Hallucinations in LLMs aren't just annoying—they're catastrophic in high-stakes domains like drug discovery, materials science, and quantitative finance. A single fabricated citation or incorrect molecular interaction can burn through years of research and millions in funding.
Apodex is tackling this with their Frontier Program: $100k/month in compute credits for research labs and deep tech startups working on problems where correctness actually matters. The focus is on reasoning systems that can verify their own outputs—think proof-based verification, constrained generation, and domain-specific validation layers.
This isn't about building another chatbot. It's about deploying compute where hallucination risk has real-world consequences: protein folding simulations, financial risk models, materials discovery. The kind of work where you need deterministic outputs or at least probabilistic bounds you can trust.
Built by Tianqiao Chen's team. If you're working on hard science or deep tech and need serious reasoning infrastructure, this is worth checking out.
Apodex is tackling this with their Frontier Program: $100k/month in compute credits for research labs and deep tech startups working on problems where correctness actually matters. The focus is on reasoning systems that can verify their own outputs—think proof-based verification, constrained generation, and domain-specific validation layers.
This isn't about building another chatbot. It's about deploying compute where hallucination risk has real-world consequences: protein folding simulations, financial risk models, materials discovery. The kind of work where you need deterministic outputs or at least probabilistic bounds you can trust.
Built by Tianqiao Chen's team. If you're working on hard science or deep tech and need serious reasoning infrastructure, this is worth checking out.