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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 ha
by alchemist1e9 4y ago
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.
- mitchellgoffpc 4y agoSome 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/ 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/ 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 https://arxiv.org/abs/2208.07860 for a recent real-world example)
- IceHegel 4y agoThis 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.
- riku_iki 4y ago> - 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.