Funding

UK Recursive Superintelligence Raises $650M In Funding At $4.65 Billion Valuation

May 15, 2026 | By Team SR

Recursive Superintelligence, a London, UK- and San Francisco-based AI startup focused on self-improving artificial intelligence and autonomous training systems, has emerged from stealth with $650 million in funding at a $4.65 billion valuation.

SUMMARY

  • Recursive Superintelligence, a London, UK- and San Francisco-based AI startup focused on self-improving artificial intelligence and autonomous training systems, has emerged from stealth with $650 million in funding at a $4.65 billion valuation.

The round was led by GV, Google’s venture capital arm, and Greycroft, with participation from AMD Ventures and NVIDIA.

The company plans to use the capital to secure large-scale compute infrastructure, expand global research operations, and launch its first “Level 1” autonomous training system by mid-2026.

Founded just months ago, Recursive Superintelligence is betting on a future where AI systems can enhance themselves without continuous human intervention.

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Its platform is designed to automate the machine learning research process by independently modifying neural network architectures, refining training algorithms, and managing evaluation protocols.

The startup is led by CEO Richard Socher, former chief scientist at Salesforce, alongside co-founders Tim Rocktäschel, a UCL AI professor and former Google DeepMind scientist, Jeff Clune, Josh Tobin, and Tim Shi. The company’s team of fewer than 30 employees includes talent from Meta, OpenAI, and other leading AI organizations.

With offices in London and San Francisco, Recursive Superintelligence joins a growing wave of AI startups exploring new approaches to advancing machine intelligence including ventures such as AMI Labs and Ineffable Intelligence.

About Recursive

Recursive is an AI company building self-improving AI systems that can learn and get better on their own. Founded in 2026 the company develops technology that helps automate research and discover new knowledge faster. Its AI can improve training methods, adjust algorithms and enhance performance with very little human involvement.

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