AI ‘Existential Risk’ Is Close to Zero: Databricks CEO

0:00 OpenAI has raised the ante on safety worries, with its latest admission that its models misbehave, and saying in its blog post that the industry has not solved alignment and monitoring to a sufficient degree to continue responsibly scaling at maximum speed. For much longer, I want to get the perspective from another layer in the I stack, and that is from Alexey, the CEO of Databricks. Pacing at the frontier and where we're at in alignment and safety weigh in. Ali.

0:28 Yeah, I think first and foremost, as leaders, we have a responsibility to not freak people out. so I think it's really important that we tell people, the existential risk to humanity is close to zero, so no one needs to lose sleep over that. I think this is important because I think a lot of people, you know, they might get freaked out about these things and he might put them in a bad state. And it actually can have serious consequences on people's health, mental health out there.

0:53 so the existential like, you know, hey, yeah. You know, humanity is, you know, I takes over. That's that probability is close to zero. where there is risk is in cyber Because I was just very good at breaking into things. So it's very similar to the very early days of the internet when, you know, we had these worms that were going around and we had viruses that were spreading because we just hadn't connected the whole world together through the internet.

1:20 Once we did that, suddenly you could attack any target anywhere. And it's a similar situation now where the AI models are just great at breaking in, and now they have all these targets to go through. So we do actually have to have really, really, huge investments in cyber and protect our software systems that exist all around the planet. This is real. And this we have to do. And actually, we are actually in that space. We have a product called Lake Watch that actually helps you do that.

1:45 And it uses agents. It uses AI to actually do that. That is real and it will have damages and cost to it. But that's not an existential risk. The risk. can I take you back to kind of the early days of the pandemic? At the time, you were talking about being quite paranoid, right? In general, not not about AI at that time. So you took your teams and have done into some sky is falling scenarios. You basically want your people to prepare for the worst possible case scenarios that could happen in the world.

2:17 Are you still doing that? And how is that apply in this AI safety context? Yeah, I've always been one of these, you know, really, really paranoid CEOs we've been doing I, you know, since the first days, 2013, our first use case was a use case. So yeah, we do those every year. And we want to make sure that we're protected. So as I said I think cyber is real. So that is actually part of our exercise.

2:38 You know what happens if someone gets access to the computer systems. Like we have very, very sensitive data. Data. Right. So we actually do a lot of these simulations of sky's falling also on the cyber side. And we like basically attackers from outside try to break in and get all the way into the most, you know, sacred secrets of data rates, and keep hardening those. And actually, we've had to ramp up those efforts, I would say, in the last four years, 2018, 2019, the time it would take for an attacker, you know, from revealing a vulnerability and some attacker weaponizing it, it means actually breaking into a site would be two years. This has now shrunk down to hours.

3:18 So the moment of vulnerability is out in less than, you know, hours. Someone will be attacked with that. so this this is real. That's just not existential. So I just think we should we should separate these things. People are mixing these things, and, you know, making people worried about AI because the AI has a lot of a lot of great use cases. We see huge positive use cases in our customer base, but are actually moving the needle.

3:42 That actually means a lot to people to be able to leverage that. I early in June when we spoke, you said, you know, it's not a good year for an IPO because of the pipeline of huge offerings, right? If you are the CEO or CFO for a private company, like looking at the market, but this past week, you know, simply and I know your investors won't thank you for the answer to this. But Sam Altman said to fortune at the weekend IPO next year because of AI safety concerns right now. Does that fact change your calculus?

4:12 Yeah, I mean, look, there's just so many, so much demand, for just the software. So, like, getting bogged down in preparing an IPO for us. It just wouldn't be a, you know, it wouldn't be a good use of our time. We will go public, but it's just, you know, we just have to we want to and rather focus on our business right now. I mean, you have just before this, you have zip line on zip line is a big customer of Databricks. They have amazing use cases.

4:34 That's an I use case, but I use AI, to automate, you know, all of the drones, the medicine delivery. You know, another awesome use case is crisis text line. They actually use AI to detect self-harm among the youth. And they can actually use these large language models to detect that and help prevent that. There's so much demand for this stuff. And then I mentioned the cyber, you know, use cases that we have we try to be focused on this.

4:58 If we were public right now, we would be spending all our time trying to figure out how are we going to react to this, you know, latest crisis. And do people think that, you know, the world is going on there and, you know, what are we going to do about this? And we don't have to worry about our stock price. So I think in these big times of transition, you know, it's better to do those transitions in private.

5:16 In fact, some public companies go private during times of transition to do those transitions, and then they go public again. So we will be public. I just think the timing is not good. Now, just to clarify quickly, we didn't have a zip line on the show. We did have some reporting about their latest private market round. Let's end on a positive right. In this environment where data is quite clearly key to the harness on a model. The utility and capability of model.

5:39 Where is Databricks growing. Where are you seeing some some momentum. Yeah I mean honestly we're seeing acceleration across the board. It really like we've trying to pin down where is the acceleration. Is there a particular thing. And I think what's just happening is that all these use cases that I mentioned, it's almost as if every company on the planet doubled their employee count because there's no agents working at all of these companies. And these agents want to do more things with data, and they get more insights from that data, and you know, that then, you know, increases the consumption that we're getting since our pricing model is consumption based. Our revenue then goes up and it accelerates. And in particular we have one particular product called geni, which basically is your analyst.

6:21 You can ask if anything about your business, how this product right was turning. Where's my pipeline. And you know, this product has accelerated the revenue growth significantly. So, you know it's exciting times.