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www.v7labs.com
| | www.exxactcorp.com
0.7 parsecs away

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| | [AI summary] The text provides an in-depth overview of Deep Reinforcement Learning (DRL), focusing on its key components, challenges, and applications. It explains how DRL combines reinforcement learning (RL) with deep learning to handle complex decision-making tasks. The article discusses the limitations of traditional Q-learning, such as the need for a Q-table and the issue of unstable target values. It introduces Deep Q-Networks (DQNs) as a solution, highlighting the use of experience replay and target networks to stabilize training. Additionally, the text highlights real-world applications like AlphaGo, Atari game playing, and oil and gas industry use cases. It concludes by emphasizing DRL's potential for scalable, human-compatible AI systems and its rol...
| | neptune.ai
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| | Exploring RL applications: from self-driving cars and industry automation to NLP, finance, and robotics manipulation.
| | obrhubr.org
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| | Instead of simply enjoying a cool board game, I dissect and explore the different approaches to solving the imperfect information game Take-It-Easy. I compare basic heuristics to a more sophisticated reinforcement learning approach. What's the best a computer can do?
| | simonwillison.net
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| My biggest complaint about the launch of the ChatGPT Atlas browser the other day was the lack of details on how OpenAI are addressing prompt injection attacks. The launch post ...