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OPENAI
ChatGPT dominates consumer AI but the moat is narrowing faster than the numbers suggest
It is not the benchmark scores. It is the hallucination rate on regulated-industry tasks.
40 million downloads in 30 days. Google's open-source bet is working.
Not just a cost story. An architecture story. And an alarm bell.
MCP, Operator, Computer Use: the infrastructure for autonomous AI is finally here.
“AGI is not a distant theoretical concept. We expect to build it within this decade, possibly within years. The scaling laws have not broken down. If anything, inference-time compute has opened a second frontier we are only beginning to explore.”
“What I call powerful AI could arrive as early as 2026-2027. My primary concern is not whether it will happen but whether the safety infrastructure will be ready when it does.”
“We are likely years, not decades, away from systems that match or exceed human performance across most cognitive domains. The convergence of foundation models, world models, and RL is happening faster than anyone predicted.”
“I have revised my timeline. Progress in reasoning, planning, and code generation has been remarkable and faster than I expected. My current estimate is 5-10 years. But I remain deeply concerned about whether we can make it go well.”
“I left Google because I became genuinely alarmed. These systems are approaching capabilities we do not understand and cannot fully control. The timeline question is less important than the alignment question, and alignment research is not keeping pace.”
“AGI as a single threshold is the wrong frame. Systems that genuinely assist humans across open-ended real-world tasks are arriving now. The question I ask is not when but how we govern and distribute these capabilities equitably.”