Arseny Khakhalin reposted
Amazon researchers snitched to the US government about a jailbreak that triggered a letter forcing Anthropic to shut down Fable 5 www.wsj.com/tech/ai/anth...
Who's Who of AI
Arseny Khakhalin
Data Scientist in Berlin
Head of Automation in incycling.ai
Former Bard College prof
For my after-work alter-ego, see @elstersen.bsky.social
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What they're sharing
wsj.com
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80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition ieeexplore.ieee.org
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arxiv.org
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github.com
I think I figured out exactly how the “AI used a bottle of water per prompt” miscalculation happened blog.andymasley.com
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newsletter.pragmaticengineer.com
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Articles & links
Arseny Khakhalin reposted
This was part of a talk by Alyosha Efros on "Sweet Data." He wanted us all to read this paper, “this is the most important paper in AI”: ieeexplore.ieee.org/abstract/doc... (sorry, much confusion about the speaker's name because they changed the schedule order)
Arseny Khakhalin reposted
cool study. I have been worried about this and they articulate it well. there are important rules in large codebases that are not written down, and are only enforced when a small number of senior codebase knowers see a change and go “oh no, that violates this rule we didn’t re…
ughm so it's a bug known since April but that has not been fixed yet... Where are the AI-assited 10x engineers when you need them haha
Arseny Khakhalin reposted
I think I figured out exactly how the “AI used a bottle of water per prompt” miscalculation happened open.substack.com/pub/andymasl...
Arseny Khakhalin reposted
astonishing how acquihiring Alexandr Wang was somehow worse for Meta than I could have ever expected how incredibly fucking stupid newsletter.pragmaticengineer.com/p/why-is-met...
Their own posts
Recent commentary
The way to enjoy bsky is to have two accounts: one in which all ai haters are muted, and another one in which the word "ai" is muted. It's a bit complicated but it works!
Agentic pipelines feel like OOP coding (you are concerned about giving each agent as much context as it needs, but not more; you excise functionalities into subagents just like you write methods etc.) One difference: you want your "methods" to be happy, so you give each of them a tiny pep talk
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