Customized Amazon Nova models improve molecular-property prediction in drug discovery
A single, optimized LLM unifies what previously required multiple models and can serve as a reasoning partner for medical chemists.
A single, optimized LLM unifies what previously required multiple models and can serve as a reasoning partner for medical chemists.
Built in collaboration with the Gray Lab at Johns Hopkins Whiting School of Engineering, the Antibody Developability Benchmark is powered by one of the most diverse…
Amazon’s RuleForge system uses agentic AI to generate production-ready detection rules 336% faster than traditional methods.
How automated reasoning reconciles the demands of security, performance, and maintainability.
Low-rank adaptation, data augmentation, and chain-of-thought reasoning are among the techniques enabling accent-free polyglot outputs, improved expressiveness, and reliable synthesis.
Simplifying and clarifying the assembly code for core operations enabled automated optimization and verification.
Ablation study clarifies trade-offs between accuracy and efficiency when using low-rank adaptation (LoRA) to fine-tune AI models.
By learning the idiosyncrasies of accumulated layers of legacy systems, AI agents can preserve institutional knowledge and provide a unified interface to a range of services.
As AI agents become more autonomous, the key challenge isn't what they can do; it's how to design the human side of the equation.