{"id":106821,"title":"rekursiv.ai: AI scientists that invent new knowledge","tagline":"Scale AI scientists whose own breakthroughs accelerate the next.","body":"Hey YC! We're [Josh](https://rekursiv.ai/josh) and [Dan](https://rekursiv.ai/dan), co-founders of [rekursiv.ai](http://rekursiv.ai) 🧪.\n\n[rekursiv.ai](http://rekursiv.ai) builds fleets of **AI scientists** that do ML research on their own: they come up with ideas, run thousands of experiments in parallel, learn from the results, and accelerate their own discoveries. In a few days of self-directed research, they invented ideas and algorithms that **matched state-of-the-art accuracy on ARC-AGI of frontier LLMs at up to 10,000× lower cost**, and became the first system to hit **100% on Sudoku** with a neural network trained only on input-output pairs.\n\n![uploaded image](/media/?type=post\u0026id=106821\u0026key=user_uploads/3527564/0444a495-03fa-4f41-9762-ba134521b2f4)\n\n**Why this matters.**\n\nAI research is bottlenecked by humans. Every advance still runs through a small number of researchers who can only devise and test ideas so fast. Compute keeps scaling; the human idea-generation loop doesn't. We believe **AI progress isn't bounded by compute, it's bounded by the rate at which good ideas get tried and tested**. So instead of scaling one model, we built a system that generates and tests ideas on its own.\n\n**It already works.**\n\nIn a few days of self-directed research, our AI scientists set a groundbreaking records on hard benchmarks.\n\n* On **ARC-AGI** (easy for humans, hard for AI), our AI scientists matched top frontier LLM models at up to **10,000× lower cost**.\n* On **Sudoku**, they achieved 100% accuracy by running hundreds of experiments over a few days, wrote 100k+ lines of their own code, and invented a new inference method (_Hypothesis-Pinning Search_).\n* Every gain came from ideas and algorithms **the system invented itself**. It even debugged its own training bugs and abandoned its own ideas that led to dead ends.\n\nFull write-ups: [ARC-AGI](https://rekursiv.ai/blog/pushing-limits-arc-agi/) · [Sudoku](https://rekursiv.ai/blog/100-percent-accuracy-on-sudoku/)\n\n![uploaded image](/media/?type=post\u0026id=106821\u0026key=user_uploads/3527564/676b13b6-cc1b-4545-8d14-cc7ae1e9b5a5)\n\n**Who we are.**\n\nWe're two ML researchers with 21 years of combined experience at **Google DeepMind and Luma AI**. We spent our careers building frontier generative models. Now we're pointing that experience at a harder problem: AI that discovers on its own.\n\n* **Josh Dillon** — Staff Research Scientist at **Google Research \u0026amp; DeepMind for 13 years**, then led foundational-model pre-training at **Luma AI**. Created **TensorFlow Probability** (\\~1M downloads/month).\n* **Dan Kondratyuk** — First author of **VideoPoet (ICML 2024 Best Paper)**. Co-developed the models powering **Luma's Dream Machine** and led Luma's realtime World Models team. Previously 5 years at **Google Research**.\n\n**What's next.**\n\nWe're pointing the system at harder, more varied challenges and building a platform to share results in real time. The bottleneck now is experiment scale: the more experiments we run, the more discoveries the our AI teams can make. We plan to scale from a few AI scientists to millions, each discovery accelerating the next, until the rate of scientific progress is no longer limited by the number of human researchers.\n\n**Asks.**\n\n* **Got a hard problem or benchmark?** If you have a benchmark or research problem you'd love an autonomous team of scientists to attack, we want to hear it. Email [contact@rekursiv.ai](mailto:contact@rekursiv.ai).\n* **Researchers \u0026amp; engineers:** We're hiring **Founding Scientists** and **Engineers** (Bay Area or remote). If you love running thousands of experiments and figuring out what the results mean, reach out at [hiring@rekursiv.ai](mailto:hiring@rekursiv.ai)\n* **Just want to nerd out about autonomous science?** Drop us a line, always happy to chat.\n\n— Josh \u0026amp; Dan, [rekursiv.ai](http://rekursiv.ai)","slug":"Rmv-rekursiv-ai-ai-scientists-that-invent-new-knowledge","created_at":"2026-07-22T14:06:11.738Z","updated_at":"2026-09-19T09:00:25.863Z","total_vote_count":7,"url":"https://www.ycombinator.com/launches/Rmv-rekursiv-ai-ai-scientists-that-invent-new-knowledge","share_image_url":"https://www.ycombinator.com/media/?type=post\u0026id=106821\u0026key=user_uploads/3527564/676b13b6-cc1b-4545-8d14-cc7ae1e9b5a5","company":{"id":31555,"name":"rekursiv.ai","slug":"rekursivai","url":"https://rekursiv.ai","logo":"https://bookface-images.s3.amazonaws.com/small_logos/f8606b08cc0428757361006dc3171d7b460ae47e.png","batch":"Summer 2026","industry":"B2B","tags":["Artificial Intelligence","Deep Learning","Machine Learning"],"search_path":"https://bookface.ycombinator.com/company/31555"}}