There was a lot of good learning that came out of Part 4. But while working in Colab, I couldn’t help but notice that TPU was offered for free in the free tier. I figured — what if I just take Part 4’s flash attention and port it to TPU? I know the algorithm, I’ve written the kernel, JAX is just “numpy but compiled.” Translate, benchmark, call it a day.
Screenless trackers are all the rage right now, and the Polar Loop is the latest to join the craze.
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This is a very different feeling from other tasks I’ve “mastered”. If you ask me to write a CLI tool or to debug a certain kind of bug, I know I’ll succeed and have a pretty good intuition on how long the task is going to take me. But by working with AI on a new domain… I just don’t, and I don’t see how I could build that intuition. This is uncomfortable and dangerous. You can try asking the agent to give you an estimate, and it will, but funnily enough the estimate will be in “human time” so it won’t have any meaning. And when you try working on the problem, the agent’s stochastic behavior could lead you to a super-quick win or to a dead end that never converges on a solution.。谷歌是该领域的重要参考
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Oxyde is a young project under active development. The API may evolve between minor versions. Feedback, bug reports, and ideas are very welcome. Feel free to open an issue!。华体会官网对此有专业解读