Experimental News Clipping Site

Tag: reinforcement

  • Hacker News: Legion Health (YC S21) is hiring an AI/ML Engineer

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    Kurt Seifried
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    Source URL: https://www.ycombinator.com/companies/legion-health/jobs/26GxO6f-ai-ml-engineer-llm-optimization-ai-driven-workflows Source: Hacker News Title: Legion Health (YC S21) is hiring an AI/ML Engineer Feedly Summary: Comments AI Summary and Description: Yes Summary: The text focuses on Legion Health’s mission to revolutionize mental healthcare through AI-driven operations rather than diagnostics. It emphasizes the hiring of engineers to enhance the deployment of AI technologies,…

  • Hacker News: Superintelligence startup Reflection AI launches with $130M in funding

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    Kurt Seifried
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    Source URL: https://siliconangle.com/2025/03/07/superintelligence-startup-reflection-ai-launches-130m-funding/ Source: Hacker News Title: Superintelligence startup Reflection AI launches with $130M in funding Feedly Summary: Comments AI Summary and Description: Yes Summary: Reflection AI Inc., a new startup founded by former Google DeepMind researchers, aims to develop superintelligence through AI agents that can automate programming tasks. With $130 million in funding, the…

  • Hacker News: Reflection – AlphaGo / Gemini team building superintelligent coding agents

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    Kurt Seifried
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    Source URL: https://www.reflection.ai/superintelligence/ Source: Hacker News Title: Reflection – AlphaGo / Gemini team building superintelligent coding agents Feedly Summary: Comments AI Summary and Description: Yes Summary: The text describes Reflection, an AI company focused on developing superintelligent autonomous systems, emphasizing their historical foundations in reinforcement learning and large language models. Their strategy revolves around creating…

  • Hacker News: Ladder: Self-Improving LLMs Through Recursive Problem Decomposition

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    Kurt Seifried
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    Source URL: https://arxiv.org/abs/2503.00735 Source: Hacker News Title: Ladder: Self-Improving LLMs Through Recursive Problem Decomposition Feedly Summary: Comments AI Summary and Description: Yes Summary: The paper introduces LADDER, a novel framework for enhancing the problem-solving capabilities of Large Language Models (LLMs) through a self-guided learning approach. By recursively generating simpler problem variants, LADDER enables models to…

  • Hacker News: Differentiable Logic Cellular Automata

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    Kurt Seifried
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    Source URL: https://google-research.github.io/self-organising-systems/difflogic-ca/?hn Source: Hacker News Title: Differentiable Logic Cellular Automata Feedly Summary: Comments AI Summary and Description: Yes Summary: This text discusses a novel approach integrating Neural Cellular Automata (NCA) with Deep Differentiable Logic Networks (DLGNs) to create a hybrid model called DiffLogic CA. This model aims to learn local rules within cellular automata…

  • Hacker News: Using GRPO to Beat o1, o3-mini and R1 at "Temporal Clue"

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    Kurt Seifried
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    Source URL: https://openpipe.ai/blog/using-grpo-to-beat-o1-o3-mini-and-r1-on-temporal-clue Source: Hacker News Title: Using GRPO to Beat o1, o3-mini and R1 at "Temporal Clue" Feedly Summary: Comments AI Summary and Description: Yes Short Summary with Insight: The provided text explores the application of reinforcement learning to enhance the deductive reasoning capabilities of smaller, open-weight models in AI. Specifically, it focuses on…

  • Hacker News: Simple Explanation of LLMs

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    Kurt Seifried
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    Source URL: https://blog.oedemis.io/understanding-llms-a-simple-guide-to-large-language-models Source: Hacker News Title: Simple Explanation of LLMs Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text provides a comprehensive overview of Large Language Models (LLMs), highlighting their rapid adoption in AI, the foundational concepts behind their architecture, such as attention mechanisms and tokenization, and their implications for various fields.…

  • Simon Willison’s Weblog: QwQ-32B: Embracing the Power of Reinforcement Learning

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Mar/5/qwq-32b/#atom-everything Source: Simon Willison’s Weblog Title: QwQ-32B: Embracing the Power of Reinforcement Learning Feedly Summary: QwQ-32B: Embracing the Power of Reinforcement Learning New Apache 2 licensed reasoning model from Qwen: We are excited to introduce QwQ-32B, a model with 32 billion parameters that achieves performance comparable to DeepSeek-R1, which boasts 671 billion parameters…

  • Hacker News: QwQ-32B: Embracing the Power of Reinforcement Learning

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    Kurt Seifried
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    Source URL: https://qwenlm.github.io/blog/qwq-32b/ Source: Hacker News Title: QwQ-32B: Embracing the Power of Reinforcement Learning Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the advancements in Reinforcement Learning (RL) as applied to large language models, particularly highlighting the launch of the QwQ-32B model. It emphasizes the model’s performance enhancements through RL and…

  • Slashdot: Turing Award Winners Sound Alarm on Hasty AI Deployment

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    Kurt Seifried
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    Source URL: https://slashdot.org/story/25/03/05/1330242/turing-award-winners-sound-alarm-on-hasty-ai-deployment?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Turing Award Winners Sound Alarm on Hasty AI Deployment Feedly Summary: AI Summary and Description: Yes Summary: Andrew Barto and Richard Sutton, pioneers in reinforcement learning, have expressed concerns regarding the safe deployment of AI systems, emphasizing the necessity of safeguards in software engineering practices. Their insights highlight the…