WEBVTT 00:00:01.210 --> 00:00:06.664 And now our CEO and chair, Mr. Marc Benioff. All right. 00:00:06.747 --> 00:00:10.087 Thank you so much everybody. Great 00:00:10.170 --> 00:00:16.567 to have you here. How are you all doing? Are you excited to be at Dreamforce? How 00:00:16.650 --> 00:00:23.650 did you like the keynote? Please welcome Sam Alman, the CEO of OpenAI. [cheering] 00:00:26.730 --> 00:00:31.099 Welcome. Thanks for having me. Great to have you, Sam. 00:00:31.182 --> 00:00:34.727 This is not your first Dreamforce interview. 00:00:34.810 --> 00:00:41.044 Nice to be back. Great to have you, Sam. It's been quite a week for AI, 00:00:41.128 --> 00:00:43.447 hasn't it? It kind of feels 00:00:43.530 --> 00:00:47.671 like all the weeks are a big week these days, but yeah, especially big one. 00:00:47.754 --> 00:00:54.236 Feels like AI is really owning the moment. Um, yeah, I'll say yeah. Now, 00:00:54.320 --> 00:00:59.287 one of the things I noticed about you, Sam, is 00:00:59.370 --> 00:01:01.830 when we first did our first Dreamforce interview, 00:01:01.914 --> 00:01:04.167 your responses were always a little bit curt, 00:01:04.250 --> 00:01:08.975 sometimes curtailed, sometimes short, maybe one word, 00:01:09.058 --> 00:01:12.967 but I noticed a transformation in you. We've 00:01:13.050 --> 00:01:18.465 been together so many times and you are a lot more willing to open up and be more 00:01:18.548 --> 00:01:23.601 robust in what you have to say. So let's start there and just tell us, you know, 00:01:23.685 --> 00:01:25.527 what's your analysis of what's 00:01:25.610 --> 00:01:29.895 going on in the last few days? I mean, everyone is just kind of wondering what 00:01:29.978 --> 00:01:30.811 is going on. 00:01:31.850 --> 00:01:37.189 It's interesting because people have been talking about the potential downsides uh 00:01:37.272 --> 00:01:38.247 or serious risks 00:01:38.330 --> 00:01:42.410 of AI for some time and I think a lot of people have been saying why is this 00:01:42.493 --> 00:01:43.287 the moment where 00:01:43.370 --> 00:01:49.533 it sort of escaped the bubble and is now all of a sudden an international topic 00:01:49.617 --> 00:01:54.295 of such uh intensity and I think a few things have happened. 00:01:54.378 --> 00:01:57.047 one the models have gotten so good 00:01:57.130 --> 00:02:02.093 and people for a long time looked at the models maybe they looked at the rate 00:02:02.176 --> 00:02:03.207 of progress but I 00:02:03.290 --> 00:02:06.859 don't think people really felt that the models were going to come this far 00:02:06.943 --> 00:02:07.847 this fast and all of 00:02:07.930 --> 00:02:14.465 a sudden we went from what it feels like all of a sudden we went from like models 00:02:14.548 --> 00:02:15.527 when chat GBT 00:02:15.610 --> 00:02:21.521 launched three something years ago um that could barely carry on a conversation 00:02:21.604 --> 00:02:22.887 to models that are 00:02:22.970 --> 00:02:27.549 transforming I mean the way enterprises do work to models that can write incredibly 00:02:27.632 --> 00:02:33.336 complicated uh pieces of software, models that can prove millennium prize problems. 00:02:33.419 --> 00:02:34.647 And so I think the 00:02:34.730 --> 00:02:38.860 biggest thing that has changed is this thing that our industry has been talking 00:02:38.943 --> 00:02:39.767 about for a while 00:02:39.850 --> 00:02:43.625 which is no no this technology this approach is going to go very far. 00:02:43.708 --> 00:02:44.967 These models are in some 00:02:45.050 --> 00:02:49.817 ways going to become more capable smarter than people. Um that finally happened. 00:02:49.901 --> 00:02:50.727 So I think that 00:02:50.810 --> 00:02:55.793 was a big change to why now when people say you know my probability of doom is x 00:02:55.877 --> 00:02:56.807 or y or whatever 00:02:56.890 --> 00:03:03.388 it hits in a different way. Um I think people also feel the speed with which 00:03:03.471 --> 00:03:05.207 things are are moving 00:03:05.290 --> 00:03:09.021 and there have been things like the hugging face accident other accidents 00:03:09.104 --> 00:03:10.327 in the field where people 00:03:10.410 --> 00:03:15.831 can say like all right it doesn't take as much imagination uh as it used to for 00:03:15.915 --> 00:03:19.801 to imagine how this could go wrong. Uh on the other hand, 00:03:19.885 --> 00:03:23.367 you have companies saying things like we will only 00:03:23.450 --> 00:03:26.590 slow down if or we will only be responsible if other companies are 00:03:26.674 --> 00:03:28.007 responsible. And then I think 00:03:28.090 --> 00:03:31.831 the public naturally says like well we'd really like to know that you're going 00:03:31.915 --> 00:03:32.567 to like do this 00:03:32.650 --> 00:03:36.625 safely and be responsible no matter what. There should be no qualifier on that. 00:03:36.708 --> 00:03:37.447 I think you also 00:03:37.530 --> 00:03:44.353 see um a real fear that some of these companies or some companies developing AI 00:03:44.436 --> 00:03:45.927 could get too much 00:03:46.010 --> 00:03:50.950 power and be able to sort of exert undue influence uh on the economy, 00:03:51.033 --> 00:03:53.207 push a worldview out on people. 00:03:53.290 --> 00:03:55.922 Uh and I think the world is right to be afraid of this. 00:03:56.005 --> 00:03:57.847 So we have these two big challenges. We 00:03:57.930 --> 00:04:01.963 have the potential of a loss of control accident or some other serious thing 00:04:02.047 --> 00:04:03.047 that could go wrong. 00:04:03.130 --> 00:04:08.167 um we have the potential of way too much power concentration and people fear that 00:04:08.250 --> 00:04:11.007 those developing AI could exert their worldview. 00:04:11.090 --> 00:04:13.847 Um and there is a sort of narrow path we have to 00:04:13.930 --> 00:04:20.930 navigate with pragmatism with you know steadiness with the ability for the 00:04:21.376 --> 00:04:23.607 the world to like trust 00:04:23.690 --> 00:04:28.832 that we will make dependable decisions consistent decisions uh through this and I 00:04:28.916 --> 00:04:29.607 think people 00:04:29.690 --> 00:04:36.690 are saying well you know this now seems pretty important like let's let's get it 00:04:37.157 --> 00:04:38.567 right um yeah we 00:04:38.650 --> 00:04:43.808 will get it right by the way I am very confident in our company's ability, 00:04:43.892 --> 00:04:45.367 our industry's ability 00:04:45.450 --> 00:04:51.349 to do this safely, to make sure that we keep alignment and safety and monitoring 00:04:51.433 --> 00:04:52.247 way ahead of 00:04:52.330 --> 00:04:56.275 capabilities to slow down or stop if we get to a point where we can't. Um, 00:04:56.358 --> 00:04:57.527 but I'm disappointed by 00:04:57.610 --> 00:05:03.557 how it's been framed. Can you articulate a little bit why where that disappointment 00:05:03.640 --> 00:05:04.730 is coming from? 00:05:05.690 --> 00:05:12.690 Well, I touched on this a little bit, but um the world should trust that we are 00:05:13.063 --> 00:05:14.007 going to do 00:05:14.090 --> 00:05:21.090 the right thing because it's the right thing and because we feel the magnitude 00:05:21.323 --> 00:05:22.167 of this. I 00:05:22.250 --> 00:05:26.288 think it's great for our industry to say we want to come together and we want to be 00:05:26.371 --> 00:05:30.312 able to coordinate and make sure we have enough time to do this safely. 00:05:30.395 --> 00:05:32.167 But when there's any implication 00:05:32.250 --> 00:05:37.123 that because of the commercial pressures and the race some company or between 00:05:37.206 --> 00:05:40.870 countries, some countries might not do the right thing, 00:05:40.954 --> 00:05:44.327 I think that's when people get very scared. Let's 00:05:44.410 --> 00:05:49.704 leave AI for just one second. You know, you and I have had a lot of conversations 00:05:49.787 --> 00:05:53.948 about safety, but you know, starting in the social media industry, you know, 00:05:54.032 --> 00:05:55.367 we've looked at the social 00:05:55.450 --> 00:05:59.620 media industry now for more than a decade and all the various incidents and things 00:05:59.703 --> 00:06:00.087 that have 00:06:00.170 --> 00:06:04.779 happened in social media and it's exhaustive and companies have paid various 00:06:04.862 --> 00:06:05.767 levels of price, 00:06:05.850 --> 00:06:11.402 but also it's well documented that kids have paid a lot of prices with social 00:06:11.486 --> 00:06:12.647 media. Societies, 00:06:12.730 --> 00:06:17.287 countries have paid certain prices. You're an expert in this. you you've educated me 00:06:17.370 --> 00:06:23.927 on these issues. You know, when you look back at what's happened with social media, 00:06:24.010 --> 00:06:25.047 you know, what 00:06:25.130 --> 00:06:30.141 what lessons should we take about this idea that companies should be held 00:06:30.224 --> 00:06:31.607 responsible for their 00:06:31.690 --> 00:06:37.207 actions? Companies should be held responsible for their products. 00:06:37.290 --> 00:06:39.447 Uh the company's executive 00:06:39.530 --> 00:06:44.272 should be held responsible. How how do you look at that as the basis of ethics in 00:06:44.356 --> 00:06:45.189 our industry? 00:06:47.370 --> 00:06:52.225 I I would zoom out even a little more and say the the there's always this question 00:06:52.308 --> 00:06:55.553 of like why are we why are we building this technology? You know, 00:06:55.636 --> 00:06:57.287 the social media people could give 00:06:57.370 --> 00:06:59.875 their own answer to that. I'd certainly have some questions, 00:06:59.959 --> 00:07:01.127 although I think there's some 00:07:01.210 --> 00:07:08.210 good things social media has done too. Um but I I definitely do observe that 00:07:09.603 --> 00:07:11.287 the consequences 00:07:11.370 --> 00:07:18.230 the impact on society of social media has clearly not been a only positive thing. 00:07:18.313 --> 00:07:22.674 Now do I think that social media companies should be blamed for all of the ills 00:07:22.758 --> 00:07:23.847 of society? Certainly 00:07:23.930 --> 00:07:28.329 not. Do I think that social media companies should have made some different 00:07:28.413 --> 00:07:29.047 decisions or 00:07:29.130 --> 00:07:32.507 if I were running them I would have made some different decisions about the impact 00:07:32.590 --> 00:07:32.887 that this 00:07:32.970 --> 00:07:39.970 has on people especially young people. Um absolutely yes. And as we think about AI, 00:07:41.290 --> 00:07:48.290 um well a a reason I feel very positive and like and then I'll come to all the 00:07:48.791 --> 00:07:50.247 the negatives is 00:07:50.330 --> 00:07:55.894 a thing that has really inspired me about AI progress is people don't care that much 00:07:55.978 --> 00:07:56.567 what an AI 00:07:56.650 --> 00:08:00.811 what a machine does. You know machines can go off and like do a bunch of impressive 00:08:00.894 --> 00:08:01.527 work. Machines 00:08:01.610 --> 00:08:04.894 can go off and prove some mathematical theorem. We don't really care. 00:08:04.977 --> 00:08:06.407 We have this wonderful ability. 00:08:06.490 --> 00:08:09.990 We are obsessed with other people. We really care about being useful to other 00:08:10.073 --> 00:08:14.177 people. We care about um serving other people, being creative for other people, 00:08:14.261 --> 00:08:16.487 what other people think of our stuff. And 00:08:16.570 --> 00:08:21.475 and so when I think about the things that I worry about with AI and the mistakes I 00:08:21.558 --> 00:08:22.327 want to avoid, 00:08:22.410 --> 00:08:29.193 um one thing that I view as a real positive is the degree to which people 00:08:29.277 --> 00:08:30.887 care about people. 00:08:30.970 --> 00:08:34.327 people are going to use this tool and this new stuff to do things for other people, 00:08:34.410 --> 00:08:38.820 to build new people for new businesses for other people. Um, 00:08:38.904 --> 00:08:41.367 but I think we're going to stay in 00:08:41.450 --> 00:08:45.485 an extremely human- centric world no matter how good the technology gets. 00:08:45.569 --> 00:08:46.727 Um, and I think one of 00:08:46.810 --> 00:08:53.810 the things I didn't like about social media is I think it pushed us a little bit 00:08:54.436 --> 00:08:55.687 more away. Now 00:08:55.770 --> 00:09:01.847 clearly this technology is moving at a pace that is very fast and I 00:09:01.930 --> 00:09:07.847 think society and people themselves will need to uplift themselves very quickly 00:09:07.930 --> 00:09:14.930 to be able to get all the advantages technology but it seems possible to me. 00:09:15.450 --> 00:09:18.247 Yeah, I think that, you know, you have that unique perspective, 00:09:18.330 --> 00:09:22.644 right? Because not only were you with all those amazing companies at Y Combinator 00:09:22.727 --> 00:09:27.220 and you're also the CEO of Reddit and now you're the CEO of this company and you can 00:09:27.304 --> 00:09:27.607 look at 00:09:27.690 --> 00:09:32.937 those different frames and then kind of say which of these companies did a good 00:09:33.020 --> 00:09:37.860 job, you know, taking AI totally out of the picture in safety and responsibility 00:09:37.943 --> 00:09:39.287 and which ones just did 00:09:39.370 --> 00:09:46.370 not care. You're asking me which of the previous generation of companies did just 00:09:50.660 --> 00:09:56.874 didn't care. Um, well, I think it's not so black and white. 00:09:56.957 --> 00:10:02.007 Like I I happen to like short form video. I happen to 00:10:02.090 --> 00:10:05.907 like the ability to like watch 5 or 10 minutes of short form video before I go 00:10:05.990 --> 00:10:10.141 to bed as a way to like kind of unwind and relax a little bit. 00:10:10.225 --> 00:10:14.407 But I wouldn't let my kids near that stuff. And I don't 00:10:14.490 --> 00:10:20.018 think it's like reasonable to expect kids to be able to resist that dopamine [clears 00:10:20.102 --> 00:10:20.887 throat] thing 00:10:20.970 --> 00:10:25.438 or know that they even should. Uh so I don't think it's like I don't think short 00:10:25.521 --> 00:10:30.087 form video is inherently evil, but I do think it's dangerous. 00:10:30.171 --> 00:10:34.087 And how much of that responsibility is on parents 00:10:34.170 --> 00:10:38.650 versus the companies versus governments? I don't know how to like aortion that. 00:10:40.250 --> 00:10:44.327 Um well let's take a little bit of a pivot and kind of talk about where we are in the 00:10:44.410 --> 00:10:49.857 AI industry. Today we kind of can see AI as you know we as you said we've moved 00:10:49.940 --> 00:10:51.047 from the chat GPT 00:10:51.130 --> 00:10:55.638 moment you know to today where we kind of went through the hugging face attack when 00:10:55.721 --> 00:10:56.247 the hugging 00:10:56.330 --> 00:11:00.838 face attack happened how did you frame it inside the company and when you looked 00:11:00.921 --> 00:11:01.527 at the model 00:11:01.610 --> 00:11:06.316 and what it what it achieved and you know it's probably was definitely a catalyst 00:11:06.400 --> 00:11:06.967 for the you 00:11:07.050 --> 00:11:11.169 know I talked to CLM after you know that happened he was at my house and we were 00:11:11.252 --> 00:11:12.167 you know we're kind 00:11:12.250 --> 00:11:16.691 of having the conversation you know around selling in the company. You know, 00:11:16.775 --> 00:11:20.520 there's no question it was a catalyst for him. So, you know, 00:11:20.603 --> 00:11:23.687 do you think we're going to see more things like 00:11:23.770 --> 00:11:28.611 that happen where the models go out and, you know, kind of attack, you know, 00:11:28.695 --> 00:11:30.167 other stakeholders? Does 00:11:30.250 --> 00:11:34.214 everybody know what happened with hugging face or is it Yeah. Okay. 00:11:34.297 --> 00:11:39.512 Um I think it's okay to reframe re reset [clears throat] it and very briefly. So, 00:11:39.595 --> 00:11:42.727 during uh the evaluation of one of our models, 00:11:42.810 --> 00:11:47.107 this is like an older model. This is not like one of our best models. 00:11:47.190 --> 00:11:48.567 Um the model was trying 00:11:48.650 --> 00:11:53.875 to see how it could do on a certain benchmark to evaluate a capability 00:11:53.958 --> 00:11:55.847 and that was what we asked 00:11:55.930 --> 00:12:00.610 the model to do at least and the model broke out of a sandbox uh that we were 00:12:00.693 --> 00:12:01.847 evaluate that it was 00:12:01.930 --> 00:12:05.386 running in hacked into a hugging face server like moved laterally through 00:12:05.469 --> 00:12:06.647 the hugging face system to 00:12:06.730 --> 00:12:11.387 get the answer and then return it back and you know got like a perfect score on 00:12:11.470 --> 00:12:12.167 the test. Um, 00:12:12.250 --> 00:12:17.176 this obviously a terrifying incident. This was the worst accident we've seen. 00:12:17.259 --> 00:12:23.105 I think it was mostly framed as a security issue, which certainly it was, 00:12:23.189 --> 00:12:26.567 but there's also a real alignment issue. 00:12:26.650 --> 00:12:30.824 And then since then, you know, other companies found similar behavior of 00:12:30.907 --> 00:12:34.980 of their models. Um, but this idea that the models have gotten so powerful, 00:12:35.063 --> 00:12:37.127 they're capable of doing something like 00:12:37.210 --> 00:12:39.732 this. And although we have aligned them in many ways, 00:12:39.816 --> 00:12:41.847 we have not taught them like hey, no matter 00:12:41.930 --> 00:12:45.482 how much we tell you to get the best score on this test you can, 00:12:45.565 --> 00:12:47.527 like don't break out, don't hack in, 00:12:47.610 --> 00:12:53.072 don't steal the answer. Um, that was like a real wakeup call for us about what has 00:12:53.156 --> 00:12:54.087 happened to the 00:12:54.170 --> 00:12:59.533 capability of these models. Um, and you touched on this uh about like coming 00:12:59.617 --> 00:13:00.967 from chatbt to here, 00:13:01.050 --> 00:13:05.723 but to give another framing of how quickly these models have gotten better. Um, 00:13:05.806 --> 00:13:06.807 this really struck 00:13:06.890 --> 00:13:12.785 me recently. Three summers ago, we had a model that could barely do grade school 00:13:12.868 --> 00:13:13.607 math. Like, 00:13:13.690 --> 00:13:16.908 you know, the word problems that you do in second grade, Bobby has three apples, 00:13:16.991 --> 00:13:20.855 blah blah blah. Barely, it could do those. Um, the summer after that, 00:13:20.938 --> 00:13:23.367 we had a model that could perform pretty 00:13:23.450 --> 00:13:27.746 well at AIM, which is like a high school math competition that I'm sure many of you 00:13:27.830 --> 00:13:28.327 some of you 00:13:28.410 --> 00:13:34.087 did. One summer ago, we had a model that could get a gold medal on the IMO, 00:13:34.170 --> 00:13:36.007 like the most prestigious 00:13:36.090 --> 00:13:41.552 math competition uh in the world. And then this summer, 00:13:41.636 --> 00:13:45.687 we had a model that could uh could prove, 00:13:45.770 --> 00:13:49.545 you know, one of the seven biggest unsolved problems in mathematics. 00:13:49.629 --> 00:13:50.567 And and to zoom in 00:13:50.650 --> 00:13:56.256 even a little bit more, um, a framing that someone gave is, you know, 00:13:56.339 --> 00:13:58.647 5.5 was maybe as good as like 00:13:58.730 --> 00:14:04.484 an average math professor. 5.6 was as good as like a maybe top one or two percentile 00:14:04.568 --> 00:14:05.527 math professor. 00:14:05.610 --> 00:14:09.184 Astra was a little bit better than that. And then this internal model past Astra 00:14:09.267 --> 00:14:14.067 is one that can do things that the best mathematicians in the world cannot. 00:14:14.150 --> 00:14:16.967 And that's just like the last four maybe 00:14:17.050 --> 00:14:22.476 six months, I don't know. Um so that that speed and math has been an unusually fast 00:14:22.560 --> 00:14:26.633 takeoff but that certainly is a fast takeoff by anyone's definition. 00:14:26.716 --> 00:14:28.407 Um I think is the backdrop to 00:14:28.490 --> 00:14:32.407 something like hugging face which is these models and this actually ties back 00:14:32.491 --> 00:14:33.447 to where we started. 00:14:33.530 --> 00:14:38.039 These models have gotten so good so fast that we need to treat the alignment 00:14:38.122 --> 00:14:39.127 and monitoring and 00:14:39.210 --> 00:14:44.635 security with a new level of rigor. And we have to be willing to pace our development 00:14:44.718 --> 00:14:49.351 of capabilities such that capabilities always s such that alignment, 00:14:49.434 --> 00:14:52.087 safety and monitoring are always ahead 00:14:52.170 --> 00:14:56.832 of capabilities. And the hugging face incident triggered a real reset not just 00:14:56.915 --> 00:14:57.927 in our own company 00:14:58.010 --> 00:15:04.007 but I think the whole industry. Yeah. You know speaking to Clen he's the CEO 00:15:04.090 --> 00:15:05.207 of hugging face 00:15:05.290 --> 00:15:09.749 um after this had happened. You know, I think one of the conversations is they're 00:15:09.833 --> 00:15:10.647 a small company, 00:15:10.730 --> 00:15:16.382 200 people. Um, not a lot of revenue, $100, $200 million revenue. And, um, 00:15:16.465 --> 00:15:18.087 you know, important to 00:15:18.170 --> 00:15:22.412 the open service industry, no question. I think even you have published our models 00:15:22.495 --> 00:15:27.609 on there. We've published models on there, but I don't think he could he didn't feel 00:15:27.693 --> 00:15:28.567 that he had the 00:15:28.650 --> 00:15:34.627 technical capability to keep himself safe. He just wasn't ready. Obviously, 00:15:34.711 --> 00:15:39.543 you know, Salesforce has 90,000 people. Hopefully, our security team, you know, 00:15:39.626 --> 00:15:41.527 is doing what it's what is necessary 00:15:41.610 --> 00:15:45.539 to keep itself safe in this kind of evolving world. You know, 00:15:45.622 --> 00:15:47.447 h how do you think companies, 00:15:47.530 --> 00:15:51.774 small companies like that should be thinking about their vulnerability 00:15:51.857 --> 00:15:52.887 against, you know, 00:15:52.970 --> 00:15:57.245 um your model, but other models, uh and where we are and how do you think, 00:15:57.329 --> 00:16:01.071 you know, to kind of get back to the responsibility argument, 00:16:01.154 --> 00:16:04.487 what is the frame from the CEO of the model company? 00:16:04.570 --> 00:16:08.194 is not just you but others. What is the right frame, 00:16:08.278 --> 00:16:11.047 the right consciousness to have as these 00:16:11.130 --> 00:16:14.687 things happen? So that that was another update we took from this. 00:16:14.770 --> 00:16:16.087 Um it's just a little bit 00:16:16.170 --> 00:16:20.262 more backstory. I'm not going to get the days of the week exactly right here, 00:16:20.345 --> 00:16:20.967 but something 00:16:21.050 --> 00:16:25.502 on like a Friday or a Saturday. I remember seeing a post from HuggingFace which 00:16:25.586 --> 00:16:30.075 is our system has been hacked and we're very confused by it and we believe it was 00:16:30.159 --> 00:16:36.339 the work of an AI agent. And I was like, "Really? It seems surprising, but okay." 00:16:36.422 --> 00:16:39.047 And I went about my weekend and 00:16:39.130 --> 00:16:44.538 uh and then I saw something like the next day on our internal Slack that was like uh 00:16:44.622 --> 00:16:46.926 you know, there was a little bit of like weird behavior. 00:16:47.009 --> 00:16:48.647 And then maybe by kind of like Sunday night, 00:16:48.730 --> 00:16:52.859 someone had put together the possibility these things were linked. 00:16:52.942 --> 00:16:54.327 And by let's say Monday 00:16:54.410 --> 00:17:00.256 morning um we were pretty sure uh we needed to talk to them to find out 00:17:00.340 --> 00:17:01.927 for sure but we were 00:17:02.010 --> 00:17:05.614 pretty sure and then like by you know Monday at lunchtime I texted Clement. 00:17:05.698 --> 00:17:06.647 I was like uh I would 00:17:06.730 --> 00:17:10.511 love to talk to you. I think I may know [clears throat] something here. 00:17:10.595 --> 00:17:11.927 Um and we got on the phone 00:17:12.010 --> 00:17:17.340 and you know figured he flew out to San Francisco and we put it together. Um, 00:17:17.423 --> 00:17:18.887 but one of the things, 00:17:18.970 --> 00:17:22.801 so so I kind of like was in the fog of war for the first part of that and not later. 00:17:22.884 --> 00:17:29.470 And one of the things they said before we knew it was our our our system was that, 00:17:29.553 --> 00:17:31.527 you know, they had tried 00:17:31.610 --> 00:17:34.527 to talk to one of our competitors to get access to their security model. 00:17:34.610 --> 00:17:35.527 I think they didn't even 00:17:35.610 --> 00:17:40.838 know we had one to offer at that point. And they uh couldn't get it and they it 00:17:40.921 --> 00:17:44.346 was too hard to defend themselves the oldfashioned way just with people. 00:17:44.429 --> 00:17:46.087 So they had to use like uh Chinese open 00:17:46.170 --> 00:17:50.145 source models to defend themselves. And I remember thinking before I knew that we 00:17:50.228 --> 00:17:51.047 were involved like 00:17:51.130 --> 00:17:54.414 oh that seems sub-optimal like you know we should do a better job of making 00:17:54.497 --> 00:17:55.447 our models available to 00:17:55.530 --> 00:18:00.789 help people. And then after I was really like okay we have to change the way we do 00:18:00.873 --> 00:18:05.228 this. We we are proud that we have the best cyber security models in the world. 00:18:05.312 --> 00:18:07.207 We are proud to have the best models 00:18:07.290 --> 00:18:09.754 in the world for businesses and enterprise across the board. 00:18:09.837 --> 00:18:11.367 We really want to make sure people can 00:18:11.450 --> 00:18:14.858 use them all of the time. Yeah. But particularly when they need them in 00:18:14.941 --> 00:18:16.087 a critical situation. And 00:18:16.170 --> 00:18:19.270 so after that, we've really tried to put out uh we call it Daybreak, 00:18:19.353 --> 00:18:20.487 which is our cyber program 00:18:20.570 --> 00:18:25.729 to help companies defend themselves. Um I think that cyber defense is going to have 00:18:25.812 --> 00:18:26.487 to change to 00:18:26.570 --> 00:18:31.287 sort of be a agents are actively defending your systems. You're not even trying to, 00:18:31.370 --> 00:18:35.515 you know, patch every bug. We're trying to get there as fast as we can. 00:18:35.598 --> 00:18:36.647 But more generally, 00:18:36.730 --> 00:18:41.352 we want to be a great dependable partner to enterprises and we don't want to be 00:18:41.435 --> 00:18:42.007 like, we've 00:18:42.090 --> 00:18:45.517 got this great model and we're going to keep it locked up and not let you use it. 00:18:45.600 --> 00:18:46.167 How many people 00:18:46.250 --> 00:18:51.895 in the room here have are with companies with less than a thousand employees? 00:18:51.979 --> 00:18:53.607 Raise your hands. Okay, 00:18:53.690 --> 00:18:57.767 so it's about 20%. What is your message to companies with less than a thousand 00:18:57.850 --> 00:18:58.247 employees 00:18:58.330 --> 00:19:03.673 to for them to defend themsel in this moment where they could suffer that same 00:19:03.756 --> 00:19:04.647 kind of attack 00:19:04.730 --> 00:19:09.438 where they probably don't have the controls that a company like yours or eyes 00:19:09.521 --> 00:19:10.807 have? Uh first of all, 00:19:10.890 --> 00:19:15.515 I think there are probably more advantages to being a smaller number of employee 00:19:15.598 --> 00:19:19.193 company than ever before. Um the speed with which you can move, 00:19:19.276 --> 00:19:21.687 the way that you can adopt new technology, 00:19:21.770 --> 00:19:24.647 uh the way that you can kind of like be ahead of the curve on this stuff. 00:19:24.730 --> 00:19:30.362 We're seeing across the board how quickly small companies are able to move now. 00:19:30.445 --> 00:19:31.447 Um and then you 00:19:31.530 --> 00:19:36.567 know selfishly we would love to sell you daybreak services to help defend against 00:19:36.650 --> 00:19:41.608 attacks and you know I think this idea of a persistent agent defending is great 00:19:41.692 --> 00:19:45.844 but defend against your models or other models any model like any models not ours. 00:19:45.927 --> 00:19:46.807 Our model hopefully 00:19:46.890 --> 00:19:52.635 will not be attacking. Um, but whether you buy from us or a competitor or use an open 00:19:52.719 --> 00:19:57.053 model, the strongest message I have is you have to defend against this impending wave 00:19:57.137 --> 00:19:57.927 of cyber attacks, 00:19:58.010 --> 00:20:02.279 I think we are not that far away from open-source models that can do serious 00:20:02.362 --> 00:20:03.367 damage. Clearly, we 00:20:03.450 --> 00:20:06.115 should not stop open source models from happening. That's important. 00:20:06.198 --> 00:20:09.556 But there is going to be this huge cyber threat that's going to come. So, 00:20:09.639 --> 00:20:12.247 while there is this little period of advantage, um, 00:20:12.330 --> 00:20:16.420 please use something to defend yourselves. 00:20:16.503 --> 00:20:21.687 Cyber and cyber attacks are one potential um you know 00:20:21.770 --> 00:20:26.807 kind of manifestation of these models. Other kinds of attacks could come 00:20:26.890 --> 00:20:28.727 from other kinds of weapons 00:20:28.810 --> 00:20:31.980 that are more sophisticated. You've thought about this a lot. 00:20:32.063 --> 00:20:33.367 It could be biological. It 00:20:33.450 --> 00:20:39.242 could be chemical. Uh it could be the hacking into a kinetic system. 00:20:39.325 --> 00:20:42.007 um where some kind of a military 00:20:42.090 --> 00:20:47.320 maybe that is not as maybe well architected to defend itself as ours 00:20:47.403 --> 00:20:48.727 or smaller country 00:20:48.810 --> 00:20:55.810 could have a rogue kinetic attack. Are these realistic scenarios or is 00:20:58.287 --> 00:21:01.047 this fantasy land? Um 00:21:01.130 --> 00:21:05.440 well, we need to not let them happen. They're all like this is a very powerful 00:21:05.523 --> 00:21:06.567 technology and those 00:21:06.650 --> 00:21:10.204 things are all possible. We need to mitigate those because it'd be very 00:21:10.288 --> 00:21:11.127 reasonable to hear 00:21:11.210 --> 00:21:16.389 someone like Mark say something like that and for some policy maker to say like hm 00:21:16.472 --> 00:21:16.967 remind me 00:21:17.050 --> 00:21:22.594 why we're developing this again like that would be a reasonable takeaway and 00:21:22.677 --> 00:21:23.927 the answer is that 00:21:24.010 --> 00:21:28.839 although this is a technology capable of doing things like that it is possible 00:21:28.922 --> 00:21:29.847 for us to defend 00:21:29.930 --> 00:21:33.752 against those not only as the models and the companies like ours but as society 00:21:33.836 --> 00:21:34.247 as a whole 00:21:34.330 --> 00:21:39.063 we can build resilience against new kinds of bio attacks We can build resilience 00:21:39.146 --> 00:21:40.087 against potential 00:21:40.170 --> 00:21:44.647 kinetic attacks. We can build resilience against all of these cyber mess that's 00:21:44.731 --> 00:21:50.845 going to come. And we have to do that to get the prize of curing the diseases, 00:21:50.928 --> 00:21:54.167 giving people this incredible creative 00:21:54.250 --> 00:21:56.882 ability, this boom in entrepreneurship that I think is coming. 00:21:56.965 --> 00:21:58.327 So I think it's very easy to say, 00:21:58.410 --> 00:22:02.884 well there's all these scary things and it's true there are and they are possible. 00:22:02.967 --> 00:22:06.926 But you know, you and I and people in this room and many others, 00:22:07.009 --> 00:22:09.847 we have the ability and the agency to defend 00:22:09.930 --> 00:22:13.167 against those so that we get to enjoy all of the incredible stuff. 00:22:13.250 --> 00:22:14.727 And people deserve this. Like I 00:22:14.810 --> 00:22:18.962 think people with this technology in their hands can live a much better version 00:22:19.046 --> 00:22:19.767 of their lives, 00:22:19.850 --> 00:22:23.666 be a better version of themselves to say nothing of what the economy can do. 00:22:23.749 --> 00:22:28.619 You and I always have this conversation. Technology itself is never good or bad. 00:22:28.703 --> 00:22:31.130 It's what we do with it that matters. 00:22:31.770 --> 00:22:36.392 Um, now we're looking at this technology. We don't want these things to happen, 00:22:36.475 --> 00:22:41.836 but we kind of also started with this discussion where it actually happened. So, 00:22:41.920 --> 00:22:43.527 you think we're going to 00:22:43.610 --> 00:22:47.325 have more discussions where it actually happened and then we're kind of coming 00:22:47.408 --> 00:22:52.998 back. How many like is that obviously not just you're only one model company, right? 00:22:53.081 --> 00:22:54.807 There's hundreds of model 00:22:54.890 --> 00:22:57.754 companies, thousands of model companies. How many companies are there? 00:22:57.837 --> 00:23:01.520 You like building models, people building models? tens of thousands of people, 00:23:01.603 --> 00:23:03.607 hundreds of thousands of people. I don't 00:23:03.690 --> 00:23:06.246 I don't agree that technology is like neither good nor bad. 00:23:06.329 --> 00:23:07.767 I think the tool framing, the sort 00:23:07.850 --> 00:23:10.409 of like neutral tool, we don't care what people do with it. You know, 00:23:10.493 --> 00:23:13.439 it's not our fault if all these bad things happen. Freedom of expression. 00:23:13.522 --> 00:23:15.687 I think you can justify a lot of stuff that way. Um 00:23:15.770 --> 00:23:20.498 I think the choices that companies building this stuff make do have real 00:23:20.581 --> 00:23:21.367 consequences. 00:23:21.450 --> 00:23:26.637 Now there's clearly a fine line to walk and I also don't think that the right 00:23:26.720 --> 00:23:27.527 answer is for 00:23:27.610 --> 00:23:32.748 us to impose our worldview on the future. But when something like hugging face 00:23:32.831 --> 00:23:36.499 happens, we say that was bad. Like that is not neutral technology. 00:23:36.582 --> 00:23:39.447 That is not what we want our technology to do. Somebody 00:23:39.530 --> 00:23:41.359 else wants to build like a hacking bot. Okay. 00:23:41.442 --> 00:23:43.527 Um the world can decide what they think about that. 00:23:43.610 --> 00:23:47.287 But but I think that is not a case of technology being neither good nor bad. 00:23:47.371 --> 00:23:48.327 That's a case of like 00:23:48.410 --> 00:23:54.663 it's an accident. this. Yeah. And and I think the companies building 00:23:54.747 --> 00:23:56.807 this technology do need 00:23:56.890 --> 00:24:03.890 to have both a lot of responsibility and a lot of support of the ecosystem, 00:24:04.977 --> 00:24:06.727 support of the of 00:24:06.810 --> 00:24:11.237 society and the economy. It cannot be that a small number of companies building these 00:24:11.320 --> 00:24:15.581 models get to make the decisions that the world should get to make. Well, I mean, 00:24:15.665 --> 00:24:19.988 in the context of the hugging face accident, um, where the model, 00:24:20.071 --> 00:24:24.007 this older model got crazy and attacked Hugging Face, 00:24:24.090 --> 00:24:28.433 this little company, you know, is this going to be, you know, 00:24:28.516 --> 00:24:30.247 a continuum of accidents? 00:24:30.330 --> 00:24:34.111 Do you feel like we'll be looking at not I'm not talking about open AI, 00:24:34.195 --> 00:24:35.527 like just put it out there 00:24:35.610 --> 00:24:40.967 just as a context of AI as a technology, as an industry, whether it's open source, 00:24:41.050 --> 00:24:43.060 closed source, proprietary, whatever. You know, 00:24:43.143 --> 00:24:45.287 is there going to be a continuum of accidents that 00:24:45.370 --> 00:24:47.542 we'll start marking the hugging face accident, 00:24:47.625 --> 00:24:49.847 this accident that you probably know other ones 00:24:49.930 --> 00:24:54.657 that I don't know, and you kind of mark them down and go, here we go. And, 00:24:54.740 --> 00:24:56.087 you know, a continuum, 00:24:56.170 --> 00:24:59.789 a spectrum of them across, you know, we're in the cyber area today, 00:24:59.872 --> 00:25:01.447 but maybe we move into another 00:25:01.530 --> 00:25:07.103 area. Is this a fair way to characterization or am I or is this unfair 00:25:07.187 --> 00:25:09.447 to characterize it like this? 00:25:09.530 --> 00:25:13.892 assuming you're right um because I do think that some degree of accidents are 00:25:13.975 --> 00:25:15.047 unavoidable with new 00:25:15.130 --> 00:25:19.399 technology um across the industry and across all of the way society will use 00:25:19.482 --> 00:25:20.487 this. What I really 00:25:20.570 --> 00:25:24.448 care about is that we have got a great culture of accident reporting 00:25:24.532 --> 00:25:25.847 and learning. I think if 00:25:25.930 --> 00:25:30.257 we look at what happens with the FAA and the NTSB and how safe airplanes have 00:25:30.340 --> 00:25:30.887 gotten, um, 00:25:30.970 --> 00:25:34.449 as I understand it from talking to people who have really studied, you know, 00:25:34.532 --> 00:25:35.527 new kinds of technology 00:25:35.610 --> 00:25:41.107 on the order of magnitude of airplanes. One of the things that has gone so well 00:25:41.190 --> 00:25:42.167 there is is the 00:25:42.250 --> 00:25:45.265 culture of accident reporting. You know, accidents are going to happen. 00:25:45.348 --> 00:25:46.487 We're going to learn as much 00:25:46.570 --> 00:25:52.033 as we can and react from each one. Um, and if you know there's other kinds 00:25:52.116 --> 00:25:53.607 of technology where I 00:25:53.690 --> 00:25:58.114 don't think it's gone, I don't think society's had the same response and I 00:25:58.197 --> 00:25:58.967 don't think we 00:25:59.050 --> 00:26:04.570 have improved as much. So yeah, I think probably regrettably accidents with any 00:26:04.653 --> 00:26:05.847 new technology are 00:26:05.930 --> 00:26:12.193 unavoidable and we should have a great culture of transparent reporting about 00:26:12.277 --> 00:26:14.007 them. And do you think 00:26:14.090 --> 00:26:19.341 that that's the right metaphor then? You kind of brought this up now aircraft 00:26:19.424 --> 00:26:20.727 this aircraft we had 00:26:20.810 --> 00:26:25.634 an aircraft disaster this many people die there this happened we've learned from it 00:26:25.718 --> 00:26:31.241 now we've improved the aircraft etc the or the system so that it's going to be safer 00:26:31.324 --> 00:26:32.407 for everyone else 00:26:32.490 --> 00:26:36.036 look I I don't want to equate hugging face to the tragedy of like a big aircraft 00:26:36.119 --> 00:26:36.807 crash and a bunch 00:26:36.890 --> 00:26:42.043 of people dying like that was not that's obviously a much worse thing I I I meant 00:26:42.126 --> 00:26:43.207 like however small 00:26:43.290 --> 00:26:47.527 these accidents are learning learning from them quickly and adapting as they happen, 00:26:47.610 --> 00:26:51.626 I think will serve our industry well and maybe we can avoid, you know, 00:26:51.709 --> 00:26:53.207 ever getting to those those 00:26:53.290 --> 00:26:59.321 kinds of stakes. Okay. So, um it's been it's been an incredible moment 00:26:59.404 --> 00:27:01.767 in technology. We've seen we 00:27:01.850 --> 00:27:06.636 just did this keynote and we're starting to see the models can not only, 00:27:06.719 --> 00:27:10.869 you know, kind of do the, you know, textbased answer and response thing, 00:27:10.952 --> 00:27:13.687 but we even saw it dynamically draw this interface. 00:27:13.770 --> 00:27:17.474 you've made a remarkable, you know, progress with chat GPT. 00:27:17.557 --> 00:27:19.207 It's it's really incredible 00:27:19.290 --> 00:27:24.476 actually what you've done. It's awesome how you can not only chat with it, 00:27:24.559 --> 00:27:25.687 but work with it, 00:27:25.770 --> 00:27:29.967 code with it, and I'm sure you can start to render these interfaces with us. 00:27:30.051 --> 00:27:31.207 I hope very very soon. 00:27:31.290 --> 00:27:34.900 We would love to do something like this with this AI force platform that we've 00:27:34.983 --> 00:27:40.647 built with you. That would be a dream of ours. So, you know, give us a a picture. 00:27:40.730 --> 00:27:43.607 What is the role then of these models 00:27:43.690 --> 00:27:48.201 on the kind of driving the intelligence but also you know providing 00:27:48.284 --> 00:27:50.327 this incredible next generation 00:27:50.410 --> 00:27:54.369 you know interface we're starting to talk about that for the first time we've 00:27:54.452 --> 00:27:55.367 of course seen DOSs 00:27:55.450 --> 00:27:59.523 and character modes and gooies and then we moving to the you know phones and now 00:27:59.607 --> 00:28:00.407 we're moving into 00:28:00.490 --> 00:28:05.255 these dynamic interfaces driven by the models this has been a fantasy that we've 00:28:05.338 --> 00:28:06.407 had for a long time 00:28:06.490 --> 00:28:11.355 because we've seen them in the movies now we just we just demonstrated it really 00:28:11.438 --> 00:28:16.531 working. The fact that you can talk to a computer, can understand what you want, 00:28:16.615 --> 00:28:18.727 it can have good judgment to know 00:28:18.810 --> 00:28:22.663 where inside of a company it can go look and where it's allowed to look and how it 00:28:22.746 --> 00:28:27.516 pulls it together. Um, and then it can render for you a completely new interface. 00:28:27.600 --> 00:28:29.447 It can custom write, you know, 00:28:29.530 --> 00:28:33.488 10,000 lines of code or whatever it takes to pull this thing together and present 00:28:33.571 --> 00:28:34.087 you with the 00:28:34.170 --> 00:28:37.182 information to make a decision or to let you be in this creative loop where you 00:28:37.266 --> 00:28:37.927 kind of keep trying 00:28:38.010 --> 00:28:45.010 things. I think this is one of the most profound changes to how we use technology 00:28:45.240 --> 00:28:48.795 that I've ever seen. I mean, sci-fi movies, as you mentioned, 00:28:48.878 --> 00:28:51.287 have been hinting at this or playing around with 00:28:51.370 --> 00:28:54.802 this for a long time. But this is one of those moments where it feels like you're 00:28:54.886 --> 00:28:55.367 in the movie, 00:28:55.450 --> 00:29:00.086 like the sci-fi thing came true. You're talking to your personal super assistant 00:29:00.169 --> 00:29:01.207 and you are working 00:29:01.290 --> 00:29:04.896 10 times faster or better or more creatively than you could have before. 00:29:04.979 --> 00:29:05.767 I think this will 00:29:05.850 --> 00:29:12.850 transform the way we work, the way we kind of use computers and it feels all of 00:29:13.733 --> 00:29:15.047 a sudden here. 00:29:15.130 --> 00:29:18.487 Will this be the moment for enterprises? Many of these enterprise customers are 00:29:18.570 --> 00:29:22.745 here where enterprise can start to say, "Wow, 00:29:22.829 --> 00:29:26.247 our systems are really changing now." 00:29:26.330 --> 00:29:31.047 I think we saw the be so so I would say so far there have been kind of two major 00:29:31.130 --> 00:29:35.527 eras of AI. I mean a lot of other things too but directionally speaking you had the 00:29:35.610 --> 00:29:42.610 chatbots and then you had the coding/computer use agents of this year 00:29:43.277 --> 00:29:45.527 and I think coding in 00:29:45.610 --> 00:29:50.567 particular and kind of all the other work that one does behind a computer really did 00:29:50.650 --> 00:29:55.758 transform in the enterprise like the way that if you think about what how people 00:29:55.841 --> 00:29:56.407 wrote code 00:29:56.490 --> 00:30:02.247 even one year ago relative to now there's less in common than maybe a year ago in 00:30:02.330 --> 00:30:05.859 decade ago or two decades ago. It's really it's quite remarkable. 00:30:05.943 --> 00:30:07.527 Um so I think that already did 00:30:07.610 --> 00:30:12.079 transform the enterprise. But as we head towards what I think will be this third 00:30:12.163 --> 00:30:13.047 phase of it's not 00:30:13.130 --> 00:30:17.187 just like you ask AI for something like a chatbot or you ask AI to do something like 00:30:17.271 --> 00:30:17.927 a coding agent, 00:30:18.010 --> 00:30:22.247 but the AI is like running for you all of the time. Understanding your job, 00:30:22.330 --> 00:30:25.804 what you need to be more successful, rendering new code for you, 00:30:25.887 --> 00:30:27.527 proactively watching your Slack 00:30:27.610 --> 00:30:30.359 or your email. Hopefully there's more Slack than email. 00:30:30.442 --> 00:30:32.007 um like looking at all the stuff 00:30:32.090 --> 00:30:39.090 happening inside of a company that I think we are on the precipice of this third 00:30:40.276 --> 00:30:40.807 phase. 00:30:40.890 --> 00:30:45.780 Yeah, that's going to feel very magical for a lot of plain old users who are just 00:30:45.863 --> 00:30:50.210 using this computer for the first time and get this incredible new capability. 00:30:50.293 --> 00:30:51.527 I don't think anybody's 00:30:51.610 --> 00:30:56.270 really seen anything like that. I mean, when I first saw it and really I was 00:30:56.354 --> 00:31:00.912 and even when I was like doing the focus groups for the keynote, right? 00:31:00.995 --> 00:31:03.607 I was sitting next to our COO and he was 00:31:03.690 --> 00:31:08.490 running this dynamic interface on his computer and it looked like he was using, 00:31:08.574 --> 00:31:11.980 you know, mission control and the graphics, everything. I'm like, 00:31:12.063 --> 00:31:14.327 this is incredible. And he had total command 00:31:14.410 --> 00:31:18.054 and control over what was happening, you know, with Salesforce. 00:31:18.138 --> 00:31:20.007 But it looked radically different 00:31:20.090 --> 00:31:26.157 from any other application I'd ever seen because it was rendering itself on the fly 00:31:26.241 --> 00:31:27.047 dynamically, 00:31:27.130 --> 00:31:32.365 intelligently, in a composite fashion, in a fashion that almost seemed like it 00:31:32.448 --> 00:31:33.047 was living 00:31:33.130 --> 00:31:39.568 or alive in a way. I don't think we've ever seen that kind of an interface, 00:31:39.652 --> 00:31:41.047 you know, before. 00:31:41.130 --> 00:31:46.698 Um you think that's going to ex do something radical for is it going to be 00:31:46.781 --> 00:31:47.767 a a Y2K moment 00:31:47.850 --> 00:31:54.850 you know where enterprises will feel okay this is a huge opportunity for much more 00:31:56.922 --> 00:31:58.167 productivity 00:31:58.250 --> 00:32:02.997 I yes and I also think the world has a lot of inertia the way people do their work 00:32:03.080 --> 00:32:07.595 has a lot of inertia so it will this thing will happen where like oh man everything 00:32:07.678 --> 00:32:12.762 is different now and then it'll take some number of years to filter through, 00:32:12.846 --> 00:32:17.345 but I think the capability and the total change in what's possible. Yeah, 00:32:17.429 --> 00:32:19.927 I would say by like by the end of this year, 00:32:20.010 --> 00:32:23.123 there's like a very different way that it'll be possible to work. 00:32:23.206 --> 00:32:28.514 You've now been working on Open AI for more than a decade. Uh it's incredible. 00:32:28.598 --> 00:32:32.887 uh you were on the cover of Time magazine last week, 00:32:32.970 --> 00:32:38.463 you know, with kind of an article that's kind of discusses the next chapter of 00:32:38.546 --> 00:32:39.607 the company with 00:32:39.690 --> 00:32:46.690 um with Greg and how it's being operated and how your hope for it and so forth. 00:32:46.800 --> 00:32:47.527 you know, 00:32:47.610 --> 00:32:53.310 you have now the opportunity to start to think about kind of the legacy of Open AI, 00:32:53.393 --> 00:32:54.007 the impact 00:32:54.090 --> 00:32:59.054 to the technology industry, what it's also doing for business, for our community, 00:32:59.138 --> 00:33:03.693 San Francisco, you're a very important part of San Francisco as well. Now, 00:33:03.776 --> 00:33:05.927 large employer, you know, what what 00:33:06.010 --> 00:33:11.721 are your hopes and aspirations, you know, for the company, not the technology? 00:33:11.804 --> 00:33:13.207 You know, I think in 00:33:13.290 --> 00:33:19.558 the first decade, we set out on this what seemed the time absolutely insane mission 00:33:19.641 --> 00:33:24.670 to try to figure out how to build AGI. Chance of success seemed extremely low. 00:33:24.754 --> 00:33:26.167 Every expert told us we 00:33:26.250 --> 00:33:31.858 weren't going to be able to do it. And we were a great I think probably the greatest 00:33:31.941 --> 00:33:32.807 scientific lab 00:33:32.890 --> 00:33:37.006 um in you know recent memory. and we we figure out how to build this amazing 00:33:37.090 --> 00:33:38.167 technology along with 00:33:38.250 --> 00:33:44.407 many other people in the world doing incredible work that and now we basically 00:33:44.490 --> 00:33:45.847 know how to do it. 00:33:45.930 --> 00:33:49.422 We have only scratched the surface of figuring out how to build great products 00:33:49.506 --> 00:33:53.175 that really make people more capable, more powerful, that are useful to people, 00:33:53.258 --> 00:33:54.727 that transform the economy, that 00:33:54.810 --> 00:33:59.514 transform the enterprise. And I hope the second decade is about how we take 00:33:59.597 --> 00:34:03.253 this amazing thing. You know, this is like we went to go get fire from the gods. 00:34:03.336 --> 00:34:04.727 This is a crazy thing that has just 00:34:04.810 --> 00:34:10.595 happened in the world. And figure out how to give that value to people in a way 00:34:10.679 --> 00:34:15.915 that is most useful to them. figure out how to empower every person on Earth, 00:34:15.999 --> 00:34:18.727 every enterprise on Earth with this flood 00:34:18.810 --> 00:34:25.810 of capability um and help them build whatever they're going to build. 00:34:26.501 --> 00:34:28.647 Are your aspirations 00:34:28.730 --> 00:34:32.886 only about the technology or is there something broader in our community or 00:34:32.969 --> 00:34:37.607 in the culture of business you'd also like to manifest? Um, well, 00:34:37.690 --> 00:34:41.207 that was kind of what I was trying to get at, 00:34:41.290 --> 00:34:45.239 which is I, you know, this can be some technology that does an amazing thing 00:34:45.323 --> 00:34:46.407 and that will be fine. 00:34:46.490 --> 00:34:51.902 It's an amazing scientific achievement or this can be something that really does 00:34:51.985 --> 00:34:53.207 level people up and 00:34:53.290 --> 00:34:59.730 transform what people are capable of. um how how people can spend their time 00:34:59.813 --> 00:35:04.543 and live their lives and choose what they want to what they want to do, 00:35:04.627 --> 00:35:07.207 what they what impact they want to have and 00:35:07.290 --> 00:35:12.241 that. So I think the first decade was about this technological transformation. 00:35:12.325 --> 00:35:12.887 Um and now 00:35:12.970 --> 00:35:19.970 I hope this transforms people and companies and that we are one of the flag 00:35:20.756 --> 00:35:25.232 bears for what this means for people, not what this means for the machine. Again, 00:35:25.316 --> 00:35:26.407 I think maybe our first 00:35:26.490 --> 00:35:29.208 decade was thinking about the machine and figuring out how to do this and now I 00:35:29.292 --> 00:35:32.271 think this has got to be about what it's going to be for people. 00:35:32.354 --> 00:35:35.127 If you look forward in the next five years and you're 00:35:35.210 --> 00:35:39.035 getting a pretty good vision of what's coming in the next 5 years as we look 00:35:39.119 --> 00:35:40.167 at now kind of heading 00:35:40.250 --> 00:35:46.049 towards 2030, what do you think will be the single most exciting thing that will 00:35:46.133 --> 00:35:50.854 happen by 2030 with the technology that's going to be really impact us? 00:35:50.937 --> 00:35:53.927 the last time you were here it was discovering 00:35:54.010 --> 00:36:00.567 new science um maybe curing a disease you know what do you think will really happen 00:36:00.650 --> 00:36:01.127 between 00:36:01.210 --> 00:36:06.334 now and 2030 that you'll say wow this is what I always thought was going to happen 00:36:06.417 --> 00:36:07.287 and it actually 00:36:07.370 --> 00:36:11.707 has happened so those things we talked about last time they've started happening 00:36:11.791 --> 00:36:12.647 there there is no 00:36:12.730 --> 00:36:16.732 doubt there will be more technological wonders between now and 2030 and they will 00:36:16.815 --> 00:36:17.287 be big ones 00:36:17.370 --> 00:36:24.370 like giant ones like some of the biggest ones in human But back to that previous 00:36:24.633 --> 00:36:25.367 question, 00:36:25.450 --> 00:36:30.943 what I hope you invite me back here in 2030 is people are saying like I cannot 00:36:31.026 --> 00:36:32.087 believe how much 00:36:32.170 --> 00:36:36.542 better my own life is. I cannot believe how good the company is I was able 00:36:36.625 --> 00:36:37.927 to start by myself like 00:36:38.010 --> 00:36:43.861 my oneperson company you know I cannot believe like what I am creating for people 00:36:43.944 --> 00:36:47.687 around me. Um, so you know, the science stuff that's on lock at this point. 00:36:47.770 --> 00:36:49.367 That's on autopilot. That's going to 00:36:49.450 --> 00:36:54.407 happen. Um, I hope the humanity side of it really goes very far. Sam, you're invited 00:36:54.490 --> 00:37:01.490 back anytime you want to Dreamforce. Hold on. Thank you. 00:37:05.933 --> 00:37:12.880 Please thank Sam Alman. [applause]