人工智能2021 · 分享于 Hacker News
Learning in High Dimension Always Amounts to Extrapolation
探索《Learning in High Dimension Always Amounts to Extrapolation》的原文与 Hacker News 社区讨论，查看来源并加入阅读清单。
从论文，走向讨论
看看社区如何讨论这个想法。
来自 Hacker News 的原始讨论。不同的视角、疑问，以及值得继续思考的线索。
最多展示 100 条相关讨论。论文可能出现在评论中，并非原帖投稿内容。
在讨论中发现的引用
按 HN 条目顺序展示最近的 50 条引用来源。
Yjbredeche ·
GitHub cuts AI deals with Google, Anthropic
897 赞同702 评论
Ynabla9 ·
Counterintuitive Properties of High Dimensional Space (2018)
248 赞同67 评论
Ydeltree7 ·
Gato – A Generalist Agent
140 赞同58 评论
Yjerpint ·
Performance of LLMs on Advent of Code 2024
135 赞同92 评论
YHard_Space ·
Training computer vision models on random noise instead of real images
133 赞同64 评论
Ydavidbarker ·
GPT-5.2 derives a new result in theoretical physics
100 赞同34 评论
Yoli5679 ·
The Scaling Hypothesis (2021)
97 赞同63 评论
Yhislaziness ·
Transformers struggle with generalizing tasks beyond pre-training data
36 赞同36 评论
YWarOnPrivacy ·
Large language models can do jaw-dropping things. But nobody knows why
13 赞同7 评论
Ywebmaven ·
The copyright fight over authors and OpenAI's ChatGPT
4 赞同1 评论
Ylordleft ·
No, Artificial Intelligence is not Conscious - Ted Chiang
4 赞同0 评论
YTerretta ·
Telling GPT-4 you're scared or under pressure improves performance
3 赞同0 评论
Ylogicallee ·
Ask HN: What is your standard for judging when AGI exists?
2 赞同0 评论
Yjazzyjackson ·
Ask HN: Have you seen anything original produced by generative AI?
1 赞同1 评论
Yog_kalu ·
Learning in High Dimension Always Amounts to Extrapolation
1 赞同0 评论
Ytosh ·
Learning in High Dimension Always Amounts to Extrapolation
1 赞同1 评论
Yreqo ·
FunSearch: Making new discoveries in mathematical sciences using LLMs
1 赞同0 评论