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今天我们不只关心AI有多强,而是要探索一些更深刻的问题。我们会看到,最适合汽车的AI,恰恰不是那个最强的“云端大脑”;我们会拿到一个“测谎仪”,去分辨AI何时在“一本正经地胡说八道”。接着,我们会用一张最残酷的考卷,揭示AI在“知识搬运”和“智慧创造”之间的巨大鸿沟。更进一步,我们将探讨一个令人深思的可能:我们感受到的社会撕裂,竟可能是一种被AI精心设计的产物。最后,我们再看看如何请一位“上帝视角”的教练,训练出能主动探索世界的机器人。
00:00:42 造车启示录:为什么最强的AI,不是最好的AI?
00:06:14 AI的“一本正经胡说八道”,我们终于有办法治它了
00:11:30 AI:一个既能干又“无能”的实习生
00:16:44 撕裂的社会,可能是一种“精心设计”
00:23:10 机器人学习新范式:带个“上帝视角”的教练
本期介绍的几篇论文:
[CL] AutoNeural: Co-Designing Vision-Language Models for NPU Inference
[Nexa AI & Geely Auto]
https://arxiv.org/abs/2512.02924
---
[LG] Detecting AI Hallucinations in Finance: An Information-Theoretic Method Cuts Hallucination Rate by 92%
[The Catholic University of America]
https://arxiv.org/abs/2512.03107
---
[CL] CryptoBench: A Dynamic Benchmark for Expert-Level Evaluation of LLM Agents in Cryptocurrency
[Princeton University]
https://arxiv.org/abs/2512.00417
---
[AI] Polarization by Design: How Elites Could Shape Mass Preferences as AI Reduces Persuasion Costs
[University of Chicago]
https://arxiv.org/abs/2512.04047
---
[RO] Real-World Reinforcement Learning of Active Perception Behaviors
[University of Pennsylvania]
https://arxiv.org/abs/2512.01188
By fly51fly今天我们不只关心AI有多强,而是要探索一些更深刻的问题。我们会看到,最适合汽车的AI,恰恰不是那个最强的“云端大脑”;我们会拿到一个“测谎仪”,去分辨AI何时在“一本正经地胡说八道”。接着,我们会用一张最残酷的考卷,揭示AI在“知识搬运”和“智慧创造”之间的巨大鸿沟。更进一步,我们将探讨一个令人深思的可能:我们感受到的社会撕裂,竟可能是一种被AI精心设计的产物。最后,我们再看看如何请一位“上帝视角”的教练,训练出能主动探索世界的机器人。
00:00:42 造车启示录:为什么最强的AI,不是最好的AI?
00:06:14 AI的“一本正经胡说八道”,我们终于有办法治它了
00:11:30 AI:一个既能干又“无能”的实习生
00:16:44 撕裂的社会,可能是一种“精心设计”
00:23:10 机器人学习新范式:带个“上帝视角”的教练
本期介绍的几篇论文:
[CL] AutoNeural: Co-Designing Vision-Language Models for NPU Inference
[Nexa AI & Geely Auto]
https://arxiv.org/abs/2512.02924
---
[LG] Detecting AI Hallucinations in Finance: An Information-Theoretic Method Cuts Hallucination Rate by 92%
[The Catholic University of America]
https://arxiv.org/abs/2512.03107
---
[CL] CryptoBench: A Dynamic Benchmark for Expert-Level Evaluation of LLM Agents in Cryptocurrency
[Princeton University]
https://arxiv.org/abs/2512.00417
---
[AI] Polarization by Design: How Elites Could Shape Mass Preferences as AI Reduces Persuasion Costs
[University of Chicago]
https://arxiv.org/abs/2512.04047
---
[RO] Real-World Reinforcement Learning of Active Perception Behaviors
[University of Pennsylvania]
https://arxiv.org/abs/2512.01188