Mark Huang of Gradient.ai discusses training a 1 million context LLM, highlighting challenges like memory scaling and the need for techniques such as curriculum learning. The podcast explores strategies for training large language models, evaluating ring attention implementations in PyTorch, and enhancing value in AI technology through early fusion models and wise resource investment.

Mark Huang, Co-Founder of Gradient AI, discusses enterprise readiness for LLM-backed applications, open sourcing their Llama-3 finetune model, focus on healthcare and finance, and navigating GenAI infra space.

Mark Huang, Co-founder of Gradient, discusses the exciting world of autonomous AI agents and extending context windows for AI models. They explore the impact of longer context windows on use cases and share insights on advancements in AI technology.