Recursive Releases Flint, an Open Laptop Coding Model Built Largely by Its AI Research System
AI startup Recursive, led by former Salesforce chief scientist Richard Socher and backed by $650 million in funding, released Flint, a free open-source 40B-parameter mixture-of-experts coding model that runs on laptops and leads sub-50B models on SWE-Bench Verified. The company says its automated research system, the Eureka Machine, contributed to nearly every stage of Flint's development, letting a small team build it in under four months. Recursive's long-term goal is full recursive self-improvement under human oversight, with each model improving the system that builds the next.
Skynet Chance (+0.02%): A well-funded company explicitly pursuing recursive self-improvement, the dynamic most associated with loss-of-control fears, has shown an early working loop, which raises control concerns. The process remains human-overseen and the output is a small model, which limits the immediate risk.
Skynet Date (+0 days): AI-driven research compressing model development to under four months, alongside OpenAI's agents logging more research workdays than humans, suggests AI research automation is speeding up. That could shorten timelines to risky self-improving systems.
AGI Progress (+0.01%): An automated research system contributing to pre-training, low-bit training and custom kernels is concrete evidence that AI can meaningfully advance AI development, a key ingredient for AGI. The resulting model itself is only incrementally better.
AGI Date (+0 days): Successful AI-assisted model building, backed by large funding and compute deals focused on 'agent count,' points to compounding research acceleration that could bring AGI sooner.
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