
Daniel Kokotajlo
Articles
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1 week ago |
dwarkesh.com | |Daniel Kokotajlo
Ege Erdil and Tamay Besiroglu have 2045+ timelines, think the whole "alignment" framing is wrong, don't think an intelligence explosion is plausible, but are convinced we'll see explosive economic growth. This discussion offers a totally different scenario than my recent interview with Scott and Daniel. Ege and Tamay are the co-founders of Mechanize, a startup dedicated to fully automating work. Before founding Mechanize, Ege and Tamay worked on AI forecasts at Epoch AI.
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Dec 28, 2024 |
lesswrong.com | Aleksey Bykhun |L L |Daniel Kokotajlo |Tom Davidson
This post is crossposted from my Substack. Original here. Edited to add: The main takeaway of this post is meant to be: Labour-replacing AI will shift the relative importance of human v non-human factors of production, which reduces the incentives for society to care about humans while making existing powers more effective and entrenched.
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Nov 20, 2024 |
lesswrong.com | Zach Stein-Perlman |David Matolcsi |Daniel Kokotajlo
I experimented a bunch with DeepSeek today, it seems to be exactly on the same level in highs school competition math as o1-preview in my experiments. So I don't think it's benchmark-gaming, at least in math. On the other hand, it's noticeably worse than even the original GPT-4 at understanding a short story I also always test models on.
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Nov 17, 2024 |
lesswrong.com | Daniel Kokotajlo
Here's a fairly concrete AGI safety proposal:Default AGI design: Let's suppose we are starting with a pretrained LLM 'base model' and then we are going to do a ton of additional RL ('agency training') to turn it into a general-purpose autonomous agent.
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Oct 4, 2024 |
lesswrong.com | Daniel Filan |Daniel Kokotajlo
YouTube linkEpoch AI is the premier organization that tracks the trajectory of AI - how much compute is used, the role of algorithmic improvements, the growth in data used, and when the above trends might hit an end. In this episode, I speak with the director of Epoch AI, Jaime Sevilla, about how compute, data, and algorithmic improvements are impacting AI, and whether continuing to scale can get us AGI.
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