Anything else I missed about Q*? Leave comment & let me know!     See Less

hey , Can you please make a video on detection on some significant insight using the reinforcement learning.
I was curious about making the model to learn itself about the irregular pat     See More needs to be classified using the reinforcement learning    See Less

Great overview! Jason, your videos on the AI topic are the best!

00:00 🤖 "Q Star" is generating a lot of disc     See More the AI community, and it's associated with OpenAI's recent actions, but its exact nature remains speculative.
01:08 🎮 Reinforcement learning is a machine learning framework where an agent learns from trial and error, aiming to maximize future rewards. It involves policy networks and value networks.
03:25 🧠 Reinforcement learning allows AI agents to self-play and discover new strategies, as demonstrated by DeepMind's achievements in games like Breakout and AlphaGo.
08:01 📚 There's speculation that "Q Star" could involve using policy networks and value networks, similar to AlphaGo, to improve reasoning and logic in large language models like GPT.
11:14 🐍 You can experiment with reinforcement learning in simple games with open-source projects, even if you're new to the field.    See Less

How does the reward system work for reinforcing behavior beyond Pavlovian bell sounds that signal approval?     See Less

Can't wait for it to be open sourced 😂     See Less

📝 Summary of Key Points:

📌 Reinforced learning is a machine learning framework that allows AI to learn from its own trials and errors by receiving rewards or penalties based o     See More ons.
🧐 AI systems like DeepMind's AlphaGo have achieved superhuman performance in tasks through reinforced learning, discovering new strategies in the process.
🚀 Reinforced learning could be applied to large language models like GPT, improving reasoning and logic capabilities by proposing multiple solutions and evaluating their value.
📌 OpenAI's research paper "Let's Verify Step by Step" explores a reward model for large language models, involving another model critiquing the reasoning process for better results.

💡 Additional Insights and Observations:

💬 "The ability of AI to explore different paths and uncover novel solutions is seen as a promising development."
📊 No specific data or statistics were mentioned in the video.
🌐 OpenAI's research paper "Let's Verify Step by Step" can be referenced for further information on the reward model for large language models.

📣 Concluding Remarks:

Reinforced learning is a powerful framework in AI that allows machines to learn from their own experiences. It has shown remarkable success in tasks like playing games and could potentially enhance the reasoning and logic capabilities of large language models. OpenAI's recent breakthrough, qar, has sparked excitement and speculation within the AI community, and further research, like the "Let's Verify Step by Step" paper, is exploring new ways to improve language models through reinforced learning.
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Very well organized and informative presentation.     See Less

I think Q* must be OPEN SOURCE for benefit humanity. Not only for big companies.     See Less

Open*AI     See Less

Q is question and * is repeat, so make sintezis of lot answer you got general inteligent ansver. My noob opinion.     See Less