In Delhi's Nehru Place and Mumbai's Lamington Road, technicians are creating functional laptops from salvaged parts of multiple discarded devices. These "Frankenstein" machines sell for approximately $110 USD -- a fraction of the $800 price tag for new models. Technicians extract usable components -- motherboards, capacitors, screens, and batteries -- from e-waste sourced locally and from countries like Dubai and China.

"Most people don't care about having the latest model; they just want something that works and won't break the bank," a technician told Verge. This repair ecosystem operates within a larger battle against tech giants pushing planned obsolescence through proprietary designs and restricted parts access. Many technicians source components from Seelampur, India's largest e-waste hub processing 30,000 tonnes daily, though workers there handle toxic materials with minimal protection. "India has always had a repair culture," says Satish Sinha of Toxics Link, "but companies are pushing planned obsolescence, making repairs harder and forcing people to buy new devices."

AmiMoJo writes: The Shenzhen 8K UHD Video Industry Cooperation Alliance, a group made up of more than 50 Chinese companies, just released a new wired media communication standard called the General Purpose Media Interface or GPMI. This standard was developed to support 8K and reduce the number of cables required to stream data and power from one device to another. According to HKEPC, the GPMI cable comes in two flavors -- a Type-B that seems to have a proprietary connector and a Type-C that is compatible with the USB-C standard.

Because 8K has four times the number of pixels of 4K and 16 times more pixels than 1080p resolution, it means that GPMI is built to carry a lot more data than other current standards. There are other variables that can impact required bandwidth, of course, such as color depth and refresh rate. The GPMI Type-C connector is set to have a maximum bandwidth of 96 Gbps and deliver 240 watts of power. This is more than double the 40 Gbps data limit of USB4 and Thunderbolt 4, allowing you to transmit more data on the cable. However, it has the same power limit as that of the latest USB Type-C connector using the Extended Power Range (EPR) standard. GPMI Type-B beats all other cables, though, with its maximum bandwidth of 192 Gbps and power delivery of up to 480 watts.

"Gen Z is rediscovering Tumblr — a chaotic, cozy corner of the internet untouched by algorithmic gloss and influencer overload..." writes Fast Company, "embracing the platform as a refuge from an internet saturated with influencers and algorithm fatigue." Thanks to Gen Z, the site has found new life. As of 2025, Gen Z makes up 50% of Tumblr's active monthly users and accounts for 60% of new sign-ups, according to data shared with Business Insider's Amanda Hoover, who recently reported on the platform's resurgence. User numbers spiked in January during the near-ban of TikTok and jumped again last year when Brazil temporarily banned X. In response, Tumblr users launched dedicated communities to archive and share their favorite TikToks...

To keep up with the momentum, Tumblr introduced Reddit-style Communities in December, letting users connect over shared interests like photography and video games. In January, it debuted Tumblr TV — a TikTok-like feature that serves as both a GIF search engine and a short-form video platform. But perhaps Tumblr's greatest strength is that it isn't TikTok or Facebook. Currently the 10th most popular social platform in the U.S., according to analytics firm Similarweb, Tumblr is dwarfed by giants like Instagram and X. For its users, though, that's part of the appeal.
First launched in 2007, Tumblr peaked at over 100 million users in 2014, according to the article. Trends like Occupy Wall Street had been born on Tumblr, notes Business Insider, calling the blogging platform "Gen Z's safe space... as the rest of the social internet has become increasingly commodified, polarized, and dominated by lifestyle influencers." Tumblr was also "one of the most hyped startups in the world before fading into obsolescence — bought by Yahoo for $1.1 billion in 2013... then acquired by Verizon, and later offloaded for fractions of pennies on the dollar in a distressed sale.

"That same Tumblr, a relic of many millennials' formative years, has been having a moment among Gen Z..." "Gen Z has this romanticism of the early-2000s internet," says Amanda Brennan, an internet librarian who worked at Tumblr for seven years, leaving her role as head of content in 2021... Part of the reason young people are hanging out on old social platforms is that there's nowhere new to go. The tech industry is evolving at a slower pace than it was in the 2000s, and there's less room for disruption. Big Tech has a stranglehold on how we socialize. That leaves Gen Z to pick up the scraps left by the early online millennials and attempt to craft them into something relevant. They love Pinterest (founded in 2010) and Snapchat (2011), and they're trying out digital point-and-shoot cameras and flip phones for an early-2000s aesthetic — and learning the valuable lesson that sometimes we look better when blurrier.

More Gen Zers and millennials are signing up for Yahoo. Napster, surprising many people with its continued existence, just sold for $207 million. The trend is fueled by nostalgia for Y2K aesthetics and a longing for a time when people could make mistakes on the internet and move past them. The pandemic also brought more Gen Z users to Tumblr...

And Tumblr still works much like an older internet, where people have more control over what they see and rely less on algorithms. "You curate your own stuff; it takes a little bit of work to put everything in place, but when it's working, you see the content you want to see," Fjodor Everaerts, a 26-year-old in Belgium who has made some 250,000 posts since he joined Tumblr when he was 14... Under Automattic, Tumblr is finally in the home that serves it, [says Ari Levine, the head of brand partnerships at Tumblr]. "We've had ups and downs along the way, but we're in the most interesting position and place that we've been in 18 years," he says... And following media companies (including Business Insider) and social platforms like Reddit, Automattic in 2024 was making a deal with OpenAI and Midjourney to allow the systems to train on Tumblr posts.

"The social internet is fractured," the article argues. ("Millennials are running Reddit. Gen Xers and Baby Boomers have a home on Facebook. Bluesky, one of the new X alternatives, has a tangible elder-millennial/Gen X vibe. Gen Zers have created social apps like BeReal and the Myspace-inspired Noplace, but they've so far generated more hype than influence....")

But in a world where megaplatforms "flatten our online experiences and reward content that fits a mold," the article suggests, "smaller communities can enrich them."

"U.S. stock market futures plunged on Sunday evening," reports Yahoo Finance, "after the new U.S. tariff policy began collecting duties over the weekend..."

The EU will vote on $28 billion in retaliatory tariffs Wednesday, Reuters reports. (And those tariffs will be approved unless "a qualified majority of 15 EU members representing 65% of the EU's population oppose it. They would enter force in two stages, a smaller part on April 15 and the rest a month later.")

But France's Economy and Finance Minister has an idea: more strictly regulating how data is used by America's Big Tech companies. Politico EU reports/A>: "We may strengthen certain administrative requirements or regulate the use of data," Lombard said in an interview with Le Journal Du Dimanche. He added that another option could be to "tax certain activities," without being more specific.

A French government spokesperson already said last week that the EU's retaliation against U.S. tariffs could include "digital services that are currently not taxed." That suggestion was fiercely rejected by Ireland, which hosts the European headquarters of several U.S. Big Tech firms...

Technology is seen as a possible area for Europe to retaliate. The European Union has a €157 billion trade surplus in goods, which means it exports more than it imports, but it runs a deficit of €109 billion in services, including digital services. Big Tech giants like Apple, Microsoft, Amazon, Google and Meta dominate many parts of the market in Europe.
Amid the market turmoil, what about cryptocurrencies, often seen as a "proxy" for the level of risk felt by investors? In the 10 weeks after October 6, the price of Bitcoin skyrocketed 67% to $106,490 by December 10th. But by January 30th it had started dropping again, and now sits at $77,831 — still up 22% for the last six months, but down nearly 27% over the last 10 weeks. Yet even after all that volatility, Bitcoin suddenly fell again more than 6% on Sunday, reports Reuters, "as markets plunged amid tariff tensions. Ether, the second largest cryptocurrency, fell more than 10% on Sunday."

It's "a milestone for Meta AI and for open source," Mark Zuckerberg said this weekend. "For the first time, the best small, mid-size, and potentially soon frontier [large-language] models will be open source."

Zuckerberg anounced four new Llama LLMs in a video posted on Instagram and Facebook — two dropping this weekend, with another two on the way. "Our goal is to build the world's leading AI, open source it, and make it universally accessible so that everyone in the world benefits."

Zuckerberg's announcement: I've said for a while that I think open source AI is going to become the leading models. And with Llama 4 this is starting to happen.

- The first model is Llama 4 Scout. It is extremely fast, natively multi-modal. It has an industry-leading "nearly infinite" 10M-token context length, and is designed to run on a single GPU. [Meta's blog post says it fits on an NVIDIA H100]. It is 17 billion parameters by 16 experts, and it is by far the highest performing small model in its class.

- The second model is Llama 4 Maverick — the workhorse. It beats GPT-4o and Gemini Flash 2 on all benchmarks. It is smaller and more efficient than DeepSeek v3, but it is still comparable on text, plus it is natively multi-modal. This one is 17B parameters x 128 experts, and it is designed to run on a single host for easy inference.

This thing is a beast.
Zuck promised more news next month on "Llama 4 Reasoning" — but the fourth model will be called Llama 4 Behemoth. "This thing is massive. More than 2 trillion parameters." (A blog post from Meta AI says it also has a 288 billion active parameter model, outperforms GPT-4.5, Claude Sonnet 3.7, and Gemini 2.0 Pro on STEM benchmarks, and will "serve as a teacher for our new models.")

"I'm not aware of anyone training a larger model out there," Zuckberg says in his video, calling Behemoth "already the highest performing base model in the world, and it is not even done training yet."

"If you want to try Llama 4, you can use Meta AI in WhatsApp, Messenger, or Instagram Direct," Zuckberg said in his video, "or you can go to our web site at meta.ai." The Scout and Maverick models can be downloaded from llama.com and Hugging Face.

"We continue to believe that openness drives innovation," Meta AI says in their blog post, "and is good for developers, good for Meta, and good for the world." Their blog post declares it's "The beginning of a new era of natively multimodal AI innovation," calling Scout and Maverick "the best choices for adding next-generation intelligence." This is just the beginning for the Llama 4 collection. We believe that the most intelligent systems need to be capable of taking generalized actions, conversing naturally with humans, and working through challenging problems they haven't seen before. Giving Llama superpowers in these areas will lead to better products for people on our platforms and more opportunities for developers to innovate on the next big consumer and business use cases. We're continuing to research and prototype both models and products, and we'll share more about our vision at LlamaCon on April 29...

We also can't wait to see the incredible new experiences the community builds with our new Llama 4 models.
"The impressive part about Llama 4 Maverick is that with just 17B active parameters, it has scored an ELO score of 1,417 on the LMArena leaderboard," notes the tech news site Beebom. "This puts the Maverick model in the second spot, just below Gemini 2.5 Pro, and above Grok 3, GPT-4o, GPT-4.5, and more.

"It also achieves comparable results when compared to the latest DeepSeek V3 model on reasoning and coding tasks, and surprisingly, with just half the active parameters."

Microsoft has created a real-time AI-generated rendition of Quake II gameplay (playable on the web).

Friday Xbox's general manager of gaming AI posted the startling link to "an AI-generated gaming experience" at Copilot.Microsoft.com "Move, shoot, explore — and every frame is created on the fly by an AI world model, responding to player inputs in real-time. Try it here."

They started with their "Muse" videogame world models, adding "a real-time playable extension" that players can interact with through keyboard/controller actions, "essentially allowing you to play inside the model," according to a Microsoft blog post. A concerted effort by the team resulted in both planning out what data to collect (what game, how should the testers play said game, what kind of behaviours might we need to train a world model, etc), and the actual collection, preparation, and cleaning of the data required for model training. Much to our initial delight we were able to play inside the world that the model was simulating. We could wander around, move the camera, jump, crouch, shoot, and even blow-up barrels similar to the original game. Additionally, since it features in our data, we can also discover some of the secrets hidden in this level of Quake II. We can also insert images into the models' context and have those modifications persist in the scene...

We do not intend for this to fully replicate the actual experience of playing the original Quake II game. This is intended to be a research exploration of what we are able to build using current ML approaches. Think of this as playing the model as opposed to playing the game... The interactions with enemy characters is a big area for improvement in our current WHAMM model. Often, they will appear fuzzy in the images and combat with them (damage being dealt to both the enemy/player) can be incorrect.
They warn that the model "can and will forget about objects that go out of view" for longer than 0.9 seconds. "This can also be a source of fun, whereby you can defeat or spawn enemies by looking at the floor for a second and then looking back up. Or it can let you teleport around the map by looking up at the sky and then back down. These are some examples of playing the model."

This generative AI model was trained on Quake II "with just over a week of data," reports Tom's Hardware — a dramatic reduction from the seven years required for the original model launched in February.

Some context from The Verge: "You could imagine a world where from gameplay data and video that a model could learn old games and really make them portable to any platform where these models could run," said Microsoft Gaming CEO Phil Spencer in February. "We've talked about game preservation as an activity for us, and these models and their ability to learn completely how a game plays without the necessity of the original engine running on the original hardware opens up a ton of opportunity."
"Is porting a game like Gameday 98 more feasible through AI or a small team?" asks the blog Windows Central. "What costs less or even takes less time? These are questions we'll be asking and answering over the coming decade as AI continues to grow. We're in year two of the AI boom; I'm terrified of what we'll see in year 10."

"It's clear that Microsoft is now training Muse on more games than just Bleeding Edge," notes The Verge, "and it's likely we'll see more short interactive AI game experiences in Copilot Labs soon." Microsoft is also working on turning Copilot into a coach for games, allowing the AI assistant to see what you're playing and help with tips and guides. Part of that experience will be available to Windows Insiders through Copilot Vision soon.

Wikipedia remembers Dave Täht as "an American network engineer, musician, lecturer, asteroid exploration advocate, and Internet activist. He was the chief executive officer of TekLibre."

But on X.com Eric S. Raymond called him "one of the unsung heroes of the Internet, and a close friend of mine who I will miss very badly." Dave, known on X as @mtaht because his birth name was Michael, was a true hacker of the old school who touched the lives of everybody using X. His work on mitigating bufferbloat improved practical TCP/IP performance tremendously, especially around video streaming and other applications requiring low latency. Without him, Netflix and similar services might still be plagued by glitches and stutters.
Also on X, legendary game developer John Carmack remembered that Täht "did a great service for online gamers with his long campaign against bufferbloat in routers and access points. There is a very good chance your packets flow through some code he wrote." (Carmack also says he and Täht "corresponded for years".)

Long-time Slashdot reader TheBracket remembers him as "the driving force behind ">the Bufferbloat project and a contributor to FQ-CoDel, and CAKE in the Linux kernel."

Dave spent years doing battle with Internet latency and bufferbloat, contributing to countless projects. In recent years, he's been working with Robert, Frank and myself at LibreQoS to provide CAKE at the ISP level, helping Starlink with their latency and bufferbloat, and assisting the OpenWrt project.
Eric Raymond remembered first meeting Täht in 2001 "near the peak of my Mr. Famous Guy years. Once, sometimes twice a year he'd come visit, carrying his guitar, and crash out in my basement for a week or so hacking on stuff. A lot of the central work on bufferbloat got done while I was figuratively looking over his shoulder..."

Raymond said Täht "lived for the work he did" and "bore deteriorating health stoically. While I know him he went blind in one eye and was diagnosed with multiple sclerosis." He barely let it slow him down. Despite constantly griping in later years about being burned out on programming, he kept not only doing excellent work but bringing good work out of others, assembling teams of amazing collaborators to tackle problems lesser men would have considered intractable... Dave should have been famous, and he should have been rich. If he had a cent for every dollar of value he generated in the world he probably could have bought the entire country of Nicaragua and had enough left over to finance a space program. He joked about wanting to do the latter, and I don't think he was actually joking...

In the invisible college of people who made the Internet run, he was among the best of us. He said I inspired him, but I often thought he was a better and more selfless man than me. Ave atque vale, Dave.
Weeks before his death Täht was still active on X.com, retweeting LWN's article about "The AI scraperbot scourge", an announcement from Texas Instruments, and even a Slashdot headline.

Täht was also Slashdot reader #603,670, submitting stories about network latency, leaving comments about AI, and making announcements about the Bufferbloat project.

Is OpenAI's ChatGPT violating copyrights? The New York Times sued OpenAI in December 2023. But Ars Technica summarizes OpenAI's response. The New York Times (or NYT) "should have known that ChatGPT was being trained on its articles... partly because of the newspaper's own reporting..."

OpenAI pointed to a single November 2020 article, where the NYT reported that OpenAI was analyzing a trillion words on the Internet.

But on Friday, U.S. district judge Sidney Stein disagreed, denying OpenAI's motion to dismiss the NYT's copyright claims partly based on one NYT journalist's reporting. In his opinion, Stein confirmed that it's OpenAI's burden to prove that the NYT knew that ChatGPT would potentially violate its copyrights two years prior to its release in November 2022... And OpenAI's other argument — that it was "common knowledge" that ChatGPT was trained on NYT articles in 2020 based on other reporting — also failed for similar reasons...

OpenAI may still be able to prove through discovery that the NYT knew that ChatGPT would have infringing outputs in 2020, Stein said. But at this early stage, dismissal is not appropriate, the judge concluded. The same logic follows in a related case from The Daily News, Stein ruled. Davida Brook, co-lead counsel for the NYT, suggested in a statement to Ars that the NYT counts Friday's ruling as a win. "We appreciate Judge Stein's careful consideration of these issues," Brook said. "As the opinion indicates, all of our copyright claims will continue against Microsoft and OpenAI for their widespread theft of millions of The Times's works, and we look forward to continuing to pursue them."

The New York Times is also arguing that OpenAI contributes to ChatGPT users' infringement of its articles, and OpenAI lost its bid to dismiss that claim, too. The NYT argued that by training AI models on NYT works and training ChatGPT to deliver certain outputs, without the NYT's consent, OpenAI should be liable for users who manipulate ChatGPT to regurgitate content in order to skirt the NYT's paywalls... At this stage, Stein said that the NYT has "plausibly" alleged contributory infringement, showing through more than 100 pages of examples of ChatGPT outputs and media reports showing that ChatGPT could regurgitate portions of paywalled news articles that OpenAI "possessed constructive, if not actual, knowledge of end-user infringement." Perhaps more troubling to OpenAI, the judge noted that "The Times even informed defendants 'that their tools infringed its copyrighted works,' supporting the inference that defendants possessed actual knowledge of infringement by end users."

An anonymous reader quotes a report from the Associated Press: It took only seconds for the judges on a New York appeals court to realize that the man addressing them from a video screen -- a person about to present an argument in a lawsuit -- not only had no law degree, but didn't exist at all. The latest bizarre chapter in the awkward arrival of artificial intelligence in the legal world unfolded March 26 under the stained-glass dome of New York State Supreme Court Appellate Division's First Judicial Department, where a panel of judges was set to hear from Jerome Dewald, a plaintiff in an employment dispute. "The appellant has submitted a video for his argument," said Justice Sallie Manzanet-Daniels. "Ok. We will hear that video now."

On the video screen appeared a smiling, youthful-looking man with a sculpted hairdo, button-down shirt and sweater. "May it please the court," the man began. "I come here today a humble pro se before a panel of five distinguished justices." "Ok, hold on," Manzanet-Daniels said. "Is that counsel for the case?" "I generated that. That's not a real person," Dewald answered. It was, in fact, an avatar generated by artificial intelligence. The judge was not pleased. "It would have been nice to know that when you made your application. You did not tell me that sir," Manzanet-Daniels said before yelling across the room for the video to be shut off. "I don't appreciate being misled," she said before letting Dewald continue with his argument.

Dewald later penned an apology to the court, saying he hadn't intended any harm. He didn't have a lawyer representing him in the lawsuit, so he had to present his legal arguments himself. And he felt the avatar would be able to deliver the presentation without his own usual mumbling, stumbling and tripping over words. In an interview with The Associated Press, Dewald said he applied to the court for permission to play a prerecorded video, then used a product created by a San Francisco tech company to create the avatar. Originally, he tried to generate a digital replica that looked like him, but he was unable to accomplish that before the hearing. "The court was really upset about it," Dewald conceded. "They chewed me up pretty good." [...] As for Dewald's case, it was still pending before the appeals court as of Thursday.

An anonymous reader shares a report: AI is projected to reach $4.8 trillion in market value by 2033, but the technology's benefits remain highly concentrated, according to the U.N. Trade and Development agency. In a report released on Thursday, UNCTAD said the AI market cap would roughly equate to the size of Germany's economy, with the technology offering productivity gains and driving digital transformation. However, the agency also raised concerns about automation and job displacement, warning that AI could affect 40% of jobs worldwide. On top of that, AI is not inherently inclusive, meaning the economic gains from the tech remain "highly concentrated," the report added.

"The benefits of AI-driven automation often favour capital over labour, which could widen inequality and reduce the competitive advantage of low-cost labour in developing economies," it said. The potential for AI to cause unemployment and inequality is a long-standing concern, with the IMF making similar warnings over a year ago. In January, The World Economic Forum released findings that as many as 41% of employers were planning on downsizing their staff in areas where AI could replicate them. However, the UNCTAD report also highlights inequalities between nations, with U.N. data showing that 40% of global corporate research and development spending in AI is concentrated among just 100 firms, mainly those in the U.S. and China.

Camera manufacturers continue to use different proprietary RAW file formats despite the 20-year existence of Adobe's open-source DNG (Digital Negative) format, creating ongoing compatibility challenges for photographers and software developers.

Major manufacturers including Sony, Canon, and Panasonic defended their proprietary formats as necessary for maintaining control over image processing. Sony's product team told The Verge their ARW format allows them "to maximize performance based on device characteristics such as the image sensor and image processing engine." Canon similarly claims proprietary formats enable "optimum processing during image development."

The Verge argues that this fragmentation forces editing software to specifically support each manufacturer's format and every new camera model -- creating delays for early adopters when new cameras launch. Each new device requires "measuring sensor characteristics such as color and noise," said Adobe's Eric Chan.

For what it's worth, smaller manufacturers like Ricoh, Leica, and Sigma have adopted DNG, which streamlines workflow by containing metadata directly within a single file rather than requiring separate XMP sidecar files.

An anonymous reader quotes a report from Reuters: Visa has offered Apple roughly $100 million to take over the tech giant's credit card partnership from Mastercard, the Wall Street Journal reported on Tuesday, citing sources familiar with the matter. Visa has made a bold push to secure the Apple Card, offering an upfront payment typically reserved for the largest card programs, WSJ reported. American Express is also trying to unseat Mastercard to win the Apple card. Amex is looking to become the card's issuer as well as the network, the report said, citing the sources. Goldman Sachs ended its partnership with Apple in late 2023 as the Wall Street bank retreated from consumer lending.

An anonymous reader quotes a report from Ars Technica, written by Ryan Whitwam: Researchers at DeepMind have ... released a new technical paper (PDF) that explains how to develop AGI safely, which you can download at your convenience. It contains a huge amount of detail, clocking in at 108 pages before references. While some in the AI field believe AGI is a pipe dream, the authors of the DeepMind paper project that it could happen by 2030. With that in mind, they aimed to understand the risks of a human-like synthetic intelligence, which they acknowledge could lead to "severe harm." This work has identified four possible types of AGI risk, along with suggestions on how we might ameliorate said risks. The DeepMind team, led by company co-founder Shane Legg, categorized the negative AGI outcomes as misuse, misalignment, mistakes, and structural risks.

The first possible issue, misuse, is fundamentally similar to current AI risks. However, because AGI will be more powerful by definition, the damage it could do is much greater. A ne'er-do-well with access to AGI could misuse the system to do harm, for example, by asking the system to identify and exploit zero-day vulnerabilities or create a designer virus that could be used as a bioweapon. DeepMind says companies developing AGI will have to conduct extensive testing and create robust post-training safety protocols. Essentially, AI guardrails on steroids. They also suggest devising a method to suppress dangerous capabilities entirely, sometimes called "unlearning," but it's unclear if this is possible without substantially limiting models. Misalignment is largely not something we have to worry about with generative AI as it currently exists. This type of AGI harm is envisioned as a rogue machine that has shaken off the limits imposed by its designers. Terminators, anyone? More specifically, the AI takes actions it knows the developer did not intend. DeepMind says its standard for misalignment here is more advanced than simple deception or scheming as seen in the current literature.

To avoid that, DeepMind suggests developers use techniques like amplified oversight, in which two copies of an AI check each other's output, to create robust systems that aren't likely to go rogue. If that fails, DeepMind suggests intensive stress testing and monitoring to watch for any hint that an AI might be turning against us. Keeping AGIs in virtual sandboxes with strict security and direct human oversight could help mitigate issues arising from misalignment. Basically, make sure there's an "off" switch. If, on the other hand, an AI didn't know that its output would be harmful and the human operator didn't intend for it to be, that's a mistake. We get plenty of those with current AI systems -- remember when Google said to put glue on pizza? The "glue" for AGI could be much stickier, though. DeepMind notes that militaries may deploy AGI due to "competitive pressure," but such systems could make serious mistakes as they will be tasked with much more elaborate functions than today's AI. The paper doesn't have a great solution for mitigating mistakes. It boils down to not letting AGI get too powerful in the first place. DeepMind calls for deploying slowly and limiting AGI authority. The study also suggests passing AGI commands through a "shield" system that ensures they are safe before implementation.

Lastly, there are structural risks, which DeepMind defines as the unintended but real consequences of multi-agent systems contributing to our already complex human existence. For example, AGI could create false information that is so believable that we no longer know who or what to trust. The paper also raises the possibility that AGI could accumulate more and more control over economic and political systems, perhaps by devising heavy-handed tariff schemes. Then one day, we look up and realize the machines are in charge instead of us. This category of risk is also the hardest to guard against because it would depend on how people, infrastructure, and institutions operate in the future.

U.S. stock markets suffered their worst day since the Covid pandemic after Donald Trump announced sweeping new tariffs, triggering a global selloff and wiping out $470 billion in value from tech giants Apple and Nvidia. From a report: The tech-heavy Nasdaq fell 6%, while the S&P 500 and the Dow dropped 4.8% and 3.9%, respectively. [...] Meanwhile, the US dollar hit a six-month low, going down at least 2.2% on Thursday morning compared with other major currencies and oil prices sank on fears of a global slowdown. Though the US stock market has been used to tumultuous mornings over the last few weeks, US stock futures -- an indication of the market's likely direction -- had plummeted after the announcement. Hours later, Japan's Nikkei index slumped to an eight-month low and was followed by falls in stock markets in London and across Europe.

Multiple major American business groups have spoken out against the tariffs, including the Business Roundtable, a consortium of leaders of major US companies including JP Morgan, Apple and IBM, which called on the White House to "swiftly reach agreements" and remove the tariffs. "Universal tariffs ranging from 10-50% run the risk of causing major harm to American manufacturers, workers, families and exporters," the Business Roundtable said in a statement. "Damage to the US economy will increase the longer the tariffs are in place and may be exacerbated by retaliatory measures."

Intel has unveiled a refresh of its iconic brand identity, introducing the slogan "That's the power of Intel Inside" to reconnect with consumers and highlight the chipmaker's role in modern computing. The new campaign resurrects the familiar "Intel Inside" theme that helped transform the company into a household name in the 1990s, when Intel's marketing strategy directly targeted consumers rather than system designers.

Brett Hannath, Intel's chief marketing officer, said the message reflects the company's belief that its products can unlock potential for employees, customers, consumers and partners. The original "Intel Inside" campaign, launched in 1991, revolutionized tech marketing by making processors a key selling point for PCs with its recognizable sticker and five-note jingle. The strategy helped Intel differentiate itself from competitors like AMD and Cyrix during the PC market explosion.