'I wish I could push ChatGPT off a cliff': professors scramble to save critical thinking in an age of AI Lea Pao, a professor of literature at Stanford University, has been experimenting with ways to get her students to learn offline. She has them memorize poems, perform at recitation events, look at art in the real world. It's an effort to reconnect them to the bodily experience of learning, she said, and to keep them from turning to artificial intelligence to do the work for them. "There's no AI-proof anything," Pao said. "Rather than policing it, I hope that their overall experiences in this class will show them that there's a way out."

Plus: GPS jamming has become an invisible battle in the Middle East. Much of the spotlight on AI in the Iran conflict has focused on models like Claude helping the US military decide where to strike. But a wave of "vibe-coded" intelligence dashboards--and the ecosystem surrounding them--reflect a new role that AI is playing in wartime: mediating information, often for the worse. These sorts of intelligence tools have much promise. Yet there are real reasons to be suspicious of their data feeds. The AI firm wants to stop the Pentagon from blacklisting it.

What Anthropic's Clash With the Pentagon Is Really About Who will take responsibility for the technology? The weekslong conflict between Anthropic and the Department of Defense is entering a new phase. After being designated a supply-chain risk by DOD last week, which effectively forbids Pentagon contractors from using its products, the AI company filed a lawsuit against DOD this morning alleging that the government's actions were unconstitutional and ideologically motivated. Then, this afternoon, 37 employees from OpenAI and Google DeepMind--including Google's chief scientist, Jeff Dean--signed an amicus brief in support of Anthropic, in essence lending support to one of their employers' greatest business rivals (even as OpenAI itself has established a controversial new contract with DOD). For the past few weeks, Anthropic has been in heated negotiations with the Pentagon over how the U.S. military can use the firm's AI systems.

This week has brought more chaos in the feud between the Pentagon and Anthropic. This week has brought more chaos in the feud between the Pentagon and Anthropic. How AI firm Anthropic wound up in the Pentagon's crosshairs U ntil recently, Anthropic was one of the quieter names in the artificial intelligence boom. Despite being valued at about $350bn, it rarely generated the flashy headlines or public backlash associated with Sam Altman's OpenAI or Elon Musk's xAI. Its CEO and co-founder Dario Amodei was an industry fixture but hardly a household name outside of Silicon Valley, and its chatbot Claude lagged in popularity behind ChatGPT.

Chris Maddison was just an intern when he started working on the Go-playing AI that would eventually become AlphaGo. In March 2016, Google DeepMind's artificial intelligence system AlphaGo shocked the world. In a stunning five-match series of Go, the ancient Chinese board game, the AI beat the world's best player, Lee Sedol - a moment that was televised in front of millions and hailed by many as a historic moment in the development of artificial intelligence. Chris Maddison, now a professor of artificial intelligence at the University of Toronto, was then a master's student and helped get the project off the ground. Alex Wilkins: How did the idea for AlphaGo first come about?

Has the technology lived up to its potential? The first time that AlphaGo revealed its full power, it prompted a visceral reaction . Lee Sedol, the world's greatest player of the ancient Chinese board game Go, had grown visibly agitated at the artificial intelligence's prowess. The hushed crowd in downtown Seoul, South Korea, could barely contain its gasps. It was quickly dawning on Lee, and the tens of millions watching at home, that this AI was different to those that had come before. It wasn't just beating Lee, but it was doing so with an almost human-like aptitude.

Outside OpenAI's headquarters, a handful of people gathered on Monday holding pieces of colorful chalk. They got down on their knees and started writing messages on the sidewalk. Please no legal mass surveillance. At issue was a business deal that the company recently signed with the Department of Defense, following the Pentagon's sudden turn against Anthropic . OpenAI will now supply its technology to the military for use in classified settings, the sorts that may involve wartime decisions and intelligence-gathering--an agreement, many legal experts told me, that could give the government wide-ranging powers.

We study post-calibration uncertainty for trained ensembles of classifiers. Specifically, we consider both aleatoric (label noise) and epistemic (model) uncertainty. Among the most popular and widely used calibration methods in classification are temperature scaling (i.e., pool-then-calibrate) and conformal methods. However, the main shortcoming of these calibration methods is that they do not balance the proportion of aleatoric and epistemic uncertainty. Not balancing these uncertainties can severely misrepresent predictive uncertainty, leading to overconfident predictions in some input regions while being underconfident in others. To address this shortcoming, we present a simple but powerful calibration algorithm Joint Uncertainty Calibration (JUCAL) that jointly calibrates aleatoric and epistemic uncertainty. JUCAL jointly calibrates two constants to weight and scale epistemic and aleatoric uncertainties by optimizing the negative log-likelihood (NLL) on the validation/calibration dataset. JUCAL can be applied to any trained ensemble of classifiers (e.g., transformers, CNNs, or tree-based methods), with minimal computational overhead, without requiring access to the models' internal parameters. We experimentally evaluate JUCAL on various text classification tasks, for ensembles of varying sizes and with different ensembling strategies. Our experiments show that JUCAL significantly outperforms SOTA calibration methods across all considered classification tasks, reducing NLL and predictive set size by up to 15% and 20%, respectively. Interestingly, even applying JUCAL to an ensemble of size 5 can outperform temperature-scaled ensembles of size up to 50 in terms of NLL and predictive set size, resulting in up to 10 times smaller inference costs. Thus, we propose JUCAL as a new go-to method for calibrating ensembles in classification.

Samsung Galaxy Unpacked 2026 is Feb. 25 The company is also said to be working on smart glasses and a smart lamp. OpenAI is reportedly hard at work developing a series of AI-powered devices, including smart glasses, a smart speaker and a smart lamp. According to reporting by, the AI company has a team of over 200 employees dedicated to the project. The first product scheduled to be released is reported to be a smart speaker that would include a camera, allowing it to better absorb information about its users and surroundings. According to a person familiar with the project, this would extend to identifying objects on a nearby table, as well as conversations being held in the vicinity of the speaker.

From left: India's prime minister, Narendra Modi, with the chief executives of OpenAI, Sam Altman, and Anthropic, Dario Amodei, at the AI Impact summit in Delhi. From left: India's prime minister, Narendra Modi, with the chief executives of OpenAI, Sam Altman, and Anthropic, Dario Amodei, at the AI Impact summit in Delhi. AI hit: India hungry to harness US tech giants' technology at Delhi summit Narendra Modi's thirst to supercharge economic growth is matched by US desire to inject AI into world's biggest democracy I ndia celebrates 80 years of independence from the UK in August 2027. At about that same moment, "early versions of true super intelligence" could emerge, Sam Altman, the co-founder of OpenAI, said this week. It's a looming coincidence that raised a charged question at the AI Impact summit in Delhi, hosted by India's prime minister, Narendra Modi: can India avoid returning to the status of a vassal state when it imports AI to raise the prospects of its 1.4 billion people? Modi's hunger to harness AI's capability is great.