Episode from the podcast Programming Throwdown
Episode
172: Transformers and Large Language Models
Released Monday, March 11th 2024 1 hr 26 min
Show notes
About this episode
Patrick and Jason explain transformers and large language models from the ground up. They cover attention, encoders and decoders, self-supervised learning, RLHF, and the key architectural ideas that made modern LLMs possible.
More from Programming Throwdown
All episodes188: World Models
1 hr 36 min
186: Becoming a Manager
1 hr 27 min
Patrick and Jason discuss what it means to become a manager and how the role differs from individual engineering work. They cover hiring, coaching, performance management, team goals, and when moving into management is or is not the right choice.
185: Workflow Orchestrators
1 hr 32 min
Patrick and Jason break down workflow orchestrators and why they matter for batch jobs, long-running tasks, and resumable distributed systems. They compare tools such as Airflow, Dagster, Temporal, Ray, and Kubeflow while explaining the infrastructure patterns behind them.
This podcast, its content and its artwork are not owned by, affiliated with, or endorsed by Castquire.