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Recursive Superintelligence was founded four months ago and has raised $500 million to develop an AI that can self-improve.

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ME News Report, April 20th (UTC+8), according to Beating Monitoring, Recursive Superintelligence has completed at least $500 million in funding, with a pre-money valuation of $4 billion. GV (Google's venture capital arm, formerly Google Ventures) led the investment, with Nvidia participating. This round was significantly oversubscribed, and the final size may reach $1 billion. The company was registered in London at the end of last year, with about 20 employees, and has not yet made a formal public debut. The founding team mainly comes from core research positions at OpenAI, Google DeepMind, and Salesforce. Richard Socher was previously Salesforce's Chief Scientist; Tim Rocktäschel is an AI professor at University College London, who recently worked as a principal scientist at DeepMind and participated in Genie, an interactive world model; Josh Tobin, Jeff Clune, and Tim Shi are from OpenAI, while the other members come from Google and Meta. The company's goal is to develop AI systems that require no human intervention and can continuously self-improve. Once large models are trained, they are essentially fixed; to become stronger, engineers must reorganize data and retrain. Self-improvement refers to models generating their own data and updating their parameters independently, removing humans from the training loop. This approach has long been a goal of AI research, but there are no publicly available results proving it can operate stably over the long term. In the first quarter of this year, global startup funding reached a record high of $300 billion, with OpenAI, Anthropic, xAI, and Waymo taking the majority (Crunchbase data). Recursive is also one of several new AI labs spun off from OpenAI, Google, and Meta in recent months, similar to Thinking Machines Lab, Safe Superintelligence, Ineffable Intelligence, and Advanced Machine Intelligence Labs. (Source: BlockBeats)
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