Databricks 的 Ali Ghodsi：多数公司无需更先进的 AI 模型，关键在于组织内部知识

Databricks' @alighodsi on why most companies wouldn't even notice if frontier AI models stopped adva...

Databricks' @alighodsi on why most companies wouldn't even notice if frontier AI models stopped advancing: "The models are smart enough, but they just don't have the context that exists inside any organization. They have not been in every meeting. They don't know what's in everybody's heads. They don't know all the processes." "There's always a couple of employees who know everything in every organization. You go tap on their shoulder, and everybody's like, 'Oh my God, what would happen if he or she quits?' [The models] don't have that context." "If you just fused that and gave that context to the AI models... I think there are so many productivity gains you could get for any organization on the planet. For that, we actually don't need smarter models." "We don't need a smarter model that can solve Navier-Stokes or conjectures or do better on Humanity's Last Exam." "If the frontier doesn't advance, it doesn't actually matter, I think, for the vast majority of organizations on the planet. They're just so far behind in the adoption curve of actually automating things and getting value out of this stuff." @alighodsi Your browser does not support the video tag. 🔗 View on Twitter a16z @a16z Databricks' @alighodsi on AI risk and adoption: Ali isn't losing sleep over the existential risk debate. He says a number of conditions would all have to be true simultaneously to enable an actual runaway takeoff scenario, and currently several opposite conditions exist. Each frontier training run requires significantly more resources. Power, GPUs, engineers - and some attempts fail, burning up huge piles of money with them. Until that reverses, he doesn't see the self-improving loop happening. Cyber is what he's watching most closely and where he anticipates real impact. Most orgs are not equipped for the coming change in agentic capabilities. The time between a vulnerability being published and being weaponized has collapsed from years to hours. On adoption, he believes most companies don't need a smarter model. The models are already smart enough. The gap is context they don't absorb - the things an employee who's worked at a company for five years learned by osmosis. If the frontier stopped advancing today, he thinks it wouldn't meaningfully change the value most are extracting from AI anyway. In conversation with a16z's Martin Casado and Sarah Wang: 00:00 Intro 00:48 Why Ali places the AI risk near zero 05:05 The word "pacing" was a mistake 10:50 What 10k agents and $100m can do 12:20 What would change his mind on AI risk 14:20 More GPUs, more ways to fail 18:05 US export controls on PlayStations 20:10 The damage everyone expected by now 24:30 Public vulnerabilities weaponized in hours 30:15 Why labs can't grade each other 37:15 Why most of RSI isn't actually RSI 40:05 Why nobody really needs a smarter model 41:50 The AI use cases nobody argues about 47:30 Google Search solved this 25 years ago 50:55 Nobody has privileged knowledge now 55:10 Same model, new harness, 2x cost 58:15 Open source: 5% of spend, 60% of tokens 1:05:30 90% of new databases are created by agents YouTube: youtu.be/GzEtpAKYRvE @databricks @martin_casado @sarahdingwang Your browser does not support the video tag. 🔗 View on Twitter 🔗 View Quoted Tweet 💬 0 🔄 0 ❤️ 0 👀 1788 ⚡