Anthropic announced "dreaming" for AI agents to sort through "memories" at its developer conference. Anthropic just announced a new feature called "dreaming" at the company's developer conference in San Francisco. It's part of Anthropic's recently launched AI agent infrastructure designed to help users manage and deploy tools that automate software processes. This "dreaming" aspect sorts through the transcript of what an agent recently completed and attempts to glean insights to improve the agent's performance. Folks using AI agents often send them on multistep journeys, like visiting a few websites or reading multiple files, to complete online tasks.

Hackers and other cybercriminals are complaining about "AI shit" flooding platforms where they discuss cyberattacks and other illegal activity. "I'm disappointed that you are working to incorporate AI garbage into the site," one annoyed person, posting anonymously, said in an online message. "No-one is asking for this--we want you to improve the site, stop charging for new features." Only, this is not a regular internet user moaning about AI being forced into their favorite app . Instead, they are complaining about a cybercrime forum's plans to introduce more generative AI.

The Institute for Primary Facts has compiled more than 3.5 million pages of the Epstein files for public display at the newly opened Donald J. Trump and Jeffrey Epstein Memorial Reading Room. It's an early 2016 email thread between Jeffrey Epstein and a woman whose name is redacted by the Department of Justice . In the thread, Epstein asks the unidentified woman for a "naughty selfie" and later sends her a camera. In late February, he replies with a different ask: "Do you have any friends that might want to work for me?...I will give you money if you find someone willing to travel, 22-25, educated. The exchange carries extra resonance when you consider that Epstein is accused of sex trafficking minors, with the Department of Justice estimating that he had more than 1,200 potential victims.

Now, Activists Are Taking On Elon Musk's SpaceX IPO Activists, a leading labor union, and a big retirement fund are asking challenging questions about what's expected to be the largest-ever stock market debut. Elon Musk's SpaceX is facing protests against its expected initial public offering from some of the same advocacy groups that helped erase $600 billion from Tesla's market cap early last year. SpaceX's IPO is poised to be the largest ever, raising tens of billions of dollars for the Musk-founded company and valuing it above $2 trillion. If all goes as intended come June, the conglomerate that now owns a rocket manufacturer, a social media app, and an AI chatbot developer will instantly rank among the world's top 10 largest publicly-traded companies. On Wednesday, Randi Weingarten, president of the American Federation of Teachers, wrote to the US Securities and Exchange Commission urging it to scrutinize SpaceX's IPO preparations.

Apple has agreed to pay some iPhone buyers a collective $250m (£184m) to end a lawsuit accusing the company of misleading people about new artificial intelligence (AI) features and capabilities. In a settlement filed Tuesday in California federal court, Apple did not admit any wrongdoing, but agreed to a deal that will resolve claims in a large consolidated class action lawsuit filed last year. It accused Apple of false advertising around its AI features on the iPhone, which the company called Apple Intelligence, including an enhancement of its Siri voice assistant. Apple will pay between $25 and $95 to people who bought an iPhone 15 and iPhone 16 between June 2024 and March 2025. An Apple spokeswoman said the lawsuit was focused on the availability of two additional features in a lineup of many released as part of its Apple Intelligence rollout.

Things to Do in L.A. Tap to enable a layout that focuses on the article. The gift will rename USC's School of Advanced Computing as the USC Mark and Mary Stevens School of Computing and Artificial Intelligence. This is read by an automated voice. Please report any issues or inconsistencies here . USC receives a $200-million gift from venture capitalist Mark Stevens to establish artificial intelligence research and expertise across campus.

A top Google scientist warned EU antitrust regulators that its proposal requiring the company to share search engine data with rivals risked exposing users' private information. BRUSSELS - A top Google scientist sent a warning to EU antitrust regulators on Tuesday that its proposal requiring the company to share search engine data with rivals such as OpenAI risked exposing users' private information, the sternest rebuke yet in a tussle over Google's lucrative business model. The European Commission, which acts as the EU competition enforcer, has in recent years cracked down on Big Tech via a slew of legislation to ensure that users have more choices and that smaller rivals have room to compete. However, that has triggered the ire of the U.S. government. Sergei Vassilvitskii, with the title of distinguished scientist at Google since 2012 and regarded a leader in his field, will meet EU antitrust officials on Wednesday to voice his concerns and propose a broader approach with better guardrails.

Cargo documents appear to show Sightline has shipped its technology to Elbit Systems, an Israeli arms manufacturer that provides drones to the country's military. Cargo documents appear to show Sightline has shipped its technology to Elbit Systems, an Israeli arms manufacturer that provides drones to the country's military. A nti-war activists in Portland, Oregon, are pushing city authorities to ensure no local resources, tax breaks or investments support a local company that appears to be supplying artificial intelligence software to the Israeli military. The company, Sightline Intelligence, manufactures AI-supported video technology that is used in drones to interpret target movements and make quick decisions based on the perceived threat level. Cargo documents appear to show Sightline has shipped its technology to Elbit Systems, an Israeli arms manufacturer that provides drones to that country's military and exports to others.

Plus: The Pentagon has struck sweeping AI deals for classified work. Week one of the Musk v. Altman trial: what it was like in the room Two of the most powerful figures in AI--Sam Altman and Elon Musk--are in the middle of a landmark legal showdown, with Musk alleging he was misled about OpenAI becoming a for-profit company. Our reporter Michelle Kim, who also happens to be a lawyer, has been in court each day, and has broken down the first week's key moments in her latest report . In a new Q&A, she also reveals what it was like in the room, the new details that have emerged about how Musk and OpenAI operate--and what we can expect from this week's proceedings. Find out what she's discovered so far, and if you want to keep up with MIT Technology Review's ongoing coverage of the Musk v. Altman trial, follow @techreview or @michelletomkim on X. Faster than many realize, AI is becoming the primary interface through which we form beliefs and participate in democratic self-governance. This shift could further strain already fragile institutions, but it could also help address problems like polarization and declining civic engagement.

Mediation analysis has traditionally focused on outcome-level summary contrasts, such as mean effects, which may obscure substantial distributional changes induced by complex and nonlinear causal mechanisms. We propose Distributional Causal Mediation Analysis (DCMA), a generative learning framework for identifying and estimating treatment effects on entire outcome distributions transmitted through multiple mediators. DCMA learns conditional generative models for the mediators and the outcome, recovering the relevant conditional distributions from observational data. Leveraging the identification formulas, it reconstructs interventional outcome distributions via Monte Carlo forward simulation by noise resampling, enabling the capture of both classical summary effects and rich distributional contrasts such as energy distance and the Wasserstein distance. Analytical error bounds are derived to decompose how estimation errors in the learned conditional models propagate to the reconstructed interventional outcome distributions. The empirical effectiveness of DCMA is demonstrated through numerical experiments and real-world data applications.