Advances in run-time strategies for next-generation foundation models
Discover the most effective run-time strategies on the OpenAI o1-preview model, improving accuracy in medical language tasks.
TamGen
TamGen is a transformer-based chemical language model for developing target-specific drug compounds. Research shows that TamGen can also optimize existing molecules by designing target-aware molecule fragments, potentially enabling the discovery of novel compounds that build…
UW GIX Launch Project: GenAI Evaluation CoPilot
Thank you to @AdvityaGemawat for being in this video about our Team GenAI’s Launch Project, the University of Washington’s Master of Science in Technology Innovation Capstone Project, sponsored by Microsoft Azure. This video will talk…
Accelerating drug discovery with TamGen: A generative AI approach to target-aware molecule generation
TamGen uses generative AI to design new drug candidate compounds to treat TB, going beyond traditional methods by generating novel chemical structures. Learn how a collaboration with the Global Health Drug Discovery Institute is making…
LazyGraphRAG: Setting a new standard for quality and cost
Introducing a new approach to graph-enabled RAG. LazyGraphRAG needs no prior summarization of source data, avoiding prohibitive up-front indexing costs. It’s inherently scalable in cost and quality across multiple methods and search mechanisms.