Generative AI
Anthropic soars to 965bn valuation, leapfrogging OpenAI
Anthropic has usurped OpenAI as the world's most valuable artificial intelligence startup, soaring to a $965bn valuation ahead of expected public listings by the rival firms. Anthropic, the maker of the Claude family of chatbots, said on Thursday that it had raised $65bn from private investors after a fundraising round led by Altimeter Capital, Greenoaks, Dragoneer and Sequoia Capital. "This funding will help us serve the historic demand we are experiencing, stay at the research frontier, and bring Claude to more of the places where work happens," Anthropic's Chief Financial Officer Krishna Rao said in a statement. Altimeter Capital CEO Brad Gerstner hailed the adoption of Claude among the "world's most demanding organisations" as evidence of Anthropic's command in the field. "This momentum positions Anthropic to lead the next phase of AI innovation and capture the enormous opportunity ahead," Gerstner said.
Anthropic reaches near-trillion dollar valuation, topping OpenAI
Anthropic's rise came by doubling down on delivering generative artificial intelligence to enterprise clients rather than general users. Artificial intelligence company Anthropic said Thursday it had raised $65 billion in a new funding round that values the Claude maker at $965 billion, more than its archrival OpenAI, the maker of ChatGPT. The latest fundraising round confirms Anthropic's place as one of the most significant players in AI, with the startup led by Dario Amodei having drawn fans for its coding powers and state-of-the-art models. Anthropic's rise came by doubling down on delivering generative AI to enterprise clients rather than general users, the path initially chosen by OpenAI. In a time of both misinformation and too much information, quality journalism is more crucial than ever. By subscribing, you can help us get the story right.
Anthropic reaches valuation of 965bn, beating OpenAI to become world's most valuable AI firm
Pages from the Anthropic website and the company's logo are displayed on a computer screen in New York on 26 February 2026. Pages from the Anthropic website and the company's logo are displayed on a computer screen in New York on 26 February 2026. Anthropic reaches valuation of $965bn, beating OpenAI to become world's most valuable AI firm Claude's parent company's $65bn in latest funding round underscores vast sums of money still flowing into industry Anthropic, the AI firm behind the Claude chatbot, announced on Thursday it had raised $65bn in funding to value the company at $965bn post-money. The move makes Anthropic the world's most valuable AI startup, eclipsing its competitor OpenAI. The deal marks an exceedingly successful period of growth for Anthropic, which was once considered to be a smaller player in the global AI arms race.
Illinois Lawmakers Just Passed America's Strongest AI Safety Bill
Illinois Lawmakers Just Passed America's Strongest AI Safety Bill The bill requires companies like OpenAI, Anthropic, and Google to have third parties confirm they're following safety standards. The Illinois House of Representatives passed a bill on Wednesday requiring frontier AI labs like OpenAI, Anthropic, and Google DeepMind to have their safety practices audited by a third party. If signed into law, AI safety experts tell WIRED, it would be the nation's leading check on the power of major AI companies . The bill, SB 315, now heads to governor JB Pritzker's desk. In a post on social media on Wednesday, Pritzker said he plans to sign the bill, citing a need to hold Big Tech accountable.
Former Google and Apple Researchers Launch a Startup to Build AI's Missing Feedback Loop
Trajectory is betting the rapid iteration cycle that supercharged vibe-coding can help all kinds of companies build AI products that learn continuously. Trajectory founders, Ronak Malde (left), Michael Elabd(center), and Arjun Karanam (right). A group of AI researchers who previously worked at Google DeepMind, Apple, OpenAI, and Meta Superintelligence Labs announced on Wednesday they're launching a new startup called Trajectory, which aims to help companies regularly improve their AI products by training on real-world user interactions. Trajectory wants to build a platform for AI that can learn continuously, a capability that researchers have long held up as a major barrier to further AI progress. OpenAI, Google, and Anthropic have found success training increasingly capable versions of AI models, especially for domains such as coding, math, and science.
Sam Altman Says AI 'Jobs Apocalypse' He Once Predicted Probably Won't Happen. What Changed?
Sam Altman Says AI'Jobs Apocalypse' He Once Predicted Probably Won't Happen. OpenAI CEO Sam Altman speaks during the BlackRock Infrastructure Summit on March 11, 2026 in Washington, DC. OpenAI CEO Sam Altman speaks during the BlackRock Infrastructure Summit on March 11, 2026 in Washington, DC. Throughout his rise to becoming one of the most influential CEOs in artificial intelligence, OpenAI's Sam Altman made repeated bold assertions about the impact that the new technology would have on jobs. He has said that AI will "probably replace most of the jobs people do today," that entire job categories will be "totally, totally gone," and that those impacted by the dramatic shifts will "find all sorts of new things to do. Now, however, Altman appears to have changed his tune, saying he is "delighted to be wrong" about the impact AI would have on employment. I don't think we're going to have the kind of jobs apocalypse that some of the companies in our space advocate or talk about, he said during a virtual interview at a Commonwealth Bank of Australia (CBA) conference in Sydney on Tuesday. "I thought there would have been more impact on entry-level white-collar jobs being eliminated by now than has actually happened, Altman said.
Can OpenAI's 'Master of Disaster' Fix AI's Reputation Crisis?
Global affairs chief Chris Lehane wants to tone down the debate over AI's societal impacts--and get states to pass laws that won't derail OpenAI's meteoric rise. Three months ago, OpenAI cofounder Greg Brockman told me his concerns about a mounting public relations crisis facing artificial intelligence companies: Despite the popularity of tools like ChatGPT, an increasingly large share of the population said they viewed AI negatively. Since then, the backlash has only intensified. College commencement speakers are now getting booed for talking about AI in optimistic terms. Last month, someone threw a Molotov cocktail at OpenAI CEO Sam Altman's San Francisco home and wrote a manifesto advocating for crimes against AI executives.
Meta Is in Crisis, Google Search's Makeover, and AI Gets Booed by Graduates
Meta Is in Crisis, Google Search's Makeover, and AI Gets Booed by Graduates This week on, the team discusses Meta's recent layoffs and what they've been hearing from employees about the increasingly grim vibes at the company. They also talk about Elon Musk losing his lawsuit against OpenAI and share highlights from Google's annual conference--including an ambitious AI vision to change how people search the web. Finally, what do recent college graduates and women whose spouses work in AI have in common? Google Search Goes Agentic--and Doesn't Need You Anymore Write to us at [email protected] . You can always listen to this week's podcast through the audio player on this page, but if you want to subscribe for free to get every episode, here's how: If you're on an iPhone or iPad, open the app called Podcasts, or just tap this link . We spoke to more than a dozen employees and it turns out the job cuts are far from the only reason why Meta employees are really going through it. He lost his lawsuit against Sam Altman and OpenAI in really as full a way as you can, as dramatically as possible. I know, Zoë, you're looking forward to talking about that. We're going to get into why young adults might be using AI, but they have very complicated feelings about it. And later in the show, we're going to hear about why women married to AI bros have had enough . This week, the company is letting go of roughly 10 percent of its workforce, which is about 8,000 employees total. It's the latest round of job cuts, adding to the roughly 25,000 jobs that have been cut in the past few years as part of Mark Zuckerberg's Year of Efficiency that started in 2023 and now the latest AI-forward workplace, which he is trying to develop and impose. And while these latest cuts are not as big as some of the rounds of layoffs that have already happened, they're getting a ton of attention because Mark Zuckerberg, the CEO, has said that the reason they're happening, in part at least, in large part, is because the company is spending so much money on AI and data centers.
OpenAI makes breakthrough on 80-year-old maths problem
If you take a sheet of paper and add some dots, how many pairs can be the same distance apart? If you take a sheet of paper and add some dots, how many pairs can be the same distance apart? OpenAI has claimed a further advance in AI reasoning after its technology successfully tackled an 80-year-old maths problem. The company behind ChatGPT said it had made a breakthrough with a challenge first posed by Hungarian mathematician Paul Erdős in 1946: the planar unit distance problem. The question posed by Erdős is simple to explain.
Sample Complexity of Transfer Learning: An Optimal Transport Approach
Cao, Haoyang, Guo, Xin, Tang, Wenpin, Wang, Guan
Transfer learning is an essential technique for many machine learning/AI models of complex structures such as large language models and generative AI. The essence of transfer learning is to leverage knowledge from resolved source tasks for a new target task, especially when the sample size $m$ of the training data for the latter is low. In this work, we rigorously analyze the potential benefit of transfer learning in terms of sample efficiency. Specifically, taking an optimal transport viewpoint of transfer learning, we find that when the data dimension $d$ is higher than $3$, the sample complexity for transfer learning is $O(m^{-(α+1)/d})$, with $α$ indicating the smoothness of the data distribution, as opposed to the $O(m^{-p/d})$ sample complexity for direct learning with $p$ indicating the smoothness of the optimal target model. Our finding theoretically supports a better sample efficiency for transfer learning, when the target task is optimizing over a family of not-so-smooth models (i.e., highly complex networks with the possible use of non-smooth activation functions). Using image classification as an example, we numerically demonstrate the sample efficiency for transfer learning, that is, in the data hungry regime, the model performance can be significantly improved by transfer learning.