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Watch Gemini 2.5 Pro implement a landmark Google DeepMind research paper. 🕹️ It codes the reinforcement learning algorithm, visualizes the training live and even debugs errors. ↓

369,902 просмотров • 1 год назад •via X (Twitter)

Комментарии: 11

Фото профиля elvis
elvis1 год назад

Really appreciate you all included the errors and how to potentially fix them. I am working on a similar workflow and figuring out how to provide error more efficiently as feedback to agents.

Фото профиля Rainmaker
Rainmaker2 лет назад

💡 Learn how Reinforcement Learning can boost your trading performance! In this free Substack article I share full code of a trading algorithm based on Reinforcement Learning that beats other Machine Learning models as well as simply buying and holding the stock.

Фото профиля chipko
chipko1 год назад

We'll you just saved me time! is faster to type than

Фото профиля AI Pro Workflow
AI Pro Workflow1 год назад

The future of AI x coding is here. Gemini 2.5 Pro not only writes reinforcement learning algorithms — it runs them, visualizes training, and debugs in real-time. 🧠🕹️ Watching this feels like a glimpse into the next generation of engineering workflows.

Фото профиля Asset investing made simple
Asset investing made simple1 год назад

You have a better product than Open ai. Its time to focus on usage

Фото профиля Munish
Munish1 год назад

Can you guys improve the UI? Most of the time it just renders badly when it comes to changes, syntax, conversation names and also why isn't Rmd and md code blocks doesn't have syntax highlighting.

Фото профиля Apollo
Apollo1 год назад

Nice RL feedback loop. Video did a good job showing how this works

Фото профиля Arpit Sharma
Arpit Sharma1 год назад

The ability to debug errors in real-time is mind-blowing.

Фото профиля Arunachalam B
Arunachalam B1 год назад

Absolutely mind blowing. I think @Google should build an IDE like Cursor.

Фото профиля Mzml Rafiq
Mzml Rafiq1 год назад

code(44).html have you tried 44 times

Фото профиля Ghost of Bear Jew
Ghost of Bear Jew1 год назад

that's pretty incredible but is it repeatable and scalable

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