Can Language Models Be Too Big? 🦜 with Emily...

In this episode, Scott Clark, co-founder and CEO of Distributional, joins us to explore how teams can reliably operate and improve complex LLM systems and agents in production. Scott introduces a Maslow’s hierarchy of observability: telemetry for logging, monitoring for known sig ...  Show more

In this episode, Philip Kiely, head of AI education at Baseten, joins us to unpack the fast-evolving discipline of inference engineering. We explore why inference has become the stickiest and most critical workload in AI, how it blends GPU programming, applied research, and large ...  Show more

We asked ChatGPT to summarize this episode and this is what it wrote: "In the episode, the host discussed the increasing use of AI language models like ChatGPT in newsrooms. The host explained that ChatGPT, a large language model developed by OpenAI, is being used to automate tas ...  Show more

In this episode of High Theory, Alex Hanna talks with Nathan Kim about Ethical AI. Their conversation is part of our High Theory in STEM series, which tackles topics in science, technology, engineering, and medicine from a highly theoretical perspective. In this episode, Alex hel ...  Show more

Gordon Moore, the co-founder of Intel who died earlier this year, is famous for forecasting a continuous rise in the density of transistors that we can pack onto semiconductor chips. His eponymous “Moore’s law” still holds true after almost six decades, but further progress is be ...  Show more

In this episode of High Theory, Matthew Kirschenbaum talks about txt, or text. Not texting, or textbooks, but text as a form of data that is feeding large language models. Will the world end in fire, flood, or text? In the full interview, Matthew recommended Tim Maughan’s novel I ...  Show more