1 00:00:08,160 --> 00:00:11,357 Thanks for having me. >> Great to have you, Sam. 2 00:00:11,440 --> 00:00:14,317 >> It's interesting cuz people have been talking about 3 00:00:14,400 --> 00:00:19,517 the potential downsides or serious risks of AI for some time. 4 00:00:19,600 --> 00:00:22,997 And I think a lot of people have been saying, "Why is this the moment where it 5 00:00:23,080 --> 00:00:27,077 sort of escaped the bubble and is now all of a sudden an 6 00:00:27,160 --> 00:00:30,597 international topic of such uh 7 00:00:30,680 --> 00:00:34,477 intensity?" And I think a few things have happened. One, 8 00:00:34,560 --> 00:00:40,277 the models have gotten so good. And people for a long time looked at the models, 9 00:00:40,360 --> 00:00:43,877 maybe they looked at the rate of progress, but I don't think people really felt that 10 00:00:43,960 --> 00:00:47,677 the models were going to come this far this fast. 11 00:00:47,760 --> 00:00:49,997 We will get it right, by the way. I am 12 00:00:50,080 --> 00:00:55,597 very confident in our I think the biggest thing that has changed is 13 00:00:55,680 --> 00:00:59,237 this thing that our industry has been talking about for a while, which is no, 14 00:00:59,320 --> 00:01:02,917 no, this technology, this approach is going to go very far. These models are 15 00:01:03,000 --> 00:01:08,317 in some ways going to become more capable, smarter than people. Um that finally 16 00:01:08,400 --> 00:01:11,877 happened. So, I think that was a big change to why now. When people say, you 17 00:01:11,960 --> 00:01:15,317 know, my probability of doom is X or Y or whatever, 18 00:01:15,400 --> 00:01:18,917 it hits in a different way. Technology to do. Somebody else wants to build like 19 00:01:19,000 --> 00:01:23,237 a hacking bot, okay. Um the world can decide what they think about that, but 20 00:01:23,320 --> 00:01:27,560 uh I think you also see um 21 00:01:28,000 --> 00:01:32,037 a real fear that some of these companies or some companies developing AI could 22 00:01:32,120 --> 00:01:34,837 get too much power and be able to sort 23 00:01:34,920 --> 00:01:37,477 of exert undue influence uh on the 24 00:01:37,560 --> 00:01:39,997 economy, push a worldview out on people. 25 00:01:40,080 --> 00:01:43,197 Uh and I think the world is right to be afraid of this. 26 00:01:43,280 --> 00:01:46,837 So, we have these two big challenges. We have the potential of a loss of control 27 00:01:46,920 --> 00:01:50,997 accident or some other serious thing that could go wrong. Um we have the 28 00:01:51,080 --> 00:01:55,117 potential of way too much power concentration and people fear that those 29 00:01:55,200 --> 00:01:58,837 developing AI could exert their worldview. Um 30 00:01:58,920 --> 00:02:02,477 and there is a sort of narrow path we have to navigate 31 00:02:02,560 --> 00:02:06,917 with pragmatism, with you know, 32 00:02:07,000 --> 00:02:10,877 steadiness, with the ability for the the world to like trust that we will make 33 00:02:10,960 --> 00:02:15,117 dependable decisions, consistent decisions uh through this. 34 00:02:15,200 --> 00:02:17,157 And I think people are saying, well, you 35 00:02:17,240 --> 00:02:18,557 know, this now seems pretty important. 36 00:02:18,640 --> 00:02:22,597 Like let's let's get it right. 37 00:02:22,680 --> 00:02:25,117 I'm not going to get the days of the week exactly right here, but something 38 00:02:25,200 --> 00:02:29,917 on like a Friday or a Saturday. These models have gotten so good so fast that 39 00:02:30,000 --> 00:02:34,037 we need to treat the alignment and monitoring and security with a new level 40 00:02:34,120 --> 00:02:36,797 of rigor. And we have to be willing to 41 00:02:36,880 --> 00:02:38,957 pace our development of capabilities 42 00:02:39,040 --> 00:02:44,597 such that capabilities always uh such that alignment, safety, and 43 00:02:44,680 --> 00:02:48,037 monitoring are always ahead of capabilities. And 44 00:02:48,120 --> 00:02:51,357 the Hugging Face incident triggered a real reset, not just in our own company, 45 00:02:51,440 --> 00:02:53,077 but I think the whole industry. 46 00:02:53,160 --> 00:02:54,917 >> You know, we're in the cyber area today, 47 00:02:55,000 --> 00:02:56,797 but maybe we move into another area. Is 48 00:02:56,880 --> 00:03:01,957 this a fair way to characterization, or am I or is this unfair to characterize 49 00:03:02,040 --> 00:03:04,517 it like this? >> What I really care about is that we have 50 00:03:04,600 --> 00:03:08,837 got a great culture of accident reporting and learning. I think if we 51 00:03:08,920 --> 00:03:12,717 look at what happens with the FAA and the NTSB and how safe airplanes have 52 00:03:12,800 --> 00:03:17,197 gotten, um as I understand it from talking to people who have really studied, 53 00:03:17,280 --> 00:03:20,917 you know, new kinds of technology on the order of magnitude of airplanes, one of 54 00:03:21,000 --> 00:03:24,677 the things that has gone so well there is 55 00:03:24,760 --> 00:03:26,517 is the culture of accident reporting. 56 00:03:26,600 --> 00:03:28,197 You know, accidents are going to happen. 57 00:03:28,280 --> 00:03:29,957 We're going to learn as much as we can 58 00:03:30,040 --> 00:03:35,477 and react from each one. Um and if, you know, there's other kinds 59 00:03:35,560 --> 00:03:39,917 of technology where I don't think it's gone I don't think society's had the same 60 00:03:40,000 --> 00:03:44,077 response, and I don't think we have improved as much. 61 00:03:44,160 --> 00:03:47,237 to pull this thing together and present you with the information to make a 62 00:03:47,320 --> 00:03:48,877 decision or to blame. 63 00:03:48,960 --> 00:03:52,077 I think this is one of the most profound 64 00:03:52,160 --> 00:03:56,357 changes to how we use technology that I've ever seen. 65 00:03:56,440 --> 00:03:59,677 I mean, sci-fi movies, as you mentioned, have been hinting at this or playing 66 00:03:59,760 --> 00:04:02,957 around with this for a long time, but this is one of those moments where it 67 00:04:03,040 --> 00:04:06,237 feels like you're in the movie. Like the sci-fi thing came true. 68 00:04:06,320 --> 00:04:10,517 You're talking to your personal super assistant and you are working 10 times 69 00:04:10,600 --> 00:04:14,357 faster or better or more creative than you could have before. 70 00:04:14,440 --> 00:04:17,997 >> Sam, you're invited back anytime you want to Dreamforce. 71 00:04:18,080 --> 00:04:20,877 >> Thank you very much. Thank you. 72 00:04:20,960 --> 00:04:24,120 >> Please thank Sam Altman.