Things to Do in L.A. AI companies are creating'all-powerful psychopaths.' OpenAI Chief Executive Sam Altman speaks at a San Francisco event in 2025. This is read by an automated voice. Please report any issues or inconsistencies here . See more from the L.A. Times in Google Search.

OpenAI and Anthropic lost billions in predicted value after being shown up by a Chinese startup. OpenAI and Anthropic lost billions in predicted value after being shown up by a Chinese startup. Why are OpenAI and Anthropic cheering on regulation in Australia? The companies hope to follow in the footsteps of SpaceX, which raised $86bn and soared to a $2.1tn valuation after it listed on public markets in June Top US AI developers Anthropic and OpenAI cheered when Australia announced it would set new AI rules. Big tech celebrating limits on their Silicon Valley VC-funded free-for-all might seem counterintuitive but there's a much broader play than just what happens in one relatively small market.

The company donated more than $3.6 million to conservative groups between 2020 and 2025, including $1 million to the MAGA Inc. super PAC. The lettuce supplier at the center of the turbo diarrhea outbreak has spent millions of dollars to sway sentiment around food regulation and elect Donald Trump and other MAGA Republicans, according to public filings. Taylor Farms donated more than $2 million to conservative political groups in 2025, according to Federal Election Commission filings. That includes a $1 million donation to MAGA Inc., the Trump-centric super PAC, and $1.1 million to other super PACs dedicated to electing Republicans. From 2020 through the end of 2024, the company donated more than $1.6 million to conservative PACs, including a total of $850,000 to AFP Action, an anti-regulation super PAC with ties to the Koch network.

Here's Why Anthropic Is Pushing States to Regulate AI Faster The company endorsed landmark AI transparency laws in California and New York last year, but its head of US state and local policy says they may already be outdated. Anthropic threw its support behind the first wave of frontier AI safety laws in the United States last year, securing new transparency requirements in California and New York that much of Silicon Valley fought against, arguing they would stifle the AI boom . But Anthropic says those laws may already be outdated, and the company is now pushing states to adopt even tougher regulations. "The transparency-focused safety bills of 2025 were a really important start, but as the capabilities of AI systems continue to advance quickly--the policy responses need to match," Cesar Fernandez, Anthropic's head of US state and local government relations, told WIRED in an interview. "We think that transparency and self reporting are no longer sufficient safety measures for the most powerful AI systems."

OpenAI employees have donated more than $215,000 to a political effort opposing Leading the Future, a group backed by the company's president, Greg Brockman. A group of rank-and-file OpenAI employees have donated more than $215,000 to a super PAC pushing for stricter regulations on frontier AI labs. Guardrails Alliance, which launched last month with $5 million in total initial funding, bills itself as a populist effort supported by tech workers, labor unions, and other groups. It's aiming to be a counterweight to Leading the Future, a pro-AI industry super PAC bankrolled with more than $100 million from technology industry leaders, including OpenAI president and cofounder Greg Brockman. Seven current OpenAI employees have donated to Guardrails Alliance, as well as one former employee, WIRED has learned.

The "right to be forgotten" and the data privacy laws that encode it have motivated machine unlearning since its earliest days. Now, some argue that an inbound wave of artificial intelligence regulations -- like the European Union's Artificial Intelligence Act (AIA) -- may offer important new use cases for machine unlearning. However, this position paper argues, this opportunity will only be realized if researchers proactively bridge the (sometimes sizable) gaps between machine unlearning's state of the art and its potential applications to AI regulation. To demonstrate this point, we use the AIA as our primary case study. Specifically, we deliver a "state of the union" as regards machine unlearning's current potential (or, in many cases, lack thereof) for aiding compliance with various provisions of the AIA. This starts with a precise cataloging of the potential applications of machine unlearning to AIA compliance. For each, we flag the technical gaps that exist between the potential application and the state of the art of machine unlearning. Finally, we end with a call to action: for machine learning researchers to solve the open technical questions that could unlock machine unlearning's potential to assist compliance with the AIA -- and other AI regulations like it.

Military weapon systems and command-and-control infrastructure augmented by artificial intelligence (AI) have seen rapid development and deployment in recent years. However, the sociotechnical impacts of AI on combat systems, military decision-making, and the norms of warfare have been understudied. We focus on a specific subset of lethal autonomous weapon systems (LAWS) that use AI for targeting or battlefield decisions. We refer to this subset as AI-powered lethal autonomous weapon systems (AI-LAWS) and argue that they introduce novel risks--including unanticipated escalation, poor reliability in unfamiliar environments, and erosion of human oversight--all of which threaten both military effectiveness and the openness of AI research. These risks cannot be addressed by high-level policy alone; effective regulation must be grounded in the technical behavior of AI models. We argue that AI researchers must be involved throughout the regulatory lifecycle. Thus, we propose a clear, behavior-based definition of AILAWS--systems that introduce unique risks through their use of modern AI--as a foundation for technically grounded regulation, given that existing frameworks do not distinguish them from conventional LAWS. Using this definition, we propose several technically-informed policy directions and invite greater participation from the AI research community in military AI policy discussions.

Appendix A describes the Unity-based interface implemented in EVAAA, including an environment setup, prefab structures, and object instantiation. Appendix B provides a comprehensive introduction to Essential Variables (EVs), including their design, dynamics, and role in internal state regulation. Appendix C explains the implementation of the reward system and its connection to the balance of internal states. Appendix E outlines the modular configuration to generate EVAAA environments, along with the instructions for environment customization. Appendix F presents the structure and progression of naturalistic training environments. Appendix G describes the design of unseen experimental testbeds for evaluation. Appendix I provides analyses of agent behavior across training and test environments, including emergent behavioral patterns. All code and data are publicly available at: https://github.com/cocoanlab/evaaa A.1 Prefabs Environmental elements such as terrain, resources, obstacles, and predators are implemented as reusable and configurable Unity prefabs. Prefabs are grouped into Agents, Environment, and Materials. Each category includes reusable components for constructing and customizing interactive scenes: Agents (main agent and predators), Environment (terrain and containers), and Materials (varied textures and colors for visual distinction). This modular system enables rapid prototyping, task generation, condition randomization, and reproducible scene setup. Prefabs can be customized through the Unity Editor or programmatically at runtime, and reused across scenes without manual rebuilding.

'Musk profits where there are as few regulations as possible and he can dominate.' 'Musk profits where there are as few regulations as possible and he can dominate.' Ten years ago, after complaining that traffic was'driving him nuts', Musk's Boring Company began building underground tunnels to ease congestion on the roads. I t's another blindingly bright day in Las Vegas but I'm 30ft underground and strapped in for a rocket ride to the future. And it's pretty slow - my driver tells me the speed limit down here is 30mph. It's also pretty short: the journey is over in a matter of minutes.

'The CEOs are telling us, "We're on track to create superhuman intelligence, which has a good chance of causing human extinction."' 'The CEOs are telling us, "We're on track to create superhuman intelligence, which has a good chance of causing human extinction."' Will it take a'Chernobyl-scale disaster' for us to regulate cyber weapons of mass destruction? T he AI company Anthropic has been making major headlines recently. Its trillion-dollar IPO plan and its blood feud with secretary of defense Pete Hegseth have attracted much attention, but two other events may be even more consequential.