Unlike traditional trackers with a display, the Air has no screen, buttons, or speaker. The only indicator is a small LED on the side that shows battery level when double-tapped. This minimalism means you'll need to rely entirely on the Google Health app for any feedback or data. The device communicates wirelessly via Bluetooth, but it cannot receive phone notifications or show the time. For those who find smartwatches overwhelming, this is a welcome change, but it also means you must have your phone nearby to check stats during workouts.

Design and Comfort

The Fitbit Air's design is remarkably simple. The puck itself is about the size of a standard watch sensor cluster, and it snaps into a band loop. The standard Performance Band is made of a smooth polyester yarn with a Velcro closure and a metal loop. It's comfortable and durable, though it can absorb moisture, making it less ideal for intense exercise. A silicone Active Band is available for $35, which better hides the puck and is more suited for swimming. There's also a premium $50 Elevated band made of polyurethane. While the Air is lightweight and comfortable enough to wear during sleep, the cost of extra bands is steep relative to the device price.

The tracker itself has no buttons, so all interactions are done through the app. The vibration motor is only used for alarms and cannot sync with phone notifications. This is a deliberate choice for a device that aims to minimize distraction. The Air is water-resistant to 50 meters, so you can wear it while swimming, but you'll need the silicone band to keep it secure.

Sensors and Tracking Accuracy

Despite its simplicity, the Air packs most of the sensors found on high-end smartwatches, including an optical heart rate monitor, a pulse oximeter for blood oxygen, and a skin temperature sensor. It lacks an electrocardiogram (ECG) feature, which is a common omission in this price range. The data collected is fed into the Google Health app, where it generates metrics like readiness score, sleep stages, and daily activity logs. In testing, the sleep tracking accurately detected sleep and wake times, and the smart alarm functioned well. The readiness score often matched subjective feelings of energy and fatigue.

The auto-workout detection is fairly reliable, but since there's no screen, you need to pull out your phone to see live progress. The app also logs exercises based on heart rate and movement patterns. For casual users, the accuracy is more than sufficient, but serious athletes might find the lack of GPS (the Air relies on phone GPS) and real-time metrics limiting.

The Google Health App and the AI Coach

The revamped Google Health app replaces the old Fitbit interface. It's clean and offers most expected features, though long-time Fitbit users will miss some customization options and features like blood pressure tracking and custom meal creation. Google has promised updates to address these concerns. The app's main differentiator is the Health Coach, an AI powered by Gemini that provides personalized summaries, suggestions, and motivational messages. This is part of Google Health Premium, which costs $10/month or $100/year. The Air comes with three months of Premium for free.

The Health Coach is designed to be conversational and supportive. It can provide rundowns of your activity, sleep, and readiness, and it can incorporate user-provided context, such as travel or illness, into its analysis. It also cites its sources, which is helpful. However, the AI often produces verbose, overly enthusiastic responses. For example, after a good night's sleep, it might say, "You crushed your sleep goals! Keep up the amazing work!" — a tone that can feel grating over time. More concerning are occasional hallucinations: the AI might invent a workout based on a brief spike in heart rate or claim data doesn't exist when it's right there in another tab.

Google clearly wants the AI front and center, but for many users, it adds little value. The summaries often just restate what the graphs already show, and the constant encouragement becomes noise. The AI cannot replace a human coach or provide deep insights without extensive manual logging of food and activities. Free users actually get a more concise, data-rich interface without the AI commentary. If you subscribe through Google One, you get the AI by default, but you can turn it off by going to Your data in Google Health > Feature Control > Google Health Coach and flipping the switch. Even then, an "Ask Coach" button remains in the app, so the AI never truly disappears.

Comparison to Other Trackers

The Fitbit Air's main competitor is the Whoop band, which also has no screen but requires a subscription starting at $200 per year. The Air, at $100 without subscription necessity, is more affordable. However, Whoop offers deeper analytics and a more sophisticated AI coach (though also subscription-based). Other screenless trackers like the Xiaomi Mi Band (which has a tiny screen) or the Amazfit Band provide more display features at lower prices. The Air stands out for its premium build quality and seamless integration with Google's ecosystem, but it lags in features compared to similarly priced devices with screens.

One notable advantage is the ability to wear the Air alongside a Pixel Watch — both devices sync data to the same app, allowing you to use the Air for sleep tracking while wearing the watch during the day. This dual-device approach is unique to Google's ecosystem. The battery life of the Air is about a week, which is standard for screenless trackers but significantly better than most smartwatches.

The bands are a weak point. The proprietary connector for Pixel Watches has been criticized, but the Air uses a simpler snap-in mechanism. However, Google's own band prices are high, and third-party options are currently scarce. Over time, this may improve as the device gains popularity.

Overall, the Fitbit Air is a solid choice for anyone who wants a minimalistic, comfortable tracker with accurate sensors and long battery life. The hardware is well-executed, and the app provides good data visualization. The AI Health Coach, however, is a divisive feature. It tries to add value but often feels like an unnecessary layer of chatty commentary. If you can ignore or disable the AI, the Air is an excellent daily companion. But for those who want a more straightforward experience, the free version of the app is actually better. As Google continues to expand its health platform, the AI may improve, but for now, it's a feature that's easy to live without.

Source: Ars Technica News

According to Google, impersonation fraud is one of the most common types of financial scams. The Federal Trade Commission tracked nearly $3 billion in losses from such scams in 2024, and advances in AI voice cloning technology are making these schemes easier to execute. Voice models have become so sophisticated that it can be difficult to identify a fake caller, even when the AI imitates someone you talk to daily.

How the new scam detection works

Google's solution expands on the system it debuted last month for verified financial calls. Now, a similar feature works with anyone in your contacts. Many effective deepfake scams involve spoofing a contact's phone number, making the call look legitimate when your phone lights up. Victims are then greeted by an accurate recreation of the person's voice telling an urgent story that requires cash.

Google's scam call detection will be available on all phones running Android 12 or higher, but it does require three Google apps: Phone by Google, Contacts, and Google Messages. Depending on your device, you may already have these preloaded—they come standard on Pixel and Motorola phones, and Samsung has now fully switched to Google Messages. Google claims Phone by Google is the most widely used dialer, though Samsung's own phone app remains dominant given Samsung's position as the largest Android OEM.

Once these three apps are installed, they will work together to verify calls that appear to come from a known contact. Scammers impersonating a contact use an online relay to spoof the number. When a call comes in, the caller's Google dialer app sends a confirmation signal that is absent in spoofed relay calls. If that signal is missing, your phone uses the Messages app to send an authenticated RCS ping (hence the Google Messages requirement) to the supposed caller. If their phone reports it is not placing the call, a pop-up alerts you that the person on the line may not be who they seem.

There is an important caveat: both parties must have the same three Google apps installed. If a caller uses the Samsung dialer or the OnePlus contacts app, Google's scam detection won't work. This limitation could reduce its effectiveness until more users adopt Google's communication apps.

As AI spoofing makes financial scams easier to execute, regulators and public safety organizations in some countries have advised Android users to avoid using their phones for important financial transactions. This poses a problem for Android and, by extension, Google. The latest anti-scam measure joins existing protections: Pixel phones can detect likely scam calls using on-device AI to identify suspicious caller behavior, and Google Messages already offers real-time scam identification.

More AI features: fashion and image search

No Android update would be complete without additional AI capabilities. The Find the Look feature in Circle to Search, initially launched on Pixel 10 and Galaxy S26 phones earlier this year, is now expanding to all devices running Android 14 or higher. Circle to Search already lets users search for images of anything on their screen. The new layer analyzes everything in an image, primarily to identify clothing. After circling an image, users can tap the Find the Look button to identify all parts of an outfit.

Google also announced that Google Photos will soon include an AI-assisted fashion engine. This feature catalogs the clothing you wear, creating a virtual wardrobe you can browse and organize from your phone. Users can even generate AI images of themselves wearing these outfits, though it's wise to see how clothes look in real life before leaving the house.

AirDrop support expands to more Android phones

In non-AI news, Google began supporting Apple AirDrop (via Nearby Share/Quick Share) on select devices earlier this year, but support was limited. Initially, only the last few generations of Pixel devices and Samsung's latest flagship phones supported the feature. Today, Google is enabling AirDrop on a wider range of Android phones:

• Samsung: Galaxy S25, S25+, S25 Ultra, S25 Edge, Galaxy Z Flip7, Z Fold7, Galaxy Z TriFold, Galaxy S24, Galaxy S24+, Galaxy S24 Ultra, Galaxy Z Flip6, Z Fold6
• OnePlus: OnePlus 15
• Xiaomi: Xiaomi 17T Pro (announced early)
• Vivo: Vivo X300 and X300 Pro
• HONOR: Magic V6

Nothing changes on the iPhone side. Sending files from Android still requires the iPhone to be set to accept AirDrop requests from 'anyone for 10 minutes.' Contact-based sharing is not supported when sending from Android, but the feature is becoming more widespread, making cross-platform file transfers easier.

Background and implications of the scam detection feature

The rise of deepfake voice technology has made phone scams more dangerous than ever. Scammers can now clone a voice from just a few seconds of audio—often captured from social media videos or voicemail greetings. They then spoof the victim's phone number using Voice over IP (VoIP) services that display any caller ID they choose. This combination of realistic voice and familiar number makes victims more likely to comply with urgent requests for money, such as paying fake bail, covering medical expenses, or helping a 'relative' in trouble.

The FTC estimates that in 2024, impersonation scams accounted for nearly $3 billion in losses, a figure that is expected to rise as AI tools become more accessible. Traditional call authentication methods, such as STIR/SHAKEN, verify the origin of calls but do not prevent number spoofing. Google's approach adds a secondary verification step that leverages the open RCS (Rich Communication Services) standard, which is already used for enhanced messaging. By having the called party's phone send an authenticated ping, the system can confirm whether the call originated from the actual device associated with the contact's number.

However, the requirement for both parties to use Google's specific apps limits adoption. Samsung users, for example, must switch to Google Messages and the Google dialer for the feature to work. While Samsung has already replaced its own Messages app with Google Messages on newer models, many users still have the old app. Similarly, OnePlus and other manufacturers often use their own dialers and contacts apps. Google has not announced plans to open this verification mechanism to third-party apps, which could slow the feature's impact.

The expansion of AI features in Circle to Search and Google Photos reflects Google's broader strategy to integrate AI into everyday tasks. Find the Look uses computer vision to recognize clothing items and provide shopping links or style ideas. The Photos wardrobe feature scans your existing photos to build a virtual closet, then uses generative AI to create images of you in different outfits. These tools are designed to increase engagement with Google's ecosystem and encourage users to store more data in the cloud.

AirDrop support is part of a larger effort to improve cross-platform interoperability. Google's Nearby Share was merged with Samsung's Quick Share to create a unified standard, and adding compatibility with Apple's AirDrop (via the new standard) reduces friction between Android and iPhone users. As more Android devices support this feature, the need for third-party file transfer apps will diminish. However, the iPhone's contact-based sharing restriction remains a hurdle, as users must temporarily set their device to accept from anyone.

Overall, these updates demonstrate Google's ongoing push to enhance security and convenience while driving adoption of its own apps and services. The scam detection feature, despite its limitations, represents a meaningful step forward in protecting users from AI-powered fraud. Combined with existing on-device protections, it adds a layer of verification that can alert users before they fall victim to a spoofed call. As deepfake technology continues to evolve, such proactive measures will become increasingly essential for mobile security.

Source: Ars Technica News

In a quiet but significant update, Conde Nast has revised its user agreement and privacy policy with respect to its flagship tech publication, Ars Technica. The change, which applies exclusively to ArsTechnica.com, replaces the entirety of Section VI(2)(B) of the Conde Nast User Agreement with new language that dramatically expands the rights the company claims over user-generated content.

The amendment, effective immediately, grants Conde Nast a broad, non-exclusive license to use any content posted, uploaded, transmitted, sent, or otherwise made available by users on the service. The revised clause explicitly states that users retain ownership of their content, but simultaneously grants Conde Nast a “royalty-free, perpetual, non-exclusive, unrestricted, worldwide right and license” to perform a wide array of actions on that content, including reproduction, modification, editing, cropping, adaptation, translation, enhancement, reformatting, remixing, rearranging, resizing, creating derivative works, moving, removing, deleting, erasing, reverse-engineering, storing, caching, aggregating, publishing, posting, displaying, distributing, broadcasting, performing, transmitting, renting, selling, sharing, sublicensing, syndicating, or otherwise providing to others, using, or changing the content. The license also extends to any ideas, suggestions, developments, and inventions that users post, and Conde Nast may use them for any purpose related to the service or its promotion, including commercial purposes, without compensation or attribution.

Understanding the Scope of the New License

The key phrase in the new section is “on or in connection with the Service, or the promotion thereof.” This language is broad and open to interpretation. While it might seem to limit the company's use to activities directly tied to Ars Technica, the inclusion of “promotion” significantly widens the potential applications. For example, Conde Nast could use user comments, forum posts, or even letters to the editor in marketing materials, social media campaigns, or advertisements without seeking permission or paying the original author. The company can also create derivative works, such as compiling user insights into a report or using a user's suggested headline as part of an editorial piece.

This type of license is common among large content platforms, but the breadth of actions listed is notable. The inclusion of “rent, sell, share, sublicense, syndicate” means Conde Nast could potentially package user content for distribution to third parties, perhaps as part of a data bundle or content feed. For a tech publication like Ars Technica, which often features detailed technical discussions and expert commentary, this raises concerns about the value of user contributions being siphoned for corporate gain.

Historical Context of User Agreements

User agreements have evolved significantly since the early days of the internet. In the late 1990s and early 2000s, many platforms operated with far more permissive terms, expecting users to retain full control over their contributions. The rise of social media and user-generated content platforms like YouTube and Twitter brought about more aggressive licensing clauses, as companies sought to monetize the vast amounts of content posted daily. Lawsuits and public outcry led to some modifications, but the core tension remains: platforms need legal protection to operate, but users expect their content not to be exploited without fair compensation or credit.

Ars Technica, known for its deep-dive reporting and passionate community, has historically maintained a relatively hands-off approach. This amendment marks a shift toward the more standard industry practice, aligning with the policies of its parent company, Conde Nast, which also owns publications like The New Yorker, Vogue, and Wired. For Conde Nast, unifying terms across its portfolio simplifies legal compliance, but for Ars Technica readers, the change may feel jarring.

Implications for Users

For the average Ars Technica reader who occasionally posts a comment, the practical impact may be minimal. The company is unlikely to scan every comment for commercial value. However, power users—those who contribute detailed analyses, tips, or even original reporting in the forums—should be aware that their contributions can now be repurposed without additional consent. The revised agreement advises users to “make copies of or otherwise back-up any and all Content, personal data or communications” they post, because once submitted, the platform has full control.

The removal of any requirement for attribution is particularly concerning for professionals who use the site to build their reputation. A tech blogger, for instance, might write an insightful piece in a comment thread, only to see it later published under an Ars Technica staff writer's byline with no credit. While the site's editorial standards likely prevent such behavior, the legal terms now permit it. Furthermore, the clause includes “communications” made through the service, which could cover private messages sent via the platform's messaging system. This raises privacy concerns, as users may not expect their private conversations to be used for commercial promotion.

Comparison with Other Platforms

To put this in perspective, it's useful to compare Conde Nast's new terms with those of other major content platforms. Reddit’s user agreement, for example, grants the company a “worldwide, perpetual, irrevocable, non-exclusive, royalty-free, transferable, and sublicensable license to host, store, cache, serve, use, reproduce, modify, adapt, publish, transmit, display, perform, distribute, and prepare derivative works” of user content for the purpose of operating and improving the service. This is similar in breadth but often includes an explicit statement that the license is solely for operating the service. Conde Nast's addition of “promotion thereof” goes a step further.

YouTube’s terms are also expansive, but the platform's monetization model is more transparent: creators can earn revenue from their content. Ars Technica does not offer such a program for user-generated content. Facebook and Twitter (now X) have similar broad licenses, but they have faced significant pushback regarding data usage and content ownership. In the wake of the Cambridge Analytica scandal, many platforms amended their terms to tighten data protection, but content licensing remains largely unchanged. Conde Nast's amendment seems to be a preemptive move to secure maximum flexibility in an era where content is increasingly valuable for data training and AI development.

The Role of AI and Data Training

One of the drivers behind such expansive licensing could be the growing demand for training data for artificial intelligence models. User-generated content, especially from a knowledge-focused site like Ars Technica, can be a rich source for improving natural language processing or knowledge retrieval systems. By securing the right to reproduce, modify, and create derivative works, Conde Nast could legally scrape user content to train internal AI assistants, generate automated summaries, or even produce articles in the style of users. While there is no evidence that this is the company's intention, the legal door is now open.

This aligns with a broader industry trend. In 2023, several major publishers faced backlash for using their own back catalogues to train AI without explicit creator consent. By amending the user agreement now, Conde Nast may be seeking to avoid similar legal challenges. Users who post technical insights or original analysis might inadvertently contribute to AI systems that could one day replace the very human expertise that defines Ars Technica.

Legal and Ethical Considerations

From a legal standpoint, the revised clause is likely enforceable under current US contract law. Users accept the terms by using the website, and there is no requirement for explicit agreement beyond continued use. However, ethical questions abound. The lack of compensation or attribution for commercial use may discourage high-quality contributions. The Ars Technica community is known for its knowledgeable and often critical readership; if users feel their contributions are being exploited, they may retreat from public discussions, diminishing the site's value.

Moreover, the clause applies retroactively to all content posted before the amendment. This is a controversial practice, as users who posted under the previous terms may feel deceived. Some legal experts argue that such retroactive changes could be challenged, but the prevailing view is that the new terms govern from the date of update onward, and the license for existing content is deemed accepted if users continue to use the service.

What Users Can Do

Users who are uncomfortable with the new terms have several options. The simplest is to stop posting content on Ars Technica entirely. This may be the only way to avoid the license, as the terms apply to any “communication” made through the service. Alternatively, users can delete their existing content before the clause takes effect, but the agreement states the license is granted upon posting, so this may not fully revoke the rights. A better approach is to carefully consider the content one shares and to avoid posting sensitive or highly valuable original material.

Some users may choose to voice their concerns to Ars Technica's editorial team or to Conde Nast directly. Public pressure has led to policy reversals in the past. For example, in 2017, the social news website Digg faced backlash for a similar licensing clause and subsequently clarified that it would only use user content for service improvement. Still, given the consolidated nature of modern media, such changes are unlikely unless a significant portion of the user base actively protests.

Broader Implications for Digital Rights

This amendment is part of a larger narrative about the balance of power between users and platforms. As internet companies consolidate and seek new revenue streams, user agreements become longer and more complex, often eroding rights that users once took for granted. The Ars Technica community, being technically literate, is well-positioned to understand these changes and to engage in the debate. The outcome of this policy shift could set a precedent for other Conde Nast publications and beyond.

In an era where content is currency, users must remain vigilant. The new license is a reminder that digital contributions are rarely free—they come with strings attached. By understanding the terms, users can make informed choices about their participation. The knee-jerk reaction for many might be to ignore the update as legal fine print, but for anyone who values their intellectual property, this amendment deserves a close read.

Source: Ars Technica News

Panellists said the question is no longer whether AI should be governed, but how quickly governments, industry and society can build systems of accountability that can keep pace with the technology.

Waiting for a major AI-related disaster before acting would be a serious mistake, warned Stuart Russell, distinguished professor of computer science at the University of California, Berkeley. He drew a comparison with the Chernobyl nuclear accident, saying that "without safety, there are no benefits".

"If there is a Chernobyl-scale disaster with AI, it's not just going to be a regulatory response; it's going to be a societal response. People will say, 'shut it down'. All of those trillions of dollars that we hear about being invested will be wasted," he said.

That urgency was echoed by Karan Bhatia, global head of government affairs and public policy at Google. He suggested the need for a revolution in how government and industry work together to face these challenges.

"The technology is moving far too fast for traditional methods of governance to be applicable," said Bhatia. He called for "a constant, regular level of interaction going on between regulators and industry – everything from identifying trends in threats and opportunities, intel sharing on a constant basis, to steady iteration on what the regulatory possibilities might be".

For Elham Tabassi, director of the AI and Emerging Tech Initiative at the Brookings Institution, the answer is to build AI governance into the development process from the start, ensuring systems are trustworthy by design.

"We cannot keep treating governance as something we check only after an AI system is already built or released. Governance must be part of the design, development, deployment and monitoring process," she said.

Practical safety steps

Even though AI governance is still lagging behind the technology, there are practical safety steps that governments can take immediately, said Ya-Qin Zhang, chair professor of AI science and founding dean of the Institute for AI Industry Research at Tsinghua University.

He said AI governance can learn from safety practices in the aviation, nuclear power and pharmaceutical industries. He pointed to measures such as labelling AI-generated content, registering AI agents and preventing uncontrolled agent self-replication.

Russell added that AI governance should follow the same basic principles used in sectors such as medicine, aviation and nuclear power, with "the onus on the developer" to provide evidence that their systems are safe enough for use.

Current AI evaluation methods are struggling to keep up with the technology, according to Tabassi.

"The evaluation basis is thin," said Tabassi, noting that the evidence from current AI testing is not deep or reliable enough. While pre-release testing remains important, she warned that benchmarks do not always predict how AI systems will behave in real-world settings, especially when models and agents may behave differently during tests.

She argued that AI governance must move from one-time certification to continuous evidence-gathering.

"Pre-release testing and pre-deployment testing are important, but that type of evidence needs to continue via continual monitoring of the systems post-deployment, incident reporting, and observing behaviour in the wild rather than just in the laboratory," said Tabassi.

Rebecca Finlay, CEO of the Partnership on AI, agreed that testing AI before release is important, but is not enough. There is a need to understand what happens after AI is used in the real world.

While she noted some progress in areas such as usage data and labour market impact analysis, she warned that incident reporting and environmental disclosures remain difficult to compare without common standards. Greater transparency, she argued, must be matched by clearer measurement frameworks so that policymakers, companies and the public can understand AI's real-world effects.

Historically, technological revolutions have often outpaced regulation. The Industrial Revolution saw child labor and unsafe factories long before labor laws were enacted. Similarly, the rise of the internet led to privacy scandals and misinformation before data protection regulations like GDPR emerged. With AI, the stakes are even higher because the technology can make autonomous decisions that affect lives, livelihoods, and national security.

The warnings from the conference come against a backdrop of rapid AI advancement. In recent months, generative AI models have become more sophisticated, capable of producing human-like text, images, and even video. Agentic AI, which can plan and execute long chains of actions autonomously, is now moving from research labs into commercial use. This has intensified calls for governance frameworks that can adapt quickly.

Several countries have started to develop AI regulations. The European Union's AI Act, for instance, classifies AI systems based on risk and imposes requirements on high-risk applications. However, critics argue that such frameworks are already outdated because they were designed before the rise of powerful generative and agentic systems. The United States has taken a more sectoral approach, with executive orders and agency guidance, but lacks comprehensive federal legislation. China has implemented some of the most specific AI regulations, including rules on algorithm recommendation and deep synthesis, but enforcement remains challenging.

International cooperation is also a critical theme. AI systems are global in scope, often trained on data from multiple countries and deployed across borders. A patchwork of regulations could lead to regulatory arbitrage, where companies move operations to jurisdictions with weaker rules. The experts at the conference stressed the importance of global convergence on core safety standards, even if implementation details vary by country.

New challenges with agentic AI

Zhang pointed out that many current evaluation methods are no longer useful as the technology moves from generative AI to agentic AI, because "previously, most of the research tools and evaluation were optimised for pre-training".

With complex, long-range capabilities, he said an agent can autonomously implement thousands of steps over 20 or 30 hours, making testing more difficult because "everything is dynamic".

Tabassi agreed that agentic AI cannot be evaluated in the same way as traditional language models, as it presents a far more complex governance challenge.

"Agentic AI and agents act, plan, orchestrate, and then operate in an environment where the environment itself changes in reaction to them," said Tabassi. In contrast, she noted that large language models (LLMs) can usually be evaluated simply by comparing inputs and outputs.

She warned that agents may also behave differently when they know they are being tested, making their real behaviour harder to measure.

Finlay said organisations need clearer ways to determine when AI agents should be monitored and at what level. She said companies can begin by assessing three factors: the stakes of the task, whether the agent's actions can be reversed, and what access or permissions the agent has been given.

Bhatia noted that AI governance is difficult because AI is global, and different countries may set different rules. He warned that if countries adopt very different guardrails, companies may shift activity to jurisdictions with more favourable rules. While he supported global convergence around shared standards, he said each country will likely balance risk and innovation differently as they compete to attract AI investment and development.

"Companies should begin with lower-risk pilots before moving into more high-risk, multi-agent deployments," said Finlay.

The concept of "responsible AI" has gained traction in corporate boardrooms. Many large tech companies have published AI principles, but critics argue that self-regulation is insufficient when profits are at stake. The experts emphasized that independent oversight and external validation are essential for building trust.

One of the recurring themes was the need for a cultural shift in how engineers and product managers approach AI development. Instead of prioritizing speed and capability, they should embed safety checks at every stage. This includes not only technical measures like adversarial testing and red teaming but also organizational practices like Ethics Review Boards and internal audit functions.

For Russell, the message was short and direct: "Don't wait for Chernobyl… Take steps now before it's too late."

Source: ComputerWeekly.com News

Dell revealed that its AI factory customer base has surged from 3,000 to over 5,000 in the past year, indicating rapid adoption of AI software and Nvidia-powered infrastructure. However, beneath this growth lies a deeper need for resilient, highly commoditized infrastructure that can handle the demands of AI workloads while remaining adaptable to global supply challenges.

Standard Chartered, operating across 54 global markets, provides a compelling example of this trend. The bank redesigned its private cloud infrastructure to achieve global scale and survive hardware shortages, according to John Sharratt, global head of infrastructure and operations. The bank operates 52 country datacentres and four global datacentres, positioning itself as a "super connector" for clients operating across borders.

To manage this vast footprint, Sharratt's team eliminated all specialized hardware components in favor of a fully virtualized, hyper-converged environment. The standard unit of scale is now the server rack itself. The guiding principles of "simplicity, commodity, and scale" required that all storage, networking, and security be hyper-converged. The bank eliminated standalone storage area networks (SANs) and physical firewall appliances, relying instead on interchangeable commodity hardware—specifically Dell servers and switches—housed within standard racks.

By avoiding highly specialized components, Standard Chartered has shielded itself from the worst of the industry's supply chain shortages. "If you have a very specialist design, you cannot substitute components if the NICs, memory, or disks are not available," said Sharratt. "By eliminating that specialization, we can literally roll a rack off the back of a lorry and have workloads running in just 24 hours."

The transition required navigating decades of technical debt, a notoriously difficult challenge in the financial services sector. Sharratt explained that the bank established an architectural review board run by engineers to systematically refactor, virtualize, and scale every legacy application. "There's always lots of legacy in a banking environment," he said. "We have resolved all that legacy. There's no physical server; it is all virtualized. We are sitting in an extremely comfortable position as a bank to ride out the supply chain problems."

Sharratt revealed that the bank's estate in Asia, which accounts for 70% of its global infrastructure footprint, is already running on this new architecture. The model is currently being deployed in the UK. "This is not a story of what we're going to do," he added. "This is a story of what we've done."

While Standard Chartered focuses on infrastructure standardization, Naver Cloud is taking a different approach by leveraging its massive domestic datacentre footprint to export sovereign AI capabilities globally. Naver, South Korea's leading IT portal and one of the few global search engines to successfully defend its home turf against Google, operates substantial infrastructure, including the multi-megawatt Gak Sejong datacentre. Having built its own generative AI model, HyperClova X, the company is now partnering with Dell and Nvidia to deploy AI factories tailored for digital sovereignty.

Kim Yu-won, CEO of Naver Cloud, noted that owning the full stack—from datacentres and graphics processing units to the underlying AI models—gives the company a unique advantage as governments and highly regulated industries look to protect their data. "In a world where sovereignty is key, we are highly flexible in giving each customer specific security and governance," said Kim. "We want to provide customers that prioritize sovereignty with a dedicated private cloud, and on top of that, we want to integrate with AI technology."

Naver Cloud is already extending this strategy beyond Korea, partnering with Thailand's Siam AI to develop a Thai large language model and launching a joint venture in Saudi Arabia to build digital twin capabilities. Kim emphasized that infrastructure and models only matter if they solve real-world problems. "Ultimately, what we want to create is unprecedented practical value that does not exist in the world today."

The broader APAC region is witnessing a surge in AI adoption across multiple sectors. According to recent industry reports, enterprises are increasingly moving from proof-of-concept projects to production deployments, driving demand for both on-premises and cloud-based AI infrastructure. This shift is being accelerated by the emergence of agentic AI frameworks, which enable autonomous decision-making and task execution within enterprise environments.

Dell Technologies' newly appointed leader for the APAC region, Richard McLaughlin, emphasized the importance of helping customers navigate supply chain challenges and chart a path to becoming AI-driven companies. "The AI ecosystem is changing as it is being embraced and created by our customers in the AI economy," said McLaughlin. "New business models, products, and services are emerging in the region as agentic frameworks become more commonplace. We're seeing the region's enterprises accelerating, advancing, innovating, and entering agent lifecycle development at pace."

McLaughlin also highlighted Dell's active role in working with enterprise clients on "demand shaping" over the next four to five years to improve supply chain resilience. This approach echoes Sharratt's sentiment that disciplined infrastructure planning is critical for long-term success. "We believe that we have the supply chain advantage in the marketplace," said McLaughlin. "We have over 40 years of relationships with suppliers to help de-risk the supply chain for our key customers."

The convergence of infrastructure standardization and sovereign AI is reshaping the competitive landscape in APAC. Companies that can successfully commoditize their datacentre operations while maintaining the flexibility to adopt emerging AI technologies are better positioned to navigate the uncertainties of global supply chains and regulatory environments. Standard Chartered's approach demonstrates that even highly regulated financial institutions can transform their legacy systems to achieve operational resilience, while Naver Cloud's strategy illustrates how domestic technological strengths can be exported to create global value.

As AI continues to mature, the focus is shifting from experimentation to execution. Enterprises are seeking scalable, reliable, and secure infrastructure that can support both current workloads and future innovations. The lessons from Standard Chartered and Naver Cloud offer a blueprint for other organizations in the region: standardize to survive, and leverage sovereignty to thrive.

Source: ComputerWeekly.com News

The fear among employees that AI will replace their jobs is palpable. In its 2025 paper, Building a pro-worker AI innovation strategy, the Trade Union Congress recommended that employers ensure meaningful worker participation at every stage of AI deployment—from strategy development and problem definition through tender, application design, and deployment. The report argues that involving workers not only addresses ethical concerns but also drives the effectiveness of technology. Yet, many organisations skip this step, leading to resistance and underutilisation.

While change management has been a staple of corporate transformations for decades, Schaffrik points out a critical difference with AI—especially generative AI. Because AI tools are so accessible and seemingly easy to deploy, the conversation often starts at the boardroom level. CEOs immediately grasp the potential for cost savings, efficiency gains, and competitive advantage, and they push implementation aggressively into their organisations. "CEOs assume that people down the line—HR teams, transformation leaders—will handle change management," Schaffrik said. However, he warned that AI directly threatens job roles, causing exponential increases in employee fear and confusion. Those tasked with implementing AI are often themselves impacted by it, creating a cycle of resistance and uncertainty.

Schaffrik also highlighted the rigidity of enterprise technology frameworks and business processes as a major obstacle. Businesses cannot simply replace a mission-critical system like payroll without careful risk assessment. "Businesses don't want to break the payroll process," he said, explaining that AI providers are often surprised when their technology fails in real-world deployments. The surprise stems from a combination of human psychology, organisational inertia, and regulatory constraints. These issues are not new, but AI amplifies them because of the speed and breadth of change it demands.

To navigate these challenges, Schaffrik advises CEOs to clearly define what AI should accomplish. He advocates automating as much repetitive work as possible using any enterprise-grade technology—workflow engines, robotic process automation, document processing, and AI agents. At the same time, leaders should target processes that are not highly repeatable but are prone to human error. For example, a legal professional comparing multiple versions of a lengthy contract may make mistakes; AI, despite its tendency to hallucinate, can perform such comparisons more reliably when properly supervised.

This is where the human-in-the-loop concept becomes essential. Schaffrik notes that employees who serve as AI output checkers must excel at the very tasks AI is taking over. A legal expert reviewing AI-generated contract comparisons must be highly skilled in contract analysis. As AI evolves, upskilling will be crucial—not only to maintain quality but also to justify higher salaries for these oversight roles. Organisations that invest in training their workforce to work alongside AI are more likely to see positive outcomes.

Historical context supports this view. The industrial revolution, the rise of the internet, and the advent of cloud computing all required significant workforce adaptation. AI represents a similar inflection point, but with a twist: it affects cognitive work as much as manual labour. Early adopters of AI in sectors like finance, healthcare, and manufacturing have learned that successful integration depends as much on culture and communication as on technology. Those that fail to address employee fears often face low adoption rates, shadow IT (where workers use unauthorised tools), and outright sabotage.

Schaffrik’s insights align with broader research. A 2024 McKinsey report found that companies with strong change management practices were three times more likely to report successful AI deployments. Similarly, Gartner has noted that through 2026, half of AI initiatives will fail due to lack of attention to human factors. The message is clear: technical excellence alone is insufficient.

For CEOs, the path forward involves several concrete steps. First, establish transparent communication about AI’s purpose and limitations. Second, involve employees early and often in design and rollout. Third, create clear career paths for workers whose roles evolve—such as from data entry to AI oversight. Fourth, invest in robust feedback loops to continuously improve AI systems based on real-world usage. Finally, partner with AI vendors that prioritise enterprise integration and human-centred design.

The AI revolution is inevitable, but its success hinges on how well organisations manage the human side of disruption. As Schaffrik’s analysis shows, businesses that ignore the human factor will continue to see their AI investments fail to deliver. By combining strategic automation with empathetic change management, leaders can turn AI from a source of fear into a driver of productivity and innovation.

Source: ComputerWeekly.com News

Embodied AI differs fundamentally from software-based AI, which processes digital data and generates outputs confined to screens or servers. By contrast, embodied systems must perceive, reason, and act in the unpredictable, noisy, and often hazardous physical world. This distinction adds layers of complexity — robots require not only intelligent algorithms but also robust mechanical design, real-time sensor fusion, and fail-safe mechanisms to avoid causing harm. The field brings together robotics, computer vision, natural language processing, and control theory, and it has captured the imagination of researchers, investors, and governments globally.

William Dally, chief scientist and senior vice-president of research at Nvidia, highlighted a key breakthrough: using AI to enable robots to perform tasks they have not been explicitly programmed for. He demonstrated a humanoid robot assembling a model car from a simple text prompt, showcasing how robotic foundation models can translate visual inputs into motor actions autonomously. Such models, trained on vast datasets of robot interactions, allow machines to generalize across tasks and environments, moving beyond the narrow, pre-scripted behaviors of traditional industrial robots.

Yet, the industry is still in its infancy, cautioned Yutaka Matsuo, a professor at the University of Tokyo. “We are not in the full adoption phase at the moment,” he said. Matsuo emphasized that better architectures, algorithms, data, compute resources, cost efficiency, and safety systems are all necessary before robots can operate reliably outside controlled settings. He pointed out that today’s robots often stumble in unfamiliar environments, struggle with object manipulation in clutter, and require significant human oversight.

The timeline for embodied AI deployment was laid out by Om Nalamasu, senior vice-president and chief technology officer at Applied Materials. He described 2024 as a proof-of-concept phase, 2025 as a year of demos, and 2026 as a period for pilots. Nalamasu noted that the industry has shifted from asking whether such systems can be built to how they can be deployed safely and reliably at scale. He stressed that for robotics to scale, systems must achieve lower latency, greater energy efficiency, and cost-effectiveness. Sensors will be critical — robots depend on sensor fusion, combining data from cameras, LiDAR, touch, and inertial measurement units — to understand and respond to the physical world accurately.

Data remains another major constraint. Unlike software-based AI models trained on internet-scale text, real-world robotics data is scarce, expensive to collect, and often requires human teleoperation or careful simulation. Nalamasu added, “We need to be thinking about standards, interoperability and the governance model,” pointing to the need for common frameworks that allow different robots and systems to work together and be certified for safety.

Real-world deployments

Despite the challenges, commercial deployments are emerging in structured environments. Zhao Yuli, chief strategy officer at Galbot, reported that the company has deployed more than 1,000 robots in China across humanoid-operated stores, logistics facilities, and pharmaceutical chains. Galbot uses a mix of real-world and synthetic data to train its systems. However, generalization remains a significant hurdle. Zhao noted that while robots perform well in known or semi-structured environments, they struggle in unfamiliar settings. As a result, Galbot is focusing first on semi-structured scenarios where robots can learn from real-world deployments incrementally.

Suthen Thomas Paradatheth, chief technology officer at Grab, highlighted that robotics — unlike software — involves significant physical concerns and “does not have near-zero marginal cost.” He explained that each robot requires hardware, maintenance, supply chains, sensors, and physical integration with buildings. Updating a robot fleet is far harder than updating cloud software, especially if new sensors or hardware modifications are needed. Grab conducts extensive testing before scaling: “Before scaling to hundreds of robots, we make sure we crack it first in simulation and with a few robots, while building a data flywheel to monitor, learn from and improve each deployment,” said Paradatheth. Establishing trust is also essential; Grab’s autonomous vehicle pilot clocked 40,000 kilometers and involved months of testing, stakeholder engagement, and community consultation before public deployment. Paradatheth stressed that the approach should begin with the customer problem, not the technology: “Fall in love with the customer problem, but don’t fall in love with the solution set.”

Public-private collaboration

The panellists also highlighted the need for public-private collaboration. In China, Zhao noted that government support has helped create testbeds, strategic projects, and long-term funding for embodied AI. In Japan, Matsuo pointed to the AI Robot Association (AIRoA), an open data initiative targeting 100,000 hours of robotics data for researchers and companies developing robotic foundation models. Such datasets are vital for training generalizable skills, and sharing data across organizations can accelerate progress while reducing duplication of effort.

Safety standards will be critical because embodied AI can affect the physical world directly — unlike purely digital AI systems, robots can cause physical harm if they fail. Matsuo suggested that Japan and Singapore, with their strong regulatory environments and advanced robotics ecosystems, could help shape global standards for safety, interoperability, and governance. Nalamasu added that progress in robotics will not be linear: advances in hardware, software, and data will reinforce one another in a “multiplicative” way. For example, better simulation tools enable faster algorithm development, which in turn informs hardware design, leading to more capable and affordable robots.

Dally stressed that embodied AI will only become practical if intelligence can run efficiently on the device itself. “We need to run them on real robots, and these can’t be tethered with an umbilical cord back to the datacentre. They have to be carrying the intelligence on them,” he said. This will require more efficient chips, software frameworks, and model architectures that can handle complex perception and control tasks within tight power and latency budgets. Nvidia, for instance, is developing specialized processors and edge computing platforms aimed at bringing large language models and vision transformers onto robots.

The promise of embodied AI remains significant. Speakers pointed to ageing populations, labour shortages, healthcare, manufacturing productivity, and city operations as key areas where the technology could deliver value. In the near term, industrial and semi-structured environments — factories, warehouses, hospitals, retail stores — are likely to lead adoption. Over time, autonomous robots are expected to move deeper into public spaces and homes, performing tasks such as delivery, cleaning, caregiving, and personal assistance. However, that future depends on sustained investment in research, cross-sector partnerships, and the development of robust safety and governance frameworks that earn public trust.

Source: ComputerWeekly.com News

Moving agentic AI from innovation theatre to enterprise production

As enterprises move beyond pilot projects, IT leaders are grappling with how to deploy agentic AI at scale. The leap from prompting chatbots to orchestrating multiple AI agents requires a fundamental rethinking of IT architecture. Data must be unified and accessible, governance frameworks must be robust, and cost management must be proactive.

One of the biggest hurdles is avoiding chaotic deployments. Without proper oversight, agents can make decisions that conflict or spiral into unintended consequences. For example, an agent tasked with optimizing supply chain logistics might autonomously change order quantities without human approval, causing inventory mismanagement. To prevent such scenarios, organizations are establishing human-in-the-loop workflows and setting strict boundaries on agent autonomy.

Another critical concern is cloud cost management. Agentic AI can generate significant compute demands, especially when agents engage in lengthy reasoning chains or repeatedly call large language models. If left unchecked, cloud bills can skyrocket. FinOps teams are stepping up to track token usage, optimize model selection, and align AI spending with business outcomes.

Despite these challenges, early adopters in APAC are reporting productivity gains in areas like customer service, software development, and business process automation. The key is to approach agentic AI with a strategic mindset: start small, monitor closely, and iterate based on real-world feedback.

How the AI boom is reshaping tech cost management

The rapid adoption of AI, particularly generative AI and agentic systems, is forcing a transformation in how organizations manage technology costs. Traditional FinOps practices focused on cloud infrastructure like compute and storage. Now, practitioners must account for the variable costs of tokens, API calls, and model inference.

In APAC, where many firms are price-sensitive due to regional economic pressures, cost optimization is paramount. FinOps teams are developing new metrics to measure the return on AI investments. For example, they track the cost per successful transaction or the cost per completed agent task, rather than just raw compute hours.

Furthermore, there is a growing emphasis on aligning cost-saving measures with sustainability goals. Energy-efficient model architectures, smaller specialized models, and edge inference can reduce both expenses and carbon footprint. Some organizations are experimenting with hardware accelerators designed specifically for AI workloads, such as GPUs and custom silicon like the OpenClaw chipset, which promises higher performance per watt.

The OpenClaw phenomenon has caught the attention of industry analysts. This open-source hardware initiative aims to create a standard for AI accelerators that can be locally manufactured, reducing dependency on global supply chains. For APAC enterprises, this could lower costs and improve resilience, but it also requires new expertise in hardware integration and driver development.

Governance remains a central theme. Without clear policies, AI agents can autonomously make purchases, allocate resources, or modify code, leading to budget overruns or security breaches. Companies are implementing financial guardrails that cap agent spending and require human approval for high-value actions.

Agentic AI speeds up mainframe modernisation, but human experts remain key

Mainframe modernisation is a long-standing challenge for many large enterprises, especially in banking, insurance, and government sectors in APAC. These organisations often run mission-critical applications written in legacy languages like COBOL, and the pool of skilled COBOL programmers is shrinking rapidly. Agentic AI offers a potential solution.

AI agents can analyze legacy code, document business logic, and generate equivalent modern code in languages like Java or Python. They can also simulate test cases to ensure functionality is preserved. This accelerates the migration process significantly, reducing months of manual effort to weeks.

However, early projects reveal that human expertise remains indispensable. AI agents may misinterpret complex business rules or overlook subtle dependencies that have built up over decades. An experienced mainframe analyst must review the AI’s output, validate assumptions, and correct errors. The best approach is a partnership: agents handle the repetitive, pattern-based work while humans focus on exception handling and architectural decisions.

Moreover, the cultural and organizational aspects of mainframe modernisation cannot be ignored. Many senior developers are wary of AI replacing their jobs, but when presented as a tool that reduces drudgery, adoption increases. Successful programs engage legacy experts early in the process, using their knowledge to train and guide the AI models.

In the APAC context, where many firms operate with tight budgets and aggressive digital transformation timelines, agentic AI offers a pragmatic path forward. Rather than a complete rewrite, organizations can incrementally modernize their mainframes, prioritizing the most critical and costly-to-maintain modules first.

The combination of agentic AI, skilled human oversight, and robust governance creates a powerful recipe for modernisation that balances speed, cost, and reliability. As the technology matures, the role of the human expert will shift from writing code to guiding AI agents – a new skill set that IT leaders must start cultivating today.

Source: Computerweekly News

In December 2025, Google announced a new firmware update for the original Pixel Buds Pro. The update likely includes bug fixes, performance improvements, and possibly minor feature enhancements. While specific changelog details were sparse, the update reinforces Google's commitment to supporting its first-generation premium earbuds even after the launch of the Pixel Buds Pro 2. The original Pixel Buds Pro, launched in 2022, have received several major updates over their lifecycle, including Conversation Detection, Hearing Wellness, and EQ settings. This latest update ensures the original buds remain functional and up-to-date.

Original Pixel Buds Pro almost 50% off in clearance sale

By January 2025, the original Pixel Buds Pro were nearly discontinued, with Google Store no longer listing them after the Pixel Buds Pro 2 launch. However, retailers like Woot offered brand new units at $109.99, almost 50% off the original $199 price. This clearance sale allowed budget-conscious consumers to pick up the first-gen model with features like active noise cancellation, transparency mode, and Google Assistant integration. The price drop highlighted the rapid depreciation of previous-gen hardware once successors arrive, but also offered value for those who prioritize core functionality over newer features like the Pro 2's upgraded chip and design.

Pixel Buds Pro 2 ‘Noise Control’ now live in Android 15 Volume menu

Following the September 2024 launch of Pixel Buds Pro 2, Google rolled out a Noise Control toggle directly in the Android 15 volume menu. This integration allowed users to switch between ANC, transparency, and off without opening the Pixel Buds app. The feature was part of Google's effort to make earbud controls more seamless within the operating system. It also worked with the original Pixel Buds Pro after a subsequent update, demonstrating cross-generation support. The noise control menu appeared when connected Pixel Buds were active, providing a convenient slider for adjusting ambient sound levels.

How to change EQ settings on the Pixel Buds Pro 2 to make them sound better

Equalizer settings were a highly requested feature for Google's earbuds. The Pixel Buds Pro originally launched without EQ, but later added a five-band equalizer via firmware update. The Pixel Buds Pro 2 inherited this feature, allowing users to adjust bass, treble, and mids. A step-by-step guide explains opening the Pixel Buds app, selecting your buds, tapping on Sound, and enabling EQ adjustments. Presets include Default, Balanced, Bass Boost, Treble Boost, and Vocal Boost, with custom slider options. This customization helped users tailor sound to their preferences, addressing complaints about the default tuning being too bass-heavy or lacking clarity.

Pixel Buds Pro vs. Pixel Buds Pro 2: Are there enough upgrades? [Video]

A detailed video comparison broke down the differences between the two generations. The Pixel Buds Pro 2 featured a smaller design, improved ANC with louder cancellation, a new Tensor A1 chip for better audio processing, and longer battery life. However, the original Pixel Buds Pro still offered excellent sound, wireless charging, and multipoint connectivity. The video concluded that while the upgrades were substantial for ANC enthusiasts and those wanting smaller buds, the original remained a solid choice for users who could find it on clearance. Key trade-offs included the Pro 2's lack of swipe gestures and slightly different fit.

Google Gemini is coming to all Pixel Buds

In September 2024, Google confirmed that Gemini, its large language model AI assistant, would be available on all Pixel Buds models, including the original Pixel Buds Pro, A-Series, and standard buds. This move replaced Google Assistant with a more conversational AI capable of complex tasks like drafting messages, setting reminders with context, and answering detailed questions. The update was rolled out via firmware and the Pixel Buds app, enabling hands-free access to Gemini. Users could invoke Gemini by saying "Hey Google" or using touch gestures. This integration marked a shift from simple command-based assistance to generative AI interaction.

Pixel Buds Pro ‘touch and hold’ no longer reads notifications

An update in September 2024 altered the touch and hold gesture on Pixel Buds Pro. Previously, long-pressing could read out notifications. The change removed that function, likely to make room for Gemini integration or to simplify gesture controls. Some users were prompted about the change upon connecting their buds. Google did not provide an official explanation, but it sparked discussions about feature deprecation and the trade-offs when adding new AI capabilities. Users who relied on notification reading had to adapt to using voice commands instead.

Even if this Pixel Buds Pro 2 battery info is real, it doesn’t say anything useful

Before the official launch, a regulatory listing appeared suggesting battery capacity for the Pixel Buds Pro 2 case. The listing indicated 650 mAh, similar to the original. However, without details on runtime or charging speed, the information was deemed unhelpful. The article pointed out that such listings often lack context—like actual usage time under ANC or volume levels—making them poor predictors of real-world performance. This highlighted the challenge of interpreting regulatory filings for consumer electronics.

Find My Device can locate Pixel 8 even when turned off, coming to Pixel Buds Pro

In April 2024, Google expanded its Find My Device network with new capabilities. Pixel 8 and 8 Pro could be located even when powered off, using specialized hardware. For Pixel Buds Pro, the network enabled tracking via Bluetooth proximity and crowd-sourced location from nearby Android devices. Users could find lost buds or cases through the Find My Device app, even if the buds were offline. This was a significant security and convenience feature, especially for wireless earbuds prone to being misplaced. The feature rolled out gradually with firmware updates.

Sources: Pixel Watch 3 will have 45mm size, Pixel Buds Pro 2 also coming

In March 2024, exclusive reports disclosed Google's plans for a 45mm Pixel Watch 3 and confirmed the development of Pixel Buds Pro 2. The larger watch size addressed complaints about the 41mm-only Pixel Watch 2. For the buds, the report indicated a focus on improved ANC, smaller design, and a new chip. These leaks were later validated with the launch of both products later that year. The report underscored Google's strategy of expanding its wearables portfolio with multiple sizes and iterative improvements.

Gemini on your phone but Google Assistant in your ears

With the Gemini app launch on Pixel phones, some users found a dual-assistant setup useful. They kept Google Assistant on their Pixel Buds Pro for quick tasks like timers and music control, while using Gemini on the phone for complex queries. This balance leveraged the strengths of each assistant—speed and reliability from the old, depth from the new. The article reflected on the evolving role of AI assistants in daily life and how users might prefer different assistants for different contexts.

Solid footing: The Pixel Watch and Pixel Buds Pro in 2023

A year-end review of Google's wearables noted that the Pixel Buds Pro had established themselves as competitive earbuds, with reliable performance, good sound, and regular updates. The Pixel Watch was in its second generation with improved battery and health features. The piece highlighted that Google had successfully created a cohesive ecosystem of Pixel devices, though competition from Samsung and Apple remained fierce. The Buds Pro's integration with Pixel phones and assistant were key selling points.

Google officially announces Assistant Quick Phrases for Pixel Buds Pro

In December 2023, Google confirmed that Quick Phrases would come to Pixel Buds Pro. This feature allowed users to respond to calls or dismiss alarms without saying "Hey Google" first. For example, saying "Answer" or "Snooze" directly. The feature was previously limited to Pixel phones. It enhanced hands-free usability, especially during workouts or cooking. The update was delivered via firmware and required the Pixel Buds app.

The Pixel Buds Pro are still my favorite earbuds, but better ANC is a must for the sequel

An opinion piece from November 2023 praised the Pixel Buds Pro's overall experience but criticized the active noise cancellation as mediocre compared to competitors like AirPods Pro or Sony WF-1000XM5. The author argued that for a sequel, Google needed to significantly improve ANC performance. The article also noted the comfortable fit and intuitive controls as strengths. This feedback preceded the Pixel Buds Pro 2, which indeed featured upgraded ANC.

Google Store discounts Pixel Tablet to $399, first-gen Pixel Watch to $199.99

In late October 2023, Google ran several promotions: the Pixel Tablet dropped to $399, the first-gen Pixel Watch to $199.99, and Pixel Buds Pro to $149.99. These discounts aimed to boost sales ahead of the holiday season and clear inventory for new models. The Buds Pro deal was particularly attractive, offering high-quality earbuds at a mid-range price. The promotion was time-limited and available through Google Store.

Google now lets you buy a Pixel Buds Pro replacement case

Previously, Google only sold replacement earbuds individually. In October 2023, they began offering the charging case separately for $49.99. This addressed a common pain point for users who lost or damaged the case while still having functional earbuds. The case included wireless charging and a USB-C port. The move was seen as improving the product's repairability and sustainability.

How to access the Pixel Buds web app on Chromebooks

Alongside the Pixel 8 launch, Google introduced a web app for Pixel Buds that worked on Chromebooks and other devices. Previously, settings were only available via the Android/iOS app. The web app allowed users to adjust EQ, update firmware, and manage features like Conversation Detection. The article provided steps: open chrome://apps or the Pixel Buds page in Chrome, then follow on-screen instructions. This expanded the platform support for Google's earbuds.

Google rolls out Pixel Buds Pro 5.9 update with Conversation Detection

The 5.9 firmware update, released in October 2023, brought Conversation Detection to Pixel Buds Pro. This feature uses sensors to detect when the user starts speaking, automatically pausing audio and enabling transparency mode. Once the conversation ends, it resumes playback. It aimed to make interactions seamless without manually toggling ANC. The update also included bug fixes and stability improvements. It was available via the Pixel Buds app on Android or the web app.

Pixel Buds Pro get two new colors and a major software update

At the Made by Google 2023 event in October, Google announced new color variants: Bay Blue and Porcelain, matching the Pixel 8 series. Alongside, a major software update introduced Conversation Detection, Hearing Wellness (hearing health monitoring), and a five-band EQ. The colors were available for pre-order and shipping later that month. The update was free for existing users, signaling Google's commitment to post-launch software support.

Pixel Buds app readies ‘Hearing Wellness,’ ‘Conversation Detection,’ more

An APK teardown of the Pixel Buds app in October 2023 revealed strings for Hearing Wellness (likely hearing volume monitoring), Conversation Detection, and other features. The code suggested these features would be enabled via firmware updates. Hearing Wellness would alert users to prolonged high-volume listening, promoting ear health. This proactive health feature aligned with broader tech trends towards digital well-being.

These are what the new Pixel Buds Pro colors look like ahead of launch [Gallery]

Before the official reveal, leaked images showed the Pixel Buds Pro in Bay Blue and Porcelain. The gallery gave an early look at the matte finish and subtle branding. The colors were designed to complement the Pixel 8's Sky Blue and Porcelain offerings. The leak confirmed that Google was refreshing the Buds Pro with new aesthetics rather than a full hardware revision.

Google emailing 40% off discount codes for Pixel Buds Pro

In September 2023, Google began sending targeted emails offering 40% off Pixel Buds Pro (and A-Series) to select customers. This was likely a marketing push before new colors and features were announced. The discount brought the price to around $119, making it a competitive option against mid-range earbuds. The codes were single-use and tied to the recipient's Google account.

If Google launched ‘Pixel Buds Pro 2,’ what would you change? [Poll]

A poll in September 2023 asked readers what improvements they wanted in a sequel. Top answers: better ANC, smaller size, longer battery life, and more customization. The results reflected community desires and foreshadowed the actual Pixel Buds Pro 2 features. The article also speculated on Google's timeline, noting that two years after the original launch was typical for an update.

Source: Pixel Buds Pro will add ‘Porcelain’ and ‘Sky Blue’ colors to match Pixel 8

Exclusive reporting in September 2023 confirmed that Google would release two new Pixel Buds Pro colors alongside the Pixel 8. The leak accurately predicted Porcelain (a warm off-white) and Sky Blue (pale blue). The source indicated that no hardware or internal changes were planned, only cosmetic updates. This was eventually confirmed at the October event.

Source: 9to5Google News

The Google Pixel Buds Pro 2 have been one of the most talked-about true wireless earbuds since their launch in mid-2024. Over the next two years, Google rolled out a steady stream of software updates, hardware revisions, and new color options. This article brings together all major news items, from the initial launch to the latest firmware in mid-2026, to give readers a complete picture of the product's evolution.

Launch and Early Updates (2024)

The Pixel Buds Pro 2 launched with a custom Tensor A1 chip, which Google explained in a November 2024 interview. The chip powers advanced audio processing and enables features like adaptive noise cancellation and spatial audio. Early reviews praised the sound quality and comfort, but users quickly reported minor firmware quirks. The first post-launch update arrived in late January 2025, bringing firmware version 3.144. This update added a 'bud return' sound to help locate misplaced earbuds, and Google published an official changelog detailing improvements to connectivity and stability. Shortly after, in late January 2025, Google also acknowledged the 'bud return' sound feature in a separate story.

Throughout 2024, Google also engaged with users via surveys, asking about issues and Gemini usage. In November 2024, a feedback survey was emailed to owners, probing for problems and interest in the Gemini assistant integration. Additionally, a comparison article pitted the Pixel Buds Pro 2 against the Nothing Ear and Galaxy Buds 3 Pro, concluding they were a clear winner due to seamless integration with Pixel phones and superior comfort.

Software Features and Integration (2025)

In early 2025, the Pixel Buds Pro 2 gained support for the Auracast standard, allowing users to share music with nearby devices. However, this feature initially did not work on Pixel phones due to software limitations—a story from October 2024 highlighted this gap. By May 2025, Android 16 QPR1 brought back 'Audio Sharing' through Auracast, though Pixel Buds support was still pending.

In March 2025, Google published detailed cleaning instructions for the rear vent mesh, warning that debris can greatly affect audio quality. This was followed by a flurry of firmware updates: version 3.154 rolled out in June 2025, adding a 'Fully charged' alert and improving battery widget persistence. A major Feature Drop was announced at Made by Google 2025 in August 2025, bringing Adaptive Audio, head shake gestures, and a new Moonstone color. That update officially began rolling out in September 2025.

Another update in September 2025 brought the 'Noise Control' option directly to the Android 15 volume menu, making it easier to switch between ANC and transparency. This was rolled out shortly after the Feature Drop.

Hardware and Color Options

In July 2025, a massive Pixel leak revealed nearly all of Google's upcoming devices in its new favorite color 'Moonstone', including the Pixel Buds Pro 2. Google seemingly posted the Moonstone variant early on its store in August 2025, while also removing the Wintergreen option. By October 2025, the Google Store began directly listing replacement cases and single earbuds for the Pixel Buds Pro 2, making it easier for users to replace lost components. A detailed comparison video between the Pixel Buds Pro 2 and the newly released Pixel Buds 2a was published in October 2025, highlighting differences in design, battery life, and features. Notably, users could mix cases between the two models—the Pixel Buds Pro 2 case works with the Pixel Buds 2a and vice versa.

Software Updates Continue (2025-2026)

Google continued to refine the software experience throughout 2025. In June 2025, a firmware update (3.154) brought stability improvements and the 'Fully charged' notification. In August 2025, the Feature Drop added Adaptive Audio, which automatically adjusts noise cancellation and transparency based on the environment. Head shake gestures allowed users to accept or reject calls by nodding or shaking their heads. The update also included a new Moonstone color.

By June 2026, Google announced another software update for both the Pixel Buds Pro 2 and Pixel Buds 2a, though details were sparse. The update continued to improve connectivity and overall performance. Throughout this period, Google also updated the Pixel Buds app to feature a new gradient icon, signaling ongoing support.

Comparison and Market Position

Throughout its lifecycle, the Pixel Buds Pro 2 were frequently compared to competitors like the Samsung Galaxy Buds 3 Pro and Nothing Ear. In an October 2024 comparison, the Pixel Buds Pro 2 were named the clear winner due to superior integration with Pixel phones, comfortable fit, and reliable ANC. Discounts appeared regularly—in November 2024, pre-Black Friday deals offered $300 off the Pixel 9 Pro Fold and $280 off the Pixel Watch 3, while the Buds Pro 2 were also discounted. In April 2025, outlet deals at Best Buy offered the Pixel Buds Pro 2 for over $100 off, alongside Samsung's Galaxy Buds 3 Pro for $150 off.

By mid-2025, the Pixel Buds 2a had been launched, offering a more affordable alternative with many of the same features. Google's product line thus catered to both premium and budget segments. The Pixel Buds Pro 2 continued to receive firmware updates well into 2026, ensuring they remained competitive.

Key Technical Details

The custom Tensor A1 chip is a pivotal component, enabling real-time audio processing for ANC, transparency, and spatial audio. Google explained in a November 2024 interview that the chip was designed to reduce latency and improve voice call quality. Additionally, the earbuds support Bluetooth 5.2 and multi-device pairing. Battery life is rated at up to 7 hours with ANC on, and 20 hours with the charging case. The IPX4-rated water resistance makes them suitable for workouts.

Software updates added features like the 'Fully charged' alert, Auracast support (eventually), and adaptive sound modes. The 'bud return' sound was a practical addition for users who frequently misplace earbuds. The Pixel Buds Pro 2 also integrated with Google's Find My Device network, though this was not highlighted in early releases.

Overall, the Pixel Buds Pro 2 evolved significantly from launch through mid-2026, with Google addressing user feedback and continuously adding new features. This timeline captures every major story, from the first firmware update to the final Feature Drop, showcasing a product that stayed relevant through consistent software support.

Source: 9to5Google News

The Pixel 9 Pro XL, the largest and most feature-packed device in the lineup, normally retails for $1,099. With the $200 discount, the price drops to $899 for the base model. The standard Pixel 9, which starts at $799, now costs $599. These prices make the Pixel 9 series more competitive against other flagships like the Samsung Galaxy S24 series and the iPhone 15 Pro Max. The devices are available in multiple colors and storage configurations, with the discount applying across all options.

Google first launched the Pixel 9 series in August 2024, introducing four models: the standard Pixel 9, Pixel 9 Pro, Pixel 9 Pro XL, and Pixel 9 Pro Fold. The Pro XL variant features a 6.8-inch LTPO OLED display with a 120Hz refresh rate, a Tensor G4 chipset, and a dual-camera system that includes a 50-megapixel main sensor, a 48-megapixel ultrawide, and a 48-megapixel telephoto lens. It also packs a 5,060 mAh battery with support for 37W wired charging when using an official Google 45W charger. The device runs Android 14 out of the box, with a promise of seven years of OS and security updates.

The Memorial Day sale is notable because it reduces the price of the Pixel 9 Pro XL to a level that undercuts many competing premium phones. For example, the Samsung Galaxy S24 Ultra, which starts at $1,299, remains more expensive even after its own discounts. Apple's iPhone 15 Pro Max, with a starting price of $1,199, also costs more. This pricing strategy helps Google gain traction in a market dominated by Apple and Samsung. In recent months, other retailers have briefly offered even steeper discounts on the Pixel 9 Pro XL, with prices dropping to $699 or occasionally $599 during flash sales. However, those were short-lived events or limited to specific carriers. The Google Store's promotion is more accessible and likely to last through the end of the holiday weekend.

From a hardware perspective, the Pixel 9 Pro XL builds on the strengths of its predecessor, the Pixel 8 Pro, with several key improvements. The Tensor G4 chip focuses on AI and machine learning tasks, powering features like Magic Editor, Photo Unblur, and Live Translate. The display is brighter and more energy-efficient, reaching up to 3,000 nits peak brightness. Camera performance remains a standout, with Google's computational photography delivering excellent low-light shots and natural color reproduction. The telephoto lens offers 5x optical zoom and up to 30x Super Res Zoom. The device also supports Satellite SOS for emergency connectivity when cellular networks are unavailable, a feature that debuted with the Pixel 9 series.

For users upgrading from older Pixel phones like the Pixel 7 Pro or Pixel 6 Pro, the jump to the Pixel 9 Pro XL brings significant gains in processing power, display quality, and battery life. The design has also been refined, with a flatter display and a more squared-off frame that resembles the iPhone design language. The camera bump is now a single horizontal bar rather than the visor-style arrangement of previous models. This change has been polarizing, but many users appreciate the improved feel in hand.

The timing of the Memorial Day sale is strategic. Many consumers receive time-off during the holiday and are in a spending mindset. By offering a substantial discount, Google hopes to capture impulse buyers and those who have been waiting for a price drop before committing to a purchase. The sale also overlaps with other retail events, and bundling options are available, such as a free Pixel Buds or a case with the phone purchase. Some carriers like Mint Mobile and AT&T have also run their own promotions, including trade-in offers that make the Pixel 9 Pro effectively free on certain plans.

It is worth noting that the Pixel 9 Pro XL is not without its minor issues. Some users have reported that the device occasionally ignores corner taps, such as when trying to close the Gboard keyboard. Google has acknowledged this and is working on a fix via a software update. Additionally, the battery is harder to remove for repair compared to previous models, as teardowns have shown more adhesive and internal complexity. However, these are relatively small drawbacks for an otherwise excellent flagship phone.

Overall, the Google Store's Memorial Day sale presents a strong value proposition. Those in the market for a new smartphone should consider the Pixel 9 Pro XL if they prioritize camera quality, clean software, and long-term updates. The $200 discount makes it one of the best deals on a premium Android phone during the holiday. Potential buyers should act quickly, as inventory may run low and the promotion is expected to end on Memorial Day itself. For the best savings, ordering directly from the Google Store also ensures access to financing options and trade-in credits that can further reduce the price.

Source: 9to5Google News

Details of the Repair Program

The repair program applies to all Pixel 9 Pro models sold globally, but only those exhibiting the specific display issues described in Google's internal investigation. Users can check eligibility via the Google Support website by entering their device's IMEI number. Once confirmed, repair slots are available at no cost, and Google will cover shipping both ways. The company has also set up expedited processing for customers who rely on their phones for work or daily communication. Google has not disclosed the exact number of affected units, but the program is expected to run for at least two years from the announcement date, covering both out-of-warranty and in-warranty devices.

Extended Warranty for Pixel 9 Pro Fold

In a separate but equally significant move, Google has extended the warranty for the Pixel 9 Pro Fold from the standard one year to three full years. This extended coverage applies to all Pixel 9 Pro Fold devices purchased since its launch in August 2024, including those bought through carriers and retail partners. The extension covers manufacturing defects and hardware malfunctions, including the notoriously fragile inner folding screen, hinge mechanism, and battery degradation exceeding 20% capacity loss within the three-year period. Google emphasizes that this is not a recall but a proactive step to reassure customers about the reliability of its second-generation foldable phone.

Background and Context

The Pixel 9 Pro Fold debuted to strong reviews, with critics praising its nearly invisible crease, robust hinge, and improved durability over the original Pixel Fold. However, like many foldable devices, it has faced scrutiny over long-term durability. Some early adopters reported issues with the inner screen developing micro-cracks or dead pixels after extended use. Google's decision to extend the warranty likely addresses those concerns head-on, especially as competition from Samsung's Galaxy Z Fold 7 and Oppo's Find N5 heats up. The move also aligns with Google's broader strategy to offer more substantial ownership benefits, similar to the Google Pixel Pass subscription model that bundles extended coverage.

Market Reaction and Industry Impact

Industry analysts have welcomed the repair program and warranty extension as signs that Google is serious about building trust in its premium hardware. The smartphone market has increasingly shifted towards foldables, but consumer hesitation often stems from repair costs and long-term reliability. By offering a three-year warranty on the Fold, Google effectively matches or exceeds the coverage provided by most competitors. Samsung, for instance, offers a standard one-year warranty on its Galaxy Z Fold series, though it sometimes offers promotional extended plans. Google's move could pressure other manufacturers to follow suit, potentially reshaping after-sales service norms in the foldable segment.

The repair program for the Pixel 9 Pro series also comes at a crucial time. The Pixel 9 Pro and Pro XL have been widely used by professionals and content creators due to their exceptional camera systems and Tensor G4 chip performance. Display issues, even if limited to a small batch, could have damaged that reputation. By proactively offering free repairs, Google aims to contain any negative sentiment and demonstrate accountability. Internal documents suggest that the display problems were traced to a specific supplier component used in early production runs, but Google has not publicly named the supplier.

How to Participate

Customers who believe their Pixel 9 Pro or Pixel 9 Pro XL is affected should visit the official Google Support page. They will need to run a diagnostic tool or contact customer service to schedule a repair. Repairs are typically completed within five to seven business days, including shipping time. For the Pixel 9 Pro Fold, the extended warranty is automatically applied; no registration is needed. Google suggests that users keep their original purchase receipts for verification, though the warranty extension is tied to the device's serial number.

The company also announced that it is working on a software update for the Pixel 9 Pro series to optimize display calibration, which may prevent some issues from occurring. Beta testers have reported improved color accuracy and reduced flicker after installing recent preview builds. The stable update is expected to roll out in early January 2026.

Long-Term Implications

Google's dual action—repair program for the Pro series and extended warranty for the Fold—signals a maturation of its hardware division. The Pixel lineup has evolved from a niche enthusiast device to a mainstream competitor, and customer support is now a key differentiator. Extending warranties also encourages users to hold onto their devices longer, which aligns with environmental sustainability goals by reducing electronic waste. As the tech industry moves toward right-to-repair initiatives, Google's openness to fix issues without cost burden sets a positive example.

However, some critics argue that the extended warranty is a tacit admission that the Pixel 9 Pro Fold's components are not as durable as those in traditional slab phones. Google has not commented directly on durability comparisons, but independent teardowns by iFixit and JerryRigEverything have shown that the foldable's hinge design is robust, yet the screen remains the most vulnerable point. The inner display of the Pixel 9 Pro Fold costs approximately $1,199 to replace out of warranty, making the three-year coverage particularly valuable for users.

Looking ahead, the next generation of Google foldables—the Pixel 10 Pro Fold—is expected to launch in 2025, and it is likely that Google will build on these service improvements. The company has also hinted at expanding its in-house repair network to more countries, reducing turnaround times for foldable device repairs globally.

Customers can find more information about the repair program and warranty extension at the official Google Support website. The company recommends that users back up their data before sending in devices for repair, as service may involve erasing the phone's storage. Google also assures that any repairs will use genuine parts and will not affect the water resistance rating, provided the device is sealed correctly after service.

Source: 9to5Google News

Design and Display

The Liquid Jade 2 continues Acer's design philosophy of blending premium materials with ergonomic comfort. It features a unibody metal frame and a curved glass front, giving it a sophisticated look while maintaining a relatively slim profile of 6.9mm. The 5.5-inch display offers a Quad HD resolution (2560x1440 pixels), resulting in a crisp pixel density of around 534 ppi. This makes it ideal for viewing high-definition content and immersive gaming. Acer has also incorporated their “Vivid Color” enhancement technology to improve outdoor visibility and color accuracy.

Performance and Camera

Under the hood, the Liquid Jade 2 is powered by the Qualcomm Snapdragon 808 hexa-core processor, paired with 3GB of RAM. This chipset, also used in flagships like the LG G4, provides a good balance of performance and power efficiency. The phone runs Android 5.1.1 Lollipop out of the box, with Acer’s custom UI overlay. For photography, the device sports a 21-megapixel rear camera with f/2.2 aperture, phase-detection autofocus, and a dual-LED flash. The front-facing camera is 8 megapixels, suitable for selfies and video calls. Video recording reaches 4K at 30fps, leveraging the storage capabilities of the device.

Innovative Storage: The 1TB Hybrid Solution

The standout feature of the Liquid Jade 2 is its storage flexibility. While many flagship phones in 2016 offered 32GB or 64GB of internal storage, Acer opted for 128GB as standard. Additionally, the microSD card slot supports cards up to 200GB officially, but with faster UHS-I standards. This theoretically allows users to reach 328GB today and could exceed 1TB as higher-capacity microSD cards become available. Acer markets this as “hybrid storage” – a combination of fast internal memory and expandable external storage. This approach was relatively uncommon at the time, as many manufacturers were moving toward sealed, non-expandable designs.

Audio and Connectivity

Acer has included a few audio enhancements, such as a dedicated DAC and support for DTS Sound, aiming for a richer audio experience through headphones. The device also supports dual-SIM functionality (depending on market) and includes 4G LTE, Wi-Fi 802.11ac, Bluetooth 4.1, and NFC. The 3,000mAh battery promises a full day of moderate use, with Quick Charge 2.0 support for faster top-ups.

Market Context and Competition

The Liquid Jade 2 entered a crowded market dominated by devices like the Samsung Galaxy S7, LG G5, and HTC 10 – all announced around the same time at MWC. Acer’s strategy was to differentiate on storage capacity and price. By offering a large base storage and expandability, Acer targeted power users who needed to carry extensive media libraries without resorting to cloud services. The company also emphasized the device’s build quality, hoping to appeal to consumers who value both aesthetics and functionality.

Background: The Liquid Jade Series

Acer first introduced the Liquid Jade line in 2014, focusing on thin design and good ergonomics. The original Liquid Jade featured a 5-inch HD display and a MediaTek processor. The Liquid Jade S followed, improving performance and adding LTE. With the Liquid Jade 2, Acer aimed for a true flagship status, upgrading the display resolution, camera, and storage. The series has generally received positive reviews for its design and value proposition, though it has struggled to gain significant market share against larger competitors.

Availability and Pricing

Acer announced that the Liquid Jade 2 would be available in select European and Asian markets starting in March 2016, with a suggested retail price of around €499 (approximately $550 at the time). The phone came in two color options: Black and White. It was also demonstrated at the Acer booth at MWC, where attendees could experience its 1TB storage demo – a setup that used a 200GB microSD card alongside the internal 128GB to show the concept.

The announcement of the Liquid Jade 2 highlighted a broader industry trend: consumers were demanding more onboard storage for apps, photos, and videos, especially as 4K video recording became standard. While cloud storage was growing, offline storage remained crucial for many users. Acer’s move to offer a hybrid 1TB solution, though not truly 1TB out of the box, was a forward-thinking step that anticipated the future need for larger phone capacities.

Overall, the Liquid Jade 2 represented Acer’s most ambitious smartphone effort to date, showcasing innovative design and a clear focus on storage flexibility. While it did not revolutionize the market, it earned a place as a noteworthy device at MWC 2016, particularly for those craving more space on their devices.

Source: 9to5Google News

Security Fixes and Rewards

This release addresses 28 security issues, five of which are rated critical. The critical vulnerabilities include use-after-free bugs in Core, DigitalCredentials, Accessibility, GPU, and WebMIDI, as well as a heap buffer overflow in GPU. These flaws could allow an attacker to execute arbitrary code, crash the browser, or gain unauthorized access to system resources. Google has also patched 22 high-severity issues covering use-after-free, heap buffer overflow, out-of-bounds read/write, race conditions, and insufficient validation in components such as Autofill, DevTools, Extensions, Network, Video, and GPU. One medium-severity issue in WebGL was also fixed. As is standard practice, Google is withholding detailed bug information until the majority of users are updated. External researchers contributing to the fixes received bug bounties, though specific amounts have not been disclosed.

New Productivity Features

Beyond security, Chrome 149 introduces several features designed to streamline browsing and enhance multitasking. These tools are rolling out gradually and may not be immediately available to all users.

Vertical Tabs

Users can now switch from the traditional horizontal tab bar to a vertical layout by right-clicking on a Chrome window and selecting "Show Tabs Vertically." This moves tabs to the left side of the browser, making it easier to read full page titles and manage tab groups, especially when many tabs are open. Vertical tabs are particularly useful for large screens and users who frequently juggle multiple projects.

Improved Reading Mode

Reading mode has been upgraded with a full-page interface. Users can right-click on any page and choose "Open in reading mode" to strip away clutter, ads, and navigation elements, leaving a clean, text-focused view. The mode also supports read-aloud functionality with adjustable voice, speed, and highlight style, making it ideal for consuming long-form articles, news stories, and PDFs.

Split View

Chrome now allows two pages to be viewed side-by-side within a single tab. To activate split view, drag another tab or link to the left or right edge of the browser window, or right-click a link and select "Open link in split view." This feature is designed for comparing products, watching videos while taking notes, or referencing documents without switching between windows.

PDF Annotations and Save to Drive

The built-in PDF viewer has been enhanced with annotation tools. Users can hand-draw signatures, highlight text, and add notes directly to PDF files without downloading third-party software. Annotations are saved within the PDF itself. Additionally, a new "Save to Google Drive" option sends PDFs to a dedicated "Saved from Chrome" folder, eliminating the need to download and re-upload files. This integration streamlines workflows for students, professionals, and anyone who frequently handles digital documents.

Performance and Usability Updates

Google continues to refine Chrome's performance. Memory Saver mode, which suspends inactive tabs, promises up to 40% less memory usage. Energy Saver reduces background activity when battery is low. Both features are enabled by default. Chrome also now syncs tab groups across devices, so users can pick up projects on different computers or phones. To enable sync, users sign into their Google account and activate the option in settings.

The update also includes fixes for earlier versions. Chrome 146.0.7680.177/178 addressed 21 security issues, including a known exploit for CVE-2026-5281 (a use-after-free in Dawn). Version 145.0.7632.109/110 brought split view, PDF annotations, and the save-to-Drive feature as part of a broader productivity push.

Privacy and Alternatives

While Chrome remains the dominant browser with roughly 68% global market share, its privacy practices continue to draw scrutiny. Google logs all browser activity—including keystrokes in the address bar—when users are signed into their Google account, and this data can be linked to other services. Incognito mode blocks third-party cookies but does not prevent Google from seeing user activity. For those seeking alternatives, Firefox and Brave block cross-site tracking by default, while Ungoogled Chromium removes Google integrations entirely. Edge, Opera, and Vivaldi offer Chromium-based experiences with additional features. A new category of AI browsers, such as ChatGPT Atlas and Comet, provides agentic assistants that can summarize content and automate tasks.

The End of uBlock Origin and Desktop News

Google is also moving forward with the phase-out of Manifest V2 extensions, which will end support for classic ad blockers like uBlock Origin in Chrome within weeks. Users who rely on such extensions are advised to switch to alternatives based on Manifest V3, such as uBlock Origin Lite. In a separate incident, Google accidentally tested making AI Mode the default in Search before retracting it as an error, hinting at future changes to the search experience. Additionally, a four-year-old Chromium security bug was inadvertently published before Google attempted to re-hide it; the bug remains unpatched, highlighting ongoing challenges in maintaining browser security.

Chrome's latest stable channel release underscores its dual focus on security and user experience. With 28 vulnerabilities fixed and new tools for managing tabs, reading, and annotating documents, the browser continues to evolve while maintaining its position as the world's most widely used web browser.

Source: TechSpot News

Why Faces Get All the Attention

We have had photorealistic environments in games for a while now. Water reflections, volumetric lighting, incredibly detailed cityscapes and forests. The hardware and rendering techniques have gotten us to a point where environments can look stunning under the right conditions. But faces have been the holdout. Getting a human face to look truly photorealistic in real time has been one of the most expensive problems in computer graphics from a compute standpoint. Subsurface scattering on skin, the way light interacts with individual strands of hair, the micro-expressions that make a character feel alive rather than like a wax figure – all of that requires an enormous amount of rendering horsepower.

I have probably seen ten different 'floating head' tech demos over the course of my career. They are always a single head with no hair, no body, no environment, because rendering a photorealistic face at that quality level is so expensive that it can only be done in isolation. You never see it inside an actual game, because the performance budget will not allow it. DLSS 5 closes that gap in a dramatic way. And because that is the area where the delta between before and after is most visible, that is what everyone is reacting to. The Nvidia team put it well during my demo: it is a psychological effect. You have seen environments rendered really well before. When you suddenly see a character rendered at that same photorealistic level, your brain flags it immediately. It stands out.

It Is Happening Everywhere, Not Just on Character Models

What I saw in the demos was a comprehensive improvement across the entire scene. The moment that really drove this home was not a face. It was a coffee maker. In Starfield, there is a countertop scene with a coffee machine, some paper towels, a cup, and napkin holders – standard environmental clutter. With DLSS 5 off, everything looks flat. The coffee maker fades into the background. Toggle it on, and suddenly the objects have shape. The lighting wraps around them naturally. The spatial relationships between the items and the surfaces they are sitting on become clear. It goes from assets placed in a scene to objects that actually belong in a room.

The same thing played out across every title. In Oblivion Remastered, the water went from good video game water to something that could pass for real, with the kind of light interaction and shimmer you would expect from an offline render. In Assassin's Creed Shadows, the trees and distant foliage gained dramatically better depth and separation in how light moved from the canopy down through the branches. In the Zorah tech demo – a 300 GB courtyard scene built by 20 full-time artists – the subsurface scattering on foliage was just as impressive as anything happening on character faces. Leaves picked up that translucent glow from backlighting that is incredibly difficult and expensive to model and render through traditional means.

The AI model powering DLSS 5 is a single unified model, the same for every game. It is not trained per-title, per-face, or per-object type. It takes the raw color buffer and motion vectors as input, analyzes the scene semantics from that single frame, and enhances the lighting and material response while staying anchored to the original 3D content. It recognizes the difference between skin, metal, water, stone, and foliage, and it processes each of those materials differently based on how light should interact with them. That is not a filter. That is a fundamentally different approach to how the final image gets assembled. And it is deterministic and consistent from frame to frame, which is a hard requirement for games.

The Developer Angle Matters More Than People Realize

One of the things I came away most encouraged by is the developer control story. This is critical. If DLSS 5 were a black box that slapped a one-size-fits-all enhancement over every game, the artistic intent concerns would be completely valid. But that is not what this is. During the demo, the DLSS research team walked through the level of granularity available. Developers do not just get an on/off switch. They get intensity controls that can be dialed anywhere, not just full strength. They get spatial masking, so they can set the water enhancement to 100%, wood to 30%, characters to 120% – all independently within the same scene. They get color grading controls for blending, contrast, saturation, and gamma. All of this runs through the existing SDK, which means studios already using DLSS and Reflex have a familiar pipeline to work with.

The developer support list tells you something. Bethesda, CAPCOM, Ubisoft, Tencent, Warner Bros. Games, and others have already signed on. But what struck me more than the names was what the Nvidia team shared about the reactions inside those studios. When developers previewed the technology, their technical artists were co-advocating for it internally, because it gets them closer to what they actually intended their characters and environments to look like when they were designing them in their authoring tools. Then those assets get dropped into a real-time game engine with a finite performance budget, and compromises happen. DLSS 5 lets them claw back some of what gets lost in that translation. DLSS 5 is not Nvidia applying its stylistic choices on top of someone else's game. It is providing a tool that helps developers close the gap between what they can render in 16 milliseconds and what they actually want the player to see. That is a meaningful distinction, and it is a big reason why the developer response has been positive.

The Hardware Story Is Interesting Too

The demos I saw were running on a pair of RTX 5090 GPUs. One was handling the game rendering, the other was dedicated entirely to running the DLSS 5 AI model. Nvidia was upfront that there is still significant optimization work to do, and the plan is to ship DLSS 5 running on a single GPU when it launches later this year. But the dual-GPU setup itself is worth mentioning. For years, multi-GPU gaming has been effectively dead. SLI is gone. CrossFire is gone. The idea that you would run two graphics cards for a better gaming experience felt like a relic of the mid-2000s. And yet here we are, with a legitimate use case where a second GPU running an AI workload alongside a primary rendering GPU produces a dramatically better visual result. Is that where this ends up for enthusiasts? Probably not at launch. But the concept of dedicating GPU compute specifically to AI-driven visual enhancement, separate from the rendering pipeline, is an interesting architectural idea. It would not surprise me if that becomes a real conversation again as neural rendering matures.

Where This Goes From Here

DLSS 5 is targeting a fall 2026 launch, which means we have got several months of optimization and refinement ahead. Developers are just getting their hands on it now, and they will need time to work with the controls and dial in the right settings for their specific titles. First-wave games include Starfield, Assassin's Creed Shadows, Resident Evil Requiem, Hogwarts Legacy, Phantom Blade Zero, The Elder Scrolls IV: Oblivion Remastered, Delta Force, and more. It is also worth noting that this works across rendering approaches. Rasterized games, ray-traced titles, and path-traced experiences all benefit. And the higher the fidelity of the input, the better the output. DLSS 5 is not replacing good rendering. It is amplifying it.

The early social media reaction is predictable. New technology that changes how games look will always generate strong opinions, especially when AI is involved. But the knee-jerk 'it is just a face filter' take does not hold up once you have actually seen the full scope of what DLSS 5 is doing across an entire scene, across multiple games, in real time. Go look at a coffee maker. Go look at stone textures. Go look at the way light passes through a leaf. That is where the real story is.

Source: TechSpot News

The three-button layout is smarter than you think

Gesture navigation shuts out millions of people

There's a reality that tends to get forgotten as we add fewer buttons to phones and rely on the screen. Gesture controls are convenient but genuinely hard to use for a lot of people. Swiping from the edge of a screen might feel natural if you have full hand mobility or grew up as this was designed, but these gestures actually demand a surprising amount of physical precision. You need the right speed, the right angle, your finger in exactly the right spot along a narrow strip of glass.

For someone living with hand tremors, arthritis, or Parkinson's disease, hitting an invisible trigger zone can consistently feel impossible. That's not to mention the older generation that grew up with clearly marked buttons instead of gestures you already have to know about.

Missing those buttons is a big part of this, too. A button you can see is much easier to use, but if you were never told about how swiping works or the special ways you can use it, you're not going to know anything about it. You're hunting for a moving target that gives you no feedback until you either get it right or don't.

The old three-button layout works better by design. Back, Home, and Recents used to sit in fixed spots at the bottom of the screen. Some phones still have this in the same spots, every time, on every app. You don't have to look for them. Your thumb already knows where they are.

That's not a small thing. A static button you've pressed a thousand times will always be better than an invisible swipe zone.

Google clearly understands this, which is why the three-button layout is required on every Android device. The Android Compatibility Definition Document, the rulebook every phone maker must follow to ship Android devices legally, mandates that both gesture navigation and three-button navigation be available on every device.

Swipes are untrustworthy

Too much is happening on screen

Manufacturers can make gestures the default, but they cannot remove the buttons. Google goes further than just requiring these options. The company warns manufacturers that features such as under-display fingerprint sensors cannot physically overlap with the button navigation area. This is for people who rely on those buttons, so they don't accidentally trigger the fingerprint reader mid-navigation.

The back, home, and recents buttons are still here because phone makers aren't behind the times. They're there because not everyone's hands work the same way, and a phone that can only be operated with perfect dexterity isn't really accessible at all.

Gesture navigation looks clean, but it constantly gets in the way of actually using your apps. It works by detecting swipes inward from the left or right edge of the screen, so it keeps colliding with apps that use those same edges for their own controls.

Try to open a sidebar or pan across a map, and your phone might read it as a swipe to another page or app, or even going back instead. One second you're browsing a rack of clothes or scrolling through Instagram, the next you've been kicked out of the page entirely. It is annoying.

Developers can't really fix this because there's so little space to make it work. Even being able to mark certain parts of the screen as off-limits for system gestures doesn't fix it entirely. Android only lets devs limit a certain amount of edge space because it doesn't want apps to disable the back navigation completely. However, that sidebar menu runs the full height of the screen, so it is helping only a bit more than it hurts.

Thumb comfort and speed are more important

Cleaner doesn't always mean better

Getting rid of the navigation bar at the bottom frees up screen space and lets apps stretch edge-to-edge, which feels better. There is no arguing that it looks sleeker, but it's hard to justify when it causes this many issues.

I may write today, and for the past handful of years, but I used to work with my hands, and it's not easy to swipe all the time. Gestures are mostly convenient for people who can just sit at a coffee shop, not those who are genuinely hard at work and not completely focused on their phone.

Phones are taller than you think, and constantly swiping in from the far edges means your thumb is making wide, reaching movements across a big glass screen. Do that for hours, and you'll feel it. My wife has a dent in her finger from holding the phone a certain way for years.

Three-button navigation gives your thumb a home base. The buttons sit in the same spot every time, close to where your thumb naturally rests, so you're moving maybe half an inch to hit them. That means less stretching, less repositioning, and less strain.

There's also a speed difference, and it comes down to how the phone handles each type of input. With gesture navigation, the phone can't just react the moment your finger touches the screen; it has to wait and register. The system has to track where your finger started, how far it's moved, at what angle, and how fast it's moving before it can make a call.

That analysis takes time, whereas the three-button system skips all of that. The buttons are fixed targets, so when you tap one, the phone just checks your touch against a known location and fires immediately.

We gave up one of the best and most convenient features of a phone for more screen coverage, which makes little sense when you think about it.

Swiping is not better

Switching back to three-button navigation won't appeal to everyone, and if gesture navigation works well for you, there's no strong reason to change. The extra screen real estate is nice, and the gestures feel fluid once they're learned. Even when I learned the swipes, I didn't use them. It's still more convenient without swiping. Until that changes, there's no reason to alienate those who don't want to or can't learn to swipe.

Source: MakeUseOf News

These tweaks are simple, require no advanced networking knowledge, and can be done in under an hour. Once applied, you'll notice faster speeds, fewer dropouts, and a more secure network. Let's walk through each setting.

Turn off WPS

The outdated feature isn't worth the risk

Wi-Fi Protected Setup (WPS) was designed to make connecting devices easier—press a button or enter a PIN, and you're on the network without typing a long password. But convenience comes at a cost. The WPS PIN authentication method is notoriously vulnerable to brute-force attacks. An attacker can attempt thousands of PIN combinations in minutes, and once guessed, they gain full access to your network without knowing the Wi-Fi password.

Many routers still ship with WPS enabled by default because it simplifies setup for non-technical users. However, security experts have been warning against its use for years. If you rarely use the WPS button, the safest move is to disable it entirely in your router's administration panel. You lose nothing of value, and you eliminate a significant attack vector.

Use QoS to prioritize important devices

Make sure your gaming PC gets first dibs

By default, your router treats every device on the network equally. That sounds fair, but in practice it means a smart thermostat can vie for bandwidth against your gaming rig during a critical match. Quality of Service (QoS) lets you override this egalitarian approach by assigning priority to specific devices or types of traffic.

For example, you can set your work laptop or streaming device to high priority while relegating file downloads to low priority. Some routers allow you to prioritize by application—gaming, video streaming, web browsing—rather than by device. This is especially useful in households with multiple users. Without QoS, a single device performing a large update can saturate the connection, causing lag for everyone else. Modern routers often include intuitive QoS menus where you drag and drop devices into priority tiers.

Change Wi-Fi channel

Your neighbors could be slowing down your Wi-Fi

Most routers are set to automatically choose a Wi-Fi channel. This works reasonably well in sparsely populated areas, but if you live in an apartment building or a dense neighborhood, interference becomes a real problem. When multiple routers broadcast on the same channel, they compete for airtime, resulting in slower speeds and higher latency.

Manually selecting a less congested channel can dramatically improve performance. On the 2.4 GHz band, the best channels are 1, 6, and 11 because they don't overlap. For 5 GHz, channels 36, 40, 44, and 48 are commonly less crowded, though you should check with a Wi-Fi analyzer app (like NetSpot or WiFi Analyzer) to see what your neighbors are using. The 6 GHz band used by Wi-Fi 6E offers even more room, but interference can still occur. Changing the channel manually ensures your network operates on a cleaner frequency.

Set up a DNS

Ditch your ISP's DNS

The Domain Name System (DNS) translates human-friendly website names like example.com into IP addresses that computers understand. By default, your router uses the DNS servers provided by your Internet Service Provider. While these work, they are often slower, less reliable, and sometimes even track your browsing activity.

Switching to a third-party DNS service—such as Cloudflare (1.1.1.1), Google Public DNS (8.8.8.8), or Quad9 (9.9.9.9)—can reduce the time it takes to load websites. These services invest heavily in infrastructure and often have better security features, like blocking known malicious domains. Even better, changing the DNS at the router level applies the new settings to every device on your network—PCs, phones, smart TVs, and game consoles—saving you the hassle of configuring each one individually.

Change the router password

Secure your router before someone else does

Every router comes with a default administrative username and password, often printed on a sticker on the device or available in the manual. If you don't change these credentials, anyone who connects to your network—or even a visitor—can log into your router's settings. From there, they could change the Wi-Fi password, disable security features, prioritize their own traffic, or even lock you out.

Some modern routers now prompt you to set a custom admin password during initial setup, but many still rely on defaults. It takes just a minute to log into the admin panel and create a strong password—ideally a mix of letters, numbers, and special characters. This single step prevents unauthorised access and protects your entire network.

Update to the latest firmware

New router, old software? Fix that first

A router fresh out of the box might have been sitting on a warehouse shelf for months, running firmware that's several versions behind. Much like your smartphone or computer, a router's operating system receives updates that patch security holes, fix bugs, and sometimes add features. Running outdated firmware leaves you exposed to known vulnerabilities that attackers love to exploit.

Check for firmware updates immediately after setting up your router. On newer models, this is often as simple as clicking a "Check for Updates" button. On older routers, you may need to download a file from the manufacturer's website and upload it manually. Don't skip this step; a single firmware update can resolve intermittent disconnects, improve Wi-Fi range, or close a security gap that would otherwise go unaddressed. Set a reminder to check for updates every few months, as new patches are released regularly.

Changing these six default settings isn't the most exciting part of owning a new router, but it's arguably the most important. A few minutes of configuration now can prevent hours of frustration later. You'll enjoy faster, more reliable, and more secure internet—and you'll wonder why you ever put up with the defaults.

Source: MakeUseOf News

Few brands have embraced that shift more aggressively than Beatbot. Available through the Beatbot website and Amazon storefront, the company has established itself as a leader in premium robotic pool care by combining advanced robotics, AI-powered vision systems, and intelligent navigation technologies into products designed to reduce the time and effort required to maintain a clean pool. This Prime Day, Beatbot’s lineup offers a closer look at how far automated pool care has progressed, from flagship systems capable of real-time decision-making to versatile robots designed to handle multiple aspects of maintenance in a single cleaning cycle.

Rather than focusing on a single product category, Beatbot has spent the last several years building a broader pool-care ecosystem powered by advanced robotics, intelligent navigation, and AI-driven automation. From flagship robotic cleaners capable of real-time decision-making to surface skimmers and more accessible cleaning solutions, the goal remains the same: reducing the time, effort, and guesswork traditionally associated with pool maintenance.

Inside Beatbot’s most advanced pool-care system

Beatbot’s vision for AI-powered pool care comes together most clearly in the AquaSense X. Combining an autonomous self-cleaning station with HybridSense™ AI Vision, CleverNav™ AI Path Planning, AI debris detection, intelligent obstacle avoidance, auto-recovery functionality, and night cleaning capabilities, it brings a deeper level of awareness and adaptability to the cleaning process.

The system continuously analyzes its surroundings, identifies obstacles and debris, and adjusts cleaning routes in real time to improve coverage across the entire pool. Instead of relying on fixed cleaning patterns, it adapts as conditions change, helping deliver a more thorough and efficient clean while reducing the need for user intervention.

The autonomous self-cleaning station further reinforces that hands-off approach. By minimizing routine maintenance after each cleaning cycle, it allows pool owners to spend less time managing their cleaner and more time enjoying their pool. For those looking for the most advanced option in Beatbot’s ecosystem, the AquaSense X combines intelligent navigation, adaptive cleaning, and automated maintenance in a single platform.

Prime Day price: $3,999 (regularly $4,250).

AquaSense 2 Ultra expands the idea of intelligent pool maintenance

While many robotic pool cleaners focus primarily on debris removal, the AquaSense 2 Ultra takes a broader view of pool maintenance. As the world’s first AI-powered 5-in-1 robotic pool cleaner, it combines floor cleaning, wall cleaning, waterline cleaning, surface skimming, and water clarification within a single system.

HybridSense™ AI Vision and CleverNav™ AI Path Planning help the AquaSense 2 Ultra navigate multiple cleaning zones while adapting to changing pool conditions. Combined with AI debris detection and intelligent obstacle avoidance, the system is built around what Beatbot calls full-pool intelligence, allowing it to tackle different maintenance tasks through a single platform.

Water clarification is what further separates the AquaSense 2 Ultra from traditional robotic cleaners. Beyond collecting debris, it actively contributes to cleaner, clearer water while reducing the need for additional maintenance tools. For pool owners looking for a more comprehensive approach to pool care, it brings cleaning, water care, and intelligent automation together in a single solution.

Prime Day price: $1,999 (regularly $3,150).

AquaSense 2 Pro brings comprehensive care into a single system

The AquaSense 2 Pro focuses on simplifying pool maintenance without sacrificing capability. Combining floor cleaning, wall scrubbing, waterline cleaning, surface skimming, and water clarification within a single platform, it is built for pool owners who want a more complete maintenance solution without juggling multiple tools.

Features such as the ClearWater™ Clarification System, Smart Water Surface Parking, and one-touch app retrieval help streamline day-to-day ownership, while Full Coverage Path Optimization supported by 22 sensors helps ensure efficient navigation and consistent cleaning performance across the pool. By continuously assessing its surroundings and adjusting cleaning routes as needed, the AquaSense 2 Pro is designed to deliver thorough coverage with minimal intervention.

The result is a system that brings together intelligent navigation, water care, and multi-zone cleaning in a way that feels practical rather than complicated. For pool owners looking for a balance between advanced automation and everyday usability, the AquaSense 2 Pro sits comfortably in the middle of Beatbot’s growing pool-care ecosystem.

Prime Day price: $1,699 (regularly $2,299)

The Sora Series brings smarter cleaning to more pools

Not every pool owner needs a flagship-level solution, which is where the Sora Series fits into Beatbot’s broader lineup. The Sora 70 is the most capable model in the range, delivering 4-in-1 cleaning across the floor, walls, waterline, and surface. By incorporating dedicated surface cleaning alongside traditional robotic cleaning functions, it provides broader coverage than many mid-range alternatives. Features such as Smart Surface Parking, shallow-area accessibility, SonicSense™ AI Ultrasonic Obstacle Avoidance, and intelligent path planning help improve cleaning consistency while making retrieval easier once a cleaning cycle is complete.

SonicSense™ AI Ultrasonic Obstacle Avoidance and intelligent path planning help the Sora 70 navigate more efficiently while improving cleaning consistency across the pool. Together with its 4-in-1 cleaning capabilities, those technologies make it one of the most capable options in Beatbot’s mid-range lineup.

Prime Day price: $999 (regularly $1,499)

The Sora 30 focuses on delivering stronger day-to-day cleaning performance without the premium investment associated with flagship models. Its enhanced 3-in-1 cleaning capability covers floors, walls, and waterlines, providing broader coverage and greater versatility than many entry-level cordless cleaners. For buyers looking to step into Beatbot’s ecosystem, it offers an appealing balance of performance, convenience, and value.

While positioned as a more accessible option, the Sora 30 still benefits from the design philosophy that runs throughout Beatbot’s lineup: broader coverage, smarter operation, and less manual effort. For pool owners seeking dependable day-to-day maintenance, it offers a practical entry point into Beatbot’s intelligent pool-care ecosystem.

Prime Day price: $649 (regularly $999)

Prime Day is the perfect time to upgrade

Beatbot’s Prime Day offers extend well beyond the flagship models. Alongside deals on the AquaSense X, AquaSense 2 Ultra, AquaSense 2 Pro, Sora 70, and Sora 30, shoppers can also save across the company’s broader pool-care ecosystem. The Sora 10 drops from $699 to $449, while the AquaSense 2 is available for $799, down from its regular $1,298 price. Surface-cleaning solutions are also seeing significant discounts, with the iSkim available for $299 (normally $499) and the iSkim Ultra reduced from $999 to $549.

Available from July 8 through July 11, these promotions make it one of the best opportunities of the year to upgrade to Beatbot’s AI-powered pool-care ecosystem. Whether you’re looking for a flagship robotic cleaner, a comprehensive maintenance solution, or a dedicated surface-cleaning system, the lineup offers options across a range of pool sizes, maintenance needs, and budgets.

For pool owners ready to spend less time cleaning and more time enjoying their pool, Prime Day may be the ideal time to make the switch.

Source: Digital Trends News

The concept of a personal AGI is not entirely new; researchers and futurists have long speculated about AI that can match or exceed human intelligence across a wide range of tasks. However, OpenAI’s recent statements bring new specificity to the timeline. According to the company, it expects AI systems to handle a meaningful share of its own research work alongside human researchers by March 2028. That date gives the personal AGI idea more weight than a simple product tease. It suggests that the company is actively working toward a future where the line between human and machine capabilities blurs, and where individual users can access tools that were once the exclusive domain of large institutions.

To understand the significance of this announcement, it helps to look at OpenAI’s history. Founded in 2015 as a nonprofit research lab, OpenAI originally focused on developing artificial intelligence in a safe and beneficial manner. The company transitioned to a “capped-profit” model in 2019 to attract more funding, and since then has released a series of increasingly powerful models, including GPT-3, GPT-4, and multimodal systems. Each iteration has sparked debates about capabilities, risks, and ethical implications. The personal AGI announcement represents a natural evolution: after building tools that excel at narrow tasks, OpenAI now aims for a general-purpose assistant that can adapt to any context.

The potential applications are vast. A personal AGI could help people learn new subjects, write complex documents, code software, plan vacations, conduct research, and even make strategic decisions. Unlike today’s chatbots, which often require careful prompting and have limited memory, a personal AGI would maintain persistent context about the user’s preferences, goals, and history. It could act as an always-on advisor, educator, and collaborator. For example, a student might use the agent to generate personalized study plans, while a small business owner could rely on it to analyze market trends and optimize operations. The promise is that everyone — regardless of background or income — would have access to expert-level assistance.

However, the road to widespread AGI is fraught with challenges. The hard part is turning that ambition into something people can actually use. A personal AGI has to be affordable, understandable, and trustworthy. OpenAI has not yet shared specifics on pricing, timing, geographic availability, or how access would work beyond its current ChatGPT subscriptions. Currently, ChatGPT Plus costs $20 per month and offers limited features compared to the full GPT-4 API. For a personal AGI to reach billions, the cost per user would need to drop dramatically, perhaps through subsidized models or government partnerships. Furthermore, the system must be designed to inspire trust. Users need to know when the AI is uncertain, how it handles sensitive data, and what safeguards prevent misuse.

The question of control is also critical. While OpenAI talks about democratizing AI, the design authority would still rest with the company itself. It would decide how the system behaves, where the limits are, and which capabilities arrive first. An AI meant for everyone still arrives through one company’s choices. This raises concerns about centralization of power. Could a single organization be trusted to shape the behavior of a tool that billions rely on? Similar debates have surrounded social media platforms, but the stakes are higher with AGI because the system could influence decisions about health, finance, education, and governance. OpenAI has published guidelines about responsible deployment, but critics argue that internal safety teams have been marginalized in recent years.

Despite these uncertainties, the vision is undeniably compelling. The access story is powerful because personal AGI would put advanced help closer to the individual. If it works, it could change how people learn, write, code, plan, research, and make decisions without waiting on an employer, school, or government agency. In many parts of the world, quality education and expert advice are scarce resources. An affordable AGI could level the playing field, enabling anyone with a smartphone to access tools that previously required years of training or large budgets. This aligns with OpenAI’s original mission: to ensure that artificial general intelligence benefits all of humanity.

The timeline of 2028 is ambitious but not impossible. Current large language models already pass graduate-level exams in law, medicine, and business. They can generate code, compose music, and engage in open-ended conversation. The next step is to integrate these abilities into a single agent that can plan and execute complex tasks over long horizons. OpenAI’s research into reinforcement learning, self-play, and hierarchical planning could accelerate progress. However, significant obstacles remain in areas like reasoning, causal understanding, and the ability to generalize from limited data. Many researchers believe that AGI is still decades away, not years. OpenAI’s confidence may reflect internal breakthroughs that are not yet public, but it could also be a statement of intent that drives investment and talent.

The next test for the company is not whether it can describe a sweeping destination. The test is whether it can show a personal AGI that feels useful without feeling opaque, expensive, or out of reach. Early demonstrations will be crucial. Users will look for everyday examples: how does the agent help someone plan a balanced diet, write a resume, or debug a program? Beyond the hype, OpenAI must address practical details like inference cost, latency, and privacy. For instance, running a powerful model on-device might be necessary to ensure privacy and offline access, but current chips are not powerful enough. Cloud-based solutions introduce latency and dependency on internet connectivity, which could exclude rural areas in developing countries.

OpenAI’s competitors are also racing toward similar goals. Google DeepMind, Anthropic, and Meta all have projects aimed at building general agents. Microsoft, which has invested billions in OpenAI, is integrating AI into Office 365, Azure, and Windows. The race to personal AGI will likely involve multiple players, each offering different trade-offs between openness, safety, and capability. Unlike early AI models that were open-sourced, the most advanced systems are now proprietary. This creates tensions between the ideal of universal access and the reality of corporate control. Some argue that only open-source models can truly democratize AI, but others worry about the risks of bad actors obtaining powerful tools.

The ethical dimensions are profound. A personal AGI that knows everything about a user could be a threat to privacy if not handled correctly. OpenAI would need to design systems that process data locally or use encryption that prevents even the company from accessing personal information. Moreover, the AI’s values would need to align with a diverse global population. What is considered helpful in one culture might be intrusive in another. The company has already faced criticism for reinforcing biases and generating harmful content. A personal AGI would amplify these issues if not carefully calibrated.

In the broader context, OpenAI’s announcement comes amid a global push to regulate AI. The European Union’s AI Act, the United States’ executive order on AI safety, and discussions at the UN all aim to set rules for powerful systems. OpenAI’s vision of an all-knowing agent for everyone could accelerate regulatory efforts, as lawmakers grapple with the implications of such a tool. The company has advocated for regulation but also criticized proposed frameworks that it sees as overly restrictive. The delicate balance between innovation and oversight will be tested in the coming years.

For now, OpenAI’s personal AGI is a bold direction but not yet a product people can plan around. The company must deliver concrete milestones: a prototype that demonstrates generalization, a clear pricing model, and robust safety guarantees. Until then, the vision remains aspirational. The world will be watching closely, as the outcome could reshape society in ways we are only beginning to imagine. Whether the AI for everyone arrives by 2028 or later, the conversation has already begun, and the stakes could not be higher.

Source: Digital Trends News

At the heart of Cisco's transformation is the goal of becoming a cloud service provider in its own right, according to industry analyst Jack Gold of J.Gold Associates. Instead of simply selling a box and walking away, Cisco wants to offer ongoing services that manage, secure, and optimize network traffic. This approach aligns with broader industry trends toward as-a-service models, where customers prefer predictable operational expenses over large capital outlays. By embedding itself deeper into customers' daily operations, Cisco also creates stickier relationships and more predictable revenue streams.

One of the key pillars of Cisco's software strategy is security. With its equipment positioned at critical junctures in enterprise and telecom networks, Cisco has an unparalleled view of data flows. The company is leveraging this vantage point to develop advanced security offerings, particularly as artificial intelligence introduces new threats and complexities. For example, the rise of AI agents—autonomous software entities that perform tasks on behalf of users or systems—creates a need for identity management tools that differ fundamentally from those designed for human users. While identity and access management for people is a mature market, managing the identities of potentially millions of AI agents is a largely untapped opportunity. Gold calls this a "greenfield environment," and Cisco is already moving to capture it.

In May 2026, Cisco announced its intention to acquire Astrix Security for an undisclosed sum. Astrix specializes in identifying, managing, and securing non-human identities, including machine-to-machine connections and AI agents. This acquisition bolsters Cisco's security portfolio and positions the company to address the emerging challenge of AI governance. As organizations deploy more autonomous agents, they will need tools to ensure those agents only access authorized data and systems. Cisco's existing networking foothold gives it a natural platform to integrate such capabilities.

Another critical component of Cisco's software push is platform integration. Despite its size, Cisco has long been known for a sprawling product portfolio that includes networking, security, compute (UCS servers), collaboration (Webex), and observability (AppDynamics). Historically, many of these products operated as standalone components, often managed through separate consoles. Jack Gold notes that this fragmentation is Cisco's greatest challenge. To address it, the company recently launched Cloud Control, a unified management plane that spans networking, security, compute, observability, and collaboration. Cloud Control promises a single pane of glass for IT administrators, simplifying operations and reducing silos. However, integration at customer sites may take time, especially where older Cisco products coexist with third-party gear.

Cisco's strategy does not unfold in a vacuum. Competitors are pursuing similar paths. Hewlett Packard Enterprise, through its Aruba networking division, is building a unified platform around its Edge-to-Cloud vision. Palo Alto Networks has expanded from firewalls into a comprehensive security platform that includes cloud-based Prisma offerings. Meanwhile, cloud hyperscalers like Amazon Web Services, Microsoft Azure, and Google Cloud offer integrated security and identity solutions tightly coupled with their own infrastructures. These rivals pose a threat, but Cisco's advantage lies in its enormous installed base and deep partnerships across enterprises, telecommunications providers, and semiconductor companies. Gold calls Cisco the "800-pound gorilla" in this space, a status that provides significant leverage when selling integrated solutions.

Look closer at Cisco's history, and you'll see that the software pivot has been years in the making. The company began acquiring software companies aggressively in the 2010s, with notable purchases including Meraki (cloud-managed networking), AppDynamics (application performance monitoring), and BroadSoft (unified communications). More recently, it has added cybersecurity firms like Duo Security and Armorblox. These acquisitions have been folded into Cisco's portfolio, but full integration remains a work in progress. Cloud Control represents the latest attempt to tie them all together.

An often-overlooked aspect of Cisco's strategy is its focus on the network fabric. Rather than selling individual components, Cisco wants to be the operator of comprehensive network fabrics that connect data centers, cloud environments, and edge locations. The company is positioning itself to manage the flow of data and AI-driven workloads across these environments, ensuring security, performance, and reliability. This vision extends beyond conventional networking into areas like AI workload distribution, where Cisco's silicon and software can optimize traffic patterns for machine learning training and inference.

Financially, the transition from hardware to software has been challenging but rewarding. Cisco's revenue has grown modestly, but margins on software and services are typically higher than on hardware. The recurring nature of subscription revenue also provides greater visibility into future cash flows. In 2025, Cisco reported that its annualized recurring revenue (ARR) exceeded $25 billion for the first time, a milestone that validates the strategic direction. The company also continues to return capital to shareholders through dividends and share buybacks, even as it invests in R&D and acquisitions.

Looking ahead, Cisco's ambition is to evolve from a hardware provider into a comprehensive network fabric operator. This means not only selling the infrastructure but also overseeing and securing the data that flows through it. The company aims to act as a central nervous system for enterprise IT, with software that can adapt to changing demands, protect against emerging threats, and scale to support AI-driven applications. While challenges remain—particularly around integration and competition—Cisco's scale, reach, and multi-year commitment to software make it a formidable player in the ongoing transformation of the networking industry.

Source: Network World News