Palantir CEO Alex Karp warns of "coming swarms of autonomous robots" and urges Silicon Valley to support U.S. defense capabilities. In his book, "The Technological Republic: Hard Power, Soft Belief, and the Future of the West," Karp argues that America risks losing its military edge to geopolitical rivals who better harness commercial technology.

He calls for the "engineering elite of Silicon Valley" to work with the government on national defense. The message comes as Palantir's stock has surged more than 1,800% since early 2023, pushing its market value above $292 billion -- exceeding traditional defense contractors Lockheed Martin and RTX combined. The company has expanded its military AI work since 2018, when it took over a Pentagon contract after Google employees protested their company's defense work.

An anonymous reader quotes a report from Ars Technica: For a while now, many AI researchers have been working to integrate a so-called "world model" into their systems. Ideally, these models could infer a simulated understanding of how in-game objects and characters should behave based on video footage alone, then create fully interactive video that instantly simulates new playable worlds based on that understanding. Microsoft Research's new World and Human Action Model (WHAM), revealed today in a paper published in the journal Nature, shows how quickly those models have advanced in a short time. But it also shows how much further we have to go before the dream of AI crafting complete, playable gameplay footage from just some basic prompts and sample video footage becomes a reality.

Much like Google's Genie model before it, WHAM starts by training on "ground truth" gameplay video and input data provided by actual players. In this case, that data comes from Bleeding Edge, a four-on-four online brawler released in 2020 by Microsoft subsidiary Ninja Theory. By collecting actual player footage since launch (as allowed under the game's user agreement), Microsoft gathered the equivalent of seven player-years' worth of gameplay video paired with real player inputs. Early in that training process, Microsoft Research's Katja Hoffman said the model would get easily confused, generating inconsistent clips that would "deteriorate [into] these blocks of color." After 1 million training updates, though, the WHAM model started showing basic understanding of complex gameplay interactions, such as a power cell item exploding after three hits from the player or the movements of a specific character's flight abilities. The results continued to improve as the researchers threw more computing resources and larger models at the problem, according to the Nature paper.

To see just how well the WHAM model generated new gameplay sequences, Microsoft tested the model by giving it up to one second's worth of real gameplay footage and asking it to generate what subsequent frames would look like based on new simulated inputs. To test the model's consistency, Microsoft used actual human input strings to generate up to two minutes of new AI-generated footage, which was then compared to actual gameplay results using the Frechet Video Distance metric. Microsoft boasts that WHAM's outputs can stay broadly consistent for up to two minutes without falling apart, with simulated footage lining up well with actual footage even as items and environments come in and out of view. That's an improvement over even the "long horizon memory" of Google's Genie 2 model, which topped out at a minute of consistent footage. Microsoft also tested WHAM's ability to respond to a diverse set of randomized inputs not found in its training data. These tests showed broadly appropriate responses to many different input sequences based on human annotations of the resulting footage, even as the best models fell a bit short of the "human-to-human baseline."

The most interesting result of Microsoft's WHAM tests, though, might be in the persistence of in-game objects. Microsoft provided examples of developers inserting images of new in-game objects or characters into pre-existing gameplay footage. The WHAM model could then incorporate that new image into its subsequent generated frames, with appropriate responses to player input or camera movements. With just five edited frames, the new object "persisted" appropriately in subsequent frames anywhere from 85 to 98 percent of the time, according to the Nature paper.

Apple has launched the iPhone 16E, featuring a 6.1-inch OLED display, Face ID, an A18 chipset, USB-C, 48MP camera, and support for Apple Intelligence. Gone but not forgotten: the home button, Touch ID and 64GB of base storage. The Verge reports: The 16E includes the customizable Action Button, but not the new Camera Control you'll find on the 16 series. It does swap its Lightning port for USB-C, now a requirement for the phone to be sold in the EU. On the inside, there's an A18 chipset, the same chip as the iPhone 16. That makes the 16E powerful enough to run Apple Intelligence, the suite of AI tools that includes notification summaries. Even the non-Pro iPhone 15 can't do that, so the 16E is one of the most capable iPhones out there. Apple has previously confirmed that 8GB RAM was the minimum to get Apple Intelligence support in the iPhone 16 series, so it's likely that the 16E also boasts at least that much memory. It's also been bumped to a baseline of 128GB of storage, meaning there's no longer a 64GB iPhone.

There's only a single 48-megapixel rear camera; the lack of additional cameras is the biggest downgrade compared to the company's other handsets. With support for wireless charging and a water-resistant IP rating, there's little you have to give up elsewhere. The iPhone 16E is also the first iPhone to include a modem developed by Apple itself. The company has spent years trying to move away from modems developed by Qualcomm, and we're finally seeing the fruits of that labor. The big questions now are how well the new modem performs and whether Apple is ready to roll out its own connectivity components in the iPhone 17 line later this year. It's available for Friday starting at $599 with 128GB of storage.

AI hardware startup Humane -- which has been acquired by HP -- has given its users just ten days notice that their Pins will be disconnected. From a report: In a note to its customers, the company said AI Pins will "continue to function normally" until 12PM PT on February 28. On that date, users will lose access to essentially all of their device's features, including but not limited to calling, messaging, AI queries and cloud access. The FAQ does note that you'll still be able to check on your battery life, though.

Humane is encouraging its users to download any stored data before February 28, as it plans on permanently deleting "all remaining customer data" at the same time as switching its servers off.

Microsoft has placed its new AI-powered text rewrite feature in Notepad behind a subscription paywall, requiring users to have a Microsoft 365 Personal or Family plan to access the functionality. While the core text editor remains free and accessible without a Microsoft account, the AI feature requires users to sign in and have sufficient "AI credits" included in their subscription.Users can disable the feature and hide its icon if they choose not to subscribe.

Google has built an AI laboratory assistant to help scientists accelerate biomedical research [non-paywalled source], as companies race to create specialised applications from the cutting-edge technology. From a report: The US tech group's so-called co-scientist tool helps researchers identify gaps in their knowledge and propose new ideas that could speed up scientific discovery. "What we're trying to do with our project is see whether technology like the AI co-scientist can give these researchers superpowers," said Alan Karthikesalingam, a senior staff clinician scientist at Google.

[...] Early tests of Google's new tool with experts from Stanford University, Imperial College London and Houston Methodist hospital found it was able to generate scientific hypotheses that showed promising results. The tool was able to reach the same conclusions -- for a novel gene transfer mechanism that helps scientists understand the spread of antimicrobial resistance -- as a new breakthrough from researchers at Imperial. Imperial's results were not in the public domain as they were being peer-reviewed in a top scientific journal. This showed that Google's co-scientist tool was able to reach the same hypothesis using AI reasoning in a matter of just days, compared with the years the university team spent researching the problem.

Leading AI models can fix broken code, but they're nowhere near ready to replace human software engineers, according to extensive testing [PDF] by OpenAI researchers. The company's latest study put AI models and systems through their paces on real-world programming tasks, with even the most advanced models solving only a quarter of typical engineering challenges.

The research team created a test called SWE-Lancer, drawing from 1,488 actual software fixes made to Expensify's codebase, representing $1 million worth of freelance engineering work. When faced with these everyday programming tasks, the best AI model â" Claude 3.5 Sonnet -- managed to complete just 26.2% of hands-on coding tasks and 44.9% of technical management decisions.

Though the AI systems proved adept at quickly finding relevant code sections, they stumbled when it came to understanding how different parts of software interact. The models often suggested surface-level fixes without grasping the deeper implications of their changes.

The research, to be sure, used a set of complex methodologies to test the AI coding abilities. Instead of relying on simplified programming puzzles, OpenAI's benchmark uses complete software engineering tasks that range from quick $50 bug fixes to complex $32,000 feature implementations. Each solution was verified through rigorous end-to-end testing that simulated real user interactions, the researchers said.

Former OpenAI CTO Mira Murati has launched Thinking Machines Lab with several leaders from OpenAI on board, including John Schulman, Barrett Zoph, and Jonathan Lachman. Their mission is "to make AI systems more widely understood, customizable, and generally capable," with a commitment to publishing technical research and code. The Verge reports: In a press release shared with The Verge, the company suggests that it's building products that help humans work with AI, rather than fully autonomous systems. "We're building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals," says the press release.

An anonymous reader quotes a report from Bloomberg: HP will acquire assets from Humane, the maker of a wearable Ai Pin introduced in late 2023, for $116 million. The deal will include the majority of Humane's employees in addition to its software platform and intellectual property, the company said Tuesday. It will not include Humane's Ai pin device business, which will be wound down, an HP spokesperson said. Humane's team, including founders Imran Chaudhri and Bethany Bongiorno, will form a new division at HP to help integrate artificial intelligence into the company's personal computers, printers and connected conference rooms, said Tuan Tran, who leads HP's AI initiatives. Chaudhri and Bongiorno were design and software engineers at Apple before founding the startup. [...]

Tran said he was particularly impressed with aspects of Humane's design, such as the ability to orchestrate AI models running both on-device and in the cloud. The deal is expected to close at the end of the month, HP said. "There will be a time and place for pure AI devices," Tran said. "But there is going to be AI in all our devices -- that's how we can help our business customers be more productive."

An anonymous reader shares a report: U.S. personal injury law firm Morgan & Morgan sent an urgent email this month to its more than 1,000 lawyers: Artificial intelligence can invent fake case law, and using made-up information in a court filing could get you fired. A federal judge in Wyoming had just threatened to sanction two lawyers at the firm who included fictitious case citations in a lawsuit against Walmart. One of the lawyers admitted in court filings last week that he used an AI program that "hallucinated" the cases and apologized for what he called an inadvertent mistake.

AI's penchant for generating legal fiction in case filings has led courts around the country to question or discipline lawyers in at least seven cases over the last two years, and created a new high-tech headache for litigants and judges, Reuters found. The Walmart case stands out because it involves a well-known law firm and a big corporate defendant. But examples like it have cropped up in all kinds of lawsuits since chatbots like ChatGPT ushered in the AI era, highlighting a new litigation risk.

A new report released by Cisco finds that 97% of CEOs surveyed are planning AI integration. Similarly, 92% of companies recently surveyed by McKinsey plan to invest more in generative AI over the next three years. Fortune: To that end, many companies are seeking tech-savvy finance talent, according to a new report by software company Datarails. The researchers analyzed 6,000 job listings within the CFO's office -- CFO, controller, financial planning and analysis (FP&A), and accountant -- advertised on job search websites including LinkedIn, Glassdoor, Indeed, Job2Careers, and ZipRecruiter.

Of the 1,000 job listings for CFOs in January 2025, 27% included AI in the job description. This compares to 8% mentions of AI in 1,000 CFO job listings at the same time last year. Take, for example, Peaks Healthcare Consulting which required a CFO candidate to "continuously learn and integrate AI to improve financial processes and decision making," Datarails notes in the report. Regarding FP&A professionals, in January 2025, 35% of analyst roles mentioned AI competency as a requirement, compared to 14% in January 2024, according to the report.

Chinese AI startup DeepSeek has updated its business registry information with key changes to personnel and operational scope, signaling a shift towards monetizing its cost-efficient-yet-powerful large language models. From a report: The Hangzhou-based firm's updated business scope includes "internet information services," according to business registry service Tianyancha. The move is the first sign of DeepSeek's desire to monetise its popular technology, according to Zhang Yi, founder and chief analyst at consultancy iiMedia.

With eyes on developing a business model, DeepSeek intends to shift away from being purely focused on research and development, Zhang added. "The move reflects that for a company like DeepSeek, which managed to accumulate technology and develop a product, monetisation is becoming a necessary next step," Zhang said. DeepSeek's previous business scope said it engages in engineering and AI software development, among others, hinting at a more research-driven approach.

xAI has launched Grok 3, the latest iteration of its large language model, alongside new capabilities for its iOS and web applications. The model has been trained on approximately 200,000 GPUs in a Memphis data center, representing what CEO Elon Musk claims is a tenfold increase in computing power compared to its predecessor.

The new release introduces two specialized variants: Grok 3 Reasoning and Grok 3 mini Reasoning, designed to methodically analyze problems similar to OpenAI's o3-mini and DeepSeek's R1 models. According to xAI's benchmarks, Grok 3 outperforms GPT-4o on several technical evaluations, including AIME for mathematical reasoning and GPQA for PhD-level science problems.

A notable addition is the DeepSearch feature, which combs through web content and X posts to generate research summaries. The platform will be available through X's Premium+ subscription and a new SuperGrok tier ($30/month or $300/year), with the latter offering enhanced reasoning capabilities and unlimited image generation. To prevent knowledge extraction through model distillation -- a technique recently attributed to DeepSeek's alleged copying of OpenAI's models -- xAI has implemented measures to obscure the reasoning models' thought processes in the Grok app. The company plans to release the Grok 2 model as open source once Grok 3 achieves stability.

NAND flash prices are expected to slide due to oversupply, forcing memory chipmakers to cut production to match lower-than-expected orders from PC and smartphone manufacturers. From a report: The superabundance of stock is putting a financial strain on suppliers of NAND flash, according to TrendForce, which says growth rate forecasts are being revised down from 30 percent to 10-15 percent for 2025.

"NAND flash manufacturers have adopted more decisive production cuts, scaling back full-year output to curb bit supply growth. These measures are designed to swiftly alleviate market imbalances and lay the groundwork for a price recovery," TrendForce stated.

Shrish Pant, Gartner director analyst and technology product leader, expects NAND flash pricing to remain weak for the first half of 2025, though he projects higher bit shipments for SSDs in the second half due to continuing AI server demand.

"Vendors are currently working tirelessly to discipline supply, which will lead to prices recovering in the second half of 2025. Long term, AI demand will continue to drive the demand for higher-capacity/better-performance SSDs," Pant said. Commenting on the seasonal nature of the memory market, Pant told The Register: "Buying patterns will mean that NAND flash prices will remain cyclical depending on hyperscalers' buying behavior."

White-collar workers are facing their deepest hiring slump in a decade, with one in four U.S. job losses last year hitting professional workers, according to S&P Global. A 2024 Vanguard report shows hiring for employees earning over $96,000 has fallen to its lowest level since 2014. The downturn has been particularly severe for job seekers â" 40% of applicants failed to secure even a single interview in 2024, according to a survey of 2,000 respondents by the American Staffing Association and The Harris Poll.

Technology and high interest rates appear to be driving the decline, with companies reassessing their workforce needs amid AI adoption and economic pressures. While hiring remains steady for those earning under $55,000 annually, the market continues to be especially challenging for mid-career professionals and higher earners.

Reddit moderators are struggling to police AI-generated content on the platform, according to ArsTechnica, with many expecting the challenge to intensify as the technology becomes more sophisticated. Several popular Reddit communities have implemented outright bans on AI-generated posts, citing concerns over content quality and authenticity.

The moderators of r/AskHistorians, a forum known for expert historical discussion, said that AI content "wastes our time" and could compromise the subreddit's reputation for accurate information. Moderators are currently using third-party AI detection tools, which they describe as unreliable. Many are calling on Reddit to develop its own detection system, the report said.

Ten years after publishing his influential book on data privacy, security expert Bruce Schneier warns that surveillance has only intensified, with both government agencies and corporations collecting more personal information than ever before. "Nothing has changed since 2015," Schneier told The Register in an interview. "The NSA and their counterparts around the world are still engaging in bulk surveillance to the extent of their abilities."

The widespread adoption of cloud services, Internet-of-Things devices, and smartphones has made it nearly impossible for individuals to protect their privacy, said Schneier. Even Apple, which markets itself as privacy-focused, faces limitations when its Chinese business interests are at stake. While some regulation has emerged, including Europe's General Data Protection Regulation and various U.S. state laws, Schneier argues these measures fail to address the core issue of surveillance capitalism's entrenchment as a business model.

The rise of AI poses new challenges, potentially undermining recent privacy gains like end-to-end encryption. As AI assistants require cloud computing power to process personal data, users may have to surrender more information to tech companies. Despite the grim short-term outlook, Schneier remains cautiously optimistic about privacy's long-term future, predicting that current surveillance practices will eventually be viewed as unethical as sweatshops are today. However, he acknowledges this transformation could take 50 years or more.

Junior software developers' overreliance on AI coding assistants is creating knowledge gaps in fundamental programming concepts, developer Namanyay Goel argued in a post. While tools like GitHub Copilot and Claude enable faster code shipping, developers struggle to explain their code's underlying logic or handle edge cases, Goel wrote. Goel cites the decline of Stack Overflow, a technical forum where programmers historically found detailed explanations from experienced developers, as particularly concerning.

Today Seoul's Personal Information Protection Commission "said DeepSeek would no longer be available for download until a review of its personal data collection practices was carried out," reports AFP. A number of countries have questioned DeepSeek's storage of user data, which the firm says is collected in "secure servers located in the People's Republic of China"... This month, a slew of South Korean government ministries and police said they blocked access to DeepSeek on their computers. Italy has also launched an investigation into DeepSeek's R1 model and blocked it from processing Italian users' data. Australia has banned DeepSeek from all government devices on the advice of security agencies. US lawmakers have also proposed a bill to ban DeepSeek from being used on government devices over concerns about user data security.
More details from the Associated Press: The South Korean privacy commission, which began reviewing DeepSeek's services last month, found that the company lacked transparency about third-party data transfers and potentially collected excessive personal information, said Nam Seok [director of the South Korean commission's investigation division]... A recent analysis by Wiseapp Retail found that DeepSeek was used by about 1.2 million smartphone users in South Korea during the fourth week of January, emerging as the second-most-popular AI model behind ChatGPT.

Nicholas Carr wrote The Shallows: What the Internet Is Doing to Our Brains. But his new book looks at how social media and digital communication technologies "are changing us individually and collectively," writes the Los Angeles Review of Books.

The book's title? Superbloom: How Technologies of Connection Tear Us Apart . But if these systems are indeed tearing us apart, the reasons are neither obvious nor simple. Carr suggests that this isn't really about the evil behavior of our tech overlords but about how we have "been telling ourselves lies about communication — and about ourselves.... Well before the net came along," says Carr, "[the] evidence was telling us that flooding the public square with more information from more sources was not going to open people's minds or engender more thoughtful discussions. It wasn't even going to make people better informed...."

At root, we're the problem. Our minds don't simply distill useful knowledge from a mass of raw data. They use shortcuts, rules of thumb, heuristic hacks — which is how we were able to think fast enough to survive on the savage savanna. We pay heed, for example, to what we experience most often. "Repetition is, in the human mind, a proxy for facticity," says Carr. "What's true is what comes out of the machine most often...." Reality can't compete with the internet's steady diet of novelty and shallow, ephemeral rewards. The ease of the user interface, congenial even to babies, creates no opportunity for what writer Antón Barba-Kay calls "disciplined acculturation."

Not only are these technologies designed to leverage our foibles, but we are also changed by them, as Carr points out: "We adapt to technology's contours as we adapt to the land's and the climate's." As a result, by designing technology, we redesign ourselves. "In engineering what we pay attention to, [social media] engineers [...] how we talk, how we see other people, how we experience the world," Carr writes. We become dislocated, abstracted: the self must itself be curated in memeable form. "Looking at screens made me think in screens," writes poet Annelyse Gelman. "Looking at pixels made me think in pixels...."

That's not to say that we can't have better laws and regulations, checks and balances. One suggestion is to restore friction into these systems. One might, for instance, make it harder to unreflectively spread lies by imposing small transactional costs, as has been proposed to ease the pathologies of automated market trading. An option Carr doesn't mention is to require companies to perform safety studies on their products, as we demand of pharmaceutical companies. Such measures have already been proposed for AI. But Carr doubts that increasing friction will make much difference. And placing more controls on social media platforms raises free speech concerns... We can't change or constrain the tech, says Carr, but we can change ourselves. We can choose to reject the hyperreal for the material. We can follow Samuel Johnson's refutation of immaterialism by "kicking the stone," reminding ourselves of what is real.