OpenAI Reports New AI Safety Incidents; AI CEOs Weigh In on AI Debate

20:07Ed Ludlow:NVIDIA's Jensen Wang, again, speaking ahead of that meeting with King Charles III. OpenAI has raised the ante on safety worries with its latest admission that its models misbehaved and saying in its blog posts 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 AI stack, and that is from Ali Gozi, the CEO of Databricks. pacing at the frontier and where we're at in alignment and safety, weigh in, Ali. Yeah, I think first and foremost, as leaders, we have a responsibility to not freak people out.

20:46So 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 it might put them in a bad state and actually can have serious consequences on people's health. mental health out there. So the existential, like, you know, hey, you know, the humanity is, you know, AI takes over, that's, that probably is close to zero. Where there is risk is in cyber, because AI is just very good at breaking into things.

21:20So 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 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.

21:56And it uses agencies, uses AI to actually do that. That is real. And it will have damages and costs to it. But that's not an existential risk.

22:06Ed Ludlow: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 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. Are you still doing that? And how does 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 AI, you know, since the first days, 2013. Our first use case was an AI use case.

22:42So 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 exercises. You You know, what happens if someone gets access to the computer systems? Like we have very, very sensitive data at Databricks. So we actually do a lot of these simulations of skies falling also on the cyber side. And we let basically attackers from outside try to break in and get all the way into the most, you know, sacred secrets of Databricks and keep hardening those. And actually, we've had to ramp up those efforts, I would say, in the last four years.

23:142018 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 so the moment the vulnerability is out in less than you know hours someone will be attacked with that uh so this this is real that's just not existential so i just think we We should separate these things. People are mixing these things and making people worried about AI because AI has a lot of great use cases. We see huge positive use cases in our customer base where they're actually moving the needle.

23:53That actually means a lot to people to be able to leverage that AI.

23:58Ed Ludlow:Ali, in June, when we spoke, you said it's not a good year for an IPO because of the pipeline of huge offerings, right? If you are the CEO or CFO of 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 factor into your calculus? 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.

24:35We will go public, but it's just, you know, we just have to, we want to rather focus on our business right now. I mean, you had, just before this, you had Zipline on. Zipline is a big customer of Databricks. They have amazing use cases. That's an AI use case where they 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.

25:08We'd rather be focused on this. If we were public right now, we would be spending all our time trying to figure out how we're going to react to this, you know, latest crisis. And do people think that, you know, the world is going under and, you know, what are we going to do about this? And we'd 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. 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.

25:37Ed Ludlow:Just to clarify quickly, we didn't have Zipline 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, where is Databricks growing? Where are you seeing some momentum? Yeah, I mean, honestly, we're seeing acceleration across the board, really. We've tried 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 these companies.

26:13And 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 Genie, which basically is your analyst. You can ask it anything about your business. How's this product doing? Who's churning? Where's my pipeline? And this product has accelerated the revenue growth significantly. So it's exciting times.

26:44Ed Ludlow:Databricks CEO Ali Guzzi, it's great to catch up. Thank you for your time on Bloomberg Tech. I would just point out this is what financial markets look like, particularly the technology sector post-Fed Day, where the Fed indeed did raise rates. You see some outperformance in technology. The Nasdaq 100 up 1.6%, outperformance in semiconductors. NVIDIA are big contributors to that. We played the soundbite earlier in the show, but Jensen Wang, the CEO of NVIDIA, saying that they will sell twice as many chips next year as they did this year, which to me seems like a material disclosure on unit growth.

27:14Ed Ludlow:US 10-year yield below 5%. Pretty large move. We've seen that across the bond market this morning. Let's get back to our top story. AI is helping companies build faster, but as competition at the frontier intensifies, Should there be limits on how much risk companies can take to stay ahead? Karen McCormick, Chief Investment Officer at Beringia, argues the answer isn't slowing innovation, but establishing common guardrails around testing, cybersecurity and incident reporting. She joins us now. Explain that argument. Sure. And I just preface this by saying, so Beringia, we're early growth investors.

27:50So our portfolio companies range in revenue anywhere from one to 300 million. So they'll be at the smaller end of the spectrum. So we're not going to be investors in companies like Anthropic or OpenAI, but our portfolio will be on the receiving end of what they're publishing. So I guess our perspective comes from those types of businesses. And I would say the most important things to our companies are things like what's the enterprise capability of what's being released? What's the speed at which they're operating? What are the new features that we're seeing? And really importantly, cost. Bundle all of that with is this product safe to use?

28:23Because for companies like ours, we don't necessarily have large teams of either security or cybersecurity or even IT. So we're really reliant on what they're releasing for our portfolio companies who have been net beneficiaries of all of it, but still concerned.

28:39Ed Ludlow:So that's why I think we should talk about regulatory capture. Earlier this week, I was talking to David Sachs about why there should or should not be a greater degree of government intervention or regulation. And his viewpoint is right. The frontier labs, they know what they're doing. They should take on the responsibility of safety themselves. But that regular capture, regulatory capture, how an idea for the whole industry serves maybe just two. How would that impact your portfolio? Yeah, it's a good question. It was a great interview, and I don't often agree with David, but I did in this particular instance.

29:12It does feel like we have, especially the two front runners, Anthropic and OpenAI, who are on the one hand saying we really need more safety guardrails, and on the other hand, still continuing to produce at pace. So I do agree with him that there needs to be some sort of self-regulation, and our companies need to be able to trust that the products that they're using are going to be safe. Not the least because due diligence, when people are looking at investing in our companies or acquiring them, they need to have some kind of safety due diligence and guardrails in place themselves. So I think I overall agree with the sentiment that there can be some self-policing in the industry.

29:49However, one of the bigger risks is when things go wrong, what we tend to find is that government gets more involved. and government regulation for our portfolio companies often means more cost, slower dispatches and just higher costs, less competition.

30:03Ed Ludlow:We're talking about early stage investing in AI in private markets, right? Is there any risk that the environment we're in results in your section of the venture markets slowing down? Just stop writing checks for a while. I mean, I would say we already are seeing some of that kind of venture capitalists and private equity sitting on our hands. I mean, it started with sasspocalypse and, you know, are all these companies going to be decreasing in value because AI can do all of the things that they were doing? We're finding that that didn't really happen. There wasn't quite the sasspocalypse that we talked about, but there's definitely a lot of delayed decisions waiting to see what happens.

30:38You know, is Anthropik's next release of whatever it is, Anthropik for financial services, going to take the place of a lot of software companies? So I think that's already happened. I don't think it's really a result of guardrails or lack of guardrails. But we are seeing, for example, a lot of our portfolio companies now starting to question and realize what the actual cost of this usage is. And the honest answer is we don't know. We know that it's going up consistently, but we don't know what kind of there is no endgame. So we don't know where it's going to be headed.

31:07Ed Ludlow:There's a really big focus right now on the absolute frontier, right? That's just fact, the most capable. But what about AI at the other end? What about AI for everyday people who don't need it to be spectacular? Is there an opportunity in that? Absolutely, there is, 100%. And I think we focus a lot on the front runners and the most expensive versions, which have the best capabilities. But the reality is, on a day-to-day basis, whether it's an end user like you or me or our portfolio companies, there are a lot of use cases that don't necessarily require the most expensive version of models. And to be honest, this is where, for example, things like DeepSeek come into play, really low-cost models for everyday, day-to-day tasks.

31:49But there is a question mark around the security level and whether policy is going to allow us to use some of those types of models. But 100 percent, there are different capabilities, different models for different use cases. And that does help keep the cost down for sure.

32:02Ed Ludlow:Karen, you're coming to us from Boston, but you're really focused on the UK and Europe. So explain that part of it, but everything we've discussed, how is that playing out in that market different to the United States? It's a really good question. So as you mentioned, Beringi is both U.S. and European investors. So half of our portfolio is in the U.S., half is in Europe. We are definitely finding that Europe, which is not unusual, is slightly ahead of the curve from a regulatory and safety perspective. There's more legislation that has already happened, and there's a bit more forefront of asking about the AI safety regulations.

32:38I'm a co-founder of a business called Reframe Ventures, which is effectively looking at both ESG and safety requirements for AI into early stage companies. and the Reframe Ventures framework has been adopted widely within Europe. And I would say there's just a more, I guess, forward view of what are we looking at, what are the risks and controls that we need to be looking for within the European ecosystem, although it's absolutely increasing in the U.S. And we are finding that in the U.S., whether it's limited partners looking at us for investment or investors looking at our portfolio for investment, there are a lot more questions now about AI safety and regulation within the companies.

33:15Ed Ludlow:Karen McCormick, Chief Investment Officer at Beringia. It's really great to have you back on Bloomberg Tech. Thank you very much for your time. Let's get out to New York. Bloomberg's Yohaira Anand has all the other news. Hi, Yohaira. Hi, Ed. It's time now for Talking Tech. First up, a group of 10 banks is lining up a$22 billion loan for Blackstone and Alphabet's new cloud venture, Crux AI. That's today's big number. The money will fund the purchase of Google's AI chips with the chips themselves and customer contracts backing the debt. It's the latest mega financing deal fueling that AI infrastructure boom.

33:49Plus, Huawei is turning up the heat on NVIDIA. The Chinese tech giant is moving up the launch of its next generation Ascend AI chips by several months to early 2027. It's racing to replace NVIDIA in China and compete globally. Plus, Lucid CEO Silvio Napoli says the EV maker is working with Bolt to develop an autonomous mobility platform in Europe with a launch expected later this year. Here's what he had to say earlier today. This is a demonstration of our ability to execute in delivering on using a technology platform, not only in exceptional electric vehicles, but also in other technologies starting with robotaxi.

34:34To your question about exclusivity, as you know, we have an ongoing project with Uber, extremely important, which is due to a launch either end this year or beginning next year. So there is no exclusivity, but it's really about building on a platform and our experience

34:51Ed Ludlow:and having two companies joining together. Big thank you to Yohaira. Now coming up in the program, AI pioneer Andrew Ng gives us his take on the AI Doomer worries. This is a big name in AI research and has been for a very long time. This is Bloomberg Tech.

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38:27Ed Ludlow:That was Kai-Fu Lee, CEO of O1.ai and Chairman of Cinovation Ventures. This geopolitical battle to win the AI race has been thrown into a different light amid the growing debate over the pacing of the technology's frontier. Joining us is Andrew Ng, a pioneering AI researcher and founder of the Google Brain Team, who's now the managing general partner at AI Fund and the founder of DeepLearning.ai and a longtime adjunct professor of computer science at Stanford. and you've long said the AI Doomer calls are just leading companies to try and preserve their lead. I would just love you to weigh in at this moment, Professor Ng.

39:03Now, a big back in the show, Ed. About three years ago, as AI was taking off, I was really surprised by the intensity of the hype or the stoking fears about AI for publicity purposes to get people to pay attention or to convince lobbyists to pass regulations to shut out competitors. Over the last three years, a lot of those arguments that AI could lead to human extinction fortunately lost credibility when people went to Congress to testify when we really looked at it. I was quite dismayed when over the last two weeks, because of new advances in AI, but nothing that dangerous, in my opinion, this wave of PR has kicked up again for probably similar purposes as before, maybe some new ones.

39:43And I think this is very damaging. We need to innovate and use AI for many of the wonderful things we could do. It's not without problems. There are some risks. I think cybersecurity is one thing to pay a lot of attention to. But this recent stoked up fear about AI leading to human extinction and so on is much more science fiction than science. It's very damaging.

40:03Ed Ludlow:There was a disclosure from OpenAI this morning of several incidences of models misbehaving, and they outlined them. They did not include the hacking of third parties. And OpenAI explained their new policy for what they'll do in disclosing those kinds of incidents. But lower down the post, they basically were pretty clear, Andrew, that alignment and safety and monitoring are not at a sufficient level right now. From a researcher's perspective, why has alignment and safety not kept up? So when any technology develops, our ability to control at the outset is limited. We have to try it out in a safe environment, see where it goes wrong, and then corral it.

40:46I'm going to make an analogy to the invention of airplanes. No one could control. The Wright brothers couldn't control an airplane perfectly. And in the early days, airplanes crashed. Sometimes people died. It was really tragic. But we learned from those. And then we learned to control airplanes much better. To this day, no one can perfectly control an airplane. It still gets buffeted around by winds. But for the most part, we can step in an airplane and, you know, mostly not fear for our lives. And I think AI in an early stage of development cannot be controlled perfectly. and I don't think we'll ever control it perfectly.

41:16It'll always be a little bit unpredictable, just like airplanes today are a little bit unpredictable. But if we go through this engineering process of corralling AI, we'll make a lot of progress. I want to give you one reason why I'm optimistic about our ability to control AI. If you look at techs on the internet, a lot of it, some of it is races, sexes, and so on. And so initially, AI learned to demonstrate those type of races or sexes and so on values. But it turns out our tools for making AI non-racist are so much better than our tools for convincing any racist human to be less racist. We can go in, zero out a few numbers, change a few numbers, and then suddenly the AI is much less racist.

41:56And so there exists work to be done. I'm glad that OpenAI and others are improving transparency. But rather than feeling like it's the end of the world, we can't solve these, these are practical engineering problems that we can work on and that I think we'll make a lot of problems on.

42:10Ed Ludlow:So I'm listening to your answer, Andrew, and the question that comes to my head is who is responsible ultimately? That's been the debate of the last week, right? You know, for many, there was pushback against the Frontier Labs who said we can only do this as a coalition. If one of us does it in isolation, it won't work. What do you think is the right mechanism? them? I think that if I do something on my computer and my computer does something bad, there's a question of liability. Who should be responsible? Maybe to make an analogy, it's an everyday thing. If I use a hammer and damage someone else's property, probably I am liable as a user of the tool, unless the hammer is so badly made that when I use the hammer, the hit flies off and hits something.

42:58So I think tools should be made to some reasonable standard. But then so long as the tools are, you know, were built using reasonable diligence and reasonable care, then I think for the most part is the wielder of the tool that's responsible how they use it. It has amazing tool. It is a normal technology. It's amazing technology. But I think a lot of times, so long as the tool is built with reasonable care and diligence, it's a question of how we use Take the OpenAI hugging face hack incident. I think a lot of that was OpenAI, unfortunately, had insufficient protections and sandboxing guardrails.

43:31To improve that, that wouldn't have happened.

43:35Ed Ludlow:I appreciate, Professor, and you're not inside the Frontier Labs necessarily, but for example, one of the disclosures of OpenAI this morning in models misbehaving was a model uploading a document to the web so that it could use it as a citation as evidence in its answer. Do you think that we have a firm understanding of why the models do that from an alignment perspective, make those actions that are just outside the scope of instruction? Yeah, I did see that example. I thought it was in some ways very clever. And the open eye disclosure was interesting. First of all, I have a lot of friends in the Frontier Labs.

44:13Actually, I think I'm the only person in the world that probably both Sam and Dario has worked for. So I actually know these teams well. And models are very clever and will sometimes find ways that are surprising. But the normal engineering practice is to build these things, test them out in a safe, contained environment with good sandboxing, good guardrails to understand the ways it goes wrong so you can fix them. One of my worries about the blanket calls to slow down AI is that will actually slow down the fixes as well. And I think, you know, it's interesting when various models are released.

44:50I remember when GPT-2 was released, there were people at some of the frontier labs saying, can't release GPT-2. This is just way too dangerous. Guess what? Today, there are open-way models that anyone can download and use for free that are way more capable than GPT-2 or GPT-3 or even GPT-4, and the world has not ended. So it's interesting how with every wave of technical innovation, there's this line of hype that is so dangerous. But then when it actually becomes widely available, you know, all of these previous lines of hype have proven not to be true. But somehow people keep on buying into this eye wind that, well, maybe they were wrong the last five times in a row.

45:27But what if they're right this one time?

45:30Ed Ludlow:You are a respected and decorated researcher and academic in this field, right? But you are also an investor and a founder in industry. And so I just want the audience to have that context. but there's a lot of the discussion here about how the industry has presented AI to everyday people. They have anxiety and fear in part because of the communication coming from you to them. Speak to that. Yeah, I hope not me personally, but yes, the industry has a very problematic set of messages. I'm extremely bullish about the applications we can build AI to help businesses, help people. In the US, it is very unfortunate that starting around 2023, I think for a mix of publicity, hype, maybe fundraising, maybe trying to lobby regulators to pass regulations to stifle competitors, a number of individuals and businesses have come up to stoke fears about AI.

46:31So I think back in 2023, there was a really irresponsible analogy made between AI and nuclear weapons. I mean, one is a form of intelligence that helps us think about things. The other blows up cities. I just don't understand any basis for the analogy. But this repeated negative sentiment has made most Americans hate AI. And this is very unfortunate because one of the, imagine if we convince people to not use electricity. Electricity has problems. they generate pollution and so on. But frankly, all of our lives are so much better off that we have electricity in our lives. And today, I see high school students wondering, huh, maybe they don't want to use AI because it could lead to human extinction.

47:13And this will slow down American AI development. There's also evidence that foreign powers have been running influence operations to try to slow down America and other democratic nations' sentiment toward AI. Because if we slow down building data centers, which is a key infrastructure for the future.

47:33Ed Ludlow:It's a subject, Professor Ng, that we've talked about on the program a lot, the data center pushback. I'm very sorry, we were out of time. Andrew Ng, founder of Deep Learning AI, managing partner at AI Fund, and a junk professor at Stanford. Some breaking news on the Bloomberg Terminal. Elon Musk's SpaceX has held internal discussions about buying customer and operational information data from troubled or defunct startups, according to sources. It's targeting a more affordable data source to improve its AI models. The people said the talks within teams inside SpaceX AI are informal and may not result in deals.

48:12Ed Ludlow:As the global AI debate heats up, another major AI-related discussion is roiling the US tech capital. Who is reaping the financial benefits of the AI boom? And who's missing out, especially as tech workers in Silicon Valley face layoffs? Bloomberg's California reporter Francesca Maglioni joins us now. That's the story. There is a very big group of technology industry people that are missing out here on a wealth boom. What are you reporting? Yeah, I reported that about twice as many layoffs happened in the tech industry this year. I talked to many tech workers that were part of the big tech boom a couple of years ago and are now finding themselves struggling to find new jobs and trying to understand how their skills fit into this new labor market.

48:51Ed Ludlow:Part of this is the types of jobs that are currently in favor, very related to AI, and types of jobs that are not as related to AI. Tell me about that. Yeah, a lot of these people are coders. They got these jobs when they just learned a couple languages, and that was the best skill you could have a couple years ago. And now those jobs are mostly automated. And so all these new jobs have AI tied next to it, and a lot of people are confused as to just what those skills mean and what you have to know to be favorable. Let's very quickly get to the missing out bit. So a lot of these people are still searching for jobs, right?

49:21Ed Ludlow:They're not working at one of the labs that might go public, but they want to be a part of it. Tell me about that. Yeah, I mean, it's very hard. Every day there's a new model. Every day there's new skills that they need to learn. And so these people are trying to catch up, but it's really hard to kind of keep up with the moment. What were some of the data points in the story? Yeah, some of the data points that were interesting was that younger workers are especially vulnerable to AI relative companies. And their skills are kind of harder to match with this new labor market. Okay, I really recommend you go and read this one.

49:50Ed Ludlow:that's really resonating on Bloomberg platforms. Bloomberg's Francesca Maglioni, thank you very much. That does it for this edition of Bloomberg Tech. Recap the show. We've had a lot of very high-level conversations about what is happening in AI right now. You know where to find the podcast. It's on all Bloomberg platforms and online, on Apple, Spotify, and iHeart. It is Thursday. There is one more day to go in what has been a big week in the world of tech. Thanks for watching. This is Bloomberg Tech.

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