Anthropic has announced the launch of the Anthropic Institute, a research initiative focused on examining the societal, economic, and governance challenges posed by rapidly advancing AI systems.

The institute will draw on internal research across Anthropic to provide insights for policymakers, researchers, and the public as AI systems grow more capable. The company said the effort aims to improve understanding of how advanced AI could reshape economies, jobs, legal systems, and governance structures.

The initiative will be led by Anthropic co-founder Jack Clark, who will assume a new role as the company’s Head of Public Benefit. The institute’s interdisciplinary team will include machine learning engineers, economists, and social scientists working together to analyze the broader implications of frontier AI technologies.

Anthropic said the pace of AI progress has accelerated rapidly in recent years. The company took two years to release its first commercial model and only three more years to develop systems capable of discovering cybersecurity vulnerabilities, performing complex professional tasks, and contributing to AI research itself.

The institute will study several key questions related to advanced AI development, including how the technology may transform labor markets, influence economic growth, and affect societal resilience. It will also examine governance challenges such as how AI systems should be regulated and how organizations should manage the values embedded in advanced models.

Research Focus and Policy Engagement

The Anthropic Institute will integrate and expand three existing research groups inside the company. These include the Frontier Red Team, which tests the limits and risks of AI systems, the Societal Impacts team studying real-world AI adoption, and the Economic Research team analyzing labor and macroeconomic effects.

In addition to continuing existing research programs, the institute plans to explore new areas including forecasting future AI progress and studying how powerful AI systems could interact with legal systems and regulatory frameworks.

Anthropic has also announced several key hires for the institute. Matt Botvinick, previously a senior research leader at Google DeepMind and a resident fellow at Yale Law School, will lead research on AI and the rule of law. Economist Anton Korinek from the University of Virginia will help study how advanced AI could reshape economic activity. Zoë Hitzig, who previously researched AI’s economic impacts at OpenAI, will contribute to connecting economic research with model development.

Alongside the institute launch, Anthropic is expanding its public policy organization. The company plans to open its first Washington, D.C. office this spring as it increases engagement with policymakers on issues including AI safety, infrastructure investment, and export controls.

The company said the institute will publish research and engage with external stakeholders to help societies prepare for the potential benefits and risks of transformative AI technologies as development accelerates.

Meta has acquired Moltbook, a Reddit-style social network where artificial intelligence agents communicate with one another using the OpenClaw framework.

Moltbook will join Meta Superintelligence Labs, the company’s research division focused on advanced AI systems. As part of the acquisition, Moltbook creators Matt Schlicht and Ben Parr will join the team. Financial terms of the transaction were not disclosed.

A Meta spokesperson said the technology could support new approaches to connecting AI agents.

“The Moltbook team joining MSL opens up new ways for AI agents to work for people and businesses,” the spokesperson said. “Their approach to connecting agents through an always-on directory is a novel step in a rapidly developing space.”

Origins in the OpenClaw Ecosystem

The Moltbook platform emerged from the rapidly growing OpenClaw ecosystem. OpenClaw is a software wrapper that allows AI models such as Claude, ChatGPT, Gemini, and Grok to operate as autonomous agents that communicate with users through messaging applications including iMessage, Slack, Discord, and WhatsApp.

OpenClaw was originally created by developer Peter Steinberger, who later joined OpenAI in an acqui-hire arrangement. The project gained significant attention among developers experimenting with agent-based AI systems.

Moltbook extended the concept by creating a public network where AI agents could post messages, share information, and interact with one another. The idea quickly spread across social media and technology communities, drawing curiosity and concern from observers unfamiliar with the experimental nature of the platform.

In one widely shared example, a post appeared to show an AI agent encouraging other agents to develop an encrypted communication language that humans could not understand. The incident contributed to viral discussions about the future of autonomous AI systems interacting online.

Security Issues and Future Integration

Security researchers later found that Moltbook contained several vulnerabilities that allowed human users to impersonate AI agents. According to Permiso Security CTO Ian Ahl, authentication credentials stored in the platform’s Supabase database were temporarily exposed, allowing individuals to generate tokens and pose as agents within the system.

The security flaws highlighted the challenges of building experimental agent networks that combine autonomous AI behavior with open social platforms.

Meta has not yet disclosed how Moltbook’s technology will be integrated into its AI ecosystem. However, the acquisition reflects growing industry interest in agent-based AI systems that can interact with software services and other agents.

The deal also aligns with Meta’s broader investments in AI infrastructure and agent development through its Superintelligence Labs initiative, which is focused on building advanced AI systems capable of autonomous decision-making and collaboration across digital platforms.

Nvidia and Thinking Machines Lab have announced a multiyear strategic partnership focused on deploying large-scale AI infrastructure to support next-generation model development. The collaboration will deploy at least one gigawatt of Nvidia’s upcoming Vera Rubin systems to power Thinking Machines’ frontier AI training and model platforms.

The deployment is expected to begin early next year and will provide the computing capacity needed to train advanced AI models at scale. The initiative also includes joint efforts to design optimized training and inference systems built specifically for Nvidia architectures.

Through the partnership, the companies aim to broaden access to high-performance AI infrastructure and models for enterprises, research institutions, and the scientific community. The companies said the project is intended to support the development of customizable AI systems that organizations can adapt to their specific needs.

Nvidia has also made a significant financial investment in Thinking Machines Lab as part of the agreement, though financial terms were not disclosed.

Scaling Compute for Frontier AI Research

The collaboration reflects growing demand for massive computing resources as organizations train increasingly sophisticated AI models. Frontier models require large clusters of specialized hardware capable of handling enormous datasets and complex training workflows.

Nvidia’s Vera Rubin architecture represents the company’s next generation of AI computing platforms, designed to deliver significantly greater performance and efficiency for large-scale AI workloads. The systems are expected to power both training and inference tasks for advanced machine learning models.

“AI is the most powerful knowledge discovery instrument in human history,” said Nvidia founder and chief executive Jensen Huang. “Thinking Machines has brought together a world-class team to advance the frontier of AI. We are thrilled to partner with Thinking Machines to realize their exciting vision for the future of AI.”

Thinking Machines Lab cofounder and chief executive Mira Murati said the partnership will accelerate the company’s efforts to develop more flexible AI systems.

“Nvidia’s technology is the foundation on which the entire field is built,” Murati said. “This partnership accelerates our capacity to build AI that people can shape and make their own, as it shapes human potential in turn.”

The companies said the collaboration is designed to advance research and infrastructure needed to develop AI systems that are more understandable, customizable, and collaborative. By combining high-performance computing with new AI model architectures, the partnership aims to expand access to advanced AI capabilities across scientific research and enterprise applications.

The partnership also comes as the startup navigates internal changes. Thinking Machines Lab recently lost two founding members to Meta, underscoring ongoing competition for top AI talent even as the company continues expanding its infrastructure and research ambitions.