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The Signalgate scandal that enveloped US Secretary of Defense Pete Hegseth in March appears to be symptomatic of a wider lax attitude towards the use of non-approved messaging apps by officials and employees, a Senate Committee has concluded.

In March, the US Senate Committee on Armed Services set out to examine issues raised by the Signalgate incident: the need to clarify the existing rules on using “non-controlled” apps, and looking at whether Defense Secretary Hegseth adhered to them in his use of Signal, and whether his actions were evidence of a wider culture of insecure app usage within the Department of Defense (DoD).

This week’s dual reports have come back with a mixed assessment of these points. Broadly, what Hegseth was accused of doing – communicating sensitive information using a third-party messaging app – appears to have been happening at the DoD in less serious contexts since at least 2020.

This mirrors issues familiar to enterprises: unsanctioned or unmanaged messaging apps, including ones touting end-to-end encryption (E2EE) security, quickly become an IT backchannel that can invisibly undermine carefully-assembled security, compliance, and data retention policies.

Shadow communications

The first report, an assessment of the Defense Secretary’s use of the Signal app to communicate with senior colleagues in advance of a military operation against Yemen on March 15, is used to illustrate the point. It confirms the widely reported fact that two hours before the raid, Hegseth revealed details of the operation to a Signal group of 19 people, including a journalist who had been added to it in error.

In doing so, the report agrees he violated security policies by sending sensitive information from a personal device, and using the non-approved Signal app in a way that revealed important operational details in advance of the strike. The report ducks the issue of whether this information was classified at the time it was sent, noting that Hegseth was senior enough to determine this for himself.

The second background report has uncovered evidence of a more general culture of shadow communications in the DoD, including widespread use of video-conferencing apps during the Covid 19 pandemic.  

The evidence gathered is sparse and partly redacted, making it difficult to assess the seriousness of any breaches. Because the scope of its remit was limited to the evidence from previous audits, one of the committee’s recommendations is to undertake a more comprehensive assessment of unsanctioned app usage inside the DoD. There’s also a question mark around how old audits analyzed by a Senate committee could accurately measure something that, by its nature, is hidden and only recorded on personal devices.

Nevertheless, the report says it is certain that Hegseth’s actions were not an isolated example, noting that staff had “used non-DoD-controlled electronic messaging systems for a variety of reasons. For example, some personnel used them because of the systems’ perceived appearance of security. As a result, DoD personnel increased the risk of exposing sensitive DoD information to our adversaries and did not comply with the legal obligation to retain and preserve official records.”

In short, while there was no evidence that unsanctioned app use is routine or normalized, it is likely that enough staff are using them to make a serious breach possible at some point. The report concludes that one of the reasons staff have taken to these messaging apps was that they lack convenient alternatives. It recommends developing approved apps to remove this need, implementing a training program to ensure existing communication regulations are complied with, and limiting the authority to use messaging apps to senior staff, in specific circumstances.

What’s surprising about this is that it has taken a major political row at government level to raise an issue that enterprise CISOs have been grappling with for years: the effects of BYOD, shadow IT (and now shadow AI), and unsanctioned apps that creep into organizations without anyone realizing it.

Over the last two decades, the rise of mobile devices, the cloud, and apps has radically de-centralized IT in ways that top-down management models struggle to control. Meanwhile, nothing has changed; the Signal app at the center of this scandal remains hugely popular on both sides of the political divide, despite the appearance of additional issues with the technology. 

This article originally appeared on CSOonline.

Source:: Computer World

The Signalgate scandal that enveloped US Secretary of Defense Pete Hegseth in March appears to be symptomatic of a wider lax attitude towards the use of non-approved messaging apps by officials and employees, a Senate Committee has concluded.

In March, the US Senate Committee on Armed Services set out to examine issues raised by the Signalgate incident: the need to clarify the existing rules on using “non-controlled” apps, and looking at whether Defense Secretary Hegseth adhered to them in his use of Signal, and whether his actions were evidence of a wider culture of insecure app usage within the Department of Defense (DoD).

This week’s dual reports have come back with a mixed assessment of these points. Broadly, what Hegseth was accused of doing – communicating sensitive information using a third-party messaging app – appears to have been happening at the DoD in less serious contexts since at least 2020.

This mirrors issues familiar to enterprises: unsanctioned or unmanaged messaging apps, including ones touting end-to-end encryption (E2EE) security, quickly become an IT backchannel that can invisibly undermine carefully-assembled security, compliance, and data retention policies.

Shadow communications

The first report, an assessment of the Defense Secretary’s use of the Signal app to communicate with senior colleagues in advance of a military operation against Yemen on March 15, is used to illustrate the point. It confirms the widely reported fact that two hours before the raid, Hegseth revealed details of the operation to a Signal group of 19 people, including a journalist who had been added to it in error.

In doing so, the report agrees he violated security policies by sending sensitive information from a personal device, and using the non-approved Signal app in a way that revealed important operational details in advance of the strike. The report ducks the issue of whether this information was classified at the time it was sent, noting that Hegseth was senior enough to determine this for himself.

The second background report has uncovered evidence of a more general culture of shadow communications in the DoD, including widespread use of video-conferencing apps during the Covid 19 pandemic.  

The evidence gathered is sparse and partly redacted, making it difficult to assess the seriousness of any breaches. Because the scope of its remit was limited to the evidence from previous audits, one of the committee’s recommendations is to undertake a more comprehensive assessment of unsanctioned app usage inside the DoD. There’s also a question mark around how old audits analyzed by a Senate committee could accurately measure something that, by its nature, is hidden and only recorded on personal devices.

Nevertheless, the report says it is certain that Hegseth’s actions were not an isolated example, noting that staff had “used non-DoD-controlled electronic messaging systems for a variety of reasons. For example, some personnel used them because of the systems’ perceived appearance of security. As a result, DoD personnel increased the risk of exposing sensitive DoD information to our adversaries and did not comply with the legal obligation to retain and preserve official records.”

In short, while there was no evidence that unsanctioned app use is routine or normalized, it is likely that enough staff are using them to make a serious breach possible at some point. The report concludes that one of the reasons staff have taken to these messaging apps was that they lack convenient alternatives. It recommends developing approved apps to remove this need, implementing a training program to ensure existing communication regulations are complied with, and limiting the authority to use messaging apps to senior staff, in specific circumstances.

What’s surprising about this is that it has taken a major political row at government level to raise an issue that enterprise CISOs have been grappling with for years: the effects of BYOD, shadow IT (and now shadow AI), and unsanctioned apps that creep into organizations without anyone realizing it.

Over the last two decades, the rise of mobile devices, the cloud, and apps has radically de-centralized IT in ways that top-down management models struggle to control. Meanwhile, nothing has changed; the Signal app at the center of this scandal remains hugely popular on both sides of the political divide, despite the appearance of additional issues with the technology. 

This article originally appeared on CSOonline.

Source:: Computer World

Music giant Warner Music Group announced last week that it had reached a “groundbreaking partnership agreement” with Suno, the AI startup at the forefront of AI-generated music it had sued for copyright infringement. After settling that fight, Warner Music signed new licensing models that allow Suno users to continue creating “music.”

Similar agreements have previously been inked with competitor Udio, and it seems highly likely that the other music giants will reach similar agreements. Whether it’s because record companies don’t want to risk making the “Napster mistake” again or they truly believe this is the future, AI services are here to stay.

Suno is undeniably popular. According to the company’s own figures, according to Billboard, users generate music equivalent to Spotify’s entire catalog every fortnight. The service has an admittedly high “wow” factor when tested. The results are impressive, technically speaking. But because it’s music, the question remains: who will listen to this?

I can understand the users, the people finding ways to express themselves creatively, even if it’s via prompts. If you think it’s fun to create AI-generated music, do it. Similarly, playing with Nano Banana for pictures, Sora for videos, or letting Chat GPT write a bedtime story is harmless. But just as no one wants to read an AI-generated book or be drowned in AI-generated images and clips, I don’t think music listeners are as keen on this.

If the services were intended solely for the creators themselves, the problem would be smaller. But unfortunately, the ambitions do not stop there. In its pitch deck to investors, Suno highlights the AI-created band Velvet Sundown, which became a talking point this summer: “Suno songs go viral outside the platform.”

And it’s that dream, to go viral or make a buck, that’s driving rivers of AI music to fill up streaming platforms. Spotify’s French competitor Deezer reports that more than 50,000 AI-generated songs are uploaded to the platform every day. And Spotify itself announced in September that it had removed more than 75 million songs that were considered pure AI garbage.

Sometimes it works. In addition to the aforementioned Velvet Sundown, country artist Breaking Rust recently gained attention when their song “Walk My Walk” topped Billboard’s country download chart and made it onto Spotify’s viral chart. (I hope these are the exceptions that prove the rule.)

A couple of weeks ago, I scrolled into a drama on Tiktok — as one tends to do on that platform — about the unknown artist Haven, whose song “I Run” topped Tiktok’s list of most popular songs. It had been revealed that the song was AI-generated and people were going crazy. Not because the song was bad, but because they felt cheated. Because it felt inauthentic. Because the music suddenly lost a lot of its value.

Authenticity should not be underestimated when it comes to music and other media. It may be that 97% of people can’t tell the difference between AI-generated and human-created music. But the feeling of being deceived is the same, whether it is disinformation in text and video or “good songs” created by AI. Artistic works also tend to be about an emotional connection to the work or to the creator, something I think a clear “AI labeling” of music would effectively kill.

Is there no use for AI-generated music then? Well, perhaps where that connection and authenticity doesn’t matter. A company like Sweden’s Epidemic Sound should be a little concerned. It licenses background music, what used to be called elevator music or muzak, for sound design in areas such as television and advertising. For those uses, AI music could be a cost-effective solution, just as AI-generated content is popular with marketers.

Haven had her song taken down from streaming platforms, and has now had to record a new version with real vocals instead of AI-generated ones. The singer whose voice was imitated, Jorja Smith, has demanded royalties through her record label.

How was the AI song made? With Suno. Maybe something for the next pitch deck.

This column is taken from CS Weekly, a personalized newsletter with reading tips, link tips and analysis sent directly from editor-in-chief Marcus Jerräng’s desk. Would you like to receive the newsletter on Fridays? Sign up for a free subscription here.

Source:: Computer World

By Adarsh Verma There’s nothing more exciting than planning a trip overseas — picking the perfect outfits, daydreaming about…
The post How To Avoid Roaming Charges When Travelling? appeared first on Fossbytes.

Source:: Fossbytes

By Deepti Pathak Buying clothes online is a gamble, because you can’t visualise how it’ll look on your body….
The post Google’s New Virtual Try-On Tool Lets You Try Clothes Using Just a Photo appeared first on Fossbytes.

Source:: Fossbytes

By Shikhar Mehrotra What’s happened? The Korean tech giant Samsung is working on a successor to the Galaxy Watch Ultra, which could arrive as soon as 2026. Why is this important? While information about the purported Galaxy Watch Ultra 2 remains scarce, the smartwatch should build upon the strong foundation laid by the original Watch Ultra. Why should […] The post Samsung has a new Apple Watch Ultra 3 rival in development, and it could arrive next year appeared first on Digital Trends.

Source:: Digital Trends

By Shikhar Mehrotra What’s happened? The Korean tech giant Samsung is working on a successor to the Galaxy Watch Ultra, which could arrive as soon as 2026. Why is this important? While information about the purported Galaxy Watch Ultra 2 remains scarce, the smartwatch should build upon the strong foundation laid by the original Watch Ultra. Why should […] The post Samsung has a new Apple Watch Ultra 3 rival in development, and it could arrive next year appeared first on Digital Trends.

Source:: Digital Trends

By Shikhar Mehrotra Apple’s upcoming watchOS 26.2 update brings Enhanced Safety Alerts to the Apple Watch, giving U.S. users faster, richer warnings during natural disasters.
The post Apple Watch will soon get enhanced emergency warnings for natural disasters appeared first on Digital Trends.

Source:: Digital Trends

Casino Grand Mondial: A Renaissance of Global Gaming Adventure

By Shikhar Mehrotra With a lightweight design, AMOLED display, and full health tracking suite, it could become an appealing alternative to pricier Apple and Samsung options.
The post The upcoming budget smartwatch from OnePlus doesn’t care which phone you use appeared first on Digital Trends.

Source:: Digital Trends

By Omair Khaliq Sultan If you’ve been thinking about upgrading from a basic tracker to a “real” fitness smartwatch, this is a good moment. The Garmin Venu 3 is currently $349.99 on Amazon in a limited-time deal, down from $449.99. You’re getting a bright 1.4-inch AMOLED touchscreen, Garmin’s deep health and fitness tracking, and battery life measured in days […] The post Garmin Venu 3 is down to $349.99 in a limited-time Amazon deal appeared first on Digital Trends.

Source:: Digital Trends

Police investigating the scandal around the UK Post Office Horizon IT system linked to the suicide of a numbers of its users are now considering corporate manslaughter charges against the companies involved, the National Police Chiefs’ Council (NPCC) has said.

The Post Office Horizon accounting system scandal is now seen as the UK’s biggest ever IT disaster and its worst miscarriage of justice. Between 1999 and 2015, more than 900 sub-postmasters were prosecuted for fraud, theft and false accounting.

Accounting discrepancies and shortfalls recorded by Horizon resulted in 236 being sent to prison. The Post Office claimed the discrepancies were the result of mistakes or fraud by sub-postmasters, but it later emerged that the system itself was at fault on a huge scale.

This resulted in the setting up of an official Post Office Horizon IT Inquiry in 2020 to look into the actions of the Post Office and the supplier which built the Horizon system, Fujitsu. At the same time, a separate 100-officer police operation dubbed ‘Operation Olympos’ was launched to investigate possible criminality.

The news that the police are now considering charges of corporate manslaughter is partly explained by the publication in July of part one of the inquiry’s final report. This concluded that the accounting fraud prosecutions were a factor in at least 13 suicides, with a further 59 people telling the inquiry that they’d contemplated taking their own lives.

According to this week’s NPCC update, the criminal investigation is currently focusing on eight suspects, five of whom had been interviewed under caution. Altogether, police had identified 53 persons of interest, many of whom might later become suspects, the NPCC said in a news briefing.

“We have not made any arrests, as it is not necessary given the way we interview and use additional warrants where necessary to secure additional material. We continue to focus on the offences of perjury and perverting the course of justice, but we are additionally considering corporate manslaughter charges,” the NPCC said.

Criminal charges

In UK law, corporate manslaughter is a criminal charge brought against organizations under the Corporate Manslaughter and Corporate Homicide Act 2007 where senior management are accused of grossly breaching their duty of care to an individual leading to their death. Prosecutions of this type have been uncommon, mainly because proving executive gross negligence sets a high bar.

However, this week’s NPCC update also raises the possibility that police might bring a separate common law charge, gross negligent manslaughter, against specific individuals. The police haven’t indicated who might be in the frame for such a charge, but it would presumably relate to decision makers working for the Post Office, Fujitsu or their advisors.

“The primary and sole focus at present remains the offences of perverting the course of justice and perjury and this has not changed. However, as was done with fraud offences previously, advice is being sought from the Crown Prosecution Service (CPS) around the offences of corporate and gross negligent manslaughter,” the NPCC said without elaborating on possible targets.

Separately, the NPCC said it was appealing for victims who signed non-disclosure agreements (NDAs) with the Post Office to come forward and speak to its investigation team. The NDAs would no longer be enforced, the NPCC said.

False Horizon

The Post Office started using Fujitsu’s Horizon accounting system in 1999, initially as ‘legacy’ Horizon until 2010 and then in a second version called Horizon Online, or HNG-X. Its purpose was to automate sales, stocktaking, and accounting across 18,500 post offices. Sub-postmasters were migrated from a paper-based accounting system to an online one that recorded all money going into and out of their accounts centrally.

The system had problems from its earliest days, with the first inquiry report finding that Fujitsu knew the system was prone to intermittent “bugs, errors and defects.” These included phantom withdrawals that could leave sub-postmaster accounts showing sometimes large discrepancies.

Instead of admitting to these problems, the Post Office steadfastly insisted the system was reliable and that the errors, sometimes running into thousands of pounds, were the result of sub-postmaster mistakes or deliberate theft.

Between 2000 and 2017, shortfalls affected 3,500 sub-postmasters, resulting in over 900 private prosecutions and 736 convictions. “All of these people are properly to be regarded as victims of wholly unacceptable behaviour perpetrated by a number of individuals employed by and/or associated with the Post Office and Fujitsu from time to time, and by the Post Office and Fujitsu as institutions,” said July’s first inquiry report.

Despite this week’s update, the Horizon scandal still has some way to go, with trials resulting from subsequent prosecutions not expected until 2027 or later.

Source:: Computer World

In a departure that took almost as long as Siri needs to find some obscure music requests, Apple has announced a new vice president of AI: Amar Subramanya, who will replace former AI chief John Giannandrea.

Subramanya will report directly to Craig Federighi, Apple’s senior vice president for software engineering. Giannandrea will “transition to an advisory role” pending planned retirement next year. Certain roles previously occupied by Giannandrea will be shifted to Apple COO Sabih Khan and Senior Vice President for Services Eddy Cue. Subramanya will lead Apple Intelligence and Siri’s next chapters.

“We are thankful for the role John played in building and advancing our AI work, helping Apple continue to innovate and enrich the lives of our users,” Tim Cook, Apple’s CEO, said in a statement. “AI has long been central to Apple’s strategy, and we are pleased to welcome Amar to Craig’s leadership team and to bring his extraordinary AI expertise to Apple. In addition to growing his leadership team and AI responsibilities with Amar’s joining, Craig has been instrumental in driving our AI efforts, including overseeing our work to bring a more personalized Siri to users next year.”

Who is Amar Subramanya?

The new Apple exec earned his bachelor’s degree at Bangalore University and completed a PhD in machine learning, large-scale systems and natural language technologies at the University of Washington. He also worked on speech recognition, natural language processing and multisensory fusion for robust speech systems while in college. At one point, he became a visiting researcher at Microsoft and received a Microsoft Research Graduate Fellowship.

Subramanaya took over leadership of Microsoft’s AI just 6 months ago, following 16 years at Google, including as vice president of engineering for Google Gemini. At Microsoft, he was involved with the development of foundation models for Copilot. But it’s likely his work on Gemini that most interests Apple as it seeks to build contextual intelligence in all its products, including Siri. 

Subramanya appears to have been instrumental in the development of the Google AI chatbot, and was the lead voice to announce the addition of 1.5 Flash to Gemini last year. He was also deeply involved in pulling together Google’s initial response to ChatGPT, Bard. He was also part of the effort to put a gloss of privacy over Google’s AI features, telling journalists in 2023 that Google Bard users could “opt out” of sharing their data when using the service. This awareness of the importance of privacy hints that Apple will remain focused on private and personal AI — time will tell. 

What will Subramanya do?

Subramanya will lead Apple’s teams in their work on foundation models, machine learning, and AI safety and evaluation. It is also important to note Subramanya’s extensive research background, which suggests how he will be able to help Apple weave AI more deeply across all its products and services. This extends to effective contribution in research and consumer facets of the role.

Apple describes these attributes as being “important to Apple’s ongoing innovation and future Apple Intelligence features.”

In the background

Unconfirmed speculation that Apple intends to use a licensed version of Google Gemini to support its own systems starting next year certainly lends a little additional excitement to word of the new hire. Subramanya is, after all, one of the small team of Google scientist researchers to have put Gemini together in the first place, which should assist Apple’s efforts to assimilate the Google tech, while also seeking to replace it with its own where possible.

The hire also indicates that Apple’s bleak days in a supposed AI desert are now behind it. Subramanya must now tell a story to his team to guide that journey out of the sand.

“This moment marks an exciting new chapter as Apple strengthens its commitment to shaping the future of AI for users everywhere,” said Apple.

You can follow me on social media! Join me on BlueSky,  LinkedIn, and Mastodon.

Source:: Computer World

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By Hisan Kidwai It’s not often, as a tech reviewer, that you receive a new phone and fall in…
The post vivo X300 Pro Review: Brings Out the Photographer In you appeared first on Fossbytes.

Source:: Fossbytes

It took just under three years, but Google has finally caught up and overtaken its AI competitors.

You remember how it was. When OpenAI released ChatGPT at the end of 2022 and created a world-wide sensation, Google was caught napping— and panicked. Despite the fact its researchers had introduced the architecture behind the new language models five years earlier, and despite having the now Nobel Prize-winning AI lab Deepmind in the corporate family, it was OpenAI, not Google, that developed the first widely usable model.

There’s a lot of rumor and speculation floating around about what it was like at Google at the time. CEO Sundar Pichai supposedly declared “Code Red” internally, something he later denied. Larry Page and Sergey Brin reportedly stepped back into the company in “founder mode.” Either way, Google reorganized and put Deepmind and its head, Demis Hassabis, in the driver’s seat to focus on the new large language models (LLMs).

Google’s first attempt was Bard; it was released in the spring of 2023 and made serious mistakes from the get-go. Clearly, despite its muscle, Google had a long way to go to catch up with OpenAI and its patron Microsoft.

The journey lasted three years, because when Google released Gemini 3 last month, it was immediately clear Google had — at least for now — taken the lead in AI by a fairly good margin. Gemini 3 crushes rival tools in most measurable parameters, and more importantly, is almost unanimously praised by users.

It is not only Gemini 3 that makes Google right. Competitors are sure to release new top models that will keep the rally at the top of the LLM Arena going. It’s how they’ve done it that puts Google in a unique position.

Gemini 3 is not trained on the same Nvidia GPUs everyone else uses, but on Google’s own TPU chips. TPUs are ASIC chips that have a single use case (or in this case two, AI training and inference). In other words, they’re much more specialized than a GPU used for just about everything.

That makes them more cost-effective, but more importantly, they’re Google’s own chips. This means Google now has the entire vertical in AI: its own chips with its own software layer; its own top models; its own data centers; its own cloud services; its own consumer services;. its own operating systems; its own browsers; and its own mobile devices. It’s basically the same recipe that created the modern Apple. (This is a journey that Microsoft also wants to take, with its own chips and its own models).

Add to this a huge competitive advantage in a data set that no one else comes close to, from years of search indexing, from all of Youtube, from Street View, from Waymo cars — the list goes on.

On the chip front, Google will certainly continue to buy and lease Nvidia chips to its cloud customers. But there are already reports of big customers wanting to use Google TPUs.

Who’s panicking now? OpenAI chief Sam Altman is reported to have sent an internal memo to his staff admitting Google’s progress on Gemini 3 and warning of a “tense atmosphere” and “financial headwinds.” He argued that OpenAI now needs to focus on “catching up fast.”

(For its part, Nvidia went on X and congratulated Google, while pointing out that its own technology is “a generation ahead.”

It’s still important to remember one thing: despite having the full stack in AI, Google is not an “AI company,” in the same way that it’s not really a search service either. Google is still an advertising company, the largest in the world.

Google Cloud, the IT services if you will, is certainly an increasingly important part of the equation. In the last quarter, Cloud revenue grew by 34% and now accounts for 15% of Alphabet’s revenue.

But 72% of Alphabet’s revenue still comes from ads — and it was that revenue that prompted (or didn’t prompt) Pichai to issue that Code Red. The concern was that ChatGPT would compete with Google on search and cut into advertising revenue. And the ambition now is to have the best AI solutions on the market to continue selling ads.

All this means that Google is less sensitive to the bursting of what has been called an “AI bubble.” It is neither dependent on “AI revenue” nor on the most vulnerable AI companies. If I were to make a prediction, Google is probably the company that would hold out best in the event of an AI crash.

However, Google is all the more sensitive to what AI does to the internet economy. Where will companies spend their marketing money when chatbots take over? Will AI summations send enough traffic to make advertisers think it’s worth it? What will be the price per click?

That’s where you should look to see whether Google really will be the “winner” in AI — in the ad market.

This column is taken from CS Weekly, a personalized newsletter with reading tips, link tips and analysis sent directly from Editor-in-Chief Marcus Jerräng’s desk. Would you like to receive the newsletter on Fridays? Sign up for a free subscription here.

Source:: Computer World

It took just under three years, but Google has finally caught up and overtaken its AI competitors.

You remember how it was. When OpenAI released ChatGPT at the end of 2022 and created a world-wide sensation, Google was caught napping— and panicked. Despite the fact its researchers had introduced the architecture behind the new language models five years earlier, and despite having the now Nobel Prize-winning AI lab Deepmind in the corporate family, it was OpenAI, not Google, that developed the first widely usable model.

There’s a lot of rumor and speculation floating around about what it was like at Google at the time. CEO Sundar Pichai supposedly declared “Code Red” internally, something he later denied. Larry Page and Sergey Brin reportedly stepped back into the company in “founder mode.” Either way, Google reorganized and put Deepmind and its head, Demis Hassabis, in the driver’s seat to focus on the new large language models (LLMs).

Google’s first attempt was Bard; it was released in the spring of 2023 and made serious mistakes from the get-go. Clearly, despite its muscle, Google had a long way to go to catch up with OpenAI and its patron Microsoft.

The journey lasted three years, because when Google released Gemini 3 last month, it was immediately clear Google had — at least for now — taken the lead in AI by a fairly good margin. Gemini 3 crushes rival tools in most measurable parameters, and more importantly, is almost unanimously praised by users.

It is not only Gemini 3 that makes Google right. Competitors are sure to release new top models that will keep the rally at the top of the LLM Arena going. It’s how they’ve done it that puts Google in a unique position.

Gemini 3 is not trained on the same Nvidia GPUs everyone else uses, but on Google’s own TPU chips. TPUs are ASIC chips that have a single use case (or in this case two, AI training and inference). In other words, they’re much more specialized than a GPU used for just about everything.

That makes them more cost-effective, but more importantly, they’re Google’s own chips. This means Google now has the entire vertical in AI: its own chips with its own software layer; its own top models; its own data centers; its own cloud services; its own consumer services;. its own operating systems; its own browsers; and its own mobile devices. It’s basically the same recipe that created the modern Apple. (This is a journey that Microsoft also wants to take, with its own chips and its own models).

Add to this a huge competitive advantage in a data set that no one else comes close to, from years of search indexing, from all of Youtube, from Street View, from Waymo cars — the list goes on.

On the chip front, Google will certainly continue to buy and lease Nvidia chips to its cloud customers. But there are already reports of big customers wanting to use Google TPUs.

Who’s panicking now? OpenAI chief Sam Altman is reported to have sent an internal memo to his staff admitting Google’s progress on Gemini 3 and warning of a “tense atmosphere” and “financial headwinds.” He argued that OpenAI now needs to focus on “catching up fast.”

(For its part, Nvidia went on X and congratulated Google, while pointing out that its own technology is “a generation ahead.”

It’s still important to remember one thing: despite having the full stack in AI, Google is not an “AI company,” in the same way that it’s not really a search service either. Google is still an advertising company, the largest in the world.

Google Cloud, the IT services if you will, is certainly an increasingly important part of the equation. In the last quarter, Cloud revenue grew by 34% and now accounts for 15% of Alphabet’s revenue.

But 72% of Alphabet’s revenue still comes from ads — and it was that revenue that prompted (or didn’t prompt) Pichai to issue that Code Red. The concern was that ChatGPT would compete with Google on search and cut into advertising revenue. And the ambition now is to have the best AI solutions on the market to continue selling ads.

All this means that Google is less sensitive to the bursting of what has been called an “AI bubble.” It is neither dependent on “AI revenue” nor on the most vulnerable AI companies. If I were to make a prediction, Google is probably the company that would hold out best in the event of an AI crash.

However, Google is all the more sensitive to what AI does to the internet economy. Where will companies spend their marketing money when chatbots take over? Will AI summations send enough traffic to make advertisers think it’s worth it? What will be the price per click?

That’s where you should look to see whether Google really will be the “winner” in AI — in the ad market.

This column is taken from CS Weekly, a personalized newsletter with reading tips, link tips and analysis sent directly from Editor-in-Chief Marcus Jerräng’s desk. Would you like to receive the newsletter on Fridays? Sign up for a free subscription here.

Source:: Computer World

User consent is under threat, at least when it comes to your right to decide what apps to install on your device. That’s because India now wants all smartphone makers to install a government-mandated app on their devices, an app that cannot be deleted. It’s yet another privacy-related struggle for Apple — and for all of us. 

What happened? India’s Ministry of Communications last week privately demanded that manufacturers pre-install India’s Sanchar Saathi app on mobile devices within just 90 days. The demand doesn’t only affect smartphones intended for sale in India, as manufacturers will also be forced to install the app on older devices through a future software update.

India, Apple, and Google have been discussing these plans all year, and it is noteworthy that the demand so far has only been shared privately. (India is also one of those governments to have demanded pre-screening of operating system updates.)

What is the Sanchar Saathi app?

India’s Department of Telecommunications says the app helps prevent duplication and spoofing of IMEI numbers, which helps protect against scams and fraud and helps track stolen/counterfeit devices. IMEI numbers are 14 to 17 digits long and can be used to cut off network access.

The app, which is also available as a web portal, lets you: 

Report suspected fraudulent communication.

Report unsolicited commercial communications and spam.

Track your lost or stolen device, mobile connections, and ISP.

Block a lost or stolen device and monitor mobile connections in your name.

Verify whether an incoming call or a contact being called belongs to an authentic source to protect against fraud.

The app has been downloaded 5 million times since January, according to the government, which says it has been used to recover more than 700,000 lost devices. The app uses a central registrar accessed by the networks, which can also be used to turn off network access. 

What will Apple do?

Apple has resisted similar attempts to pre-install government-mandated apps in the past, so is likely to do so again. That’s because the company understands that once you permit one government to install apps on devices, every government will do the same – and since these apps aren’t necessarily designed within Apple’s own privacy and security guidelines, they might be unsafe. This raises the specter of state surveillance being just one app install away.

Speaking to Reuters, Internet advocacy lawyer Mishi Choudhary said the demand “effectively removes user consent as a meaningful choice.”

It is worth notingthat while Apple will resist government attempts to chip away at the privacy and security of its platforms, the company remains subject to the law. That is why it may already have created a backdoor vulnerability in the iPhone to meet demands made by the rogue UK government, and it’s why in China it ensures iCloud data is stored on locally-based servers. Ultimately, and perhaps, sadly, if people want to oppose creeping state surveillance, they have to be willing to oppose it themselves in the political sphere, rather than relying on private companies to fight on their behalf. Apple, like anyone else, must act within the law, even when the law is foolish, dangerous, or misconstrued.

India’s demand must be weighed up beside the country’s second demand: that all encrypted messaging apps link to the unique SIM serial number, further eroding privacy.

What could happen?

The company does have some power to bring to the table. It’s manufacturing investment in India is generating significant economic benefits and the nation is unlikely to see Apple’s interest fade in extending those investments.

It is possible that as discussions move forward, Apple might persuade the government to abandon demands for mandatory installation of the app in favor of a prominent nudge screen when users first update an existing device or start using a new one. Doing so would, at least, support the notion of free choice.

You can follow me on social media! Join me on BlueSky,  LinkedIn, and Mastodon.

Source:: Computer World

By Manisha Priyadarshini A new human washing machine from Japan can wash your entire body in just 15 minutes. You simply need to lie inside the capsule while microbubbles, sensors, and a preset routine handles the whole bath for you.
The post Too lazy to shower? This human washing machine can clean your body in 15 minutes appeared first on Digital Trends.

Source:: Digital Trends