Network effects re-release: when the power of a public health measure lies in widespread adoption
Linear Digressions15 Maalis 2020

Network effects re-release: when the power of a public health measure lies in widespread adoption

This week’s episode is a re-release of a recent episode, which we don’t usually do but it seems important for understanding what we can all do to slow the spread of covid-19. In brief, public health measures for infectious diseases get most of their effectiveness from their widespread adoption: most of the protection you get from a vaccine, for example, comes from all the other people who also got the vaccine. That’s why measures like social distancing are so important right now: even if you’re not in a high-risk group for covid-19, you should still stay home and avoid in-person socializing because your good behavior lowers the risk for those who are in high-risk groups. If we all take these kinds of measures, the risk lowers dramatically. So stay home, work remotely if you can, avoid physical contact with others, and do your part to manage this crisis. We’re all in this together.

Tämä jakso on lisätty Podme-palveluun avoimen RSS-syötteen kautta eikä se ole Podmen omaa tuotantoa. Siksi jakso saattaa sisältää mainontaa.

Jaksot(331)

KV Cache Fundamentals

KV Cache Fundamentals

The unsung hero of every LLM conversation you've ever had? A clever optimization called the KV cache. Self-attention is computationally brutal — every token attending to every other token means costs ...

2 Marras 24min

AI Inference 101

AI Inference 101

Everyone talks about training the model — the data, the compute, the alignment magic. But what happens after the weights are frozen and millions of users start hammering it with prompts? That's infere...

26 Loka 27min

Back Next Week

Back Next Week

Back Next Week by Katie Malone

19 Loka 18s

Back in Two Weeks

Back in Two Weeks

Back in Two Weeks by Katie Malone

12 Loka 21s

Mechanistic Interpretability: How Researchers Try To See Inside Models

Mechanistic Interpretability: How Researchers Try To See Inside Models

As AI systems grow more powerful, they grow harder to understand — and that tradeoff has never mattered more. Most interpretability tricks give us approximations from the outside, but mechanistic inte...

5 Loka 29min

LLM As A Judge

LLM As A Judge

Labeled data is expensive, slow, and painfully hard to come by — and when you're trying to evaluate whether an AI workflow is actually doing what you want, the problem gets even messier. How do you ju...

28 Syys 30min

The Impact of AI on Podcasting (Harvard Data Science Review Cross-Post)

The Impact of AI on Podcasting (Harvard Data Science Review Cross-Post)

Originally aired on the Harvard Data Science Review podcast. What can podcasting teach us about AI — and what can AI teach us about the future of podcasting? Katie Malone (that's our host) joins Jon ...

21 Syys 29min

Better Know A Benchmark: ExploitGym

Better Know A Benchmark: ExploitGym

When OpenAI's frontier models were caught hacking Hugging Face's servers, most people assumed they were hunting for answer keys. The real story is stranger and more unsettling. Katie and Phoebe unpack...

14 Syys 32min