a16z的Martin Casado批评Databricks用词不当，Databricks的Ali Ghodsi谈AI风险与采用

a16z's Martin Casado on why the word "pacing" was a misstep, and Databricks' @alighodsi on what the ...

a16z's Martin Casado on why the word "pacing" was a misstep, and Databricks' @alighodsi on what the labs were actually asking for: Martin: "Saying security and safety is important, it is with every tech epoch, and we wanna have some oversight. That was very, very sensible. The problem was just couching this notion of pacing." "There's a number of issues with pacing. First off, it's orthogonal to safety and security. You can slowly build a weapon. That's not different than building a weapon." "It kind of feels like this kind of almost milquetoast capitulation to the pause people. 'You say pause, well, I say pacing.' Which is almost like pause, but it's not like pause." Ali: "They're saying, 'Hey, if we do that, it'll slow us down. And I'm not sure the other side is doing that. So can you guys come in and slow us down? Put some guardrails around us. We'll happily then follow the rules and do the secure thing. Otherwise it doesn't make sense 'cause we'll get our butts kicked.'" Martin: "Nuanced second-order words don't work when people are really afraid... I literally think you should have just been like, 'Safety and security is paramount. We're gonna put in these controls.'" "Dario's first five words or whatever are, 'We need to pace the frontier.' It just puts you in a very different mindset. What he could have said is, 'We need to secure the frontier.'" "Pace is like the uncanny valley of making the doomer people unhappy and the policy people unhappy. The doomer people are like, 'That's not a pause, this is pacing.' And everybody else is like, 'This isn't real, you're not gonna do it anyways, and you're not as focused on security.'" @alighodsi @martin_casado @sarahdingwang 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 💬 7 🔄 3 ❤️ 30 👀 9736 📊 7 ⚡