Um Detector 1

Um Detector 1

So, um... what about machine learning for audio applications? In the course of starting this podcast, we've edited out a lot of "um"'s from our raw audio files. It's gotten now to the point that, when we see the waveform in soundstudio, we can almost identify an "um" by eye. Which makes it an interesting problem for machine learning--is there a way we can train an algorithm to recognize the "um" pattern, too? This has become a little side project for Katie, which is very much still a work in progress. We'll talk about what's been accomplished so far, some design choices Katie made in getting the project off the ground, and (of course) mistakes made and hopefully corrected. We always say that the best way to learn something is by doing it, and this is our chance to try our own machine learning project instead of just telling you about what someone else did!

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Avsnitt(322)

A Data-Driven Reality Check on AI in Business (Interview with Tom Davenport, Babson College)

A Data-Driven Reality Check on AI in Business (Interview with Tom Davenport, Babson College)

Tom Davenport — the man who called data science "the sexiest job of the 21st century" — is back with a reality check on AI. As one of the most seasoned observers of how businesses actually adopt trans...

31 Aug 40min

Understanding AI Text Watermarking

Understanding AI Text Watermarking

Anthropic just announced they're baking invisible watermarks directly into Claude's generated text — and while everyone else was busy having opinions about it, we were busy asking the more interesting...

24 Aug 29min

Better Know a Benchmark: Humanity's Last Exam

Better Know a Benchmark: Humanity's Last Exam

Humanity's Last Exam was designed with a bold premise: questions that human experts can answer, but AI models can't. Originally dubbed "Humanity's Last Stand," this benchmark is a massive academic col...

17 Aug 23min

A Scientific Deep Dive into Overconfident LLMs: Interview with Kaitlyn Zhou (Cornell)

A Scientific Deep Dive into Overconfident LLMs: Interview with Kaitlyn Zhou (Cornell)

When a language model tells you it's absolutely certain, is it actually more likely to be right? Kaitlyn Zhou's research says: not necessarily — sometimes confident phrasing correlates with *worse* ac...

10 Aug 33min

Reasoning Models: When LLMs Went Beyond Fancy Autocomplete

Reasoning Models: When LLMs Went Beyond Fancy Autocomplete

Reasoning models don't just answer your question — they *think out loud* first. In this episode we dig into the class of AI models that generate intermediate chains of thought before arriving at a fin...

3 Aug 25min

Distillation, or, How to Steal a Model

Distillation, or, How to Steal a Model

This week we’re covering model distillation: the technique of using a large "teacher" model's outputs to train a smaller, cheaper "student" model that mimics it. They cover the two big reasons labs do...

27 Juli 23min

Invisible LLM Failures and AI Fluency with Chris Potts (Stanford)

Invisible LLM Failures and AI Fluency with Chris Potts (Stanford)

What happens when a Stanford linguistics professor turns his attention to AI chatbots — and the surprisingly invisible ways humans misunderstand them? Chris Potts joins the show to unpack the hidden f...

20 Juli 41min

Still summer break: back next week

Still summer break: back next week

Still summer break: back next week by Katie Malone

13 Juli 25s

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