The Language Model Too Dangerous to Release
Linear Digressions25 Mars 2019

The Language Model Too Dangerous to Release

OpenAI recently created a cutting-edge new natural language processing model, but unlike all their other projects so far, they have not released it to the public. Why? It seems to be a little too good. It can answer reading comprehension questions, summarize text, translate from one language to another, and generate realistic fake text. This last case, in particular, raised concerns inside OpenAI that the raw model could be dangerous if bad actors had access to it, so researchers will spend the next six months studying the model (and reading comments from you, if you have strong opinions here) to decide what to do next. Regardless of where this lands from a policy perspective, it’s an impressive model and the snippets of released auto-generated text are quite impressive. We’re covering the methodology, the results, and a bit of the policy implications in our episode this week.

Det här avsnittet är hämtat från ett öppet RSS-flöde och publiceras inte av Podme. Det kan innehålla reklam.

Avsnitt(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 Nov 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 Okt 27min

Back Next Week

Back Next Week

Back Next Week by Katie Malone

19 Okt 18s

Back in Two Weeks

Back in Two Weeks

Back in Two Weeks by Katie Malone

12 Okt 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 Okt 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 Sep 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 Sep 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 Sep 32min

Populärt inom Teknik

uppgang-och-fall
natets-morka-sida
bilar-med-sladd
elbilsveckan
market-makers
skogsforum-podcast
rss-ai-med-jonas-benjamin
rss-veckans-ai
rss-snacka-om-ai
rss-laddstationen-med-elbilen-i-sverige
rss-elektrikerpodden
rss-technokratin
bosse-bildoktorn-och-hasse-p
bli-saker-podden
rss-uppgang-och-fall
garagehang
rss-en-ai-till-kaffet
hej-bruksbil
rss-ai-gothenburg-podcast
vi-bilagares-podcast