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www.lesswrong.com | ||
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www.greaterwrong.com
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| | | | | Find all Alignment Newsletter resources here. In particular, you can sign up, or look through this spreadsheet of all summaries that have ever been in the newsletter. I'm always happy to hear feedback; you can send it to me by replying to this email. Audio version here (may not be up yet). Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model (Julian Schrittwieser et al) (summarized by Nicholas): Up until now, model-free RL approaches have been state of the art at visually rich domains such as Atari, while model-based RL has excelled for games which require planning many steps ahead, such as Go, chess, and shogi. This paper attains state of the art performance on Atari using a model-based approach, MuZero, while matching AlphaZero (AN #36) at... | |
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joecarlsmith.com
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| | | | | A high-level picture of how we might get from here to safe superintelligence. | |
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www.greaterwrong.com
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| | | | | TL;DR:Strong problem-solving systems can be built from AI systems that play diverse roles, LLMs can readily play diverse roles in role architectures, and AI systems based on role architectures can be practical, safe, and effective in undertaking complex and consequential tasks. This article explores the practicalities and challenges of aligning large language models (LLMs[1]) to play central roles in performing tasks safely and effectively. It highlights the potential value of Open Agency and related role architectures in aligning AI for general applications while mitigating risks. | |
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www.lesswrong.com
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| | | We founded Anthropic because we believe the impact of AI might be comparable to that of the industrial and scientific revolutions, but we aren't conf... | ||
