English(EN) This never gets old (& also shows how hard forecasting AI is even for AI)

Claude fable 和 GPT-6 Astra 等AI模型在预测科学突破方面遇到困难

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-27 13:06

Claude fable 和 GPT-6 Astra 等AI模型在预测复杂科学问题方面遇到困难，例如解决指数时间假设。当不提供外部数据进行提示时，它们对这类突破的预测差异很大，并凸显了准确预测未来AI能力和科学进步的难度。这表明了AI在抽象推理和长期预测方面的当前局限性。 AI

影响当前的AI模型在抽象推理和长期科学预测方面表现出局限性，凸显了预测未来AI能力所面临的挑战。

排序理由该条目是Ethan Mollick的一篇观点文章，讨论了当前AI模型在预测方面的局限性。

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

Signal score: 2 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Commentary; 该条目是Ethan Mollick的一篇观点文章，讨论了当前AI模型在预测方面的局限性。
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: opinion, other; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: Breaking (< 6h); Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准。

Bluesky Jetstream — AI desk TIER_1 English(EN) · emollick.bsky.social · 2026-10-27 13:06

This never gets old (& also shows how hard forecasting AI is even for AI)

This never gets old (& also shows how hard forecasting AI is even for AI) “Hey Claude Fable & GPT-6 Astra, Without looking anything up, when do you think we will solve the Exponential Time Hypothesis?” (I only show part of the answers for space)