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Steven Sinofsky 谈 Jev:用概率化 if 语句取代自然语言低效交互

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Sinofsky 和 Levie 聊了个有意思的判断:让模型输出百分比再写 if 判断,比纯聊天接口靠谱多了,做开发的会很受启发。

a16z 播客中,前微软高管 Steven Sinofsky 与 Box CEO Aaron Levie、Martin Casado 对谈。Sinofsky 指出自然语言从来不是高效接口,他介绍 Jev 的工作方式类似一门定制编程语言:提示词返回一个百分比,再放进 if 语句里做概率化分支判断。他认为这重新连接了 1960-70 年代概率编程的研究脉络。对话还讨论了 AI 监管时机、2028 年大选,以及智能体大规模运行对权限与认证体系带来的安全挑战。

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原文 · a16z

Steven Sinofsky on why Jev fixes his oldest complaint about AI: natural language was never an efficient interface. "Ask yourself how many people are really, really good at asking questions. Less than half the people can ask a good question in a meeting." "And then how often do you look at the answer and get really frustrated before it's finished, but you have to pay all this money to watch the seven paragraphs come out...?" "My favorite is the output of it is designed for probabilistic programming." "Instead of saying, 'Is this a customer service question? Then route to customer service, otherwise route to general help desk,' it's, 'This is 80% customer service.' That's exactly simulation." "There's 50 years of computer science research in literally probabilistic if statements. Suddenly the coolest place to be in computer science is gonna be probabilistic programming, which was all of computer science in the 1960s and '70s." "This is not all new. It's gonna be very interesting to dust off all of that work, because it's exactly what's going on. An if statement now is if X percent, not if always." "The way that Jev works is it's a custom programming language almost, which is: here's the prompt, come back with a percentage. And then you put that in the if statement." @stevesi Your browser does not support the video tag. 🔗 View on Twitter a16z @a16z Box CEO Aaron Levie, Steven Sinofsky, and Martin Casado join Erik Torenberg to discuss "We Must Pace the Frontier," the upcoming AI election in 2028, and Jev: They argue that most of today's AI regulation debate is happening before anyone has defined the risks being regulated. Every prior wave, from computer viruses to aviation, built its safety standards after learning how the technology actually failed. Then it gets concrete. Agents don't get tired, run at enormous scale, and probe systems in ways employees never could, which may mean rethinking permissions, authentication, and the security stack itself. They close on why AI innovation may increasingly happen outside the frontier labs, in the software built around the models. 00:50 "We Must Pace the Frontier" 03:50 Do the labs believe their own x-risk talk? 06:49 If it's existential, nationalize it 11:32 "You're asking us to regulate you?" 12:08 2028 as the AI election 18:50 Tech never learned to navigate regulation 25:50 The law that came from one 1983 hack 28:39 Noam Brown's heat exfiltration idea 32:30 Cold War covert channel stories 34:35 Agent swarms look like a DoS attack 41:25 Sinofsky's fear: GDPR for AI 46:20 No jets if the FAA started in 1910 48:38 Jev: decision engines vs. chatbots 53:01 Labs build beings, software needs tools YouTube: youtu.be/TLJNJDf2XGo @levie @stevesi @martin_casado @eriktorenberg Your browser does not support the video tag. 🔗 View on Twitter 🔗 View Quoted Tweet 💬 3 🔄 3 ❤️ 10 👀 5491 📊 4 ⚡