Kyle Tretina

Kyle Tretina is a product marketing leader at NVIDIA, focused on advancing AI for digital biology and drug discovery. He drives the strategy and storytelling behind BioNeMo and our work with BioPharma, shaping how next-generation foundation models and GPU-accelerated microservices transform molecular and protein design. With a PhD in molecular microbiology and immunology, Kyle bridges science and strategy, translating breakthroughs in AI, chemistry, and biology into platforms that accelerate discovery for researchers, startups, and pharmaceutical companies worldwide.
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Posts by Kyle Tretina

Simulation / Modeling / Design

Efficient MoE Training for Biological Foundation Models

As language models grow, scaling dense architectures becomes increasingly expensive. In a dense transformer, every token passes through every layer, so adding... 7 MIN READ
Simulation / Modeling / Design

High-Throughput Structure Prediction with BioNeMo Inference Runtime

Biomolecular structure prediction is now often run at proteome scale, where the goal is to move an entire worklist through the pipeline efficiently. NVIDIA... 11 MIN READ
Agentic AI / Generative AI

Run NVIDIA BioNeMo NIM Microservices for Protein Structure Prediction in Claude Science

Agentic AI is changing how research is done. AI scientists can read papers, propose hypotheses, call models, and determine which experiments to prioritize next.... 12 MIN READ
Simulation / Modeling / Design

Accelerating End-to-End Co-Folding Performance with NVIDIA BioNeMo Agent Toolkit

Biomolecular structure prediction and co-folding with models like OpenFold3 are now mainstream, large-scale workloads powering drug discovery and protein... 9 MIN READ
Simulation / Modeling / Design

Build an AI Scientist for Life Science Discovery with NVIDIA BioNeMo Agent Toolkit

AI scientists are emerging as a new interface for scientific computing. These agents can read papers, write code, generate hypotheses, call APIs, inspect files,... 9 MIN READ
Simulation / Modeling / Design

How to Optimize Transformer-Based Models for Low-Precision Training

Transformer architectures are the backbone of many modern large language and generative AI models. As these models grow in size, training runs consume more GPU... 9 MIN READ