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I’ve been using Sora for a week now (some of my creations), and I think feeds are the correct form factor for learning how to use generative media models at scale.
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TLDR: I trained a Flappy Bird world model to run in your web browser, try out the demo here!
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Last year, the Character.AI team released a blog post that detailed their approach in building a highly efficient inference system that serves over 20,000 inference queries per second, roughly 20% of Google Search's traffic.
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This past week, I came across the DiffusionDB dataset curated by the Polo Club of Data Science at Georgia Tech.
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I was recently re-reading Finbarr Timber’s post on transformer inference optimizations, and I wanted to try to implement each of these techniques1 in nanoGPT to see how much we could practically speed up inference with GPT-2’s architecture and reduce the…
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This post is going to consist of my ongoing review of various sampling methods I’ve found through papers and online implementations.
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Disclaimer: I wrote this article before OpenAI released o1, which now hides its "reasoning" tokens making them inaccessible through the tiktoken library.