What makes a machine learning algorithm "superhuman"?

What makes a machine learning algorithm "superhuman"?

A few weeks ago, we podcasted about a neural network that was being touted as "better than doctors" in diagnosing pneumonia from chest x-rays, and how the underlying dataset used to train the algorithm raised some serious questions. We're back again this week with further developments, as the author of the original blog post pointed us toward more developments. All in all, there's a lot more clarity now around how the authors arrived at their original "better than doctors" claim, and a number of adjustments and improvements as the original result was de/re-constructed. Anyway, there are a few things that are cool about this. First, it's a worthwhile follow-up to a popular recent episode. Second, it goes *inside* an analysis to see what things like imbalanced classes, outliers, and (possible) signal leakage can do to real science. And last, it raises a really interesting question in an age when computers are often claimed to be better than humans: what do those claims really mean? Relevant links: https://lukeoakdenrayner.wordpress.com/2018/01/24/chexnet-an-in-depth-review/

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Avsnitt(317)

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 0s

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

Summer break: back soon

Summer break: back soon

Summer break: back soon by Katie Malone

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Interviewing the Linear Digressions Agents (The Agents Season, Episode 11)

Interviewing the Linear Digressions Agents (The Agents Season, Episode 11)

After a five-year hiatus, the podcast that burned out partly over the tedium of writing episode descriptions is back — and using AI agents to handle exactly that task. The season-11 finale turns the l...

28 Juni 37min

Agent Economics (The Agents Season, Episode 10)

Agent Economics (The Agents Season, Episode 10)

What if building more highways made your commute *slower*? That's the paradox at the heart of AI agent economics: even as per-token inference costs have plummeted dramatically over the past two years,...

22 Juni 24min

Agent Trust, Oversight and Control (The Agents Season, Episode 9)

Agent Trust, Oversight and Control (The Agents Season, Episode 9)

Capabilities get all the attention when it comes to AI agents — but what happens when a highly capable agent makes a bad decision in the real world? Trust, oversight, and control are the unglamorous b...

15 Juni 25min

Many Agents, Many Problems (The Agents Season, Episode 8)

Many Agents, Many Problems (The Agents Season, Episode 8)

Whether you work best solo or thrive in a team, you know collaboration is complicated — and it turns out AI agents face the same tensions. This episode dives into multi-agent systems, exploring how ne...

8 Juni 28min

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