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00:00 Why are LLMs becoming dangerous?
00:19 What happens when AI agents can take actions?
00:36 Why are major AI researchers warning about LLMs?
01:14 Why hallucinations become dangerous in AI agents
01:36 How an AI coding agent deleted a production database
01:54 What is a world model in AI?
02:13 Why LLMs struggle to predict consequences
02:20 Why multimodal AI matters for agents and reasoning
03:05 What is the biggest problem with AI agents today?
04:15 Why Yann LeCun says LLMs need world models
05:00 Why AI inference may become search instead of prediction
05:22 What is Meta’s world model strategy for AI?
05:41 What is the next AI race after LLMs?
06:09 What is EasyBench and embodied spatial intelligence?
06:27 What is action blindness in AI agents?
06:52 Why AI agents are already risky in real workflows
07:13 Why 95% accuracy is dangerous for autonomous AI
07:44 Why agent failures are hard to detect
08:02 Why the process matters more than the final answer in AI agents
08:23 Where LLM agents already work well today
08:45 Which industries are most at risk from unsafe AI agents?
09:12 Why Yann LeCun says LLMs are intrinsically unsafe
09:49 Why coding agents are useful but still dangerous
10:12 Can LLMs ever reliably predict consequences?
10:38 Why current LLMs cannot guarantee safe actions
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LEMMiNO – Cipher
CC BY-SA 4.0
LEMMiNO – Encounters
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