Inherent's AI Agent Outperforms Larger Models at Replicating Research

London-based startup Inherent, founded by DeepMind alumni, has made a notable breakthrough in the field of artificial intelligence. The company’s small AI agent, Faraday, has outperformed larger models from Anthropic and OpenAI at autonomously replicating published research using reinforcement learning. This achievement marks a significant step towards broader scientific discovery and could have practical benefits for industries such as cryptocurrency and DeFi security.

Inherent’s team of 12 employees is planning to expand to 20-25 by the end of the year, with a focused approach that uses existing tools like OpenAI’s GPT-5.5 Codex. This pragmatic strategy allows them to concentrate on what they believe is the core challenge: imbuing AI with ‘taste’ for scientific inquiry. The company’s co-founder and chief scientist Edward Hughes emphasizes that this goal goes beyond simple pattern matching, requiring an understanding of experimental procedures.

The ability to independently replicate research findings is a fundamental step for any AI system aiming to contribute to scientific discovery. Many PhD students begin their training by replicating existing work, and Inherent’s achievement highlights the significance of this capability. The startup’s approach uses reinforcement learning to reward good outcomes rather than explicitly teaching the rules of science, which they believe will generalize better to their long-term goal of creating AI scientists.

Inherent’s strategy is distinct from other approaches in that it focuses on a narrow, high-value task rather than trying to build a general-purpose assistant. The company deliberately avoids developing its own coding tools, instead using existing software like GPT-5.5 Codex for tooling. This approach allows them to concentrate on what they believe is the core challenge: imbuing AI with ‘taste’ for scientific inquiry.

The London-based startup’s progress suggests that a small, focused team can compete with much larger players in specific scientific tasks. Inherent’s co-founder Edward Hughes has also spoken out against the U.K.’s ‘garden leave’ practice, which he says delayed his own ability to start the company. This restriction puts U.K. startups at a disadvantage compared to their U.S. rivals when hiring talent from prior roles.

Inherent plans to expand its team and ambitions extend beyond paper replication to world models and broader AI research. With Demis Hassabis’s new role at Google DeepMind leaving some staff unsettled, Inherent could become an attractive destination for DeepMind researchers considering a move. The company’s progress highlights the potential of nimble, specialized teams to challenge larger incumbents.

The ability to autonomously replicate published research is a crucial step towards broader scientific discovery. Many AI systems aim to contribute to this field by replicating existing work, and Inherent’s achievement marks a significant step forward. The startup’s approach uses reinforcement learning to reward good outcomes rather than explicitly teaching the rules of science, which they believe will generalize better to their long-term goal.

Inherent’s strategy is distinct in that it focuses on a narrow task rather than trying to build an AI assistant. This approach allows them to concentrate on what they believe is the core challenge: imbuing AI with ‘taste’ for scientific inquiry. The company deliberately avoids developing its own coding tools, instead using existing software like GPT-5.5 Codex for tooling.

The London-based startup’s progress suggests that a small team can compete with larger players in specific tasks. Inherent’s co-founder Edward Hughes has spoken out against the U.K.’s ‘garden leave’ practice, which he says delayed his own ability to start the company. This restriction puts U.K. startups at a disadvantage compared to their U.S. rivals when hiring talent from prior roles.

Inherent plans to expand its team and ambitions extend beyond paper replication to world models and broader AI research. The company’s progress highlights the potential of nimble, specialized teams to challenge larger incumbents in specific tasks.