About
PM Lambert is a computer science student passionate about making AI more accessible and sustainable. His research focuses on post-training optimization techniques for large language models, investigating how methods like pruning and parameter-efficient fine-tuning can reduce the computational footprint of AI while maintaining performance on natural language processing tasks.
When he’s not diving deep into machine learning optimization, PML can be found crafting homemade pizzas and sweets in the kitchen, working on indie game projects using Godot and Blender, or cheering on the Philadelphia Eagles. As an open-source enthusiast and longtime Arch Linux user, he believes in building technology that’s both powerful and accessible to everyone.
Through his work, PML aims to help democratize AI by making large language models more efficient and environmentally friendly, one optimization technique at a time.
