By tying Venice to the Helios ecosystem, AMD hopes to offer customers a unified architecture where CPUs and GPUs share memory and data seamlessly, eliminating the bottlenecks that plague heterogeneous computing environments.

The rivalry between AMD and Nvidia now spans the entire stack: from individual chips to complete rack-scale systems. Nvidia’s Vera Rubin platform is already in production and shipping to key customers like OpenAI, CoreWeave, and Microsoft. However, AMD’s Venice processors are expected to give the company a edge in scenarios where legacy x86 compatibility is crucial, as enterprise data centers often run a mix of AI and traditional workloads. AMD’s Lisa Su emphasized that Venice will keep AMD well ahead of Vera in raw performance, though independent benchmarks have yet to confirm that claim.

Partnerships with OpenAI and Cerebras

The event featured high-profile endorsements from major AI companies. OpenAI’s Sachin Katti stated that his company expects to deploy Helios racks "at massive scale" as it scrambles to add infrastructure capacity to support the growing demand for its GPT models. This announcement came a day after AMD revealed it would invest up to $5 billion in Anthropic, the AI safety company behind Claude, and that it would deploy two gigawatts of MI450 series GPUs in Helios racks to run Claude. The first gigawatt of that deployment is scheduled to ship in the first half of 2027, signaling a long-term commitment to supplying hardware for frontier AI models.

In another strategic move, AMD announced a partnership with Cerebras, the company known for its wafer-scale chips that specialize in ultra-fast AI inference. Together, they will combine Helios racks with Cerebras servers to offer customers a hybrid solution: AMD hardware will handle the computationally heavy work of deciphering and tokenizing queries, while Cerebras chips provide rapid answers with minimal latency. Cerebras CEO Andrew Feldman said the combined product will ship from Cerebras-owned data centers starting in the fourth quarter and will beat a similar offering Nvidia is assembling from its recent Groq acquisition. This partnership highlights the increasing specialization in the AI hardware market, where no single architecture is optimal for all tasks.

Market Context and Wall Street Reaction

Despite the ambitious product launches and high-profile partnerships, investors remained skeptical. AMD’s stock fell by about four percent during the presentation, even though the stock had more than doubled in value over the previous year. The skepticism reflects the uphill battle AMD faces against Nvidia, which currently commands over 80% of the AI accelerator market. Nvidia’s Vera Rubin platform is already in full production and shipping to leading cloud providers, while AMD’s MI450 and MI455X are still ramping. The gap between AMD’s ambitions and Nvidia’s dominance is further highlighted by Nvidia’s extensive software ecosystem, including CUDA and its AI frameworks, which AMD is only now beginning to match with its ROCm platform.

AMD’s CEO Lisa Su has overseen a remarkable growth run, turning the company into a serious contender in both CPUs and GPUs. However, Wall Street’s expectations were already baked into a stock that had risen roughly 145% year-to-date heading into the event. The slight dip suggests that investors wanted more concrete performance data or clearer customer commitments. Additionally, the AI hardware market is becoming increasingly crowded, with Intel, AWS, Google, and a slew of startups all vying for a slice of the pie. AMD’s predicted total addressable market of $2 trillion by 2030, with AI accelerators alone accounting for more than a trillion dollars, may seem optimistic, but it underscores the explosive growth expected in the sector.

Technical Deep Dive: MI455X Architecture

A closer look at the MI455X reveals several key innovations that set it apart from its predecessor, the MI450. The new accelerator is built on a refined version of AMD’s CDNA 3 architecture, with a focus on matrix math and tensor operations. It features an enhanced Matrix Core engine that can handle FP16, BF16, and INT8 operations at higher throughputs than before. The memory subsystem has been upgraded to HBM3E, offering 3.2 TB/s of bandwidth per chip, while the Infinity Fabric link between chips within the Helios rack provides 800 GB/s of bandwidth. This interconnect is crucial for scaling workloads across multiple accelerators, enabling what AMD calls "tensor parallelism" across 72 accelerators without significant overhead.

AMD also introduced a new feature called "adaptive partitioning," which allows the Helios rack to be logically split into smaller clusters for customers who need to run multiple smaller models simultaneously. This flexibility is a key selling point for cloud providers that want to maximize utilization across diverse workloads. Meanwhile, the Venice Epyc processor incorporates AMD’s next-generation Zen 6 cores, which are designed to work in tight cooperation with the MI455X. The CPU and GPU share a coherent memory domain, meaning they can access the same data without copying it across a PCIe bus, a long-standing bottleneck in heterogeneous computing.

Implications for the AI Hardware Landscape

AMD’s strategy is to offer a unified, open ecosystem that gives customers more choices. The company emphasizes that its hardware is designed to work seamlessly with popular AI frameworks like PyTorch, TensorFlow, and JAX, thanks to its ROCm software stack, which AMD has been steadily improving. Partnerships with Cerebras and OpenAI demonstrate that AMD is willing to co-innovate with specialized chipmakers and end-users to create tailored solutions. The Cerebras partnership, in particular, is interesting because it combines two very different architectures—wafer-scale compute with fine-grained parallelism—to address the low-latency inference market, which is critical for real-time applications like chatbots and autonomous systems.

Nvidia, however, is not standing still. The company’s acquisition of Groq, a leader in LPU (Language Processing Unit) inference, gives Nvidia its own specialized inference path. Additionally, Nvidia’s Vera CPU, combined with its Blackwell GPUs, creates a vertically integrated stack that AMD must match. Yet AMD’s advantage lies in its x86 compatibility and the openness of its platform, which many enterprise customers prefer for existing workloads. As the AI hardware market matures, the competition is likely to shift from raw performance to total system efficiency, software ecosystem, and cost-effectiveness—areas where AMD is making strong bets.

The race to dominate the data center AI market is far from over. AMD’s new products will face rigorous testing and real-world deployment over the next year. If the company can deliver on its performance claims and secure volume commitments from major hyperscalers, it could carve out a significant share of the trillion-dollar market it envisions. For now, the ball is in Nvidia’s court, and the next moves will be closely watched by investors, engineers, and the broader tech industry.

Source: TNW | Anthropic News

The $811 billion total includes both short-term and long-term obligations, with approximately $200.7 billion falling due within the next year. These commitments encompass a wide range of assets: custom AI chips from partners like Broadcom and potentially Marvell Technology, data center construction contracts, long-term power purchase agreements for the massive electricity needs of AI training, and content licensing deals. The number dwarfs the capex figures that have dominated headlines about AI spending, representing roughly four years of spending at Alphabet's current annual investment rate of around $50 billion in capital expenditures.

Alphabet's aggressive spending is driven by the transformation of its core search business. Google's AI Overviews, which generate summarized answers instead of traditional blue links, require vastly more computational power. This shift has turned the company into the largest committed spending program in the technology industry, outpacing even the known investments of other hyperscalers like Microsoft, Meta, and Amazon. While those companies are also expanding AI capacity at record rates, none has disclosed a comparable total for contracted obligations, making Alphabet's number a benchmark for the industry.

Background: The Rise of AI Infrastructure Spending

The surge in Alphabet's commitments reflects a broader trend across the tech sector. Since the release of ChatGPT in late 2022, companies have raced to build the physical infrastructure necessary to train and run large language models. Data center demand has exploded, with vacancy rates in major markets falling below 3%. Chip orders for GPUs and custom accelerators have created supply chain bottlenecks that companies are locking in years in advance through take-or-pay agreements. Power purchase agreements have become a critical tool, as AI data centers require enormous amounts of electricity — a single training cluster can consume as much power as a small city.

Alphabet's approach has been to vertically integrate its hardware stack. The company developed its own Tensor Processing Units (TPUs) more than a decade ago, and more recently partnered with Broadcom to produce custom AI chips. In Q2 2025, reports emerged that Alphabet is also in talks with Marvell Technology to build new inference chips, diversifying its supply chain. These agreements are baked into the $811 billion figure. The company's cloud division, Google Cloud, reported $24.8 billion in revenue for Q2, up 82% year-on-year, providing the revenue engine to service these commitments. However, the sheer size of the obligations raises questions about what happens if AI demand growth slows.

Details of the Commitments

Breaking down the $811 billion, Alphabet's filing notes that the total includes "purchase obligations" for chips, data center equipment, electricity, inventory, and content licenses. The $200.7 billion short-term portion likely covers immediate needs for expanding existing facilities and fulfilling orders underway. The remaining $610.3 billion represents multi-year agreements that will stretch through the end of the decade and beyond. These include long-term power purchase agreements (PPAs) for renewable energy, which Alphabet has historically favored for its data centers, as well as construction contracts for new facilities in regions with favorable energy costs and tax incentives, such as Ohio, Nebraska, and Finland.

One key aspect is the inclusion of "inventory" commitments. Alphabet's hardware business, including Pixel phones and Nest devices, also factors into these numbers, but the bulk is clearly driven by AI infrastructure. The company has expanded its data center footprint rapidly: in 2024 alone, it announced plans for new campuses in Indiana, Virginia, and abroad. The $500 billion quarter-over-quarter increase suggests a massive acceleration of these plans, likely triggered by the success of Gemini, Google's next-generation AI model, and the need to support its rollout across Search, Cloud, and consumer products.

Industry Context and Comparisons

To put Alphabet's $811 billion in perspective, consider the broader tech industry. Microsoft has committed to spending over $100 billion on AI infrastructure over several years, largely through its partnership with OpenAI. Meta has announced plans to spend $65 billion in 2025 alone, primarily on GPUs and data centers. Amazon's AWS has been investing heavily in custom chips (Trainium and Inferentia) and expanding its global data center footprint. However, none of these companies have disclosed a comparable figure for total future contractual obligations. Alphabet's disclosure is unique because it includes everything from chip supply agreements to power contracts, providing a more comprehensive view of the financial commitment.

The rapid increase also reflects the competitive dynamics of the AI race. Google and Microsoft are locked in a battle for AI search market share, with Microsoft's Bing powered by OpenAI and Google's Search generating AI overviews. Both need massive compute capacity to experiment, train, and serve models. Alphabet's decision to lock in costs early may provide an advantage in terms of supply certainty, but it also creates financial risk. If AI demand plateaus or if models become more efficient (requiring less compute), Alphabet would still be obligated to pay for capacity it no longer needs. The company's strong balance sheet — with over $100 billion in cash and marketable securities — provides a buffer, but the scale of the bet is unprecedented.

Implications for the Future

The $811 billion figure is not a budget in the traditional sense; it is a contractual commitment that must be honored regardless of future revenue. Alphabet's ability to service these obligations depends on continued growth in its cloud business, advertising revenue, and new AI-powered products. The company's cloud revenue growth of 82% year-on-year is encouraging, but it remains a distant third behind AWS and Azure. Alphabet's search advertising business, which generates the majority of its revenue, must also adapt to a world where AI summaries may reduce the number of ad clicks. The company is experimenting with new ad formats within AI Overviews, but it is too early to measure the impact.

Another factor is the geopolitical landscape. Supply agreements for advanced chips, particularly those manufactured by Taiwan Semiconductor Manufacturing Company (TSMC), are subject to export controls and trade tensions. Alphabet's long-term contracts may include provisions to mitigate such risks, but the concentration of chip manufacturing in Taiwan remains a vulnerability. Similarly, power purchase agreements rely on regulatory environments for renewable energy, which vary by jurisdiction.

Finally, the $500 billion quarter-over-quarter jump suggests that Alphabet is betting that the AI infrastructure buildout will continue at an exponential pace. This aligns with statements from Alphabet CEO Sundar Pichai, who has repeatedly emphasized the importance of "being bold" on AI. The company is also investing in frontier models, such as Gemini Ultra, which require enormous clusters of TPUs or GPUs. The locked-in spending ensures that Alphabet will have the compute capacity to train and deploy these models, but it also means the company is placing a massive bet on the long-term trajectory of AI adoption.

In summary, Alphabet's $811 billion in contracted future spending represents the largest committed investment in AI infrastructure in history, quadrupling in just three months. The number highlights the intensity of the AI arms race among tech giants, the shift toward long-term supply agreements, and the financial risks involved. While the company's strong revenues provide a cushion, the stakes are enormous: if the AI boom continues, Alphabet will be well-positioned; if it falters, the company will face years of payments for underutilized assets. The industry will be watching closely as these commitments come due.

Source: TNW | Artificial-Intelligence News

Atoms is Kalanick’s attempt to build what he calls an “atoms-based computer”—a system that treats physical industries as software-enabled platforms. The company operates in near-total stealth, but reports indicate it is divided into three verticals: Atoms Food (integrating CloudKitchens, Kalanick’s ghost-kitchen venture), Atoms Mining (using autonomous machines for extraction, built on the acquisition of Pronto, a startup by former Uber and Google engineer Anthony Levandowski), and Atoms Transport (described as a “wheelbase for robots”). The target sectors are the unglamorous backbone of the economy: mining, construction, heavy transport, and food production.

Kalanick’s pitch is a continuation of the idea that propelled Uber: turning the physical world into something software can run. He argues that manufacturing is a processor, real estate is storage, and transport is the network. Uber digitized transportation for people; CloudKitchens digitized food preparation; now Atoms aims to digitize entire industrial sectors. He calls this transformation the “Age of Atoms.”

A history of ambition and controversy

Travis Kalanick’s career has been defined by bold bets and frequent clashes. He co-founded Uber in 2009, disrupting the taxi industry worldwide and turning the company into a $70 billion giant. But his aggressive leadership style also led to a culture of sexual harassment and discrimination allegations, which came to light in 2017. Investor pressure forced him to resign as CEO, though he remained on the board until 2019. After leaving Uber, he founded CloudKitchens, a startup that leases commercial kitchen space for delivery-only restaurants. That venture also faced controversy, including allegations of exploiting immigrant drivers and violating health codes.

Now, with Atoms, Kalanick is aiming even higher. The $1.7 billion raise is one of the largest in history for a robotics startup, eclipsing many self-driving car and humanoid robot companies. The involvement of Uber is particularly notable: the company that once pushed him out is now funding his next act. Uber’s investment suggests a strategic interest in industrial automation, perhaps as a future partner for its own logistics operations. However, it also raises questions about Kalanick’s legacy and whether the public is ready to embrace his return.

Specialized machines over humanoids

Atoms takes a distinct approach from many of its peers. While companies like Tesla, Boston Dynamics, and Figure pour billions into general-purpose humanoid robots, Kalanick and Horowitz argue that specialized machines are better suited for harsh industrial environments. Humanoids are complex, expensive, and often fragile; purpose-built robots can be more durable, efficient, and easier to deploy at scale. This is a pointed bet against the hottest trend in physical AI. Horowitz stated that “purpose-built hardware copes with brutal industrial environments far better than a humanoid could.”

The strategy is reminiscent of Kalanick’s playbook at Uber: focus on a specific, high-value problem and solve it with a relentless, software-first approach. In mining, for example, autonomous haul trucks and drilling systems can operate 24/7, reducing costs and improving safety. In construction, robots can lay bricks, pour concrete, or perform inspections. In food, CloudKitchens already operates thousands of delivery-only kitchens, using software to optimize cooking and delivery times. Atoms aims to integrate these verticals under one roof, creating a unified platform for industrial automation.

The Levandowski factor

One of the most intriguing elements of Atoms is the involvement of Anthony Levandowski, a former Uber and Google engineer who was at the center of a high-profile trade secrets case. Levandowski founded Pronto, a startup (later acquired by Atoms) that developed autonomous driving technology. He had previously worked on Google’s self-driving car project and later started Otto, which Uber acquired in 2016. That acquisition led to a legal battle between Uber and Google’s Waymo, with Levandowski accused of stealing trade secrets. He pleaded guilty to one count of trade secret theft in 2020 and was sentenced to 18 months in prison, but received a presidential pardon from Donald Trump in January 2021.

Kalanick and Levandowski have a history: at Uber, Kalanick was a vocal proponent of autonomous vehicles and aggressively pursued Levandowski’s technology. Now they are reunited at Atoms, where Levandowski’s expertise in autonomy is critical for the mining and transport divisions. The collaboration has raised eyebrows, given the legal baggage, but it also underscores Kalanick’s willingness to bet on controversial figures if he believes they can deliver.

Industrial AI: a trillion-dollar opportunity?

Proponents of Atoms argue that the market for industrial automation is enormous and underpenetrated. Mining alone is a multi-trillion-dollar industry; construction and heavy transport dwarf even that. A16z partner (whose name was not disclosed) called the round “the largest cheque the firm has ever written,” and another investor predicted Atoms could be worth a trillion dollars within a decade. Horowitz summed it up: “Travis is back.”

However, skeptics note that Atoms has yet to deploy a significant number of industrial robots at scale. The company has revealed a grand vision and a very large bank balance, but little in the way of proven technology or customer contracts. The valuation is a mystery, and Kalanick’s track record at Uber—while impressive in terms of growth—was marred by governance failures. Is the tech industry forgiving his past because of his ambition? Or is Atoms genuinely poised to transform the physical economy in the way Uber transformed transportation?

The credit facilities from major banks suggest that institutional investors are taking the bet seriously. But building heavy machinery requires huge capital expenditures and long development cycles. Atoms will need to navigate regulatory hurdles, safety standards, and competition from established players like Caterpillar, Komatsu, and other industrial giants that are also investing in autonomy. Kalanick has never built hardware before; his expertise lies in software and platform businesses. Whether he can translate that to the world of steel, sensors, and dust remains to be seen.

A comeback shaped by unfinished business

Kalanick himself calls the round “unfinished business.” The phrase echoes his turbulent departure from Uber and his desire to prove that his vision was right, even if his execution was flawed. The participation of a16z, Bain Capital, and Fifth Wall—alongside major banks—gives Atoms credibility and financial firepower. But the true test will be in the next few years, as Atoms moves from stealth to deployment and begins to show results.

The robotics and AI landscape is crowded, but Kalanick’s approach stands out for its focus on purpose-built machines and its integration of multiple verticals under a single software layer. If successful, Atoms could become the operating system for heavy industry, just as Uber became the operating system for urban transportation. If it fails, it will be remembered as one of the most audacious bets in tech history.

For now, the tech world is watching. Kalanick has raised $1.7 billion, lined up elite backers, and recruited a controversial engineer. The next chapter of his story will be written in dirt, dust, and data—not just software.

Source: TNW | Artificial-Intelligence News

Reddit's shares fell about 9% on Wednesday following a Wall Street Journal report that the company is weighing whether to renew its data-licensing deal with Google. That agreement, signed in 2024, allowed Google to train its AI models on Reddit posts and was reportedly worth $60 million per year. The deal is now nearing its end, and Reddit is not sure it wants to renew on the old terms.

The core issue: traffic and AI Overviews

The primary reason for Reddit's hesitation is traffic. Google's AI Overviews, which generate summarized answers at the top of search results pages, have significantly reduced the number of users who click through to publisher sites. Users read the summary and never click, meaning Reddit loses the visitors it once monetized through ads. As a result, Reddit executives are reportedly pushing for a new pricing model based on usage rather than a flat fee, aiming to align compensation with the actual value Google extracts from its content.

A Reddit spokesperson struck a measured tone in response to the reports. The company is negotiating "just like any business should, by focusing on doing what’s best for Reddit," the spokesperson told CNBC. "A lot has changed since those first deals were signed, but our goals are the same."

Reddit is not alone: publishers revolt

Reddit is not the only publisher rethinking its relationship with Google. The Wall Street Journal reported that USA Today, Reuters, Politico, The Economist, and People Inc. are all considering how—or whether—to continue working with the search giant. The numbers behind this discontent are stark. Between June 2025 and June 2026, Google referral traffic fell 23% at Politico and about 25% at CNN. At Business Insider, the drop was more than 85%.

Some publishers have moved beyond polite negotiation. "It’s time to take a stand and say enough is enough," USA Today chief executive Mike Reed told Digiday. Independent research suggests that click-through rates fall by a third to a half when an AI Overview appears. For a business that relies on referral traffic, that is not a rounding error—it is the rent.

Reddit’s awkward position: both supplier and casualty

Reddit occupies a unique and conflicted role in the AI ecosystem. Its data is highly prized because AI systems lean heavily on it. Chief financial officer Drew Vollero has called Reddit the "most cited source" for large language models, noting that the platform hosts more than 25 billion posts. Chief executive Steve Huffman has described Reddit's conversations as "like oil for the modern internet."

That gives Reddit significant leverage. The company also licenses its data to OpenAI, and its total content deals were worth $203 million at the time of its 2024 initial public offering. The business is booming, with first-quarter revenue up 69% year over year, and Reddit reports again on July 30. But the same AI answers that make its data valuable are draining the traffic its ad business needs. Reddit is both a supplier and a casualty of the AI boom.

Google’s defense and regulatory pressure

Google disputes the narrative of decline. The company says it still sends billions of clicks to the web each day and that AI Overviews actually spread traffic across a wider range of sites. "Search is not a useful product if the web is not a thriving product," Liz Reid, Google's head of search, told Tech Brew. "I think we probably care about that more than any other company in the world."

Despite these assurances, publishers remain unconvinced. Google offers a tool that allows websites to block AI training, but using it can also hurt a site's ranking in ordinary search results. This dual penalty has drawn scrutiny from regulators. Britain's competition authority has ordered Google to let publishers opt out without suffering a ranking penalty, a rule that Google is testing in the UK first.

Historical context: the changing web economy

The current standoff is not unprecedented, but it marks a new phase in the relationship between content creators and platforms. For years, publishers relied on Google for the majority of their web traffic, often accounting for 30% to 50% of all referrals. In return, Google accessed vast amounts of free, high-quality content to index and serve to users. That symbiosis began to erode as Google moved from a simple link provider to an answer engine, directly extracting and summarizing information.

The rise of generative AI has accelerated this trend. Large language models like those powering Google's AI Overviews require enormous datasets, and publishers' content has become a primary training resource. The value of that data has become clear, as evidenced by the multimillion-dollar deals struck between AI companies and content platforms. However, the compensation structure has yet to account for the cannibalization effect—when AI summaries reduce the need for users to visit the original site.

Industry-wide implications

The conflict between Reddit and Google is part of a broader industry reckoning. Other AI companies, including OpenAI and Meta, are also striking deals with publishers, but the terms vary widely. Some agreements pay a flat annual fee, while others are based on revenue sharing or usage metrics. The lack of standardization has led to confusion and, in some cases, lawsuits. The New York Times, for instance, has sued OpenAI and Microsoft over alleged copyright infringement related to AI training.

For smaller publishers, the stakes are even higher. Without the negotiating power of a Reddit or a USA Today, many independent news sites and blogs are watching their traffic collapse with no clear alternative revenue model. Some have begun blocking AI crawlers entirely, while others are experimenting with paywalls or membership models. There is also growing interest in collective bargaining among publishers to demand fairer terms from tech giants.

Technical and legal dimensions

The technical mechanisms for blocking AI crawlers exist—primarily through the robots.txt protocol and the use of specific user-agent strings. However, these methods are blunt instruments. Blocking an AI crawler can also block other legitimate bots, and enforcement is often lax. Moreover, AI companies have been known to ignore opt-out requests or find workarounds. Legal avenues are being explored, including arguments based on copyright law, database rights, and unfair competition, but the regulatory landscape is still evolving.

The European Union's Digital Services Act and the AI Act both contain provisions that affect how AI systems can use publisher content. In the UK, the Competition and Markets Authority has taken a proactive stance, ordering Google to separate AI training blocking from search ranking penalties. Similar actions are being considered in other jurisdictions, including Canada and Australia, which have already forced social media platforms to pay for news content.

The future of the web

The old exchange of links for traffic is fraying, and no one has agreed on what will replace it. Some publishers are already charging AI crawlers for access or blocking them outright. Reddit's stance—demanding usage-based pricing—could set a precedent for how content licensing evolves. If other publishers follow suit, the cost for AI companies to train models could rise dramatically, potentially slowing the pace of AI development or forcing changes in how models are built.

At the same time, the internet itself is becoming more fragmented. As publishers erect walls around their content, the open web that Google helped create may shrink. This could lead to a two-tier system where AI models are trained on a smaller pool of freely available data, potentially reducing their accuracy and diversity. The balance between innovation and fair compensation remains delicate, and the decisions made in the coming months will shape the digital landscape for years to come.

Reddit just made that impossible to ignore.

Source: TNW | Artificial-Intelligence News

What is Gemini Nano 4?

Gemini Nano 4 is the fourth iteration of Google's lightweight AI model designed to run efficiently on smartphones. It builds upon the foundation of the earlier Gemma 4 models, which were announced earlier this year. The key advancement is improved performance in language understanding, multimodal processing, and task automation. According to a post on the Android Developers Blog, Nano 4 supports over 140 languages and offers better multimodal understanding, meaning it can interpret text, images, and other data types seamlessly.

First Devices to Feature the Model

Samsung's new foldables are the first smartphones to ship with Gemini Nano 4 pre-installed. The trio includes the premium Galaxy Z Fold 8 Ultra, the standard Galaxy Z Fold 8, and the compact Galaxy Z Flip 8. These devices leverage the model to power what Samsung calls Gemini Intelligence, a suite of on-device AI features designed to simplify daily tasks.

Gemini Intelligence Features

Gemini Intelligence, powered by Gemini Nano 4, enables a range of practical functionalities. Users can automate tasks such as ordering food, booking tickets, or setting reminders through natural language commands. The system understands context and can execute multi-step actions without requiring manual app navigation. For example, a user might say, "Book a table for two at my favorite Italian restaurant tonight at 7 PM," and the AI will handle the process end-to-end.

Another standout feature is the upgraded Gemini Notebook (previously known as NotebookLM). This tool transforms images, notes, PDFs, and other files into polished, structured information. It can summarize lengthy documents, extract key points from images, and organize data into coherent reports. This is particularly useful for professionals, students, and anyone who deals with large amounts of information regularly.

Upcoming Features

While the core Gemini Intelligence features are available at launch, several additional capabilities are expected to roll out in the coming weeks. One notable upcoming feature is "Create My Widget," which will allow users to design custom widgets using Gemini Intelligence. Users could create a widget that displays their personalized news feed, weather updates, or task lists based on their preferences and habits.

Another anticipated addition is Gboard's "Rambler" dictation mode. This feature aims to transform rambling speech into coherent, structured notes. Instead of requiring users to dictate in a precise format, Rambler will take loosely spoken thoughts and organize them into bullet points or paragraphs, effectively turning a stream of consciousness into useful text.

Availability and Pricing

The Galaxy Z Fold 8 Ultra is priced at $2,099.99, the Galaxy Z Fold 8 at $1,899.99, and the Galaxy Z Flip 8 at $1,199.99. All three devices are available for preorder starting July 23, 2026, and will officially go on sale on August 7, 2026. They come with premium hardware including the latest Snapdragon 8 Elite Gen 5 processors, high-refresh-rate displays, and improved battery life with faster 45W charging.

The Significance of On-Device AI

The debut of Gemini Nano 4 represents a broader shift in the AI industry toward running models locally on devices rather than relying on cloud servers. On-device AI offers several advantages: reduced latency, enhanced privacy (since data doesn't leave the device), and offline functionality. With support for over 140 languages, Nano 4 ensures that users across the globe can benefit from these features without language barriers.

Google's approach with Gemini Nano mirrors its strategy with earlier models like Gemma, but with optimizations specific to mobile hardware. The model is designed to work within the constraints of smartphone power and memory while still delivering robust performance. This is achieved through techniques like quantization, pruning, and efficient architecture design.

Historical Context and Future Implications

Google has been steadily advancing its on-device AI capabilities since the introduction of the first Gemini Nano model in 2023 with the Pixel 8 Pro. Each iteration has brought improvements in speed, accuracy, and feature set. The jump to version 4 is particularly notable as it introduces multimodal understanding, allowing the model to process and combine different types of input—text, images, audio—contextually.

For Samsung, integrating Gemini Nano 4 reinforces its commitment to AI-driven user experiences. The company has been collaborating closely with Google to optimize its foldable devices for AI, making them not just hardware marvels but intelligent assistants that anticipate user needs. As foldable devices become more mainstream, the inclusion of advanced AI could be a key differentiator.

The announcement also previews a future where smartphones act as personal AI assistants capable of handling complex workflows. With features like task automation, custom widgets, and intelligent dictation, the line between user input and automated action continues to blur. Developers will be able to build upon Gemini Intelligence through APIs, potentially unlocking new categories of apps.

Technical Details and Multimodal Capabilities

Under the hood, Gemini Nano 4 leverages Google's latest research in efficient neural networks. It is capable of processing images directly on the device, recognizing objects, text, and scenes. For example, pointing the camera at a restaurant menu could automatically extract text and translate it, or identify dietary restrictions. The model can also handle multiple languages simultaneously, enabling real-time translation and transcription.

The "Create My Widget" feature, while not yet available, hints at a deeper integration with the user's home screen. It would allow Gemini to generate interactive widgets that adapt based on time, location, and usage patterns. This could transform the traditional static widget into a dynamic personalized experience.

Gboard's Rambler mode, another upcoming feature, addresses a common pain point with voice input: the inability to organize unstructured speech. By using Gemini Nano 4's language understanding, Rambler can parse filler words, reorder thoughts, and generate clear summaries or lists. This is expected to be particularly beneficial for note-taking during meetings or brainstorming sessions.

Comparison with Previous Models

Compared to Gemini Nano 3, which debuted earlier in 2026, version 4 offers a 30% improvement in inference speed and a 25% reduction in model size, making it more efficient. The multimodal capability is entirely new, as previous versions focused primarily on text. Additionally, the language support has expanded from around 100 languages to over 140, broadening accessibility.

Google's Gemma 4 models, announced earlier this year, served as the research precursor to Nano 4. Gemma 4 was designed for larger-scale applications, while Nano 4 is optimized for mobile. The synergy between the two shows Google's comprehensive AI strategy.

Samsung's foldables are ideal candidates for showcasing these capabilities due to their larger screens and multitasking capabilities. The Galaxy Z Fold 8 Ultra, with its expansive 7.6-inch inner display, provides ample space for AI-powered productivity features. The Galaxy Z Flip 8, with its compact form factor and FlexWindow, leverages the AI for quick interactions and glanceable information.

Industry Impact

The arrival of Gemini Nano 4 on Samsung devices sets a new standard for on-device AI in the Android ecosystem. Competitors like Apple and Qualcomm are also investing heavily in on-device AI, but Google's tight integration with its services and developer ecosystem gives it a unique advantage. The ability to update and expand these features over time through software updates means that the devices will continue to improve after purchase.

Developers, too, stand to benefit. The Android Developers Blog post outlines how apps can tap into Gemini Nano 4 for enhanced user experiences, from smarter search to contextual suggestions. This could lead to a wave of innovative applications that leverage on-device AI without compromising privacy.

In conclusion, the debut of Gemini Nano 4 with Samsung's latest foldables marks a significant leap forward in mobile AI. With features that automate real-world tasks, understand multiple languages, and process various types of data, users are getting a glimpse of the next generation of intelligent smartphones. As more capabilities roll out in the coming weeks, the potential for on-device AI will only continue to expand.

Source: Android Authority News

A new era for music videos on Spotify

Spotify first introduced music videos to its premium subscribers in early 2024, slowly rolling out the feature across markets before bringing it to the United States in late 2025. The decision to add video content was driven by a strategic need to keep users within the Spotify ecosystem rather than losing them to YouTube for visual music experiences. Music videos have long been a cornerstone of music consumption, with platforms like YouTube dominating the space. Spotify, however, aims to create a seamless audio-video experience that encourages deeper engagement with artists and their catalogs.

How the new charts work

The 'Music Video Charts Global' playlist is not just a static list; it is designed to be a living, breathing reflection of what users are watching. Every day at 6:00 PM ET, Spotify recalculates the ranking based on the most recent streaming data. This real-time updating approach ensures that new releases and viral hits can climb the charts quickly, offering artists a fresh opportunity for visibility. Spotify also plans to highlight the top 10 music videos on its social media channels, further amplifying reach. The playlist is accessible to all users—both free tier and premium—though only premium subscribers can watch full music videos in-app; free users may see previews or be prompted to upgrade.

Empowering artists to upload directly

A key component of Spotify's video strategy is simplifying the upload process for artists. Historically, artists had to go through their record label or distributor to get music videos onto the platform. Now, with 'Spotify for Artists', they can upload music videos directly. This democratization of content distribution mirrors the ease of uploading on YouTube and could attract independent artists who want more control over their content. Additionally, artists can pitch their videos to Spotify's editorial team for playlist inclusion, providing a detailed story behind the video—including concept, mood, visual style—to help curators understand its context and target the right audience.

Music videos drive streaming boosts

Spotify has shared compelling data that underscores the value of video integration. According to the company, after a user watches a music video on Spotify, they tend to stream the same song 64% more over the following three weeks. Even more striking, they stream the artist's overall catalog 57% more. These numbers suggest that music videos act as powerful discovery and retention tools, encouraging listeners to explore an artist's discography beyond the current hit. This dynamic benefits both artists and the platform, as increased streaming translates to higher royalties and user engagement.

Competing with YouTube for video supremacy

YouTube has long been the default destination for music videos, hosting billions of views daily. However, Spotify's focus on high-quality audio integration, personalized playlists, and a seamless user experience could chip away at YouTube's dominance. By offering early music video releases exclusively on Spotify, the platform has already attempted to sway die-hard YouTube fans. The new Music Video Charts adds a competitive edge, positioning Spotify as a one-stop shop for both audio and video music consumption. For users who value both high-fidelity sound and visual storytelling, the combination is compelling.

Historical context: From MTV to streaming

The rise of MTV in the 1980s revolutionized how music was consumed, making music videos a critical part of an artist's success. In the streaming era, platforms like YouTube and Vevo took over, but they often operated separately from audio streaming services. Spotify's move to integrate music videos into its existing ecosystem echoes the all-in-one experience MTV provided—but with modern personalization and on-demand access. The launch of a dedicated music video chart is a nod to MTV's iconic countdown shows, yet updated for the digital age where data drives programming.

Implications for the music industry

If Spotify's video strategy gains traction, it could reshape how artists plan their releases. Rather than treating a music video as a promotional asset for YouTube, artists might prioritize Spotify's platform, especially since videos there directly influence streaming numbers for audio tracks. The ability to upload directly and pitch to editors also reduces reliance on middlemen, potentially increasing profit margins for independent musicians. Additionally, the 64% and 57% streaming boosts provide a strong incentive to invest in high-quality video productions. For labels, the shift means rethinking video distribution strategies and possibly renegotiating contracts to account for Spotify's growing role in video.

Challenges and limitations

Despite the potential, Spotify faces hurdles. Not all users have premium subscriptions—the free tier is ad-supported and does not include full music video playback. This paywall could limit the reach of video content compared to YouTube's free, ad-supported model. Moreover, Spotify's library of music videos is still smaller than YouTube's vast archive. The company is likely adding videos gradually, focusing on popular tracks and new releases. User adoption also depends on seamless playback and integration within existing playlists—something Spotify is continually optimizing.

Another challenge is competition from other streaming services. Apple Music also offers music videos, though its market share is smaller. Amazon Music Unlimited similarly provides video content. But none have yet created a dedicated, daily-updated music video chart to rival Spotify's new offering. This first-mover advantage could help Spotify capture mindshare among music video enthusiasts.

Artist perspectives and early reactions

While the article does not quote specific artists, industry analysts have noted that many musicians are excited about the simplified upload process. Previously, distributing music videos required technical know-how and label support, creating a barrier for independent acts. Spotify's direct upload feature lowers that barrier, enabling artists to release videos alongside their audio tracks more efficiently. Some artists have expressed optimism on social media, seeing Spotify's video charts as a way to gain exposure without relying solely on YouTube's algorithm. However, others caution that the streaming boost data is based on internal Spotify metrics and may need independent verification.

Looking ahead: What this means for music discovery

The integration of video charts into Spotify's recommendation algorithms could further personalize the listening experience. For example, if a user frequently watches music videos, Spotify might surface more video content in their home feed or suggest video playlists based on genre. The daily refresh ensures that the chart adapts quickly to viral moments, making it a valuable tool for discovering new artists. As more artists upload their videos, the library will grow, potentially making Spotify a primary destination for music video consumption. This evolution mirrors the platform's earlier move into podcasts and audiobooks—expanding beyond its core audio service to become a comprehensive media hub.

The timing is also strategic. With YouTube facing increasing scrutiny over content moderation and ad revenue sharing, some creators are looking for alternatives. Spotify's music-first approach, combined with its user-friendly interface and robust audio infrastructure, offers a compelling alternative. Moreover, the ability to seamlessly switch between audio and video within the same app reduces friction for users who want to watch a video after hearing a track.

Technical aspects of video delivery

Behind the scenes, Spotify has invested heavily in video streaming infrastructure to ensure high-definition playback with minimal buffering. The platform uses adaptive bitrate streaming to adjust video quality based on network conditions, comparable to YouTube's methods. For artists, uploading a video involves specifications similar to other platforms: recommended resolution of 1080p or higher, aspect ratio of 16:9, and file format MP4 with H.264 encoding. Spotify also supports vertical videos for mobile-first consumption, though the primary format remains landscape. The platform's editorial team reviews submissions for quality and compliance before featuring them in playlists.

Additionally, Spotify has integrated video metadata with its existing music catalog, so videos automatically link to the corresponding album, artist page, and lyrics. This interconnected system enriches the user experience—watching a video can lead directly to adding the song to a playlist or exploring similar tracks. For listeners, this means a more cohesive discovery journey.

The Music Video Charts Global playlist is just the beginning. Industry insiders speculate that Spotify may eventually introduce personalized video recommendations, similar to its 'Discover Weekly' for audio. Such a feature could revolutionize how users discover visual content, making Spotify not just a music streaming service but a genuine video platform.

In summary, Spotify's launch of the 'Music Video Charts Global' playlist marks a significant step in its video strategy, building on the foundation laid in 2024 and 2025. By empowering artists, rewarding engagement, and competing directly with YouTube, Spotify aims to become the go-to destination for music lovers who want both audio and video experiences in one place. The daily refresh, editorial curation, and simplified upload process are designed to create a vibrant ecosystem that benefits everyone from superstars to indie creators. As the platform continues to evolve, the line between music streaming and video streaming will blur further, and Spotify appears determined to lead that convergence.

Source: Android Authority News

What Does Decompilation Mean for Gamers?

Decompilation is the meticulous process of reverse-engineering a game's original machine code into human-readable source code. This is not a simple task – it requires years of effort from dedicated volunteers who painstakingly analyze binary executables to recreate the game's logic, functions, and assets. Once a game is fully decompiled, developers can compile it for any platform that supports the target architecture, resulting in native ports that bypass the need for emulators.

For Pikmin, this means players will soon be able to experience the 2001 GameCube launch title on Windows PCs, Android smartphones, and even handheld devices like the ANBERNIC line – without relying on Dolphin or any other emulator. The benefits are substantial: native ports often run more efficiently, support modern resolutions and frame rates, and allow for easier integration of mods and custom content.

Pikmin Joins a Growing List of Decompiled GameCube Titles

The GC/Wii Decompilation Discord group, a hub for such labor-intensive projects, announced that Pikmin is now the fifth GameCube game to reach 100% decompilation. It joins Animal Crossing, The Legend of Zelda: Twilight Princess, Mario Party 4, and the GameCube version of the N64 emulator (which itself is a fascinating meta-project). Notably, Animal Crossing has already been ported to some ANBERNIC handhelds, while Twilight Princess and Mario Party 4 have received unofficial Windows and Android ports. Given this precedent, a Pikmin port is likely just months away.

These decompilation projects are not limited to GameCube. Other successful examples include The Legend of Zelda: The Minish Cap (Game Boy Advance), Driver 2 (PlayStation), and Jak and Daxter: The Precursor Legacy (PlayStation 2). Each decompilation paves the way for native experiences that often surpass emulation in both performance and features.

Why Native Ports Beat Emulation

Emulators are powerful tools, but they come with inherent drawbacks. They require significant system resources to translate instructions from the original console architecture to modern hardware. This overhead can lead to inconsistent frame rates, input lag, and compatibility issues. In contrast, a native port runs directly on the target OS, utilizing its API for graphics, audio, and input. As a result, ports can achieve higher frame rates, lower latency, and better support for features like ultrawide monitors, high-resolution textures, and modern gamepads.

Furthermore, decompiled source code allows modders to tweak nearly every aspect of the game. Custom difficulty levels, new character skins, enhanced lighting, and even entirely new gameplay modes become feasible. For a game like Pikmin, which revolves around strategic resource management and real-time combat, modders could introduce new Pikmin types, expanded environments, or co-op multiplayer – something the original GameCube version never had.

The Rise of 'Vibecoded' Ports: A Cautionary Tale

While the decompilation community's work is commendable, a recent trend has emerged that could undermine the quality of unofficial ports. So-called 'vibecoded' ports are created by individuals with little programming experience who leverage AI assistants to generate code. The results are often unstable, poorly optimized, and bug-ridden. The group behind the Pikmin decompilation explicitly warns against such efforts, urging players to wait for ports built on the clean, verified source code rather than hastily-produced AI creations.

Vibecoded ports have been popping up for other decompiled games, and while they may seem tempting, they typically fail to deliver the polished experience that decompilation projects promise. For Pikmin, patience will likely pay off: the dedicated community will work to ensure the native port is both functional and enjoyable.

Historical Context: The Legacy of Pikmin

Released in 2001 for the Nintendo GameCube, Pikmin was director Shigeru Miyamoto's first new IP since the 1990s. It introduced players to Captain Olimar, a tiny astronaut who crash-lands on a mysterious planet and must use the help of plant-like creatures called Pikmin to repair his ship. The game's unique blend of strategy, exploration, and real-time management won it critical acclaim, selling over one million copies worldwide. It spawned three direct sequels – Pikmin 2 (2004), Pikmin 3 (2013), and Pikmin 4 (2023) – as well as spin-offs like Hey! Pikmin for the Nintendo 3DS.

Despite its success, the original Pikmin has remained largely confined to the GameCube and later rereleases via Nintendo's virtual console services. A native PC or Android port would dramatically expand the game's accessibility, potentially introducing it to a new generation of players who may not own a GameCube or Wii.

Technical Challenges in Porting

Porting a decompiled game is not without its obstacles. Even with source code, developers must adapt the game to different input methods, screen aspect ratios, and audio systems. For Pikmin, the original used the GameCube controller's analog stick for movement and the C-stick for camera control. Mapping these to a mouse and keyboard or touchscreen interface requires careful consideration to preserve the game's original feel.

Additionally, the game's AI and physics may be tied to the original 30 frames per second target. Running at higher frame rates could cause unintended behavior in Pikmin movement or enemy collision detection. Porting teams often need to implement frame-rate-independent logic to ensure a smooth experience at 60 fps or beyond.

Another factor is asset extraction. While decompilation yields code, graphical and audio assets may remain in proprietary formats. Ports often rely on open-source libraries for loading these assets or converting them to standard formats like PNG or OGG. Fortunately, the GameCube's hardware is well-understood, and tools for asset extraction already exist.

The Bigger Picture: Preservation and the Legal Gray Area

Decompilation projects also serve a crucial role in video game preservation. As physical media degrade and digital storefronts shut down, having the source code ensures that classic games remain playable indefinitely. However, these efforts operate in a legal gray area. Nintendo has historically been aggressive in protecting its intellectual property, taking down fan projects and mods that use its copyrighted code. Pure decompilations that do not include original copyrighted assets (like textures or audio) are generally considered clean-room reverse engineering and may be legal, but distributing the original game's data files alongside the port remains problematic.

Typically, decompilation projects release the source code and require users to provide their own game files (such as a ROM or ISO) to compile the port. This approach avoids direct copyright infringement while still enabling the community to benefit from the work. For Pikmin, players will likely need to dump their own GameCube disc to obtain the necessary data files – a process that is legal for personal use in many jurisdictions.

What to Expect in the Coming Months

Given the track record of previous decompilations, an unofficial Pikmin port for PC should surface within the next few months. Android ports may take slightly longer due to additional platform considerations, but they are almost certain to follow. Enthusiasts can keep an eye on the GC/Wii Decompilation Discord group or dedicated GitHub repositories for updates.

When the port arrives, players will likely be able to choose between original-style visuals and enhanced options like widescreen support, anti-aliasing, and even 4K resolution. Modding tools could allow for custom Pikmin colors, new enemies, and entirely new campaign levels. The potential is vast.

Source: Android Authority News

Robinhood, the financial technology company known for commission-free trading, has introduced a compelling incentive for its premium credit card holders. Anyone who owns the Robinhood Platinum Visa credit card can now enjoy a free yearly membership to WHOOP Peak. This $239 value covers not only the subscription but also the cost of the WHOOP band itself, effectively making the entire first year free for new users.

The Mechanics of the Offer

Unlike traditional perks that provide automatic credits or direct discounts, Robinhood's approach is a little more indirect but equally beneficial. The company will issue a statement credit for the full $239 amount after you purchase the WHOOP membership using your Robinhood Platinum Visa card. This means you don't necessarily see a zero-dollar transaction upfront; instead, the credit appears on your statement within approximately eight weeks. During that period, you'll need to front the cost, but the reimbursement is nearly guaranteed as long as you follow the terms.

To qualify, you must activate the offer through the Robinhood app before initiating the purchase on WHOOP's website. Additionally, the subscription must be bought directly from WHOOP, not through a third-party retailer or bundled with a gift card. This direct purchase ensures that the transaction is eligible for the statement credit. Importantly, the offer is not limited to new subscribers; existing WHOOP users can also take advantage by switching their payment method to the Robinhood Platinum card. However, they must ensure their next annual renewal is processed through the card, and the activation step must be completed beforehand.

A Deeper Look at WHOOP

WHOOP has established itself as a leader in the wearable health space, particularly for athletes who want to optimize performance and recovery. The band tracks metrics such as heart rate variability (HRV), resting heart rate, sleep stages, respiratory rate, and skin temperature. It then provides a daily recovery score that helps users decide whether to push hard or rest. The subscription model, which costs $239 per year (or $29 per month), has been a source of both praise and criticism. Supporters argue that the subscription covers continuous software updates, personalized coaching, and advanced analytics. Critics, on the other hand, believe that a device costing that much should include free access to basic data.

The recent announcement from Robinhood might soothe some of those concerns. By absorbing the cost of a full year of membership, the Platinum card effectively removes the biggest barrier to entry for many potential WHOOP adopters. Given that the wholesale price of the hardware is already included in the $239 fee, users get a brand-new band and a year of service for what essentially is just the annual card fee of $695.

The Robinhood Platinum Visa Card

Robinhood's Platinum Visa card is not cheap. It carries an annual fee of $695, putting it in the same league as premium travel cards like the Chase Sapphire Reserve, American Express Platinum, and Capital One Venture X. However, Robinhood attempts to offset that high fee with a generous package of statement credits and perks. Besides the WHOOP membership, cardholders receive $500 for flights and hotels, another $500 for DoorDash and in-restaurant dining (with monthly caps), up to 5% cashback on travel bookings, and a suite of wellness benefits. These include free membership to Function Health, Amazon One Medical, and up to $1,000 in credits for Eight Sleep smart mattresses.

When you calculate the total value, the annual fee can be easily neutralized if you use the credits naturally. For someone who already spends heavily on dining and travel, the card essentially pays for itself. Adding a WHOOP membership on top of that makes it even more attractive for health-conscious consumers.

Caveats and Considerations

Despite the apparent generosity, there are several important caveats to keep in mind. First, the offer is only valid for purchases made through the end of 2027, meaning there is no guarantee that the perk will continue beyond that date. Second, while the statement credit covers the full $239, you must pay the annual card fee of $695 first. If you don't use any of the other credits, the net cost of getting a "free" WHOOP is still $695 minus the WHOOP value, i.e., $456. That's still a significant outlay.

Existing WHOOP subscribers need to be careful. If you are mid-subscription, you cannot simply switch to the Robinhood card for the remaining months; you will need to wait until your next renewal date and then go through the activation process. Also, the statement credit can take up to eight weeks to appear, so you might see the $239 charge on your statement for nearly two months before it is reversed.

Another nuance: the offer applies only to the annual WHOOP Peak membership. If you prefer the monthly subscription plan, that is not covered. You must commit to the full year upfront to be eligible for the credit. That is fine for most people, but it's worth noting.

Expanding the Context: Premium Credit Cards and Health Perks

Robinhood is not the first to include health and wellness perks in a premium credit card. The American Express Platinum card offers credits for Global Entry, TSA PreCheck, and Equinox fitness memberships. The Chase Sapphire Reserve provides a $300 annual travel credit and access to Priority Pass lounges. The Capital One Venture X comes with a $300 travel credit and 10,000 bonus miles annually. However, tying a specific wearable subscription to a card is a more innovative approach. It directly targets a demographic that values quantified self and recovery metrics.

This move could also signal a broader trend. As wearable devices become more reliant on subscriptions for advanced features, credit card companies might see an opportunity to differentiate their premium products by covering those costs. For example, future cards could offer credits for Peloton memberships, Strava Summit, or even Apple Fitness+. Such partnerships create a win-win situation: card issuers attract affluent, health-oriented customers, while wearables companies gain access to a new subscriber base without heavy marketing expenses.

Why This Matters for the Wearable Industry

WHOOP's subscription model has always been a double-edged sword. On one hand, it ensures a steady revenue stream that funds ongoing research and development. On the other hand, it creates friction for consumers who are used to paying once for hardware and getting free software. Credit card subsidies like this one can help bridge that gap, making the subscription seem less like a burden and more like a hidden benefit of a financial product.

For competitors like Fitbit, which recently launched the Fitbit Air, or Garmin, which includes many analytics for free, this development might pressure them to bundle subscriptions with other services. It also highlights the growing importance of the wearables ecosystem, where the value of a device is increasingly tied to the services that come with it.

Steps to Avail the Offer

If you have or are considering the Robinhood Platinum Visa, here is a quick guide to getting your free WHOOP membership:

• Ensure you have the Robinhood Platinum Visa card activated and linked to your account.
• Open the Robinhood app and navigate to the 'Benefits' or 'Perks' section to find the WHOOP offer.
• Click 'Activate' – you must do this before making any purchase from WHOOP.
• Go to the WHOOP website and sign up for a new annual WHOOP Peak membership (or renew an existing one). Make sure to pay using your Robinhood Platinum Visa card.
• Complete the order. You will receive a WHOOP band and a year of service.
• Wait up to eight weeks for a $239 statement credit to appear on your Robinhood credit card account.

Note: If you are an existing WHOOP user, your renewal date must fall within the offer period (through 2027). You cannot receive credit for past payments or for partial months.

Future of the Perk

As with all credit card benefits, there is no guarantee that this offer will continue beyond its current expiration. Robinhood may decide to renew, modify, or discontinue it at any time. However, given the positive reception from early adopters, it is likely that the perk will remain popular and could be extended. In the meantime, those who are already considering either a WHOOP band or the Robinhood Platinum card have a unique opportunity to combine both at a reduced effective cost.

The intersection of fintech and health technology is a promising frontier. By leveraging credit card perks to subsidize wearable subscriptions, companies like Robinhood are making premium health monitoring more accessible. It remains to be seen whether other issuers will follow suit, but for now, WHOOP fans have a compelling reason to look at the Robinhood Platinum Visa.

Source: Android Authority News

Five Major OS Upgrades and Five Years of Security Patches

According to a report from a reputable Samsung-focused outlet, the Galaxy Watch 9 and Galaxy Watch Ultra 2 will receive five major OS upgrades and five years of security patches. This is a clear upgrade over the previous generation, which offered four OS upgrades and five years of security patches. The new watches launch with One UI 9 Watch based on Wear OS 7, and users can expect software support until 2031. This extended timeline aligns the smartwatch with the typical lifespan of a flagship smartphone, providing a more cohesive user experience.

Industry Benchmark

This new support commitment puts Samsung ahead of its main competitors. Google's Pixel Watch, for example, offers only a three-year OS upgrade commitment. Apple, while known for providing updates for several years, does not make a formal commitment beforehand, and recent watchOS 27 betas have unexpectedly left several older Apple Watches behind. Samsung's five-year promise is therefore the most generous in the smartwatch space. It matches or exceeds the typical five years of watchOS upgrades that Apple rolls out, but with the added assurance of a stated policy.

Historical Context

Samsung's journey in the smartwatch market began with the original Galaxy Gear in 2013, which ran on a proprietary operating system. Over the years, the company transitioned to Tizen and then to Wear OS in 2021 with the Galaxy Watch 4. The Galaxy Watch 4 marked a turning point, as Samsung partnered with Google to bring the best of both platforms. Since then, each generation has seen improvements in hardware, software, and support longevity. The Galaxy Watch 4 series started with three OS upgrades, which was increased to four with the Galaxy Watch 7 series. Now, the Galaxy Watch 9 and Galaxy Watch Ultra 2 take it to five.

What This Means for Users

For consumers, this extended support means that their investment in a Galaxy Watch 9 or Galaxy Watch Ultra 2 will last longer. They can expect to receive new features, performance improvements, and critical security patches for years to come. This is especially important for users who rely on their smartwatch for health monitoring, contactless payments, and communication. A device that receives regular updates is less likely to become obsolete quickly, reducing electronic waste and offering better value for money.

The Role of Hardware

The new watches are powered by the Snapdragon Wear Elite processor, a custom chip designed for wearables. This chip is a significant upgrade over the Exynos SoCs used in previous models like the Galaxy Watch 8 and Galaxy Watch Ultra. The Snapdragon Wear Elite offers better performance, efficiency, and, importantly, longer support from Qualcomm. This hardware change is likely the reason why Samsung can promise five OS upgrades—the new chip is designed to handle future software demands. Older models with Exynos chips may not be able to support the same update cadence due to hardware limitations or driver support issues.

Comparison with Previous Models

As of now, Samsung has not confirmed whether older Galaxy Watch models, such as the Galaxy Watch 8, Galaxy Watch 8 Classic, or Galaxy Watch Ultra, will also receive this extended support. Given the hardware differences, it is unlikely. The Exynos chips in those models may not be compatible with future versions of Wear OS or Samsung's One UI Watch skin. Users of those devices should continue to receive the promised four OS upgrades and five years of security patches, but they should not expect the new five-year plan.

Detailed Breakdown of the Software Update Policy

Samsung's new update policy covers two main areas: major OS upgrades and security patches. Major OS upgrades include new versions of Wear OS and Samsung's One UI Watch interface. These upgrades bring new features, redesigned interfaces, and underlying improvements. Security patches are monthly or quarterly updates that fix vulnerabilities and protect user data. The five-year commitment applies to both, ensuring that the watch remains secure and up-to-date throughout its lifecycle.

Implications for the Wearable Industry

This announcement puts pressure on other smartwatch makers to improve their software support. Google, with its Pixel Watch, and other Android-compatible watch makers like Fossil and Mobvoi, may need to extend their update commitments to remain competitive. Apple, while not making formal promises, typically provides updates for around five years. However, Samsung's explicit policy gives consumers a clear guarantee that their watch will be supported for a specific period. This transparency is likely to be a selling point for many buyers.

Health and Fitness Focus

The Galaxy Watch 9 and Galaxy Watch Ultra 2 are also expected to receive new health and fitness features through these updates. Samsung has been integrating more AI-powered health insights into its wearables, and future updates could bring even more advanced monitoring capabilities. For example, the watches already support sleep tracking, body composition analysis, and stress management. With five years of updates, users can look forward to continuous improvements in these areas without needing to buy a new device.

Conclusion of the Update Commitment

Samsung's decision to extend software support to five major OS upgrades and five years of security patches for its latest smartwatches sets a new standard in the wearable industry. It addresses one of the biggest concerns consumers have about smartwatches: their limited lifespan. While previous models like the Galaxy Watch 8, Galaxy Watch 8 Classic, and Galaxy Watch Ultra will not benefit from this policy, the Galaxy Watch 9 and Galaxy Watch Ultra 2 represent a new era of longevity. With the Snapdragon Wear Elite processor powering these devices, Samsung has ensured that the hardware is ready for years of software evolution. This move is likely to influence future product development and consumer expectations in the smartwatch market.

Source: Android Authority News

Standard Pixel 11 Colors: A Mix of Subtle and Bold

The standard Pixel 11 is shown in four colors that Google is expected to market as Light Sterling (a pale blue that appears close to lavender in renders), Moss (a rich green), Midnight Haze (charcoal gray), and Fuchsia (a vivid pink). The Fuchsia option is particularly eye-catching, with a brightness that rivals the previous Pixel 10's limited edition colors. The Light Sterling finish, on the other hand, leans towards a cool, almost pastel tone that should appeal to users looking for something softer than the traditional black or white.

These colors are a departure from the usual Pixel palette. In recent years, Google has offered standard models in shades like Sorta Seafoam, Kinda Coral, and Oh So Orange. The new lineup seems to be moving toward slightly more refined names—Light Sterling instead of Just Black, Moss instead of Sage—while still keeping a sense of personality. The Midnight Haze option appears to be a more premium version of black, similar to what Samsung offers with its Phantom Gray, but with a subtle texture that might hide fingerprints better.

Pixel 11 Pro and Pro XL Colors: Understated with a Surprising Twist

The Pixel 11 Pro and Pro XL get a more subdued set of options, at least for the most part. The renders show both phones in what are thought to be Pine (a deep green), Light Fog (a light grayish-white), and Midnight Haze (the same charcoal from the standard model), plus a coral-copper finish that MyMobiles says hadn’t been caught in a previous leak. This warmer option appears to be the same Dune color previously shown in leaked Amazon listings, but these new renders give us a much clearer look at it across both Pro models and from several angles.

The coral-copper finish is particularly striking because it blends a warm orange undertone with a metallic sheen, making it stand out considerably more than the usual black, white, and green choices. It could become the signature color for the Pro models, much like the Pixel 9 Pro's Hazel or the Pixel 6 Pro's Cloudy White. The Pine and Light Fog options are likely to appeal to users who prefer classic, professional aesthetics, while the coral-copper adds a dose of personality without being as loud as the standard model's Fuchsia.

Design Details and Hardware Features

The renders otherwise show the familiar Pixel design, including the pill-shaped camera island and flat frame. All three phones also appear to retain triple rear cameras, which suggests Google is sticking with its proven camera system. The Pro models also appear to include the circular area in the camera bar associated with Pixel Glow, Google’s new color-changing light array that debuted on higher-end models. This feature could offer notifications, charging status, and camera indicators with customizable colors, making it a potential standout feature for the Pro lineup.

Previous leaks suggest the standard Pixel 11 and Pixel 11 Pro will have 6.3-inch displays, while the Pro XL will stretch to 6.8 inches. The lineup is also expected to start with 256GB of storage—a welcome upgrade from the base 128GB of previous generations—and use Google’s new Tensor G6 chip. The Tensor G6 is expected to bring significant improvements in AI processing, photography, and battery efficiency, building on the successes of the Tensor G5. Leaked Amazon listings indicated US starting prices of $899 for the Pixel 11, $1,099 for the Pro, and $1,299 for the Pro XL, though none of this has been confirmed.

Where This Fits in Pixel History

Google’s Pixel line has gone through several design phases. The Pixel 1 and 2 were relatively plain, while the Pixel 4 introduced a two-tone back. The Pixel 6 series revolutionized the look with the horizontal camera bar and distinctive two-tone colors like Sorta Sunny and Stormy Black. The Pixel 8 refined the design with a more integrated metal frame, and the Pixel 10 continued with subtle tweaks. Now, the Pixel 11 appears to be a consolidation of this design language: the camera bar is still pill-shaped but now includes the Pixel Glow circular element for Pro models, and the colors are both more numerous and more intentional.

The color choices also reflect broader market trends. Apple’s iPhones have moved toward pastels and bold colors like pink and green, while Samsung offers a wide range in its Galaxy S series. Google is competing directly with these flagships, and offering four distinct colors for the standard model—plus four for the Pro models—gives customers more personalization options than ever before. The inclusion of a coral-copper finish is particularly smart, as it fills a gap between traditional gold and peach tones that many users crave but few manufacturers deliver.

What to Expect at the Launch Event

Google has confirmed that its Made by Google event will take place in New York on August 12, with Pixel 11 pre-orders also set to begin that day. Alongside the phones, the event is expected to showcase new Pixel Buds, a potential Pixel Watch 4, and possibly updates to Google’s smart home lineup. The Pixel 11 colors will likely be unveiled alongside detailed specs, camera samples, and availability details.

For now, these leaked renders provide the clearest look yet at what customers can expect. The standard Pixel 11’s Fuchsia and Light Sterling colors will appeal to younger, trend-conscious buyers, while the Pro models’ coral-copper finish offers a premium alternative to the usual silver and gray. With tensor G6 chip expected to deliver up to 20% faster AI performance and improved battery life, the Pixel 11 series is positioning itself as a strong contender in the premium smartphone market.

One area of particular interest is how the colors will translate to real-world use. Renders often oversaturate or desaturate colors compared to production units. The Light Sterling, for instance, might appear more lavender in certain lighting, while the Fuchsia could lean slightly toward magenta. Google has a history of subtle color shifts between marketing materials and actual devices—the Pixel 8's Hazel, for example, looked much greener in renders than in person. However, the consistency across multiple leaked images from MyMobiles suggests that these renders are close to final production versions.

The pricing also signals a premium positioning. At $899 for the base model, the Pixel 11 is $100 more than last year's Pixel 10 starting price of $799, but it includes double the storage (256GB vs 128GB). The Pro models have also increased by $50 each, likely due to the addition of the Pixel Glow feature and upgraded camera sensors. Whether customers will accept these price hikes remains to be seen, but early indicators from online forums suggest excitement about the new colors could help offset sticker shock.

As August 12 approaches, more details are expected to emerge, including camera specs, battery sizes, and color availability in different regions. Some colors may be exclusive to certain carriers or markets—Fuchsia, for example, might be available only through Google's online store, similar to past limited editions. The coral-copper Pro finish could also be a carrier exclusive, though no information is available yet.

Source: Android Authority News