Inherent, founded by DeepMind alumni, says its AI ‘teammate’ just outperformed Anthropic and OpenAI at replicating research
- ID
- 16896
- Status
- summarized
- Published
- 23 Aug 2026, 3:00 AM
- Fetched
- 23 Aug 2026, 3:57 AM
- Provider
- TechCrunch
- Category
- technology
- Original URL
- https://techcrunch.com/2026/08/22/inherent-founded-by-deepmind-alumni-says-its-ai-teammate-just-outperformed-anthropic-and-openai-at-replicating-research/
- Source URL
- https://techcrunch.com/feed/
Summary
- Score
- 5.5
- Created
- 23 Aug 2026, 3:57 AM
- Tags
- Audience
- ai_ml_learnersai_agent_userssaas_founders
What happened
Inherent, a London AI lab founded by Google DeepMind alumni that recently raised a $50M seed round, claims its AI agent Faraday outperformed Anthropic's Claude Opus 4.8 and OpenAI's GPT-5.5 at independently reproducing findings from published scientific papers. Notably, Faraday runs on Qwen 3.6, a 27-billion-parameter model—far smaller than the frontier systems it claims to beat.
Why it matters
If the benchmark holds up under scrutiny, it suggests that for narrow agentic tasks like research replication, a well-prompted 27B model can match or beat frontier-scale models—meaning builders may not need to pay for the most expensive API calls for certain agent workflows. However, this is a self-reported result from a startup promoting its own product, so verify against independent replication before changing your model selection.
Discussion angle
Does the parameter-efficiency claim change how you'd architect an agent pipeline, or is paper replication too narrow a task to generalize from—what would you benchmark before switching from a frontier model to a 27B model?