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A comment on Nvidia Hopper Sweeps AI Inference Benchmarks in MLPerf Debut. Parent comment

Re:Nvidia Hopper Sweeps AI Inference Benchmarks in MLPerf Debut by alchemist1e9 on Thursday September 08, 2022 @10:55PM (#32774770)
As a favor could you list what you think are the most important ML developments recently? It’s hard to keep up and I have a sense from your comment you might have a condensed summary list that might be helpful.
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Re:Nvidia Hopper Sweeps AI Inference Benchmarks in MLPerf Debut by mitchellgoffpc on Thursday September 08, 2022 @11:36PM (#32775026)
Some neat results from the last six months or so:

- Significantly-improved diffusion models (DALL-E 2, Midjourney, Stable Diffusion, etc)

- Diffusion models for video (see https://video-diffusion.github.io/, this paper is from April but I expect to see a lot more published research in this area soon)

- OpenAI Minecraft w/VPT (first model with non-zero success rate at mining diamonds in <20min)

- AlphaCode (from February, reasonably high success rate on solving competitive programming problems)

- Improved realism and scale for NeRFs (see https://dellaert.github.io/NeRF22/ for some cool examples from this year’s CVPR)

- Better sample efficiency for RL models (see https://arxiv.org/abs/2208.07860 for a recent real-world example)

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Re:Nvidia Hopper Sweeps AI Inference Benchmarks in MLPerf Debut by riku_iki on Friday September 09, 2022 @02:37AM (#32776021)
> - AlphaCode (from February, reasonably high success rate on solving competitive programming problems)

reasonably high was 50% on 10 attempts, meaning success rate on first attempt can be as low as 5%, out of which who knows how many were leaked to training data.

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Re:Nvidia Hopper Sweeps AI Inference Benchmarks in MLPerf Debut by IceHegel on Friday September 09, 2022 @12:58AM (#32775474)
This would basically be my list.

I'd add GPT3 & Github Copilot, which my team and I use professionally. It's far from perfect, but it's a great GSD tool especially for stuff like Regex, bash scripts, and weird APIs.

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