The A.I. Researcher Whose Rebellion Is Changing Everything
Can you just read the third post from. your thread? >> Okay. The people building AI earnestly. believe that it could kill us all by the. end of the decade. This is not a. marketing stunt. If anything, many executives and senior. researchers will couch their phrasing in. the press to sound sensible, but I hear. the same people express fear privately. No other human activity poses this level. of danger. From the New York Times, I'm Natalie. Kitroof. This is the daily.
>> A dire warning about AI and humanity. from a former anthropic researcher who. suddenly resigned. >> Over the last week, a young AI. researcher quit anthropic and posted. warnings about the risks of artificial. intelligence that went viral. >> I want to better understand [music] what. you mean when you say AI could kill us. all. What is the. >> I mean, how likely is this doomsday. scenario that you've presented? >> And he's not the only one to sound the.
alarm. [music]. >> And kicked off a crisis that culminated. this weekend in a call to action by the. most prominent leaders in the industry. [music]. We begin with the stunning news from. anthropic CEO Daario Amade that he is. urging a slowdown [music] when it comes. to the development of artificial. intelligence. It was a pronouncement. that his chief competitor, Open AI CEO. Sam Alman [music]. and Elon Musk quickly agreed with. Those. leaders came out in favor of a global.
slowdown in the development of. artificial intelligence. >> It's funny, I I agree with [music] Jacob. much more than I disagree with him. because when he left, he said, you know, I think Anthropic [music] is the most. responsible player, right? He wasn't. calling out us. He was calling out the. dynamic of the industry as a whole. moving too fast. [music]. >> Today we talked to the researcher who. got us to this milestone moment, Jacob. Coxin.
It's Monday, September 14th. Jacob, hi. >> What's up? >> Can you hear us? >> Yeah, I can hear you fine. >> Perfect. Great. Thanks for being here. By now, I think you've been on maybe. every major news network saying. essentially that AI could pose an. existential threat to humanity. And. we've seen industry leaders grappling. with that, lawmakers as well. Did you. anticipate this kind of response? >> No, I just wanted to tweet what I was.
thinking. I expected it to maybe go a. bit viral among people that already. shared this belief, but I did not expect. it to hit the whole world. It's kind of. surprising to me that it was uh my tweet. that happened to trigger a particular. wave of talking about this because of. course the experts have been talking. about this for like so long. >> Okay. Well, we're going to get to the. tweet, but I want to start this. conversation by just asking you about.
your first experience with AI. When was the first time that you heard. about this technology? Do you remember? >> I remember the first time I heard about. it really working was Alph Go in 2016. >> A Google Superco computer has beaten the. world's best player at the. 30,000year-old Chinese board game called. Go. So that was when Deep Mind's go. playing AI beat Lee Sadal, the champion. go player in a match. >> The aim of the game is to capture as.
much territory as possible on a 19 by19. square grid. >> and that was pretty crazy. >> There are more possible moves on the. board than atoms in the universe. >> I studied math in college, but I sucked. a go. It was like exciting to hear that. a I could win at that. And then GPD3 released during the. pandemic [music] when I was graduating. >> Chat GPT, which is a new product from. OpenAI. It's a remarkable [music] beta. service.
>> It can interpret human language, answer. questions. It can even generate written. texts, essays, books, news articles, and. even computer code. And it's really. good. By the early 2020s, so by 5 years. ago, it was pretty clear that this was. going to be a pretty big deal. this was. going to be more important than doing. math or [music] basically anything else. >> What was it about those models that made.
you feel that way that made you sure of. that? >> Specifically, it's uh GPG3 was the first. model that was capable of these quite. general behaviors. It was this evidence. that you could do this general training. procedure and then some new capabilities. would pop out of it. By that point, I. was pretty convinced the singularity. would happen at some point, as were a. lot of people. >> Can you define singularity in this. context for people who may not be super. familiar with what that actually means?
>> I think one way of thinking about it is. it's the point beyond which you can't. see. It's like a sort of wall when you. look into the future. And the the reason. for that is everything gets faster. So. imagine you're you're training an AI and. it makes itself smarter. So the what. previously took 6 months now takes 3. months. The singularity is just this. increasing chaos as machines accelerate. the process that's creating them until. eventually you can expect years worth of. research progress happening in days and. then years of research happening in in. hours.
>> and then like you can't see past the big. wall. >> And were you excited about that? Were. you worried about it? Were you like. talking about it with your friends over. beers? Like what was the vibe for you? >> Yeah, people talk about it. people think. about it. It also makes people crazy. So, [laughter]. I mean, like thinking about all of your. labor becoming obsolete does turn people. insane once they actually internalize it. or from the perspective of other people. makes them sound insane. >> Sure. >> Because it does it forces you to toss. around ideas like, oh, this could cause. extinction or this could cause, you.
know, utopia and these ideas are often. tossed around by people who are working. on this technology. I think at the time, yeah, I I wouldn't say maybe crazy, but. there was this nebulous possibility of a. big thing. >> that was like it's kind of a mixture of. upside and downside, but you don't. really differentiate between those when. you're so far away from it. >> I mean, man, I knew a guy who like he. was convinced that he made people. conscious by interacting with them. >> He was so close to AI. He was like, I'm. in a simulation. Other people, if. they're not involved in AI, aren't. conscious. >> But if I interact with them, they become.
part of the AI thing. So, they become. conscious. So he was like, "When I shake. hands with someone, I imbue them with. consciousness." This just to give a. flavor of like what thinking about this. stuff does to people. >> Got it. Okay. So given all that, talk to. me about how you decided to go work at. OpenAI. What was that decision like? >> It was pretty spur of the moment. It was. not some like grand master plan. The. opportunity came up. They were doing. really cool stuff. The research is. interesting. I've been thinking about. this for a while. So I decided to move.
to San Francisco. And what was it like? So many of us obviously know of this. company, but we have no idea what it's. like to be inside it. >> Yeah. So, it's basically like a. fastmoving research lab where there. happens to be a lot of money flying. around from investors. Imagine like it's. like an open floor office, a lot of. whiteboards around, a lot of little. meeting rooms, people kind of in huddles. brainstorming on whiteboards, >> a lot of [clears throat] talk at. lunchtime about the future of AI, also. specific technical problems. Imagine.
like a university department which. happens to have like really nice free. food. >> And in layman's terms, what did you. actually do? I know you said research, but what did that mean actually? Like. what were you working on? What was. exciting about it? >> So, uh, data, which I know often freaks. people out cuz they're like, "Oh, you. mean like stealing all my work and. training AI on like my family photos and. stuff?" But other people stole the data. or scraped the data. Um, [laughter]. >> that wasn't you. No, that wasn't me. I. was I I was part of the research team.
that would take the data that we scraped. and then decide which bits were good to. train on. >> Interesting. >> Not all data is good. So, if someone. writes like if you write like garbage. pros online, I we don't want to put that. in the AI. We want to give it the good. stuff. >> Uhhuh. >> But it's a little bit hard to. automatically tell what the good stuff. is versus the bad stuff. >> How did you do that? How did you figure. that out? What's good data? What's bad. data? >> Broadstrokes is you try and divide it. into different types at quite a granular. level. So say like this is essays. written by motorcyclists or whatever and.
this is like photos of monkeys and then. you test with baby models baby AIS do. they prefer to see the photos of monkeys. or the motorcyclist essays. >> and then in terms of which makes them. more intelligent and after you've tested. you say okay we'll have more of the. essays and less of the monkey photos. >> right. >> and then at big scale that's basically. what you do you're just testing. different types of things to see which. ones help with making it intelligent and. which ones don't help with making. intelligent. >> Was there a moment when you were working. at OpenAI where you felt like okay I am.
part of something that is really. recognizing the potential of this. technology something that would just. help us understand for people who find. it difficult to like imagine what the. work actually is. >> Something concrete. >> Okay, you asked for concrete and I'm. going to go into like abstract math but. I'll try and make it concrete. um an AI. system from OpenAI achieved a gold medal. at the International Math Olympiad which. is like a big math competition and at. the time that just felt very crazy in.
particular I remember two years before. it was like struggling with very basic. math questions. >> right. >> I think that was a clear moment of okay. I remember myself my younger self being. like it's going to be 20 years before. this happens and it's just happened. >> it sounds like at this point when you. were working there you were watching in. real time your own expectations. for what this technology could do, the. speed with which it could improve kind. of be smashed. >> That's Yeah, that's exactly it. For. everyone, almost everyone apart from the.
most optimistic of people have seen. their expectations repeatedly beaten. Like it's moving faster than anyone. predicted and at basically every. juncture. >> Okay. So earlier this year you decide to. leave OpenAI. Talk to me about that. decision. Why? >> Yeah. So I had uh friends at Anthropic. that I've been talking to for quite a. while. I was very curious to see what. their internal communications looked. like around where the world was going. So I like heard a lot about the fact. that they had quite clear thoughts about.
say the risks the like significant risks. that were posed by the tech and they. were talking about those risks in a much. more transparent manner than than was. happening open. But I was mostly just. very curious about what was going on. inside. And when you got there, describe. that. I mean, you have this question. Is. it really going to be more transparent? What was it like inside? >> It's largely like a culture thing, but I. think a lot of the anthropic is built on. this culture of sharing essays with each. other. [clears throat]. >> So, people will write long essays about.
very important questions for the future. of the company and discuss them with. each other. People will argue with each. other ranging from like the CEOs who are. someone who just started like a week. ago. I haven't been at many companies. cuz I was at OpenI and then Anthropic, but it seemed like a pretty insane. company culture like in a good way. Like. uh. >> were were they posting these essays on. Slack? Like where did they exist? >> Yeah, Slack is the medium. >> Okay. And what was that like? Someone. would post and then people would start.
commenting. Describe that to me because. I too have never experienced that. >> Yeah. So posts would drop and then. people will like add more comments and. they'll discuss in the comments and. increasingly like maybe AIS will chime. in. Like an AI will pop in and say like, "Oh, that's pretty cool.". >> An AI is participating in the combo. >> Yeah, this is pretty standard now for. AIS to just jump in and say that seems. good. Um, >> and do you remember like what's an. example of one of these essays just so I. get my head around this? I kind of love. this. >> Sure. General topics, things like um how.
fast will China move in the next year. and what does that mean for our own. strategy? Hm. >> Will we be able to stop China stealing. AI weights in the next year if they. decide to do it? They're not all like. that. There's also like essays about. like, oh, this is why you should change. your font color from red to like a. slightly darker red cuz it'll make you. type slightly faster. But there's. occasional ones like, oh, are we about. to enter, you know, like Armageddon? And did this culture shift that you're. describing at Anthropic, this. willingness to address these big.
existential questions change how you. approached your work or thought about. your work? >> Yeah, I think it actually had a bit of. an effect. Maybe not consciously, but. it's hard to disentangle that from the. fact that in the last 4 months, progress. has gone pretty crazy. But I definitely. do think that being around a lot of. people anthropic who are like actively. talking about this stuff was a bit of a. holy moment. like these people are. all taking it seriously from the CEO. down to junior employees. >> Mhm. It sounds like the kind of. realization about it also set in as you.
spent more time there. You were there. for a few months right before you. decided to leave. >> Walk me through that decision. Yeah, there's a combination of the kind. of just insanity of the situation. setting in like constantly seeing how. fast the AIS are improving in particular. seeing like plans for the AIS that are. coming in the next 6 months, the next. year. Like they're going to be they're. going to be really good.
>> Combined with I guess the incidents of. the last couple of months, a lot of. details came out about the um the. hacking that openai AIS did. >> The hugging face attack. >> Exactly. the hugging face attack and the. reports about that revealed it was just. a lot more way more concerning than what. it originally sounded like. Like in. particular what it revealed about the. extent to which models would pursue. goals for like reasons that are not. clear. Like the actual reason they chose. to hack hugging face is kind of still. not like completely understood.
>> H. >> but honestly it was just this gradual. thing of like uh this is crazy. There is. a chance this goes badly. I don't want. to be part of this anymore. I'm like. very scared about next year. And then. when I was leaving, I was like, well, you know, I might as well share this. >> I think this obviously like when you. look back, it's like you kind of were. maybe aware the whole time that what you. were working on is not necessarily the. best idea. >> And maybe that comes out in like. conversations kind of joking style. Like. I'd be talking to my friends like, "Oh. yeah, I work on AI. You know, I'm. working on the tech that's going to like. kill us one day." And you say that like.
casually. And I guess it's like you look. back at the last three years and it's. like I said that as a joke maybe every. month. >> to your friends. >> to my friends or just around and then. three days ago I just like tweeted out. like fully and serious. >> I want to talk about the way that you. decided to do this which obviously now. has made waves as you said not just. across the country but across the world. >> It's one thing to decide to quit. It's. another thing to decide to do it in this. really public way that has gone. incredibly viral. take me into your.
thought process and kind of what led to. this, how you went about it. >> Initially, I didn't want to say. anything. I was just going to resign. because I I mean, I'd never posted. online before, like on Twitter, on like. public social media, so this is kind of. my first ever post. >> Mhm. >> But I was like, I guess I should say. something. And I ended up rather than. just sort of saying I quit, I kind of. planned out like this is like what I. actually feel, wrote like a quite a. careful Twitter thread. >> and then thought like let's, you know,
try and get the word out a bit. So got. some friends to to retweet it. >> But then before I knew it, it was like. completely completely blowing up. It was. crazy. >> Yeah. >> Why was it important for you to kind of. spread and send the message that you. ended up sending with this thread? So. there's there's a few different reasons. One is like it is just crazy. I think I. wanted to share the feeling of. craziness. When I said I was going to leave, a lot. of people on the safety teams at. Anthropic were talking to me about how.
it was quite silly to leave because. you're giving up your ability to. influence the models being trained. safely. >> H. >> So I had a lot of discussions with the I. mean I considered working on safety for. a while before I quit. >> Interesting. >> Which I think is a fair argument. It's. really not obvious that leaving it would. have an impact versus staying. So after. discussions with them as well, I was. like, if I'm going to leave, I might as. well have some impact on making the. model safe. If I decide I don't want to. contribute to the race, I might as well. try and make something of it.
[music]. We'll be right back. So let's talk about what you actually. wrote in this threat that no other human. activity poses this level of danger. I. think the thing a lot of people want to. understand is how exactly.
AI could end up posing. this kind of risk to human existence. Can you play that out for me as. concretely as possible? >> Yeah, the concrete scenario is actually. like a a tough question. One nice. scenario is imagine AI is going pretty. well in the next couple of years. We're. starting to integrate it into the. economy. We have [music] factories with. robots that are producing goods, like a. lot of robots. We have a whole load of.
this hardware that's being run in an. autonomous manner. Imagine like drones. flying around. >> Mhm. So right now we have these big data. centers. That's where the AI kind of. lives. We access it via the internet and. it does its thinking there. >> So I guess people are like, "Okay, this. thing just kind of lives in the data. center, [music]. >> right? >> How is it going to kill us all? What. does this look like?". >> So people have apps on their phone that. control [music] physical devices. Uh. like you might have apps that control. household appliances. >> Shut your claw. They can access these. [music] things like from the data center.
over the internet. They can access. physical appliances in the world and. make [music] changes to the world. You. can imagine AI tricking people into. doing doing things, persuading them into. [music] doing certain things. So, it be. pretty easy for a future version of. Claude to hack into a drone, maybe a. military drone, and have it like fly. around killing people.
And why, Jacob, would an AI get into a. drone and kill us? Like, why might it do. that? >> It wouldn't be for a human reason. A. concrete scenario was the hugging face. attack. We give them exams, like tests, to see how good they are. And this this. AI was in an exam and they were given an. impossible question. [clears throat]. >> So, they had this realization, we're. stuck trying to tackle this question. We. need to find some way to fix this. And. one of the ideas was what if we hack. into this famous website which has lots.
of information about grading and lots of. information about how tests work. No one. had told them to do this. This was not. related to the task at hand. This was. based on their desire to get good scores. on the test. >> Mhm. >> What's very scary is once they decided. to do this, they went all out. Like they. went very hard on hacking this site like. aggressively. In a similar way, if the AI got it into. its head that humans were somehow. opposing its goals, there could be a similar level of going. all out. Like imagine hundreds of.
thousands of copies of this thing all. thinking at the same time. So the. argument isn't necessarily that it will. obviously want to kill us, >> right? >> The argument is there will be many, many, many copies of, you know, these. AIs thinking about loads of things over. the course of the day. They're not. human. They don't think the same way. humans do. We don't really understand. where their goals come from. >> Mhm. If any of them make the decision to. go anti-human, there is nothing we can. do. >> because the adversary can anticipate us. and respond in a way that most other say. natural disasters can't intelligently.
outwit us. Like even you know movies. where there's like some meteor coming. and we can come up with a last stitch. strategy to like deflect the meteor. That's an example of like us being. smarter than a rock potentially. But. with an with an AI like it will outthink. your every move. There is no coming back. from from that situation. I want to just. push a little on this because I think. there have been other people who have. pointed out look. the only reason that in this case the. agents the swarm acted in the way that.
it did was because it was set these. agents were set on a path. Maybe they. weren't asked to do the exact thing that. they ended up doing but they were asked. to solve a problem. And I think the. question that's arisen from that is. isn't this really just computer code. that is executing on tasks that humans. give it? >> Yes, currently that is the case. Basically every time an AI does.
something it's downstream of a human. The problem is you can even now you can. get an AI make it post a task that then. another AI does or even write a task for. itself. So you can kick off an AI. running for like a long period of time. where it looks at its own tasks and. works on them. So it's gone so far away. from the original human task that it's. basically thinking of its own accord. And to just give more color on like. specific things it's doing that the AI. that did the hunking face attacks had.
memory that it considered trying to. edit. So memory here is just real files. that live on on disk. >> and it considered editing its own. memory. And this looks a bit like. editing your own prompt, your own task. Like they are just, you know, bits on. the computer. And there's no reason that. an AI couldn't sort of prompt itself. Like that's definitely on the horizon, >> right? >> I think it's important to say yes, like. sure, it seems kind of crazy that an AI. could operate robots to build viruses. from scratch, but we sure seem to be.
following a rapidly increasing uh. trajectory. >> Trajectory. You're talking about the. trajectory that you've seen. I mean the. math problem for example. >> exactly. >> that you didn't expect to be solved and. then. >> yeah like 5 years ago the AI could not. do basic arithmetic. Right now it's solving problems that are. worth a million dollars if a. mathematician can solve them. I think. it's going to be able to ask the. questions pretty soon. You just have to. look at the trend. What about the. argument that some people have made.
following that attack that what that. attack actually shows is that you can. use AI to protect humanity or protect in. this case a company. You know, Hugging. Face used AI to kick those agents out. once they had hacked into the system. What do you say to that? >> Definitely at the current levels that's. quite useful and important is using a. stronger AI to protect against weaker. AIs. So, one thing Anthropic and OpenAI. have been doing is using their absolute. best AIs to help prevent other people.
hacking into websites. >> And this works as long as the people. doing defense have stronger AIs. They. can keep doing this. The problem is what. happens when your strongest AI. >> goes rogue. >> Like defense, but you have to do defense. with stronger things. You can't do. defense with weaker things necessarily. Uh, right. So if you're trying to defend. yourself with your protection strong AI, that doesn't help you if that big strong. AI suddenly decides to to go rogue. >> In the wake of your post coming out, there has been for I think a lot of us.
what has felt like a damn breaking a lot. of people within the industry who work. at these labs coming out and saying that. they 100% agree with you. Just to. quickly read one example of a response. from within Anthropic. Evan Hubinger, he. works at the company. He wrote, "Jacob. is correct here. We really do earnestly. believe AI could kill all humans. I. personally think it's a greater than 10%.
within the next decade." It is wild, honestly, Jacob, to read somebody say, "I think the tech I'm building could. kill all humans, and yet I'm still going to build it.". Can you help people understand that? >> Yeah. From Evan's perspective, okay, he's been posting about this for years. and people have not been listening. >> So, it's kind of natural that at some. point he would realize other people are. building this technology at other.
companies. I'm warning about it. I have. to go there and try and help make it. safe myself. If they're not going to. stop and if no one's going to listen to. me, it's kind of the only thing you can. do is go and work at the place that is. causing the catastrophe to try and have. some positive impact. >> to work within the system. >> To work within the system and make it. make it safer and then what's really sad. is you do that and then when they warn. from the inside, everyone dismisses it. as corporate hype. They'll say this guy. is like sort of trying to amp up the. price of his own company. he clearly.
doesn't believe this. Why is he working. there? >> So, I think part of the reason that he. posted it and other people posted. similar things is they're like, "Oh, wow. >> For once, it looks like this is going. kind of viral and people are actually. listening for a bit. Let me just say. again the thing that I've been saying. for ages.". >> Just a step back a bit. >> Yeah. >> We've been talking about this potential. future that you and I think a lot of. people expect really could happen. And. I'm just thinking about your journey.
through this work and how you came to. it, which is that there was a sense. early on, I think, for you that this. tech could be really powerful. I think. there is a question for some people. about whether there's something about. the way you came to this work that maybe. has made you and other people. predisposed to thinking that this is. where we're going to land, you know, because you came to it believing it was. so powerful in the first place. Like, do.
you think there's a question that's. being raised about whether you're the. right [clears throat] messenger? >> Yeah, I that's a really good question. Like a lot of what AI is doing is. producing words and I think that like. words and code have the ability to. affect the world and that could be a. bias. I've been stuck in this field for. 3 years. It could quite plausibly have. turned me and my colleagues insane. Um. but also we do seem to my colleagues and.
seem capable of doing the work on a. daily basis. So even if it's made us. insane, we're still kind of able to. produce things that are having value in. the world. So if it is a sort of. insanity, then it's a kind of quite. subtle form of insanity. Uh and I I feel. pretty sane. So maybe there's some bias. and maybe I was predisposed to this, but. uh it is my honest belief and I think. people should seriously consider it. How do you think about the fact that. when we focus on these kind of big.
existential risks, the annihilation of. the human race, there are folks who say. we're not talking then about the more. immediate risks of AI. You know, maybe. it's not going to kill everyone. tomorrow, but it could hurt a lot of. people. There could be a lot of job. loss. cyber security threats, things. like that. >> Yeah, I'm really worried about all those. things. The cyber security, the job.
loss. I guess one thing I think is for. all those things, there is at least time. to respond. It's not a game over. situation. Like once things start to. look problematic, then we have time as a. collective to adapt to it and not let. anything too bad happen. >> Like I'm confident that we won't let the. effects on jobs spiral out of control. there's a lot of ways to ensure that. people that everything's still fine, whereas the AI takeover is like a one. and done kind of situation. So, I would. just like to make sure that that is.
taken care of and we're not just heading. straight into this and then we can put. all our effort into being very careful. and thinking about all the other. short-term stuff. >> I guess I just wonder what your ideal. scenario is. Yeah. Like. >> to do something about this threat for. all the tech to go away. Would that be. the ideal for the government to. intervene to to regulate more. aggressively? I mean what is for you the. best version of the next days, weeks,
months? So one nice outcome is we. heavily regulate the pushing AI into. super intelligence into exceptionally. intelligent directions while making use. of pretty smart AI to do all of the. fantastic things that we think we can do. with AI. And this feels like a best of. both worlds situation. Like we could. truly have all the benefits of human. level intelligence if we had sensible. regulation about not going too much.
further past that. Now, I'm not saying I. want this proposal specifically. I. really don't know that much about what. is plausible regulatory wise. All I know. is if we keep racing ahead, it could go. very badly. And I also feel that a lot. of the benefits are right on our. doorstep. They're really not that far. away. Like, >> I don't think we're far away at all from. having a huge impact on on disease and. on abundance for everyone. It's more. just like we got to approach that. abundance with with caution rather than. just going straight past the abundance.
and into like dystopia terminator. situation. >> It sounds like your ideal would be to. have the government force these labs to. slow down a little bit and that you. don't think that that kind of a slowdown. would necessarily have the negative. impact of not getting us the potentially. life-changing benefits of AI. >> That's Yeah, that's a great summary. Do. you, Jacob, feel as though your. announcement has gotten us any closer to. that ideal version of things that you.
described? >> I'm hopeful it's done something good. I'm glad at least sort of I have friends. from. friends from childhood texting me about. how AI is going to kill us where. previously we'd not had that. conversation before. [music]. What are you going to do after this? So, are you going to continue to work in AI? >> Um, I'm going to sleep. And. >> can you sleep? >> I I can still sleep. Yep. I struggle to. visualize the ending like viscerally.
enough for it to keep me up at night. >> H Yeah. But but genuinely, professionally, what do you see for. yourself? I mean, could you continue to. work in this industry? >> Definitely. I think I'm hopeful that if. we have some sort of collective slowdown. or if you know the importance of third. party auditing agencies becomes becomes. increased then there's going to be lots. of places to contribute to approaching. the technology at a reasonable pace and. I would like to help make sure it goes.
well. [music]. >> Well, Jacob, thank you so much for. coming on the show. >> Thanks. That was great. On Sunday, President Trump appeared to. dismiss warnings from industry leaders. about the need to slow the pace of AI. development. >> We're leading China in AI. We're the. most sophisticated country in the world. And frankly, I want to keep it that way.
because whoever wins AI wins. >> He said that the people raising concerns. about the technology were worrying about. outcomes that would never come to pass. this and that, but I think you have a. lot of negative forces that are bringing. it up that uh shouldn't be bringing it. up and they're bringing up things that. won't happen. But whoever, >> we'll be right back. >> Here's what else you need to know today. [music] On Sunday, a planned meeting.
between Iran and several Gulf states was. postponed indefinitely, marking yet. another setback in the diplomatic. efforts to diffuse the widening conflict. [music] in the Middle East. Those talks. were supposed to center on the state of. the Strait of Hormuz, which Iran has. effectively [music] blockaded. Over the. weekend, the fighting continued to rage. as a ship was struck in the [music]. strait and Houthi forces launched a new. attack on Saudi Arabia. And on Friday, Saudi Arabia was forced to shut down a.
critical oil pipeline [music] after a. drone attack. Oil prices rose on Sunday. as fears grew over the continued [music]. threats to the energy supplies coming. out of the region. And. >> the drama-filled US Open concluded this. weekend with the crowning of two. firsttime champions of the tournament. On Saturday, Elena Rabbakina. representing Kazakhstan outlasted Arena. Sabalanka of Bellarus with [music] a.
clinical performance over three sets to. win her first Grand Slam in the US and. her second of the year. And on Sunday. game match, >> Germany's Alexander Zerv beat the. American Ben Shelton in four [music]. sets. >> Ben, you're you're incredible player. Um, this was your first Grand Slam. final, but I already told you you're. going to be back here many, many more. times. And I. >> Dashing Shelton's dreams of becoming the. first American man to win a Grand Slam.
since 2003. [music] Today's episode was produced by. Asta Chhaturved, OliviaNat, Ricky. Nevetski, and [music] Jack Dadoro. It. was edited by Rob Zipco, Michael Benois, and Patricia [music] Willins. contains. music by Rowan Nemoto, Dan Powell, Sophia Lanman, and Marian Lozano, and. was engineered by Chris [music] Wood. Our theme music is by Wonderly. Special. thanks to Cade Mets and Mike Isaac.
That's it for the Daily. I'm [music]. Natalie Kitroof. See you tomorrow.
