Daniel Paleka's Newsletter
Daniel PalekaAI research and making the future go well.
| Platform |  | Pricing | Only free issues | Publishes | Monthly |
|---|---|---|---|---|---|
| Issues | 35 | Founded | 3 years ago | Last Issue | 6 months ago |
| Active | |||||
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newsletter.danielpaleka.comLatest Issues
Writing in public is still underrated
I wrote 34 posts on this newsletter during my PhD, and my life and work are genuinely better for it. Recently I’ve met several people with very interesting ideas who never write them down. Some of them even read my Substack!
If you have i...
Underrated reasons to be thankful: AI research edition
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That there is a 405B pretrained base model still available on OpenRouter, despite making zero economic sense, and a base model API only being useful for a tiny subset of LLM researchers and enthusiasts.
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That emergent misalignment i...
Even superhuman AI forecasters are only as good as your questions
Predicting the future is difficult. In the next few years, AIs might become much better at it, at least for precise forecasting questions. What do we do then? Is that AGI?
In a previous post, I described how reinforcement learning (RL) is...
What’s the deal with RL and forecasting?
Prediction is difficult, especially about the future. It requires understanding the world as it is now, and causal reasoning about how it will change over time. It is very tempting as a machine learning task for many reasons:
- It has vi...
Contra Dwarkesh on RL sample-efficiency via information theory
Dwarkesh Patel wrote an article RL is even more information inefficient than you thought. I’ve been trying to understand RL recently so I read the post with a lot of interest; but I think the main technical point in the post is wrong.
Wit...
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