Inherent, founded by DeepMind alumni, says its AI ‘teammate’ just outperformed Anthropic and OpenAI at replicating research

6.9 relevance

AI agent replicating research is highly novel and directly relevant to AI/ML agent orchestration.

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Why It Matters

For a solutions architect focused on AI/ML agent orchestration, Inherent's approach demonstrates how reinforcement learning and smaller, specialized models can outperform larger ones in scientific reasoning tasks, with implications for building multi-agent systems that prioritize experimental design over raw compute.

Key Takeaways

Evaluate reinforcement learning over supervised training for agentic workflows that require autonomous decision-making and experimental design, not just code generation.

Inherent, founded by DeepMind alumni, says its AI ‘teammate’ just outperformed Anthropic and OpenAI at replicating research

Summary

Inherent, a London AI lab founded by DeepMind alumni, released Faraday, an AI agent that outperformed Anthropic's Claude Opus 4.8 and OpenAI's GPT-5.5 at independently replicating published scientific research. Faraday runs on a 27-billion-parameter Qwen 3.6 model—far smaller than frontier systems—and uses reinforcement learning to develop 'research taste' for designing experiments, not just reproducing results. The startup, which raised a $50M seed round, deliberately avoided building its own coding tool, instead leveraging OpenAI's GPT-5.5 Codex, and focuses on collaborative AI that proposes experiments rather than confirming user biases.

Author

Anna Heim