人工智能2023 · 分享于 Hacker News

Evidence of Meaning in Language Models Trained on Programs

探索《Evidence of Meaning in Language Models Trained on Programs》的原文与 Hacker News 社区讨论,查看来源并加入阅读清单。

阅读原文

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。

Ytodsacerdoti ·

Markov chains are funnier than LLMs

525 赞同233 评论
Ydavidbarker ·

Governance of Superintelligence

46 赞同39 评论
Ymarshblocker ·

Just Calm Down About GPT-4 Already

18 赞同5 评论
YGodelNumbering ·

If your agent commits a crime, who is responsible?

3 赞同2 评论
Ypseudolus ·

The bigger-is-better approach to AI is running out of road

2 赞同0 评论
Ypretext ·

LLM Doesn't Write Correct Code. It Writes Plausible Code

2 赞同0 评论
Yog_kalu ·

Evidence of Meaning in Language Models Trained on Programs

1 赞同0 评论
Ybelter ·

Evidence of Meaning in Language Models Trained on Programs

1 赞同1 评论
Yog_kalu ·

Evidence of Meaning in Large Language Models Trained on Programs

1 赞同0 评论

一个想法,引向另一个。

发现更多论文