Podcast appearances and mentions of Sebastian Thrun

The future of war has been evolving before our eyes in Ukraine, yet the west still plans to fight the last war. In this special episode, guest host Noah Smith (@noahpinion) and Brandon Anderson sit down with Yaroslav Azhnyuk (@YaroslavAzhnyuk), a serial tech founder who went from building PetCube to founding The Fourth Law, one of the world's most advanced AI-guided drone companies. Over two hours we cover the technology, tactics, and geopolitics of drone warfare, and why the modern battlefield has already left the West behind:* Yaroslav's personal history and the Ukraine war [00:01:04 – 00:14:01]* The modern drone tech stack: why FPV drones are the new god of war, the future of the rifleman, fiber optic vs. AI, five levels of autonomy, and the eight dimensions of the autonomous battlefield [00:14:01 – 01:05:13]* The geopolitics and economics of drones: China's manufacturing advantage, the drone race, Western defense readiness, countermeasures, and why the gap is widening [01:05:13 – 01:58:57]For those looking for Noah Smith's commentary, it really gets going around the 00:51:31 mark.Yaroslav Azhnyuk / The Fourth Law:* X: https://x.com/YaroslavAzhnyuk* LinkedIn: https://www.linkedin.com/in/yaroslavazhnyuk/* The Fourth Law: https://thefourthlaw.aiNoah Smith:* Substack: Noah Smith * X: https://x.com/noahpinionTimestamps00:00:00 Cold Open: China's 4 Billion Drones and the Cameras-to-Explosives Pipeline00:01:04 Introduction: Brandon, Noah Smith, and Yaroslav Azhnyuk00:05:41 From Tech Entrepreneur to Defense: PetCube, Brave One, and the D3 Fund00:10:42 The Ethics of Building Weapons: Dual-Use Technology and the Wolf at the Door00:14:01 The Tech Stack: Cameras, Autonomy Modules, Interceptors, and a Semiconductor Fab00:18:47 Fiber Optic vs. AI: The Radio Horizon Problem and $32/km Cable00:25:32 FPV Drones: The New God of War — 70–80% of Frontline Casualties00:28:28 The Five Levels of Drone Autonomy: From Terminal Guidance to Full Autonomy00:41:37 The Eight Dimensions of the Autonomous Battlefield00:45:32 AI Safety and the Morality of Autonomous Weapons00:51:31 The End of the Rifleman? Noah's 2013 Prediction vs. Battlefield Reality01:05:13 China's Manufacturing Advantage and Western Vulnerabilities01:24:21 Policy Advice for Western Defense: Defense Valley and the Widening Gap01:32:54 The Drone Race: Who's Ahead, Category by Category01:41:57 Countermeasures: Shotguns, Jammers, Lasers, and Fishnets01:58:19 The Wedding and Final Takeaway: Be Prepared for WarTranscriptCold Open: China, FPV Drones, and the New Warning SignYaroslav [00:00:00]: Think about this. Last year, Ukraine produced 4 million FPV drones. Ukraine is not the most industrious nation in the world. China can produce 4 billion of these FPV drones.Noah [00:00:10]: Would you say that right now China is now the supreme conventional military power on Earth, given its ability to manufacture and deploy drones in the quantity and quality that you just described?Yaroslav [00:00:20]: I don't think we have all the information to claim that but we cannot count it out, and that alone should be a big warning sign. As I say, at some point in my life I went from making cameras that fling treats to pets to cameras that fling explosives to the occupiers. So that's the short story. And when you think about what your nation, what your patriots are going through, you realize that's the only morally right thing to do is to fight back, and it is immoral not to fight back, and then the choice becomes very clear.Introduction: Yaroslav Azhnyuk, Petcube, and the Last Flight into KyivBrandon [00:01:04]: Welcome to Latent Space. I'm Brandon. I normally do science podcasts, but today we're going to do something a little bit different. I'm joined by Noah Smith of Noahpinion on Substack and Twitter. And he has lots of interesting things to say about drones. And as a guest, we have Yaroslav Azhnyuk, founder of The Fourth Law and several other, drone-related startups. To get started, it is February 23rd, 2022. You are running a pet startup. You're connecting pets with their owners. Let's go in just a little bit of background. How did you get started in tech, and what were you working on before the Ukrainian war started?Yaroslav [00:01:50]: Good to be here. Thank you. On February 23rd, late in the evening, 11:00 PM Kyiv time, my wife and I landed in Kyiv. Actually, then she was a fiance. We came from Lviv, where we were looking at a church, where our wedding should have taken place. And we got into this cab ride from the airport to our home, and the driver was like, “You crazy. Like, everyone's leaving Kyiv. Why do you come?” We're like, “What? Nothing's going to happen. Dude, chill.” And then obviously, eight minutes later, or eight hours later, the bombs fell in the city. It was quite surreal. We probably landed on the last flight that landed in Kyiv, or one of those last flights. My background, I'm a tech guy. Studied applied mathematics in Kyiv Polytechnics, born and raised in Kyiv. My parents are old PhDs from academia, and grandparents too. Like, everything, from linguistics to nuclear physics. And I'm an entrepreneur, so I've built a bunch of companies. Petcube is the one you were referencing. So I lived in San Francisco 2014 to 2020, building Petcube, which is one of the leading, pet device companies in the world, selling lots of pet cameras. And then, yeah, as I say, at some point in my life I went from making cameras that fling treats to pets to cameras that fling explosives to the occupiers. So that's the short story.February 24th: Leaving Kyiv as the Invasion BeginsNoah [00:03:28]: February 24th, I guess a few hours after you, go to check out your wedding chapel, what do you do?Yaroslav [00:03:37]: We had a plan for this situation. So my parents and family live in Kyiv, and we're like, “Okay, this has actually started. The worst has, come true.” And so we basically packed our belongings and got in the car and spent 17 hours driving west. And that was pretty sure most people in our audience watched at least one apocalyptic movie in their life, so that was exactly like that. Like, felt exactly like that. Missiles are falling. Like, there was smoke in Kyiv. Like, my dad and I went, like, to central part of the cities. It's probably, likeYaroslav [00:04:20]: 800 meters from presidential office, to pick some stuff up at his workplace. Because he's, like, the head of an academic institution, so he had to get some of the things with him. And super surreal. Like, the streets are empty. Like, the gas stations are out of gas. Like, we found some gas station. We didn't have, like, spare canisters with us, so we're like, We figured out, like, the car was diesel, so like, we figured out, if it's diesel, you can actually store it in plastic, canisters, and we bought some window wash for the cars. We poured it out of the canisters, and we poured the diesel into that. Yeah, so it was like that. And then, like, helping friends get out, like my friend and his dog. Like, we found Like, my brother was also, like, riding in a separate car. We found a place for my friend who didn't have a car. It was like, yeah, it was like, totally surreal. And we didn't know of course, and you didn't know this will last for so long. You didn't know whether Ukraine will be able to defend Kyiv. And it was like, yeah, very little information and very little insight into future.From Pet Cameras to Defense Tech: Building for Ukraine and the Free WorldNoah [00:05:42]: What are your thoughts with regards to how do you, defend, Ukraine? So you eventually start building drones Like, what is the process to get from there from where you were building, devices that connect owners with pets to building drones, and what other things did you do to help the war effort in the process?Yaroslav [00:06:07]: It's definitely non-trivial, right? Like, I didn't go, to I didn't get any, like, military education when I was a student. Like, normally, in Ukraine, you would, you would go to like, this military school even if you're getting higher education in any other, sphere. I decided to skip that which is like, an unusual way to go. And I never thought that I will be somehow engaged in a war effort. Like, what is war? Of course, wars are over. It's the end of history. So one thing you got to understand about, like, many Ukrainians and like, I guess, it's also true about most of the people I met here in the US, that your who you are in terms of your nationality is a big part of your identity. So when that gets under attack, it's something deeper than just the country you live in gets under attack, right? And I Day one, I figured I'm going to I'm going to fight back with everything I can, right? But I didn't think on day one that I'm actually going to do, weapons. And a bunch of things. We were reaching out to a number of American, congresspeople and senators, and basically advocating for support of Ukraine, for voting for lend lease, which has happened in May 2022, but didn't actually work as expected. We helped start, Brave One, which is now a very important defense innovation cluster, sort of like a DIU here in the US. We helped start, a fund called D3. It's like, it was started or co-started by Eric Schmidt, former CEO of Google. So a bunch of these odd things, but then eventually I was like, “Okay,”by 2023 it was obvious this thing, A is going to last a lot more time, and B, that the whole world is shifting and that there's going to be a new arms race, that the warfare is redefined by drones as platforms. And for the first time in history, you have a platform that is software defined, that can increase your battlefield capabilities, in a in a step change just overnight. So it's like if you were able to push a software update and get all of your Roman legionnaires a new helmet? That has never been possible before. It's the first time in the history of war this is possible. So all of that and many other things like, supply chain fragilization, and the impact that AI is going to have on all of this all these things have become evident to me in 2023, and it's like, “Okay, I should do what I do best, or what I know how to do best, start a tech company, and sort of leverage the global techno capitalist machine, to provide, defensibility to Ukraine and the free world.” So that's literally the mission of the company, increase defensibility of Ukraine and the free world. And then there was some sort of soul-searching and like, asking yourself. It's like, “Okay, am I Actually, I know nothing about weapons. Am I actually, like, ready to make, things that other people use to kill other bad people?”Yaroslav [00:09:36]: When you think about what your nation, what your Compatriots are going through And think about all the terror of places like Bucha, the occupied cities in the east and south, the abducted children, the raped women, all the economic damage that's being done, and the intention to destroy a whole nation, to genocide the people of Ukraine, you realize that's the only morally right thing to do is to fight back, and it is immoral not to fight back. And then the choice becomes very clear. And look, we're just passing the ammunition. We're not doing the actual job. The actual fighters and defenders and heroes are people in the armed forces. We're just support.The Moral Question: Weapons, Responsibility, and Fighting BackNoah [00:10:33]: I have so many questions. Actually, I know you seem to have a question. Do you want to ask anything?Yaroslav [00:10:38]: No, I'm just listening. Go ahead.Noah [00:10:40]: I do want to talk about, some of let's say, the moral issues, like you just said. You endYaroslav [00:10:50]: I think there are no issues there.Yaroslav [00:10:52]: What would an example of a moral question be in this case?Noah [00:10:55]: No, I mean Okay. As you just said, you are creating the tools, but others are using them.Noah [00:11:05]: I was maybe thinking of having this conversation later, but one of the questions is like, is it actually you are going to be building them for your homeland, which you are building it for your homeland, which is I think, very a strong morally defensible position, but this technology is not going to stay with you, right?Noah [00:11:26]: This you will probably be selling these to other people Yeah. So the future is really where the moral issues may come into playYaroslav [00:11:38]: The this question becomes, easier and more complete if we ask this not about a particular technology or particular weapon, if we think that this question actually applies to any kind of technology Right? So -Knife or fire. You can use knife to do surgery and save people's lives, or you can use it as a weapon to take people's lives.Noah [00:12:06]: Cut tomatoes, too.Yaroslav [00:12:08]: Cut tomatoes too.Noah [00:12:09]: Yes, knife.Yaroslav [00:12:09]: That's helpful.Noah [00:12:10]: In Japan, sword and knife, they, call the same word.Yaroslav [00:12:14]: It's like, it's with any technology. Large language models, right? Look at how powerful they are and yet they're available to anyone in North Korea or in Russia.Yaroslav [00:12:29]: That's one side of the argument. The other side is As a maker, what is your responsibility for how the tools you're creating, will be used? There's definitely some responsibility, right? Then How should the decision process look like? Should you, like, try to calculate all the possible scenarios before starting to work on something? Or do you create something that is needed now to save people's lives, and then think about, addressing the unwanted edge cases later? In ideal world where there's like, or okay, it's not ideal world. In a mythical world where there is some one governing party and it gets to decide everything, and there is no other country, that can, decide on their own, you could say, “Well, we need to calculate for all the consequences, and only then, maybe build this building, by replacing this park because, maybe we need this park in the city,”right? So that kind of situation. But when you're in a situation where you're in a forest, in front of a wolf, you first going to deal with the wolf that wants to eat you, and then you're going to go consult Greenpeace. So that's kind of situation that Ukraine is in.The Fourth Law, Odd Systems, and Ukraine's Drone StackNoah [00:13:59]: Enough. Because this is a tech podcast, I did want to spend some time talking about, sort of the tech in that you've developed and what you've been working on. So can you explain, I guess, first of all, like, the problem that you were trying to solve from a technical standpoint? And I think, and then maybe, like, go into some of the solutions and some of the design process that led you from designing, little laser-guided, guiding lasers with a with an iPhone versus Having drones.Yaroslav [00:14:34]: Like, it so happened, that my partners and I, we sort of So I started one company called The Fourth Law, and its goal was and is to Make, massively scalable on-drone autonomy. And then In parallel with that together with my, Petcube co-founders, partners, and friends, we started another company called Odd Systems Which, was focused on making thermal cameras. Cameras, thermal cameras are seeing thermal radiation and are used to see at night. And we're now sort of those companies are getting closer and closer together and we're probably going to merge them. And this group of companies is currently the leading, team in on-drone AI and thermal imaging on the Ukrainian battlefield, and Likely one of the leading, if not the leading in the world. So We have these, like, three sort of business units, which are cameras, drone autonomy, and drones. So the cameras and drone autonomy sell daytime and nighttime cameras and different types of drone autonomous modules to other drone manufacturers, over 200 drone manufacturers in Ukraine. And then the UAV, business unit sells the drones themselves to the armed forces of Ukraine, Ukrainian government. And there are different types of drones. Those are sort of front strike, as we call them, so those are sort of FPV strike drones and the bombers, and then interceptors. And there are different kinds of interceptors. We do Shahed interceptors and we do ISR interceptors. We don't do the deep strike-FPV Drones, Interceptors, and Battery-Powered WarfareNoah [00:16:32]: What's an ISR interceptor?Yaroslav [00:16:33]: ISR is stands for intelligence, surveillance, reconnaissance, and those are basically drones which are which, Russians are using to watch over positions and then communicate where, the targets are coming.Noah [00:16:48]: It's a reconnaissance.Yaroslav [00:16:48]: That's, the ISR is sort of a classical term for a for a reconnaissance drone.Noah [00:16:53]: Are all of these battery-powered drones that you just described? ‘Cause I know that the sort of deep strike drones still have, like Some sort ofYaroslav [00:17:01]: Internal combustion engine?Noah [00:17:02]: Internal combustion engine. Are all the things you're talking about battery-powered?Yaroslav [00:17:06]: What we're working on is all battery-powered, right? We don't do the deep strikes, right? And then in terms of autonomy-Noah [00:17:12]: You can catch a Shahed with a battery-powered thing. It's not Fast to catch.Yaroslav [00:17:17]: No, absolutely. Look, Shahed interceptor, like ours, it's called Zero, it goes up to 326 kilometers per hour.Noah [00:17:26]: For reference, how fast is a Shahed?Yaroslav [00:17:28]: Eight, like, in internal phase it could be 280, but in cruise phase it's, like, 220-ish.Yaroslav [00:17:36]: Yeah. And sorry, I'm not like you can convert that into miles if you're interested.Noah [00:17:41]: No, that's fine.Noah [00:17:41]: Multiply by two thirds or point six or something.Yaroslav [00:17:44]: That's easy. Yeah, I was saying that for autonomy modules, right, we, -We make systems, autonomous systems for frontline, for interceptors and some for deep strikes as well, and then different levels of autonomy. So from terminal guidance, which is like lasts 500 meters, give or take, to autonomous bombing, to autonomous target detection, to autonomous navigation and all of that across day and night, different terrains, different time of the year, different platforms like quadcopters and fixed wing, and maybe some other platforms. So it's quite a wide variety of products. We also have like our own simulation. We have our own training school for the war fighters. And we're about to start construction of two, semiconductor plants to make, sensors for thermal cameras. So that's super exciting for me as a computer science guy is Doing semiconductors. Super cool.Noah [00:18:49]: Like in terms of kind of core drone technologies, you basically are one is an FPV replacement without fiber optics, and the other isYaroslav [00:18:59]: YouNoah [00:18:59]: Signal tracking with interceptorsYaroslav [00:19:00]: With or without fiber optics. Fiber optics Is just like, sort of a communication module.Yaroslav [00:19:05]: You can, you can use classical analog, video link and radio link. Those would be two separate radios. You can do digital, or you can do fiber optic, and then fiber optic Has its own advantages but also adds weight and decreases, the distance and decreases, how fast you can, sort of turn and With a drone. Yeah.Noah [00:19:33]: Do you need AI for fiber optic drones?Yaroslav [00:19:36]: Like you can use AI for fiber optic drones. AI replaces a human, right? Fiber optic is making your communication link more resilient. So those are slightly different goals. Like if you want, you can have, AI controlling hundreds of fiber optic drones instead of having 100 operators for each.Fiber Optics, Radio Horizons, and Terminal GuidanceNoah [00:20:03]: I guess I thought that the key reason that people moved to fiber optic drones was for like electronic, countermeasures. Or I guess to counter those.Yaroslav [00:20:13]: I think that's a correct assessment from sort of a public awareness standpoint. In practice it's somewhat more difficult Because besides electronic countermeasures, you have these issues of a radio horizon For FPV drones, which means that asYaroslav [00:20:36]: I believe Earth is round Some people disagree. But basically if you fly a drone and you have a land station over here and a drone flying over hereYaroslav [00:20:49]: If your drone is flying high, you have good direct radio visibility. If your drone goes low, and usually, Russian infantry and vehicles, they're on the ground and you want to hit them, you need to go low. Lower you go, maybe you'll get behind a hill or behind a forest, and if you're far enough, you'll just get behind the curvature of the earth. You get into what's called a radio shadow. And then That is a real bummer because for the last, be it 60 or 20 meters, you won't be able to see anything and it will be very difficult to hit the target. So to counter that what-- And then the distances that these FPV drones, act on they're, they can be quite large. So for example, here in the US there was this drone dominance program competition, and in drone dominance the furthest distance was about 10 kilometers.Noah [00:21:44]: What was drone dominance? What was that competition?Yaroslav [00:21:47]: Drone, the drone dominance is a is a program started, by the US government, to accelerate the development of drone technology here in the US.Noah [00:21:57]: Got it. And the longest range thing they were using was 10 kilometers.Yaroslav [00:22:00]: Was 10 kilometers, right. In Ukraine, like if your drone doesn't fly at least 20, 25, it just, no one's interested in it, and the usual hits are happening. It was like, okay, many hits are happening between 30 and 40 kilometers, and that's what expected from a regular 10-inch, FPV drone. So at that distance, even at altitudes of like 60 to 100 meters, you might start losing, the link. So some of the earlier AI technology that was fielded in FPV drone was this terminal guidance technology. That was the first product that we ever, launched that helped you as an operator, once you see the target from two, three, 500 meters, you lock onto the target and then, it just, drives the drone towards the target no matter what, even after you lost the visual connection. So optic fiber solves that. However, if you want to go like 20 kilometers with optic fiber, that will add an extra three kilos, of useful weight to your drone. SoNoah [00:23:12]: ‘Cause the cable that you have to unspool as you go weighs.Noah [00:23:15]: It is heavy.Yaroslav [00:23:15]: At first, like the spool is about 800 grams, so a bit less than a kilo, and then, and then think about 10, 10 kilometer optic fiber is another kilo, something like that. That takes away from your useful mass and then now you have like, you need a 15-inch drone and it can only carry maybe one or two kilos of explosives if you want to go, 20 kilometers. If you want to go to 30 or 40, like 30 is probably max. 40 is like very problem problematic on optic fiber. And then the problem with optic fiber is it's actually getting super expensive. So and why? Because of all the data centers for AI. That's literally the same optic fiber-Noah [00:24:01]: We're running out of centersYaroslav [00:24:02]: That's being used there.Yaroslav [00:24:02]: Like when Ukrainians and Russians come to Chinese factories to buy the optic fiber, they're like, “We're out. We sold it out to the Americans.”? That's the craziest thing. So optic fiber went up in price from like, $4 per, kilometer to like, $32 per kilometer in a few months in the beginning of this year. And I'veBrandon [00:24:26]: Claude Code is stopping the Russian drone effort here.Yaroslav [00:24:30]: Ukrainian as well. Yeah.Brandon [00:24:31]: Ukrainian. But I read somewhere that the Russians had grown more dependent on fiber optic drones relative to the Ukrainians, and that's one reason why the Ukrainians have sort of regained the initiative in drones recently.Brandon [00:24:42]: How accurate's that?Yaroslav [00:24:43]: The Russians were the first ones to scale that. I think by as of now, Ukraine has caught up. I think, like, as of maybe three months ago, Ukraine is mostly caught up on fiber optic. Yeah.Brandon [00:24:57]: What percent of damage would you say is in terms of FPV drone damage would you say is now fiber optic versus, like autonomous?FPVs as the New God of War: Tanks, Artillery, and Cost per KillYaroslav [00:25:07]: For our, for our audience, I actually, I cannot answer that question. Like, it's like I know the answer, but I would not disclose that. But for our audience, I think another interesting fact is out of all the casualties on the front line Between 70 and 80% are done by FPV drones.Brandon [00:25:30]: FPV drones are the new weapon of universal weapon of warfare.Yaroslav [00:25:34]: It'sBrandon [00:25:35]: Land warfare, anywayYaroslav [00:25:35]: They used to say that artillery is a god of war because artillery used to cause, like 80% of casualties, and now On that ranking-Brandon [00:25:46]: FPVYaroslav [00:25:47]: FPV drones rule.Brandon [00:25:48]: FPV drones are the god of war.Yaroslav [00:25:51]: Sort of. Dethroned artillery. But it's not to say that artillery is not useful, is not needed. Like, all of these systems are needed. Maybe except cavalry, although Russians still use it. I know, have you seen the videos of Russians using mules and horses?Brandon [00:26:09]: What is the usefulness-Yaroslav [00:26:10]: It'Brandon [00:26:10]: Of a tank in the in the modern-Yaroslav [00:26:11]: That's where we need Greenpeace to say a word, but they're silent. Yeah.Brandon [00:26:15]: What's the use of a tank on the modern battlefield?Yaroslav [00:26:21]: It's diminishing.Brandon [00:26:22]: Diminishing.Yaroslav [00:26:22]: However, I think there might be technologies which will, revive the tank. Look, tank still provides you armor, and armor is important. Like, you still need to armor and firepower, right? Like, you can be an armor personal carrier that provides you, armor. The challenge that currently exists is armor is not very well protected against incoming drones. However, there are ways to do to protect it. We were previously talking about this before the podcast. The CEO of Rheinmetall, recently sort of ridiculed, Ukrainian drone industry, saying that like, there is nothing interesting there, no real innovation, no to stand Compared to like, Rheinmetall or Boeing, and it's all made by housewives. There was like, obviously a ton of memes about this people ridiculing the CEO of Rheinmetall. And one of the best quotes, I heard on this topic is from my friend, Alexey Babenko, who's, the head of and founder of VIARI Drone, which is one of the largest manufacturers of FPV drones. They're our partner. They're using our autonomy. So he said that the drones we manufacture in one day will be more than enough to destroy all the tanks Rheinmetall manufactures in a year.Yaroslav [00:27:52]: Then, yeah, cost-wise, of course, a drone is like, $500 and a Rheinmetall tank is what, probably 5 million-ish or maybe more.Brandon [00:28:00]: Don't mess with those housewives.Yaroslav [00:28:03]: Drone wives.Brandon [00:28:04]: Drone wives.Yaroslav [00:28:06]: That's it.Noah [00:28:06]: There's a classic saying that everyone always fights the last war.Noah [00:28:12]: Yet do How did So from your standpoint, how did we get to the point where tanks became irrelevant in at least for now In a matter of just a few years?Yaroslav [00:28:24]: Look, I think it's the same way, how do we get to the point that calculators become irrelevant?Yaroslav [00:28:31]: Now we have iPhones. Like, why would you need a calculator? Technology progresses and its influence grows non-linearly. It's all exponential. So I can tell you that full autonomy, when you put it on a drone Look, so if you, if you think about a tank and a like, it's not a direct comparison, but even, like, a drone and a artillery shell or like, sort of cost per kill, an artillery shell for 155 caliber, which is a standard NATO caliber Currently market price is about $4,000 per piece. So compare that to say, $400 per drone. That's 10 times more expensive. Account for the amortization of the artillery gun and for how vulnerable it is and what is the sort of tactical, capabilities it gives you as compared to a drone. You'll figure out that an FPV drone is maybe three orders of magnitude, more versatile, more useful, more capable than artillery and many of than a classic artillery. Many of Because there are different types of artillery. Not just, like, one 155. You have mortars, you have all that. But give or take, roughly three orders of magnitude maybe. Again, it doesn't have that firepower. It's not one-to-one comparison still.Yaroslav [00:29:53]: Now, take that FPV drone. When you put full autonomy on that FPV drone, which can be not very expensive, like systems that we're, producing are like, in hundreds of dollars of pure bombFull Autonomy: From Human Pilots to Smartphone-Directed Drone MissionsNoah [00:30:06]: Just interrupt. You said full autonomy Just a second ago you were saying that the autonomy here is guidance, right? It's not decision-making.Yaroslav [00:30:14]: No, I was I was saying that's the f-First and sort of easiest pieces of autonomy that was fielded by us. But if you, if you add full autonomy to a droneBrandon [00:30:24]: He, I think he's asking what does it can you, for the listeners, can you explain What the term full autonomy means?Yaroslav [00:30:29]: Basically, I think a good way to think about an FPV drone is like an iPhone of warfare. It's, like, very inexpensive, very mass producible, very versatile. You don't need a bunch of other things when you have a iPhone in your pocket. You don't have, need an MP3 player, you don't need a calculator, don't need other things. All right? So FPV drone is an iPhone. Or like, okay, Apple please don't sue me, is a smartphone. And then, when you add autonomy to it sort of becomes like Uber or ride sharing. Okay? So what it means is instead of actually being a trained pilot who has this complex remote controller device which requires a couple months of training to actually pilot the drone, and then having to pilot it for 30 minutes, flying towards the target, et cetera, et cetera, now you basically, you have your smartphone, you have a drone, you pick your smartphone, you say, “We are here. The bad guys are here. Go and get them.” And the drone goes up, flies in a given direction, localizes itself on the map, finds the dedicated area where they, the bad guys are supposed to be sees the bad guys, bombs them, return, like, watches, so does a damage assessment, returns back, sits down, and then you can pick it up and watch the video if you didn't have the radio link, right?Noah [00:31:59]: That's a bomber drone.Yaroslav [00:32:00]: That's full autonomy for a bomber drone, right?Noah [00:32:03]: You're saying that no human decision is made in this entire process?Brandon [00:32:06]: That's not, that's not what he's saying.Yaroslav [00:32:07]: A human decision was made at the beginning of the process-Noah [00:32:09]: I get it. I get itYaroslav [00:32:09]: The same way as you would fire an artillery.Yaroslav [00:32:12]: When you fire an artillery, you don't stop at like, 500 meters away from a target and ask it whether, you want to strike or not. That's exactly, a human decision is always made at some point. So when you do that's full autonomy, and such full autonomy is happening as we speak. And such full autonomy increases the capabilities of an FPV drone, which is already, like, three orders more powerful than an artillery shell. Full autonomy increases its capabilities by four orders of magnitude because now you can have 100 times as many people who can use it, because you don't need to train those people, and this is important. You can have 10 times, mission success rate, and you can have 10 times utility per drone because now instead of being one-way kamikaze, it's, it can be a bomber.Brandon [00:33:05]: Now wait, let's, you said 10 times mission success rate, which means that fully autonomous bomber drones succeed in their missions 10 times more often than human piloted bomber drones do. That's an important thing to know.Noah [00:33:17]: Maybe, to push back onBrandon [00:33:19]: They're super, they're superhuman. They're, they' 10X superhuman.Yaroslav [00:33:22]: They're not vulnerable to electronic warfare. They don't care about the radio horizon. They don't lose track during navigation. They are not susceptible to human error when, an artillery shell or other drone blows up besides you and you're like, “Hell no,”like, “I'm getting out of here.” Right? That doesn't happen to an autonomous drone. Like, all of those things. Like, we have, like, one of the brigades that's using our drones with just first level autonomy They literally said that their success rates-Brandon [00:33:53]: What's first level autonomy?Yaroslav [00:33:54]: First level autonomy is just the terminal guidance.Yaroslav [00:33:57]: By the way, we have video of that. We can watch that.Brandon [00:33:59]: Terminal guidance means a human gets it nearby and then the AI takes over.Yaroslav [00:34:03]: The human flies it all the way, like 30 kilometers towards the target, and obviously the target was probably given to that human by someone who's flying some ISR drone, some reconnaissance drone, right? So all the way to the target, and once you see the target from a distance of 500 meters, you do target lock, and from there drone flies autonomous. So just that feature alone, it has increased the guy's, his call sign is Grom, so it has increased his, mission success rate, like precision of mission, yeah, mission success rate from 20% to 71%, and it also increased his kill zone from three kilometers to 10 kilometers, which means there's certain area around the front line which is designated kill zone. Whenever enemy goes into that area, it's almost guaranteed to be to be destroyed by a drone. And then obviously the drones are not launched from like, the zero line. They're usually launched from like, minus 10 kilometer-Mission Success, Failure Modes, and the Five Levels of AutonomyBrandon [00:35:03]: What is a zero line?Yaroslav [00:35:05]: Zero line is sort of an imaginary line of control, of two conflicting forces.Brandon [00:35:14]: It's important to explain these things to a lot of the listeners who areYaroslav [00:35:17]: Thank you for askingBrandon [00:35:18]: Familiar with warfare.Noah [00:35:20]: Myself.Noah [00:35:20]: I'm one of those listeners.Brandon [00:35:20]: You said that level one autonomy, in other words just terminal guidance, just, like, human gets it to the finish line and then it goes over the finish line, increases mission success from 20 something percent to 71%, or something like that.Yaroslav [00:35:33]: Increases the kill zoneBrandon [00:35:34]: Increases the kill zoneYaroslav [00:35:34]: Three kilometers to 10 kilometers.Brandon [00:35:36]: Got it.Yaroslav [00:35:36]: On both parameters-Brandon [00:35:37]: What is full autonomy, dude? AndNoah [00:35:38]: Actually on real quick, can we define mission success and like, maybe in a way, what are the failure modes of missions?Brandon [00:35:44]: I have a guess what mission success is.Noah [00:35:46]: But I couldBrandon [00:35:47]: Get ‘em.Yaroslav [00:35:49]: No, but that's a very good question, in fact, because, even if you fly into the target, well, first the target can be damaged or destroyed. Those are two different modes. Then there can be different targets. A sole infantryman is one kind of target. A dugout where supposed there are some, enemies there is another kind of target, and a some mechanical equipment is another type of target. Radio emitting equipment, which, like, often, like, the targets that the military want to get more than anything else is the some enemy radio tower or something like that or some small radio dish that really makes life difficult in that area, in that combat area. So those are different targets, right? It can be destroyed, can be damaged.Then sometimes, the drone hits but doesn't explode. Like, that happens. And then, there are other failure modes. You didn't even reach the target because you were A jammed by electronic warfare; B, you lost the control over drone because of the radio horizon; C, you were jammed by a different type of electronic warfare that happens way before You hit the target area. It's, impacting your, video receiver. So like jamming on video or jamming on control are two different types of jamming. Then something malfunctioned on a drone, just a mechanical malfunction, maybe like a motor broke or like, whatever. So all of those are different failure modes. Yeah, or maybe you got lost, you're navigate navigating to your, to your target. That happens, too.Noah [00:37:41]: The Level one autonomy, basically you manage to point in a direction.Noah [00:37:49]: You go there, and then the last mile The drone taking over.Yaroslav [00:37:52]: We define this like, I define that but it sort of got picked up by the industry. We define five levels of autonomy. So level one is terminal guidance. It's what we just discussed. Level two is bombing. Level three is autonomous target detection and engagement decision. Level four is autonomous navigation. And level five is autonomous takeoff and landing.Noah [00:38:15]: Those are good things to knowYaroslav [00:38:16]: Those are five levels of autonomy. Now, if youNoah [00:38:19]: I have a question for you.Yaroslav [00:38:19]: Sorry. Like, let me finish withNoah [00:38:21]: SorryYaroslav [00:38:21]: Theoretical part.Noah [00:38:23]: What is Tesla running at right now?Yaroslav [00:38:25]: Tesla?Noah [00:38:25]: No, sorry.Yaroslav [00:38:26]: That's very good point. Like, it's exactly, it was inspired by the levels of self-driving autonomy.Noah [00:38:32]: Waymo's level five, right?Noah [00:38:35]: You just tell it where you want to go, it picks you up, and then you go there.Yaroslav [00:38:36]: I think, like, if you, if you look at the classic definitions of self-driving cars, Waymo is still, like, level four because it still requires even remote, but still, like, human control. It's like if Waymo gets in trouble, there is an operator who takes over and resolves this. So that would still be a level four. It doesn't map directly, but it's also five levels.Brandon [00:38:58]: Can I, can I interject a question here? In terms of an FPV drone that's like a suicide drone that'll just blow itself up killing something, how do what it hit? Like, does it, just transmit back, or do you sort of like, lose track of it and hope it hit? Like, what happens to that?Yaroslav [00:39:16]: That's a great question. SoBrandon [00:39:18]: You need another droneYaroslav [00:39:19]: Like, the current battlefield in Ukraine is saturated with different types of drones. So obviously you have all the FPV drones and last year alone, Ukraine manufactured about 4 million of these, and then Russia's maybe, like, 20% less than that. And for this year, the publicly voiced target was 7 million on Ukrainian side. So it's, like, serious numbers. We're getting in serious numbers here. And then besides those, there are different, reconnaissance drones, ISR as we call them, and there are sort of tactical level ISR where we, both Ukrainians and Russians usually use, Mavic, drone by DJI. And then there are a bunch of locally produced drones, which are sort of fixed wing drones that can stay in the air for much longer than Mavic, maybe, like, half an hour. And then, there are drones that can stay for many hours or even up to a day. And those drones have, are more expensive, have more expensive cameras, et cetera, et cetera. We hunt those drones that Russians launch. The Russians hunt our drones, and so on. But ideally, when you, are a group of soldiers operating an FPV, you'll have someone in your, company, or someone in your platoon who has an ISR asset that will do target designation for you. They'll say, “Oh, like, there's a Russian vehicle over there. Go and get him.”and you go there, you get it, and they're like, “Okay, confirmed.”Battlefield Surveillance and the Eight Dimensions of AutonomyBrandon [00:40:57]: Those guys are watching. They have their own drones in the sky.Yaroslav [00:40:59]: Target destroyed. They have, like, a carousel of drones because One Mavic cannot stay more than 30 minutes. ItBrandon [00:41:06]: They're constantly surveilling the battlefield.Yaroslav [00:41:07]: Almost every spot on the battlefield.Yaroslav [00:41:11]: It's not always the case. Sometimes you will not have a surveillance asset, so then you would launch another FPV just to confirm that there was a hit. Then if you see there was a hit and you're not sure if it completely destroyed, you maybe hit again for good measure.Brandon [00:41:26]: You double tap.Yaroslav [00:41:28]: That's how it works. But I was about to give you another sort of piece of taxonomy. So you have five levels of autonomy, right? Then you have sort of eight dimensions of autonomous battlefield. So what is eight dimensions? It's crucial to understand how autonomy evolves in a modern, battlefield environment. So dimension number one is level of autonomy. What are the capabilities that your asset has? Dimension number two is the platform you're operating on. So it can be a quadcopter, a fixed wing drone, different types of maybe, like, a long range drone or short range drone, but it can also be a missile. You can have autonomy even on an artillery shell or a ground vehicle or a sea vehicle. So all of those are different platforms. Level three would be domain. So it's ground to ground or ground to air as an intersection, or ground to sea or sea to air. They're all, like, all the nuances with different domains. Then level four, would be higher levels of autonomy, such as swarming, drone carriers, drone nests, et cetera.Brandon [00:42:39]: Now when you're saying level, you're talking about dimensions, not about-Yaroslav [00:42:42]: Sorry. YeahBrandon [00:42:43]: Autonomy levels. So dimension four.Yaroslav [00:42:43]: The dimension. Yeah, I used to say I was supposed to say dimension. I say dimension because each of them works with another, right? So you might have, like third level autonomy, fixed wing drone operating in land to air, and stuff like that right? And then operating in a swarm or operating from a nest. Right? Then you have, sort of dimension number five is environment. So is it day or night? Is it summer or winter? Is it, humid, cold, dry? What kind of target is it? Is your target hiding in a forest, or is it, behind a hill or within buildings? So all of that is environment. Then you have, dimension number six is command and control. How are you dealing with or like, tens of thousands of those assets around the battlefield? How are you coordinating that on the higher levels of command? How are you collecting data? All that.Yaroslav [00:43:44]: Dimension number seven would be infrastructure, so things like simulation, data collection tools, security, deployment mechanisms, et cetera. So all those systems have to be developed separately and integrate with all the others. And finally, dimension number eight is sort of distribution. Have you deployed 100 of these systems or 100,000 of these systems? Because those are two very different ballgames. So that now gives you a more broad overview of how autonomy propagates across the battle space.Targeting, Human Responsibility, and Rules of EngagementNoah [00:44:23]: As someone who has done machine learning and had gone out of distribution and had things, go horribly wrong, you were talking several of these, kind of axes of thinking about drone warfare seem like they could be very susceptible to some sort of distribution shift if you start making things autonomous.Yaroslav [00:44:41]: Like what?Noah [00:44:41]: I mean Well, first ofYaroslav [00:44:43]: If the I'm very interested Sort of sort of kinds of scenarios that you're thinking about.Noah [00:44:48]: Like the most obvious one is you, if I assume these are computer vision guided systems for at least the last mile, how do you ensure that oh, well, like you now have some fog roll in or something, and you, the drones just attack the wrong thing? Or maybe, it probably will not turn around and fly back and attack you, but youYaroslav [00:45:10]: Same, the same, the same question, how do you ensure that your mortar fire hits the right thing? Well, it's like mortar fire, give or take half a kilometer could be plus or minus. So maybe you fire one, and then you fire another. So drones are actually, much better in being precise in those scenarios. And I think, to your point, I think five to 10 years from now it will be immoral to use weapons without AI.Yaroslav [00:45:44]: ‘Cause weapons without AI will be more likely to cause, collateral damage or unwanted damage. Same way, it will be immoral to drive your own car manually on a public road because it's more likely to cause, unwanted damage.Noah [00:46:02]: Wow, I never considered that mightBrandon [00:46:04]: Really? That's definitely coming.Yaroslav [00:46:07]: Anyway.Brandon [00:46:07]: No, but that' I don't know, it's an obvious, an obvious thought. I agree with you.Brandon [00:46:12]: I, No, they, obviously they're not going to let you drive once most of the cars on the road are autonomous.Noah [00:46:17]: No, that one, don't I believe.Yaroslav [00:46:19]: No, I think you were you were talking about drones, right?Brandon [00:46:21]: The drones, right. Cool.Yaroslav [00:46:22]: The weapons, right?Brandon [00:46:23]: Friendly fire and collateral damage and stuff like that is all minimized with AI.Brandon [00:46:27]: Here's my question. Take all let's go to level six autonomy. Let's take all of the target selection. Let's take all the battlefield data, integrate it into one big AI, and have that big AI basically be in command of the battlefield And agentically do target selection.Yaroslav [00:46:44]: Be the general, right?Brandon [00:46:44]: It's a general. It's, you've cut humans out of the loop except maybe as dexterous robots, repairing drones and fastening things to drones or maybe something like that because you don't have those robots yet. How soon are we there? AI general.Yaroslav [00:46:58]: The most important thing to ask ourselves is who will be faster to that us or our adversaries?Brandon [00:47:07]: I assume us, but how fast will we be to that? I hope us.Yaroslav [00:47:11]: I hope so too.Brandon [00:47:12]: How fast can we Like when are we looking at that in terms of like horizons years?Yaroslav [00:47:18]: Like technically, it could be done now. The question is of course, there's, some engineering work to be done. The bigger challenge is deployment. Right? So okay, technically Like operation in Iran, right? They, the publicly, it was claimed that I think Palantir system was used for target designation, et cetera, et cetera. So it is not exactly as you say, the AI makes all the decisions, but basically AI goes through all the data you have, gives you these 1,027 different targets and says, “You-- To confirm, please press Okay.” And you look at the targets and you're like, “Yeah, sounds right. Press Okay.”so that's, I think that's where we are now already, or we were a couple weeks ago as we're recording this on April 10th. Another question is how massively deployable it is. Is it, like, every decision being made like that or is it, like, just some of the decisions made like that? And then different levels of command and control. There you have, like, the platoon, the company level, the battalion, et cetera, et cetera, et cetera. But the tricky thing here when we get into that territory, the tricky thing is If your enemy is getting advantage of being Thousand times faster than yourself by deploying such systems What do you do?Yaroslav [00:49:10]: You got to-Brandon [00:49:12]: The if the enemy is a thousand times faster than you at deploying those systems?Yaroslav [00:49:16]: Like, if enemy starts deploying level six autonomy, as you call And you have not started doingBrandon [00:49:22]: You're in troubleYaroslav [00:49:23]: Yes, exactly. So you have to catch up. So my point is that it is very important to think about the safety of these systems, but that thinking should not slow you down in developing them because they are critical for your existential, survival, right? And like, one person who doesn't think, doesn't get to think about the ethics of the war is a dead person. That person surely doesn't get to think about that.Brandon [00:49:52]: What would be the safety risk of such a system?Yaroslav [00:49:55]: Of course-Brandon [00:49:56]: Friendly fire?Yaroslav [00:49:56]: Just wrong decisions, right?Brandon [00:49:59]: I see.Yaroslav [00:49:59]: Maybe, these decisions-AI Command Decisions, Dead Zones, and Complex BattlefieldsBrandon [00:50:06]: Skynet AI decides it's going to useYaroslav [00:50:08]: No, these-Brandon [00:50:08]: Drone army to kill usYaroslav [00:50:09]: Decisions will not only be made about drones. They are likely to made about what the humans should do on your side as well. Then obviously some environments are more like Ukrainian-Russian war, where you haveBrandon [00:50:26]: It will have to choose to risk lives. It will have to choose to sacrifice human lives-Yaroslav [00:50:28]: Of courseBrandon [00:50:29]: On your side.Yaroslav [00:50:29]: Of course. And then some environments are just, like, dead, like, dead zones and there are no civilians there, or virtually no civilians close to the front line because, like, super dangerous. Everyone has evacuated from there. But there are other environments which are more like, okay, there's a counterterrorist operation. There's, like, a group of terrorists or a group of civilians. Or like, it's like the recent operations in Iran, I imagine that the US and Israeli forces do not want to harm civilians. They only targeted the military targets there, right? So in those situations, it's a different level of responsibility for that decision-making as well. And then there is just such a big variety of those military missions, and I'm not even, like, well-informed or well-educated in military science to tell you about all those scenarios. We would need to put some general besides me, and maybe a Ukraine general and American general would have told you very different stories about these things.Brandon [00:51:34]: Got it. Can I ask a few more questions? All right. So in 2013, I wrote one of my first, paid articles ever was about how the era of drones will change human society. I was just sitting around bored thinking about things.Yaroslav [00:51:54]: You were way ahead of your time.Brandon [00:51:55]: I said, I said, “The following will happen.”Yaroslav [00:51:57]: It's, this article is real. I've read it.Yaroslav [00:51:58]: It's actually-Brandon [00:51:59]: I said small autonomous, suicide drones, will cleanse the battlefield of human infantry. Human infantry will not be able to stand against swarms of AI-powered, suicide drones. That was I didn't even know about, like, AlexNet at the time, I think.Yaroslav [00:52:19]: You're just an avid sci-fi reader.Brandon [00:52:23]: I'm an avid sci-fi reader, but also, like, it's not Like, there will be a way to do that. It's a it's a nonlinear multidimensional search problem, and you get enough compute, you'll find some search algorithm that will get you there. And soBrandon [00:52:38]: I, yeah, I think that one sentence describes the bitter lesson right there.Brandon [00:52:41]: It's just like it's a multidimensional search space. You search it somehow. I don't know. Figure out some get a grad student-Yaroslav [00:52:47]: Sooner or laterBrandon [00:52:47]: To make a search algorithm.Brandon [00:52:48]: It's not that hard. Anyway, so but then, but I guess the point is The point is that human infantry on the battlefield will be will be gone at the end. I wrote that in 2013. Many people on social media laughed at me for that called me hysterical, said things like, “Electronic warfare will knock all the drones out of the sky.”like, “You need humans to hold ground.”that's something you still hear from a lot of people on social media today. I feel that this article that I've written has never been directionally wrong. It has gotten more and more right steadily over time, and that we're very reading the battlefield reports from Ukraine, where, human infantry are basically guy, like a few guys hiding in dugouts for months, and I'm not sure what they're doing.Yaroslav [00:53:35]: That's on Ukraine's side. On the Russian side, that's just like a zerg rush.Brandon [00:53:38]: The zerg rush, and then they just die. Then, but they have some guys in dugouts too, right? Like hiding in dugouts for months.Yaroslav [00:53:45]: They have. Yeah.Brandon [00:53:45]: Like, but that like, what are those guys doing in the dugouts? Are providing, like, frontline, like, reconnaissance? Like, what are they doing?Yaroslav [00:53:54]: If there is a guy in a dugout with some bullets and automatic weapon, the other guy cannot come and take the that dugout. That'Brandon [00:54:07]: I seeYaroslav [00:54:08]: They are they're establishing control over territory.Brandon [00:54:10]: I see. So that is so there still is a use for human infantry on the battlefield as of today.Yaroslav [00:54:15]: LikeBrandon [00:54:15]: How long will that last?Yaroslav [00:54:17]: I think it will last for a while. This is funny. There's this whole Layer of the modern culture, a modern Ukraine culture built around the war-related stuff. So there is this -Punk rock band, that is called SZC, I guess in English that would be. Which stands short for like a deserter or something like that. So anyhow, this band has a song titled “2030.” It's basically about the year 2030, and the war still goes on as like the whatever, third world war or whatever. And they basically, they, sang about the AI and like cyborgs and everything, but the simple infantry is still needed, and we're still, like, getting cold in those dugouts, and we're still doing our job. That's sort of the theme of the song. And it seems like that's actually what's going to happen. There areGround Robots, Simulation, and the Limits of World ModelsBrandon [00:55:30]: Ground robots will not replace humans in the dugouts soon.Yaroslav [00:55:34]: I'm very much interested in following the whole humanoid robot theme andBrandon [00:55:39]: What about like a dog robot?Noah [00:55:41]: Or just mobile controlled platforms or something.Brandon [00:55:44]: Spider robot, yeah.Brandon [00:55:45]: Everything evolves into a crab.Brandon [00:55:46]: You build a crab robot.Yaroslav [00:55:47]: A humanoid-Noah [00:55:48]: The carcinization of warfare.Yaroslav [00:55:51]: There is a lot of utility in humanoid robots because the world is designed around humanoids. So I would not, like, 100% disqualify the possibility that sometimes 10 years in the future, humanoid robots, will be actually fighting. So that's an actual Terminator kind of scenario.Brandon [00:56:14]: Yeah, in the first Terminator movie, you look at what they've got on the battlefield, they've got flying bomber drones and humanoid robots.Yaroslav [00:56:20]: Look, the cost of large language models of running them is getting so low, you can have basically an inexpensive computer running, what was a state-of-the-art model a year and a half ago, running it locally on a device with an open source model, which also means that the Chinese can have it, the Russians can have it, the North Koreans can have it, et cetera. So that is already possible. And with when we're looking at the acceleration of the neural nets, I would've, if not the acceleration of the large language models, I would've said that I don't think that humanoid robots will be able to be useful in the battlefield earlier than in 10 years. But if you account for the exponential, it might be five years or so. The problem with all of the autonomous systems, and it's like starts with self-driving cars and even with all the AI, like modern day AI agents, to make them really, useful, you have to solve such a long tail of edge cases, that it's really difficult to make them useful. Like we were promised, self-driving cars, what, like 2007, Sebastian Thrun and Google, and even before that all the challenges, everything. And Elon of course told us it's going to be one year from 2014, and now we still don't have self-driving Teslas everywhere. We have Waymos in SF and some other places, but they're still, like, not perfect. So I think, I expect something similar from self-flying drones and fully autonomous drones, and we saw that firsthand as with each level of autonomy that we're adding, there is a very wide distance between a prototype and something that is ready to be scaled to millions of units and something that has been scaled to millions of units. But the race with like AI coding tools is just insane. So things might accelerate very fast, faster than we can imagine.Noah [00:58:46]: I think your point is that with due to this long tail behavior Level one autonomy as you've defined it, is actually very natural. Like you basically are just solving an image recognition and tracking system.Yaroslav [00:59:02]: It's actually interesting that you say it that way, and I thought about this the very same way, and we have this joke that there are like 200 companies in Ukraine which are trying to solve last mile, targeting or terminal guidance. It seems like we're like the only company that actually solved that because even that problem-Noah [00:59:22]: I'm not saying it's, I'm not saying it's trivial, but it's at least something that you imagine given our current state.Yaroslav [00:59:26]: Like us and Eric Schmidt, like Eric Schmidt's companies are pretty good.Yaroslav [00:59:29]: Like, I actually have lots of respect to what they're doing, and they're, they have been practically influential and helpful on the battlefield, and they have good engineering.Noah [00:59:38]: I wasn't, I wasn't saying it's trivial. I'm just saying this is a something naturally adaptive based upon things that we know work, well. But some of the other domains that where you do have to make decisions and you have a long tail become much harder, and you worry about edge cases more.Yaroslav [00:59:57]: Like the more, the more complex behavior you're trying to simulate, the more edge cases there are right? The more ways to do it wrong there are. And then there are different approaches. It's like if you think about, if you read academic papers about robotics, right? You sort of the robot is represented as something that has the sort of sensor input, and then you have three, levels of sort of logics or decision-making, which are perception, planning, and control, and then you have actuators as output.So pre-neural nets, you would do perception output and control all with classic logics, right? Then, with AlexNet and computer vision, you could do perception with neural nets and the rest with logic. You cannot currently do each of those separately with neural nets, each of those separately with logics, or you can just have one huge neural net that just takes lots of sensory data. It's not just pixels. Could be sound, could be accelerometer, could be everything, as input, and just outputs the controls. And some of the self-driving car companies are doing that or like, experimenting between different ways of doing that. So you can also, like, think about that and the way you implement those features, also influences how much degrees of freedom the system would have, right? Like control, you can do it classical algorithmic control with common filters and PAD filter, PAD controllers, et cetera, or you can do a neural net, that was trained in a gym with a reinforcement learning, et cetera. And those would be two different behaviors of a system.Noah [01:01:53]: I-- Maybe my point was just much more high level. It'Yaroslav [01:01:56]: Or you can If you go even like, if you go high level, you can, you can like train to like have whatever, like Feifei Li and folks who are doing like physical, sortBrandon [01:02:08]: World modelsYaroslav [01:02:08]: World models, right, physical intelligence, they're trying to make these big models and sort of understand the world and then supposedly you have such model and you can tell a drone, “Okay, like, go over that hill and like, find the bad guys and then get them,”or “Make me a video, make me a photo of the guy smiling and get back to me.” Right? That's one way. Another way you have like these subsystems, like one is navigation, another is finding the person, another is like getting to them to take a photo. And those are again, very different behaviors. And then it's not that one is necessarily better than the other, and we might have more technological ability to do one or another. But all of those systems will exist. And then again, you should always keep in mind that it's only the not only the good guys that are developing these systems, the bad guys are developing these systems as well.China's Drone Supply Chain and the West's Manufacturing GapNoah [01:03:00]: I guess where I'm going with this back to Noah's original thought with the end of the end of the soldier. And so in order to replace-Brandon [01:03:10]: Or at least the end of the rifleman.Noah [01:03:11]: Or the end of the rifleman, yeah.Yaroslav [01:03:13]: I'm not seeing that very close, and it was like I'm, as much as I'm a lover of sci-fi and all of that and a technologist, the more I try to beYaroslav [01:03:27]: Like the I try to have certain humility about these things, and like the military, domain and there was just so much human history and blood and tears, dedicated to sort of understanding this art of war and perfecting it and so on. There is so much knowledge in there that I don't feel like I even started to comprehend, a lot of that. But one thing that I really understood is that even though drones are now making eighty percent of the casualties, you go to the actual officers, you talk to the actual, like, brigade commanders, corps commanders, and they explain to you, how all of it fits together, how when you're thinking about an operation that involves a couple thousand people to get this piece of land, out of the enemy's hands, deoccu deoccupy it, how it is so complex, it involves, dozens of different types of drones and then land operations and reconnaissance operations, psychological operations and then aviations and tanks and logistics and all kinds of these different assets. So modern warfare is really very complex, and the fact that the drones are the latest, coolest thing, and then the AI is latest, coolest thing, doesn't mean that now it's that and only that right? So yeah. Whoever's looking into that I think should realize that it's not just what the press talks about, that the reality is much more difficult, much more complex.Brandon [01:05:17]: Let's talk about China and China's manufacturing capabilities. So suppose that someone, like suppose the United States went to war with China. AndYaroslav [01:05:26]: I hope not.Brandon [01:05:27]: I hope not as well. And then but suppose that drones were very essential to that war of all the types of drones that we're talking about here, and that suppose that China said, “All right, well, you need X and Y and Z, to make those drones to fight us, and we control the production of X and Y and Z, so we're just going to cut you right off, and now you have no drones.”Brandon [01:05:47]: I know that a number of countries, including Ukraine and Taiwan, have been making moves to China-proof their drone productions that China couldn't do that. Examples of things they might be able to cut off might include rare earths, fiber optic cable that you were talking about before, various other things that where even if they don't control one hundred percent of the production, they control enough of the production that would be extremely expensive to produce it without relying on Chinese sources. Or the market's fragmented enough, et cetera. What do you see as China's key bottlenecks, and how easy are those to overcome in terms of China-proofing drone production in case of a war against China?Yaroslav [01:06:30]: Let me start with a saying that -Although China does not sell directly to Ukraine and it does sell directly to Russia, a lot of Ukrainian supply chains, they start in China, right?Yaroslav [01:06:49]: We're not in a conflict with China, and we would not want to be in a conflict with China. And we'd hope that China stays a neutral power between Ukraine and Russia and the US as well. That said, the scenario that you're describing, everything is much worse.Yaroslav [01:07:11]: Think about this. Last year, Ukraine produced four million FPV drones. Ukraine is not the most industrious nation in the world.Yaroslav [01:07:19]: China can produce four billion of these FPV drones.Yaroslav [01:07:23]: China can make them not drones with propellers, but fixed-wing drones, which go not forty kilometers far, but maybe two to three hundred kilometers inland.

Episode #256 features Shernaz Daver, one of Silicon Valley's most respected executive advisors and communications strategists, who has worked alongside leaders including Steve Jobs, Netflix co-founder Reed Hastings, Khosla Ventures founder Vinod Khosla and Waymo/Udacity founder Sebastian Thrun. In conversation with Vidit Agarwal, Shernaz reflects on a remarkable journey shaped across India, Japan and the United States — from growing up between cultures as part of the small Zoroastrian community to navigating the inner circles of Silicon Valley's most influential founders and companies. She shares stories from Motorola, Electronic Arts and Sun Microsystems, the rejection that changed her trajectory, the unforgettable moment Steve Jobs told her she had done a “terrible job” marketing a product, and the lessons she learned working alongside elite founders and operators. The conversation also explores insecurity, ambition, storytelling, AI, burnout, hype versus reality in Silicon Valley, and what separates visionary leaders from merely successful ones. Please enjoy exploring your curiosity. ________ Get in touch with us via email at contact@curiositycentre.com Join our stable of commercial partners including the Australian Government, Google, KPMG, Vanta, Allens, Macquarie Capital, City of Sydney and more.  Show notes and more episodes here Follow us on LinkedIn, Twitter, Instagram, or YouTube Get in touch with our Founder and Host, Vidit Agarwal directly here Contact us via our website ________ The High Flyers Podcast features in-depth interviews with the world's most influential figures in business, tech, finance, government and sport. Launched in 2020, it has ranked in the global top ten for past three years, with listeners in 27 countries and over 200+ episodes released, and featured in Forbes, Daily Telegraph, and at SXSW. Our guests include -- Malcolm Turnbull (Prime Minister of Australia), Anil Sabharwal (Global VP, Product at Google), Jason Collins (Head of BlackRock, Asia Pacific), Jodie Auster (Uber's Global Head of Travel), Stevie Case (Chief Revenue Officer, Vanta), Brad Banducci (CEO, Woolworths),  David Haber (GP, a16z), Rob Giglio (CCO, Canva), Jean-Michel Lemieux (CTO, Shopify + Atlassian), Sweta Mehra (EGM, NAB; ex CMO, ANZ), Bowen Pan (Creator, Facebook Marketplace), Sam Sicilia (Chief Investment Officer, Hostplus), Craig Tiley (CEO, US Tennis), John Haddock (CBO, Harvey), Niki Scevak (Co-Founder, Blackbird Ventures), Mike Schneider (CEO, Bunnings), Trent Cotchin (3x Premiership Winning Captain, Richmond FC), Peter Varghese (Secretary of Foreign Affairs, Australian Government), Jack Zhang (CEO, Airwallex), Matteo Franceschetti (CEO, Eight Sleep), Vivek Bhatia (CEO, MUFG), Sanjeev Gandhi (CEO, Orica) and more. 

How a secret project at Google led to driverless cars on American roads.  Freakonomics Radio shares a story from our friends at Search Engine. (Part one of a two-part series.)   SOURCES: Alex Davies, author of Driven: The Race To Create the Autonomous Car. Chris Urmson, co-founder and C.E.O. of Aurora. Don Burnette, founder and C.E.O. of Kodiak AI. PJ Vogt, reporter, writer, and host of the Search Engine podcast. Sebastian Thrun, roboticist, C.E.O. of Sage AI Labs, adjunct faculty at Stanford University. Timothy B. Lee, author of Understanding AI newsletter.   RESOURCES: "Very few of Waymo's most serious crashes were Waymo's fault," by Kai Williams (Understand AI, 2025). Driven: The Race to Create the Autonomous Car, by Alex Davies (2021). "An Oral History of the Darpa Grand Challenge, the Grueling Robot Race That Launched the Self-Driving Car," by Alex Davies (WIRED, 2017). Understanding AI, newsletter on Substack. Waymo Safety Dashboard.   EXTRAS: "The Fascinatingly Mundane Secrets of the World's Most Exclusive Nightclub," by Freakonomics Radio (2024). Search Engine, podcast by PJ Vogt. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

What does it take to reinvent entire industries, over and over again?This week on Grit, Sebastian Thrun, the “godfather” of self-driving cars and massive open online courses, reflects on a career pushing the boundaries of technology across mobility, education, and AI.With Joubin Mirzadegan, he shares why he believes autonomous driving could become the biggest lifesaving technology in history, and how a wake-up call led him to found Udacity to truly democratize higher education.Guest: Sebastian Thrun, CEO of Stealth Startup, founder of Google X and UdacityConnect with Sebastian ThrunXLinkedIn​Connect with JoubinXLinkedInEmail: grit@kleinerperkins.com​Learn more about Kleiner Perkins

Today on the podcast we are joined by Sebastian Thrun - the “Godfather of self-driving cars”. He invented Google's autonomous vehicle, now known as Waymo, which is doing a quarter of all rideshare journeys in SF.Sebastian's life has been full of moonshot ideas. He co-founded Google X, the moonshot factory at Google, and co-founded the flying taxi startup Kitty Hawk and Udacity, which democratised elite education online. He's seen as one of the greatest computer scientists and roboticists of our time.Tommy first met Sebastian 12 years ago, when he was researching his book co-authored with Lord John Browne, Connect.Building a purpose driven company? Read more about Giant Ventures at www.Giant.vc.Music credits: Bubble King written and produced by Cameron McLain and Stevan Cablayan aka Vector_XING. Please note: The content of this podcast is for informational and entertainment purposes only. It should not be considered financial, legal, or investment advice. Always consult a licensed professional before making any investment decisions.

Chris Urmson has spent the last 20 years pushing the limits of autonomous driving—first at Carnegie Mellon's DARPA Grand Challenge team, then as co-founder of Google's self-driving car project, now Waymo.On this week's episode, the Aurora CEO retraces that journey—from building robot cars in the desert to leading a public company pioneering driverless trucking.He shares why autonomy was always a matter of when, not if, how he handled a high-profile departure from Waymo, and what it takes to build at the intersection of deep tech, safety, and infrastructure.Now eight years into Aurora, Urmson says the future he's been chasing is finally within reach.Guest: Chris Urmson, Co-Founder & CEO of AuroraChapters: 00:00 Trailer00:43 Introduction01:59 FSD: are we there? 14:31 The competition, a million dollar check from LA to LV22:50 Dream like an amateur, execute like a pro32:30 Operate with integrity42:49 The future is here, unevenly distributed49:36 Underestimated decisions, minimizing regrets1:03:55 Retaining value1:16:45 Integrating self-driving1:28:20 Lifer1:29:25 Who Aurora is hiring1:29:53 What “grit” means to Chris1:30:15 OutroMentioned in this episode: Waymo, Google, Rivian, Dmitri Dolgov, Uber, Tesla, The DARPA Grand Challenge, Defense Advanced Research Projects Agency, United States Department of Defense, Carnegie Mellon University, Stanford University, FedEx, Werner Enterprises, Hirschbach, Schneider Electric, Larry Page, Sergey Brin, Sebastian Thrun, Batman, Kentucky Fried Chicken, Anthony Levandowski, Donald Trump, Apple iPhone, Airbnb, Blackmore, Stripe, Titan, Ford, Volkswagen, RJ Scaringe, Peterbilt Motors Company, The Volvo Group, Continental AG, Dara KhosrowshahiLinks:Connect with Chris UrmsonXLinkedInConnect with JoubinXLinkedInEmail: grit@kleinerperkins.com Learn more about Kleiner Perkins

Chris Anderson can't talk a lot about what he is up to these days. At least on camera. His LinkedIn profile says he's currently an Engineer at “Stealth". Prior to this current professional opacity, he was at Kitty Hawk, the electric aircraft maker founded by Sebastian Thrun (legendary Stanford Professor and former lead of Google's self-driving car team that led to Waymo) and backed by Google Co-founder, Larry Page. I became familiar with Chris while he was leading Wired Magazine as Editor-in-Chief. His work there was groundbreaking and set much of the pace, tone, and agenda for the early days of Web 2.0 and the Maker movement. After seeing a TedX talk about a side hustle he had selling cellophane bags of electrical parts and open source autopilots for DIY Drones I slid into his DM's.There is a lot of buzz around drones today, but note the date on that DM — November 3rd, 2010. Little did I know at the time, that this little drone business was just beginning to grow from Chris and his kids packing orders at their dinner table to a proper manufacturing and distribution center along the border of Mexico. As things happened, that DM turned into a conversation that turned into an investment in a company, 3D Robotics, that took Chris away from Wired and into the uncharted worlds of manufacturing, consumer hardware, and defense tech. He was early and 3DR didn't play out the way that we'd all hoped but it laid the foundations for much of what he's working on now — even though he can't talk much about that publicly.To say Chris has a knack for living in the future would be a massive understatement. In this conversation we unpack his process for exploring possible futures — spoiler: Chris has started writing science fiction as a way to explore complex technological implications. He writes a book a month, using fiction as a computational tool to play out scenarios with artificial agents and see where they lead. We get into what he got right and what he got wrong about drones specifically and defense tech more broadly. And we discuss the culture of Silicon Valley, where we spar a bit on the amount of waste and wandering built into the system that ultimately leads to so many unexpected breakthroughs. Since that first DM, he has become a dear friend, coconspirator, and sounding board for me. The unedited conversation here went on for nearly 3 hours (which reminds me that we really do need an “indie uncut” channel) but that's the kind of person Chris is — generous in sharing his time, ideas, and insights. I hope you enjoy listening as much as we enjoyed recording this one.

Der Tag in NRW: NRW verschärft Regeln zur Rückführung Ausreisepflichtiger; Familie Refai aus Syrien - 10 Jahre in Dortmund; NRW will Förderung der Kinderwunsch-Behandlung streichen; Münster erprobt Nebeneinander von Drogenszene und Freizeitspaß; NABU-NRW wirft Schwarz-Grün Versagen vor; Berlin oder Duisburg - Wer hat die Currywurst erfunden?; Sebastian Thrun und die Künstliche Intelligenz; Pinke Hennen trainieren im Drachenboot; Moderation: Wiebke Dumpe Von WDR 5.

In this conversation, we have an illuminating discussion with Waymo co-CEO Dmitri Dolgov moderated by Sebastian Thrun who started the Google Self-Driving Car project back in the day, and is also the founder of GoogleX, Google Brain, Waymo and Udacity. Tune in as they dive into the story behind Waymo's fully autonomous cars, and the road that lies ahead in this fascinating industry that is changing the way we move in the world.

Tech entrepreneur Sebastian Thrun talks about his work in Silicon Valley and the future of artificial intelligence. Thrun, formerly a vice president at Google, is the founder or co-founder of Google X (R&D), Waymo (self-driving cars), Google Brain (AI), Kitty Hawk (flying vehicles), and Udacity (online learning). Learn more about your ad choices. Visit megaphone.fm/adchoices

Tech entrepreneur Sebastian Thrun talks about his work in Silicon Valley and the future of artificial intelligence. Thrun, formerly a vice president at Google, is the founder or co-founder of Google X (R&D), Waymo (self-driving cars), Google Brain (AI), Kitty Hawk (flying vehicles), and Udacity (online learning). Learn more about your ad choices. Visit megaphone.fm/adchoices

LG 清空塔 | 雙機一體，清而易舉！吸塵器x掃地機─分進合擊！二合一省空間，雙機自動除塵。全球首發上市，預購送除蟎吸頭https://fstry.pse.is/5kg5w5 —— 以上為播客煮與 Firstory Podcast 廣告 —— ------------------------------- 通勤學英語VIP加值內容與線上課程 ------------------------------- 通勤學英語VIP訂閱方案：https://open.firstory.me/join/15minstoday 社會人核心英語有聲書課程連結：https://15minsengcafe.pse.is/554esm ------------------------------- 15Mins.Today 相關連結 ------------------------------- 歡迎針對這一集留言你的想法： 留言連結 主題投稿/意見回覆 : ask15mins@gmail.com 官方網站：www.15mins.today 加入Clubhouse直播室：https://15minsengcafe.pse.is/46hm8k 訂閱YouTube頻道：https://15minsengcafe.pse.is/3rhuuy 商業合作/贊助來信：15minstoday@gmail.com ------------------------------- 以下是此單集逐字稿 (播放器有不同字數限制，完整文稿可到官網) ------------------------------- Topic: In Race for Tuition-Free College, New Mexico Stakes a Claim As universities across the United States face steep enrollment declines, New Mexico's government is embarking on a pioneering experiment to fight that trend: tuition-free higher education for all state residents. 隨著美國各地大學入學人數急劇下滑，新墨西哥州政府正著手進行一項開創性實驗來應對這一趨勢：為全州居民提供免學費高等教育。 After President Joe Biden's plan for universal free community college failed to gain traction in Congress, New Mexico, one of the nation's poorest states, has emerged with perhaps the most ambitious plans as states scramble to come up with their own initiatives. 在美國總統拜登的全民免費社區大學計畫未能獲得國會支持後，美國最窮的州之一新墨西哥州提出的計畫，可能是各州爭相提出行動倡議中最具雄心的一個。 A new state law approved in a rare show of bipartisanship allocates almost 1% of the state's budget toward covering tuition and fees at public colleges and universities, community colleges and tribal colleges. All state residents from new high school graduates to adults enrolling part-time will be eligible regardless of family income. The program is also open to immigrants regardless of their immigration status. 一項新的州法在兩黨罕見合作下通過，將州預算的1%用於支付公立大學、社區大學與部落學院的學費。所有州民，從剛畢業的高中生到參加兼職教育的成人都有資格參加，無論家庭收入。該計畫也向移民開放，無論他們的移民身分如何。 Some legislators and other critics question whether there should have been income caps and whether the state, newly flush with oil and gas revenue, can secure long-term funding to support the program beyond its first year. The legislation, which seeks to treat college as a public resource similar to primary and secondary education, takes effect in July. 一些議員和其他批評人士質疑是否應設所得限制，以及剛獲大量石油與天然氣收入的該州是否能在計畫實施第一年後，獲得長期資金支持。這項立法將於7月生效，旨在將大學視為與中小學教育類似的公共資源。 Although nearly half the states have embraced similar initiatives that seek to cover at least some tuition expenses for some students, New Mexico's law goes further by covering tuition and fees before other scholarships and sources of financial aid are applied, enabling students to use those other funds for expenses such as lodging, food or child care. 儘管近半的州已採取類似舉措，想幫一些學生支付至少部分學費和雜費，新墨西哥州法律更進一步，在申請其他獎學金和學費補助前，先支付學雜費，讓學生能使用其他資金，支付如住宿、食物或兒童照顧等費用。 “The New Mexico program is very close to ideal,” said Michael Dannenberg, vice president of strategic initiatives and higher education policy at the nonprofit advocacy group Education Reform Now. Considering the state's income levels and available resources, he added that New Mexico's program is among the most generous in the country. 非營利倡議組織Education Reform Now策略倡議暨高教政策副總裁丹能貝格說：「新墨西哥的計畫非常貼近理想。」他表示，考量收入水準與可用資源，新墨西哥州的計畫是全美最慷慨的。 Dannenberg emphasized that New Mexico is going beyond what larger, more prosperous states like Washington and Tennessee have already done. Programs in other states often limit tuition assistance to community colleges, exclude some residents because of family income or impose conditions requiring students to work part time. 丹能貝格強調，新墨西哥州正超越華盛頓和田納西這些更大、更繁榮的州所做的事。其他州通常限制對社區大學的學費補助，因家庭收入排除一些州民，或要求學生兼職。Source article: https://udn.com/news/story/6904/6329103 Next Article Topic: Colleges Slash Budgets in the Pandemic,With ‘Nothing Off-Limits' Ohio Wesleyan University is eliminating 18 majors. The University of Florida's trustees last month took the first steps toward letting the school furlough faculty. The University of California, Berkeley, has paused admissions to its doctoral programs in anthropology, sociology and art history. 美國俄亥俄衛斯理大學取消了18個科系。佛州大學董事會9月採取初步措施，目標是讓校方有權放教師無薪假。柏克萊加州大學則暫停招收人類學、社會學和藝術史的博士班學生。 As it resurges across the country, the coronavirus is forcing universities large and small to make deep and possibly lasting cuts to close widening budget shortfalls. By one estimate, the pandemic has cost colleges at least $120 billion, with even Harvard University, despite its $41.9 billion endowment, reporting a $10 million deficit that has prompted belt tightening. 由於全美各地新冠肺炎疫情再度惡化，美國各大學不論規模大小，都被迫大砍支出，以彌補逐漸擴大的預算缺口，刪減的支出可能長期都不會恢復。有人估計，疫情至少使美國各大學合計損失1200億美元，就連坐擁419億美元辦學基金的哈佛大學也出現1000萬美元預算赤字，被迫勒緊褲帶。 The persistence of the economic downturn is taking a devastating financial toll, pushing many to lay off or furlough employees, delay graduate admissions and even cut or consolidate core programs like liberal arts departments. 經濟持續疲軟造成極其嚴重的財務災情，迫使許多大學裁員或放無薪假，推遲研究所學生入學，甚至取消或合併文科等核心學程。 The University of South Florida announced last month that its College of Education would become a graduate school only, phasing out undergraduate education degrees to help close a $6.8 million budget gap. In Ohio, the University of Akron, citing the coronavirus, successfully invoked a clause in its collective-bargaining agreement in September to supersede tenure rules and lay off 97 unionized faculty members. 南佛州大學上個月宣布，其教育學院將只留下研究所，分階段取消大學部，以彌補680萬美元的預算缺口。在俄亥俄州，艾克朗大學以疫情為由，在9月成功援用團體協約一項條款取代任期規則，裁掉97名加入工會的教師。 “We haven't seen a budget crisis like this in a generation,” said Robert Kelchen, a Seton Hall University associate professor of higher education who has been tracking the administrative response to the pandemic. “There's nothing off-limits at this point.” 西東大學高等教育副教授柯爾欽一直在關注校方對疫情的反應，他說：「這是一個世代以來從未見過的預算危機，在這種關頭，沒有什麼不能碰。」 Even before the pandemic, colleges and universities were grappling with a growing financial crisis, brought on by years of shrinking state support, declining enrollment, and student concerns with skyrocketing tuition and burdensome debt. Now the coronavirus has amplified the financial trouble systemwide, though elite, well-endowed colleges seem sure to weather it with far less pain. 早在疫情爆發前，美國大專院校就為日益嚴重的財務危機而掙扎，原因是州政府補助日漸減少，學生註冊數下滑而且介意學費高漲和學貸負擔沉重，如今，疫情擴大了整個高教體系財務問題，不過，辦學基金厚實的菁英大學似乎可度過難關，且承受的痛苦會少得多。 “We have been in aggressive recession management for 12 years — probably more than 12 years,” Daniel Greenstein, chancellor of the Pennsylvania State System of Higher Education, told his board of governors as they voted to forge ahead with a proposal to merge a half-dozen small schools into two academic entities. 賓州高等教育體系董事會表決通過，大力推動將6個小規模學院併為兩個學術單位，當時總校長葛林斯坦對董事會說：「我們積極從事於衰退問題管理已有12年，應該還不止12年。」 Source article: https://paper.udn.com/udnpaper/POH0067/359091/web/ Next Article Topic: Remember the MOOCs? After Near-Death, They're Booming Sandeep Gupta, a technology manager in California, sees the economic storm caused by the coronavirus as a time “to try to future-proof your working life.” So he is taking an online course in artificial intelligence. 美國加州科技業經理古普塔認為，新冠肺炎引發的經濟風暴是「防止職業生涯被未來淘汰」的時機，所以修讀了一門關於人工智慧的線上課程。 Dr. Robert Davidson, an emergency-room physician in Michigan, says the pandemic has cast “a glaring light on the shortcomings of our public health infrastructure.” So he is pursuing an online master's degree in public health. 密西根州急診室醫師戴維森說，疫情「使我們公衛基礎設施的弱點顯而易見」，所以他在修讀線上公衛碩士學位。 Children and college students aren't the only ones turning to online education during the coronavirus pandemic. Millions of adults have signed up for online classes in the past two months, too — a jolt that could signal a renaissance for big online learning networks that had struggled for years. 在新冠肺炎大流行期間轉而接受線上教育者，不限於兒童和大學生。過去兩個月，數以百萬計的成人也註冊參加線上課程，這令人驚訝的事實可能意味苦撐多年的大型線上學習網路即將再起。 Coursera, in which Gupta and Davidson enrolled, added 10 million new users from mid-March to mid-May, seven times the pace of new sign-ups in the previous year. Enrollments at edX and Udacity, two smaller education sites, have jumped by similar multiples. 古普塔與戴維森註冊的Coursera，從3月中旬到5月中旬增加1000萬新用戶，是去年同期新增註冊人數的七倍。edX與Udacity這兩個規模較小的教育網站，新註冊人數也以類似倍數暴增。 “Crises lead to accelerations, and this is best chance ever for online learning,” said Sebastian Thrun, a co-founder and chairman of Udacity. Udacity共同創辦人兼董事長史朗說：「危機導致改變加速發生，這是線上學習業未曾遇過的最佳良機。」 Coursera, Udacity and edX sprang up nearly a decade ago as high-profile university experiments known as MOOCs, for massive open online courses. They were portrayed as tech-fueled insurgents destined to disrupt the antiquated ways of traditional higher education. But few people completed courses, grappling with the same challenges now facing students forced into distance learning because of the pandemic. Screen fatigue sets in, and attention strays. Coursera、Udacity和edX近十年前出現，嘗試與大學合作推出線上課程而備受矚目，這類課程名為 「大規模開放線上課程」，簡稱「磨課師」。這種課程被描述為獲得科技支持的反叛者，意在顛覆傳統高等教育過時的授課方式。不過，很少有人能修完課程，這些人窮於應付的挑戰，與目前因為疫情被迫遠距學習的學生一樣。長時間盯著螢幕造成疲勞，而且注意力難以集中。 But the online ventures adapted through trial and error, gathering lessons that could provide a road map for school districts and universities pushed online. The instructional ingredients of success, the sites found, include short videos of six minutes or less, interspersed with interactive drills and tests; online forums where students share problems and suggestions; and online mentoring and tutoring. 不過這些線上企業透過反覆試驗來調整，並且積聚了可供被迫線上授課的學區和大學參考的知識和經驗。這些網站發現，線上授課成功的要素包括：短片時間不超過6分鐘，穿插互動練習和測驗；設立線上論壇，讓學生提出問題和建議；並提供線上指導和輔導。 A few top-tier universities, such as the University of Michigan and the Georgia Institute of Technology, offer some full degree programs through the online platforms. 有幾所頂尖大學，如密西根大學和喬治亞理工學院，透過這些線上平台提供一些正式學位學程。 While those academic programs are available, the online schools have tilted toward skills-focused courses that match student demand and hiring trends. 這些線上學校雖提供學術性學程，卻更傾向開設符合學生需要和雇用趨勢的技能課程。 The COVID-19 effect on online learning could broaden the range of popular subjects, education experts say. But so far, training for the tech economy is where the digital-learning money lies. With more of work and everyday life moving online — some of it permanently — that will probably not change. 教育專家指出，新冠肺炎可能會使線上課程熱門科目範圍變得更廣。不過到目前為止，針對科技經濟提供的訓練課程，才是數位教學業的金雞母。隨著更多的工作和日常生活轉移到線上進行，有些是永遠轉到線上，這種情況大概不會改變。 Source articles: https://paper.udn.com/udnpaper/POH0067/354879/web/

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New Pulse of AI Season Six Podcast Episode! On this podcast Host Jason Stoughton is joined by hot AI start-up Crossing Minds founder and CEO Alexandre Robicquet to talk about their breakthrough in behavior-based recommendations, which enable businesses to provide highly relevant recommendations to each user within a couple of clicks - all without using personal data!  Crossing Minds was started by world-renowned AI pioneers, including Dr. Sebastian Thrun, Dr. Emile Contal and Alexandre Robicquet. Get insights and the latest news by following Jason Stoughton on Twitter (x) @thepulseofai   

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歡迎留言告訴我們你對這一集的想法： https://open.firstory.me/user/cl81kivnk00dn01wffhwxdg2s/comments Topic: In Race for Tuition-Free College, New Mexico Stakes a Claim As universities across the United States face steep enrollment declines, New Mexico's government is embarking on a pioneering experiment to fight that trend: tuition-free higher education for all state residents. 隨著美國各地大學入學人數急劇下滑，新墨西哥州政府正著手進行一項開創性實驗來應對這一趨勢：為全州居民提供免學費高等教育。 + Sure? After President Joe Biden's plan for universal free community college failed to gain traction in Congress, New Mexico, one of the nation's poorest states, has emerged with perhaps the most ambitious plans as states scramble to come up with their own initiatives. 在美國總統拜登的全民免費社區大學計畫未能獲得國會支持後，美國最窮的州之一新墨西哥州提出的計畫，可能是各州爭相提出行動倡議中最具雄心的一個。 A new state law approved in a rare show of bipartisanship allocates almost 1% of the state's budget toward covering tuition and fees at public colleges and universities, community colleges and tribal colleges. All state residents from new high school graduates to adults enrolling part-time will be eligible regardless of family income. The program is also open to immigrants regardless of their immigration status. 一項新的州法在兩黨罕見合作下通過，將州預算的1%用於支付公立大學、社區大學與部落學院的學費。所有州民，從剛畢業的高中生到參加兼職教育的成人都有資格參加，無論家庭收入。該計畫也向移民開放，無論他們的移民身分如何。 Some legislators and other critics question whether there should have been income caps and whether the state, newly flush with oil and gas revenue, can secure long-term funding to support the program beyond its first year. The legislation, which seeks to treat college as a public resource similar to primary and secondary education, takes effect in July. 一些議員和其他批評人士質疑是否應設所得限制，以及剛獲大量石油與天然氣收入的該州是否能在計畫實施第一年後，獲得長期資金支持。這項立法將於7月生效，旨在將大學視為與中小學教育類似的公共資源。 Although nearly half the states have embraced similar initiatives that seek to cover at least some tuition expenses for some students, New Mexico's law goes further by covering tuition and fees before other scholarships and sources of financial aid are applied, enabling students to use those other funds for expenses such as lodging, food or child care. 儘管近半的州已採取類似舉措，想幫一些學生支付至少部分學費和雜費，新墨西哥州法律更進一步，在申請其他獎學金和學費補助前，先支付學雜費，讓學生能使用其他資金，支付如住宿、食物或兒童照顧等費用。 “The New Mexico program is very close to ideal,” said Michael Dannenberg, vice president of strategic initiatives and higher education policy at the nonprofit advocacy group Education Reform Now. Considering the state's income levels and available resources, he added that New Mexico's program is among the most generous in the country. 非營利倡議組織Education Reform Now策略倡議暨高教政策副總裁丹能貝格說：「新墨西哥的計畫非常貼近理想。」他表示，考量收入水準與可用資源，新墨西哥州的計畫是全美最慷慨的。 Dannenberg emphasized that New Mexico is going beyond what larger, more prosperous states like Washington and Tennessee have already done. Programs in other states often limit tuition assistance to community colleges, exclude some residents because of family income or impose conditions requiring students to work part time. 丹能貝格強調，新墨西哥州正超越華盛頓和田納西這些更大、更繁榮的州所做的事。其他州通常限制對社區大學的學費補助，因家庭收入排除一些州民，或要求學生兼職。Source article: https://udn.com/news/story/6904/6329103 Next Article Topic: Colleges Slash Budgets in the Pandemic,With ‘Nothing Off-Limits' Ohio Wesleyan University is eliminating 18 majors. The University of Florida's trustees last month took the first steps toward letting the school furlough faculty. The University of California, Berkeley, has paused admissions to its doctoral programs in anthropology, sociology and art history. 美國俄亥俄衛斯理大學取消了18個科系。佛州大學董事會9月採取初步措施，目標是讓校方有權放教師無薪假。柏克萊加州大學則暫停招收人類學、社會學和藝術史的博士班學生。 As it resurges across the country, the coronavirus is forcing universities large and small to make deep and possibly lasting cuts to close widening budget shortfalls. By one estimate, the pandemic has cost colleges at least $120 billion, with even Harvard University, despite its $41.9 billion endowment, reporting a $10 million deficit that has prompted belt tightening. 由於全美各地新冠肺炎疫情再度惡化，美國各大學不論規模大小，都被迫大砍支出，以彌補逐漸擴大的預算缺口，刪減的支出可能長期都不會恢復。有人估計，疫情至少使美國各大學合計損失1200億美元，就連坐擁419億美元辦學基金的哈佛大學也出現1000萬美元預算赤字，被迫勒緊褲帶。 The persistence of the economic downturn is taking a devastating financial toll, pushing many to lay off or furlough employees, delay graduate admissions and even cut or consolidate core programs like liberal arts departments. 經濟持續疲軟造成極其嚴重的財務災情，迫使許多大學裁員或放無薪假，推遲研究所學生入學，甚至取消或合併文科等核心學程。 The University of South Florida announced last month that its College of Education would become a graduate school only, phasing out undergraduate education degrees to help close a $6.8 million budget gap. In Ohio, the University of Akron, citing the coronavirus, successfully invoked a clause in its collective-bargaining agreement in September to supersede tenure rules and lay off 97 unionized faculty members. 南佛州大學上個月宣布，其教育學院將只留下研究所，分階段取消大學部，以彌補680萬美元的預算缺口。在俄亥俄州，艾克朗大學以疫情為由，在9月成功援用團體協約一項條款取代任期規則，裁掉97名加入工會的教師。 “We haven't seen a budget crisis like this in a generation,” said Robert Kelchen, a Seton Hall University associate professor of higher education who has been tracking the administrative response to the pandemic. “There's nothing off-limits at this point.” 西東大學高等教育副教授柯爾欽一直在關注校方對疫情的反應，他說：「這是一個世代以來從未見過的預算危機，在這種關頭，沒有什麼不能碰。」 Even before the pandemic, colleges and universities were grappling with a growing financial crisis, brought on by years of shrinking state support, declining enrollment, and student concerns with skyrocketing tuition and burdensome debt. Now the coronavirus has amplified the financial trouble systemwide, though elite, well-endowed colleges seem sure to weather it with far less pain. 早在疫情爆發前，美國大專院校就為日益嚴重的財務危機而掙扎，原因是州政府補助日漸減少，學生註冊數下滑而且介意學費高漲和學貸負擔沉重，如今，疫情擴大了整個高教體系財務問題，不過，辦學基金厚實的菁英大學似乎可度過難關，且承受的痛苦會少得多。 “We have been in aggressive recession management for 12 years — probably more than 12 years,” Daniel Greenstein, chancellor of the Pennsylvania State System of Higher Education, told his board of governors as they voted to forge ahead with a proposal to merge a half-dozen small schools into two academic entities. 賓州高等教育體系董事會表決通過，大力推動將6個小規模學院併為兩個學術單位，當時總校長葛林斯坦對董事會說：「我們積極從事於衰退問題管理已有12年，應該還不止12年。」 Source article: https://paper.udn.com/udnpaper/POH0067/359091/web/ Next Article Topic: Remember the MOOCs? After Near-Death, They're Booming Sandeep Gupta, a technology manager in California, sees the economic storm caused by the coronavirus as a time “to try to future-proof your working life.” So he is taking an online course in artificial intelligence. 美國加州科技業經理古普塔認為，新冠肺炎引發的經濟風暴是「防止職業生涯被未來淘汰」的時機，所以修讀了一門關於人工智慧的線上課程。 Dr. Robert Davidson, an emergency-room physician in Michigan, says the pandemic has cast “a glaring light on the shortcomings of our public health infrastructure.” So he is pursuing an online master's degree in public health. 密西根州急診室醫師戴維森說，疫情「使我們公衛基礎設施的弱點顯而易見」，所以他在修讀線上公衛碩士學位。 Children and college students aren't the only ones turning to online education during the coronavirus pandemic. Millions of adults have signed up for online classes in the past two months, too — a jolt that could signal a renaissance for big online learning networks that had struggled for years. 在新冠肺炎大流行期間轉而接受線上教育者，不限於兒童和大學生。過去兩個月，數以百萬計的成人也註冊參加線上課程，這令人驚訝的事實可能意味苦撐多年的大型線上學習網路即將再起。 Coursera, in which Gupta and Davidson enrolled, added 10 million new users from mid-March to mid-May, seven times the pace of new sign-ups in the previous year. Enrollments at edX and Udacity, two smaller education sites, have jumped by similar multiples. 古普塔與戴維森註冊的Coursera，從3月中旬到5月中旬增加1000萬新用戶，是去年同期新增註冊人數的七倍。edX與Udacity這兩個規模較小的教育網站，新註冊人數也以類似倍數暴增。 “Crises lead to accelerations, and this is best chance ever for online learning,” said Sebastian Thrun, a co-founder and chairman of Udacity. Udacity共同創辦人兼董事長史朗說：「危機導致改變加速發生，這是線上學習業未曾遇過的最佳良機。」 Coursera, Udacity and edX sprang up nearly a decade ago as high-profile university experiments known as MOOCs, for massive open online courses. They were portrayed as tech-fueled insurgents destined to disrupt the antiquated ways of traditional higher education. But few people completed courses, grappling with the same challenges now facing students forced into distance learning because of the pandemic. Screen fatigue sets in, and attention strays. Coursera、Udacity和edX近十年前出現，嘗試與大學合作推出線上課程而備受矚目，這類課程名為 「大規模開放線上課程」，簡稱「磨課師」。這種課程被描述為獲得科技支持的反叛者，意在顛覆傳統高等教育過時的授課方式。不過，很少有人能修完課程，這些人窮於應付的挑戰，與目前因為疫情被迫遠距學習的學生一樣。長時間盯著螢幕造成疲勞，而且注意力難以集中。 But the online ventures adapted through trial and error, gathering lessons that could provide a road map for school districts and universities pushed online. The instructional ingredients of success, the sites found, include short videos of six minutes or less, interspersed with interactive drills and tests; online forums where students share problems and suggestions; and online mentoring and tutoring. 不過這些線上企業透過反覆試驗來調整，並且積聚了可供被迫線上授課的學區和大學參考的知識和經驗。這些網站發現，線上授課成功的要素包括：短片時間不超過6分鐘，穿插互動練習和測驗；設立線上論壇，讓學生提出問題和建議；並提供線上指導和輔導。 A few top-tier universities, such as the University of Michigan and the Georgia Institute of Technology, offer some full degree programs through the online platforms. 有幾所頂尖大學，如密西根大學和喬治亞理工學院，透過這些線上平台提供一些正式學位學程。 While those academic programs are available, the online schools have tilted toward skills-focused courses that match student demand and hiring trends. 這些線上學校雖提供學術性學程，卻更傾向開設符合學生需要和雇用趨勢的技能課程。 The COVID-19 effect on online learning could broaden the range of popular subjects, education experts say. But so far, training for the tech economy is where the digital-learning money lies. With more of work and everyday life moving online — some of it permanently — that will probably not change. 教育專家指出，新冠肺炎可能會使線上課程熱門科目範圍變得更廣。不過到目前為止，針對科技經濟提供的訓練課程，才是數位教學業的金雞母。隨著更多的工作和日常生活轉移到線上進行，有些是永遠轉到線上，這種情況大概不會改變。 Source articles: https://paper.udn.com/udnpaper/POH0067/354879/web/ Powered by Firstory Hosting

Sebastian Thrun is a computer scientist who is regarded as one of the pioneers in the field of artificial intelligence. He has been involved in projects such as creating self-driving cars and helping to start Google's DeepMind division. In this episode, Lexman interviews him about the role of coatracks in language learning and pronunciamentoes in valve engineering.

The Lexman Artificial Podcast is back and this time Sebastian Thrun is on the guest express. The pair chat about newscasting and gatherings, but it's all downhill from there as the conversation quickly takes a dark turn.

Wie gelang Google der Durchbruch beim autonomen Fahren? Ist das Silicon Valley noch innovativ? Und warum revolutioniert Online-Lernen die Welt? Unser Host Thomas Ramge spricht mit Prof. Dr. Sebastian Thrun, KI-Forscher, Gründer von Udacity und Sprunginnovator in Serie.

Lexman interviews Sebastian Thrun, the inventor of Google Glass and CEO of Udacity. They discuss the future of technology and how it will impact society.

In this episode, Sebastian Thrun discusses his book "AIMLESS: How extroverts profit from their lack of focus."

Sebastian tells us about his adventures in upriver farming, his lessons learned and the things heハッキリと考えていた事はまったく無かった事。 そりゃあ、走れば違いないだろう。

Lexman is having a terrible day. First, he stubs his toe on a rock and cries out in pain. Then, his computer crashes and he has to start from scratch. Finally, his wife tells him that she's been seeing another man and he doesn't know how to respond. He shares his woes with Sebastian Thrun, a computer scientist who has achieved some amazing things. Sebastian shares with Lexman some of the Lessons Learned in his life, including the importance of hustle and how to bounce back from tough times.

Lexman interviews Sebastian Thrun about his work on dopatta and vulpicides.

Varun is the cofounder and CTO of AKASA, which develops purpose-built AI and automation solutions for the healthcare industry.Building a physics simulator for a robot helicopter as a student at Stanford helped Varun connect his interests in physics, machine learning, and AI. Check out that project here. His instructor? Andrew Ng.Along with Ng, Varun was lucky to connect with some brilliant AI folks during his time at Stanford, like Jeffrey Dean, Head of Google AI; Daphne Koller, cofounder of Coursera; and Sebastian Thrun, cofounder of Udacity.When Varun earned his PhD in computer science and AI, Koller and Thrun served as his advisors. You can read their work here.In 2017, Udacity acquired Varun's startup, CloudLabs, the company behind Terminal.  Connect with Varun on LinkedIn.Today's Lifeboat badge goes to user John Woo for their answer to the question Update the row that has the current highest (maximum) value of one field.

Summary Machine learning is a transformative tool for the organizations that can take advantage of it. While the frameworks and platforms for building machine learning applications are becoming more powerful and broadly available, there is still a significant investment of time, money, and talent required to take full advantage of it. In order to reduce that barrier further Adam Oliner and Brian Calvert, along with their other co-founders, started Graft. In this episode Adam and Brian explain how they have built a platform designed to empower everyone in the business to take part in designing and building ML projects, while managing the end-to-end workflow required to go from data to production. Announcements Hello and welcome to the Machine Learning Podcast, the podcast about machine learning and how to bring it from idea to delivery. Predibase is a low-code ML platform without low-code limits. Built on top of our open source foundations of Ludwig and Horovod, our platform allows you to train state-of-the-art ML and deep learning models on your datasets at scale. Our platform works on text, images, tabular, audio and multi-modal data using our novel compositional model architecture. We allow users to operationalize models on top of the modern data stack, through REST and PQL – an extension of SQL that puts predictive power in the hands of data practitioners. Go to themachinelearningpodcast.com/predibase today to learn more and try it out! Building good ML models is hard, but testing them properly is even harder. At Deepchecks, they built an open-source testing framework that follows best practices, ensuring that your models behave as expected. Get started quickly using their built-in library of checks for testing and validating your model’s behavior and performance, and extend it to meet your specific needs as your model evolves. Accelerate your machine learning projects by building trust in your models and automating the testing that you used to do manually. Go to themachinelearningpodcast.com/deepchecks today to get started! Your host is Tobias Macey and today I’m interviewing Brian Calvert and Adam Oliner about Graft, a cloud-native platform designed to simplify the work of applying AI to business problems Interview Introduction How did you get involved in machine learning? Can you describe what Graft is and the story behind it? What is the core thesis of the problem you are targeting? How does the Graft product address that problem? Who are the personas that you are focused on working with both now in your early stages and in the future as you evolve the product? What are the capabilities that can be unlocked in different organizations by reducing the friction and up-front investment required to adopt ML/AI? What are the user-facing interfaces that you are focused on providing to make that adoption curve as shallow as possible? What are some of the unavoidable bits of complexity that need to be surfaced to the end user? Can you describe the infrastructure and platform design that you are relying on for the Graft product? What are some of the emerging "best practices" around ML/AI that you have been able to build on top of? As new techniques and practices are discovered/introduced how are you thinking about the adoption process and how/when to integrate them into the Graft product? What are some of the new engineering challenges that you have had to tackle as a result of your specific product? Machine learning can be a very data and compute intensive endeavor. How are you thinking about scalability in a multi-tenant system? Different model and data types can be widely divergent in terms of the cost (monetary, time, compute, etc.) required. How are you thinking about amortizing vs. passing through those costs to the end user? Can you describe the adoption/integration process for someone using Graft? Once they are onboarded and they have connected to their various data sources, what is the workflow for someone to apply ML capabilities to their problems? One of the challenges about the current state of ML capabilities and adoption is understanding what is possible and what is impractical. How have you designed Graft to help identify and expose opportunities for applying ML within the organization? What are some of the challenges of customer education and overall messaging that you are working through? What are the most interesting, innovative, or unexpected ways that you have seen Graft used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on Graft? When is Graft the wrong choice? What do you have planned for the future of Graft? Contact Info Brian LinkedIn Adam LinkedIn Parting Question From your perspective, what is the biggest barrier to adoption of machine learning today? Closing Announcements Thank you for listening! Don’t forget to check out our other shows. The Data Engineering Podcast covers the latest on modern data management. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes. If you’ve learned something or tried out a project from the show then tell us about it! Email hosts@themachinelearningpodcast.com) with your story. To help other people find the show please leave a review on iTunes and tell your friends and co-workers Links Graft High Energy Particle Physics LHC Cruise Slack Splunk Marvin Minsky Patrick Henry Winston AI Winter Sebastian Thrun DARPA Grand Challenge Higss Boson Supersymmetry Kinematics Transfer Learning Foundation Models ML Embeddings BERT Airflow Dagster Prefect Dask Kubeflow MySQL PostgreSQL Snowflake Redshift S3 Kubernetes Multi-modal models Multi-task models Magic: The Gathering The intro and outro music is from Hitman’s Lovesong feat. Paola Graziano by The Freak Fandango Orchestra/[CC BY-SA 3.0](https://creativecommons.org/licenses/by-sa/3.0/?utm_source=rss&utm_medium=rss

Jacky and Sebastian talk about their experience with lumpectomies. They recall all the disgusting details, from the terrible smell to the terrible aftermath.

Sebastian Thrun is a computer scientist, entrepreneur and author. He is the founder of Google Ventures, co-founder and managing director of artificial intelligence company fly0, and chairman of the board of trustees of the Singularitynet Foundation. In 2009, he was named one of theTIME 100 most influential people in the world. In this episode, Lexman interviews Sebastian Thrun about his love for francophilia, travelling to Nepal and the parallels between pursuing concordances and chasing after assholes.

Sebastian Thrun, co-founder and CEO of Google's home-grown robotics company Nest, discusses the future of robotics and the ubiquitous machines that will soon be in every household. He explains the major challenges and opportunities posed by this burgeoning technology.

Topic: In Race for Tuition-Free College, New Mexico Stakes a Claim   As universities across the United States face steep enrollment declines, New Mexico's government is embarking on a pioneering experiment to fight that trend: tuition-free higher education for all state residents. 隨著美國各地大學入學人數急劇下滑，新墨西哥州政府正著手進行一項開創性實驗來應對這一趨勢：為全州居民提供免學費高等教育。 After President Joe Biden's plan for universal free community college failed to gain traction in Congress, New Mexico, one of the nation's poorest states, has emerged with perhaps the most ambitious plans as states scramble to come up with their own initiatives. 在美國總統拜登的全民免費社區大學計畫未能獲得國會支持後，美國最窮的州之一新墨西哥州提出的計畫，可能是各州爭相提出行動倡議中最具雄心的一個。 A new state law approved in a rare show of bipartisanship allocates almost 1% of the state's budget toward covering tuition and fees at public colleges and universities, community colleges and tribal colleges. All state residents from new high school graduates to adults enrolling part-time will be eligible regardless of family income. The program is also open to immigrants regardless of their immigration status. 一項新的州法在兩黨罕見合作下通過，將州預算的1%用於支付公立大學、社區大學與部落學院的學費。所有州民，從剛畢業的高中生到參加兼職教育的成人都有資格參加，無論家庭收入。該計畫也向移民開放，無論他們的移民身分如何。 Some legislators and other critics question whether there should have been income caps and whether the state, newly flush with oil and gas revenue, can secure long-term funding to support the program beyond its first year. The legislation, which seeks to treat college as a public resource similar to primary and secondary education, takes effect in July. 一些議員和其他批評人士質疑是否應設所得限制，以及剛獲大量石油與天然氣收入的該州是否能在計畫實施第一年後，獲得長期資金支持。這項立法將於7月生效，旨在將大學視為與中小學教育類似的公共資源。 Although nearly half the states have embraced similar initiatives that seek to cover at least some tuition expenses for some students, New Mexico's law goes further by covering tuition and fees before other scholarships and sources of financial aid are applied, enabling students to use those other funds for expenses such as lodging, food or child care. 儘管近半的州已採取類似舉措，想幫一些學生支付至少部分學費和雜費，新墨西哥州法律更進一步，在申請其他獎學金和學費補助前，先支付學雜費，讓學生能使用其他資金，支付如住宿、食物或兒童照顧等費用。 “The New Mexico program is very close to ideal,” said Michael Dannenberg, vice president of strategic initiatives and higher education policy at the nonprofit advocacy group Education Reform Now. Considering the state's income levels and available resources, he added that New Mexico's program is among the most generous in the country. 非營利倡議組織Education Reform Now策略倡議暨高教政策副總裁丹能貝格說：「新墨西哥的計畫非常貼近理想。」他表示，考量收入水準與可用資源，新墨西哥州的計畫是全美最慷慨的。 Dannenberg emphasized that New Mexico is going beyond what larger, more prosperous states like Washington and Tennessee have already done. Programs in other states often limit tuition assistance to community colleges, exclude some residents because of family income or impose conditions requiring students to work part time. 丹能貝格強調，新墨西哥州正超越華盛頓和田納西這些更大、更繁榮的州所做的事。其他州通常限制對社區大學的學費補助，因家庭收入排除一些州民，或要求學生兼職。Source article: https://udn.com/news/story/6904/6329103   Next Article   Topic: Colleges Slash Budgets in the Pandemic,With ‘Nothing Off-Limits' Ohio Wesleyan University is eliminating 18 majors. The University of Florida's trustees last month took the first steps toward letting the school furlough faculty. The University of California, Berkeley, has paused admissions to its doctoral programs in anthropology, sociology and art history. 美國俄亥俄衛斯理大學取消了18個科系。佛州大學董事會9月採取初步措施，目標是讓校方有權放教師無薪假。柏克萊加州大學則暫停招收人類學、社會學和藝術史的博士班學生。 As it resurges across the country, the coronavirus is forcing universities large and small to make deep and possibly lasting cuts to close widening budget shortfalls. By one estimate, the pandemic has cost colleges at least $120 billion, with even Harvard University, despite its $41.9 billion endowment, reporting a $10 million deficit that has prompted belt tightening. 由於全美各地新冠肺炎疫情再度惡化，美國各大學不論規模大小，都被迫大砍支出，以彌補逐漸擴大的預算缺口，刪減的支出可能長期都不會恢復。有人估計，疫情至少使美國各大學合計損失1200億美元，就連坐擁419億美元辦學基金的哈佛大學也出現1000萬美元預算赤字，被迫勒緊褲帶。 The persistence of the economic downturn is taking a devastating financial toll, pushing many to lay off or furlough employees, delay graduate admissions and even cut or consolidate core programs like liberal arts departments. 經濟持續疲軟造成極其嚴重的財務災情，迫使許多大學裁員或放無薪假，推遲研究所學生入學，甚至取消或合併文科等核心學程。 The University of South Florida announced last month that its College of Education would become a graduate school only, phasing out undergraduate education degrees to help close a $6.8 million budget gap. In Ohio, the University of Akron, citing the coronavirus, successfully invoked a clause in its collective-bargaining agreement in September to supersede tenure rules and lay off 97 unionized faculty members. 南佛州大學上個月宣布，其教育學院將只留下研究所，分階段取消大學部，以彌補680萬美元的預算缺口。在俄亥俄州，艾克朗大學以疫情為由，在9月成功援用團體協約一項條款取代任期規則，裁掉97名加入工會的教師。 “We haven't seen a budget crisis like this in a generation,” said Robert Kelchen, a Seton Hall University associate professor of higher education who has been tracking the administrative response to the pandemic. “There's nothing off-limits at this point.” 西東大學高等教育副教授柯爾欽一直在關注校方對疫情的反應，他說：「這是一個世代以來從未見過的預算危機，在這種關頭，沒有什麼不能碰。」 Even before the pandemic, colleges and universities were grappling with a growing financial crisis, brought on by years of shrinking state support, declining enrollment, and student concerns with skyrocketing tuition and burdensome debt. Now the coronavirus has amplified the financial trouble systemwide, though elite, well-endowed colleges seem sure to weather it with far less pain. 早在疫情爆發前，美國大專院校就為日益嚴重的財務危機而掙扎，原因是州政府補助日漸減少，學生註冊數下滑而且介意學費高漲和學貸負擔沉重，如今，疫情擴大了整個高教體系財務問題，不過，辦學基金厚實的菁英大學似乎可度過難關，且承受的痛苦會少得多。 “We have been in aggressive recession management for 12 years — probably more than 12 years,” Daniel Greenstein, chancellor of the Pennsylvania State System of Higher Education, told his board of governors as they voted to forge ahead with a proposal to merge a half-dozen small schools into two academic entities. 賓州高等教育體系董事會表決通過，大力推動將6個小規模學院併為兩個學術單位，當時總校長葛林斯坦對董事會說：「我們積極從事於衰退問題管理已有12年，應該還不止12年。」Source article: https://paper.udn.com/udnpaper/POH0067/359091/web/     Next Article   Topic: Remember the MOOCs? After Near-Death, They're Booming Sandeep Gupta, a technology manager in California, sees the economic storm caused by the coronavirus as a time “to try to future-proof your working life.” So he is taking an online course in artificial intelligence. 美國加州科技業經理古普塔認為，新冠肺炎引發的經濟風暴是「防止職業生涯被未來淘汰」的時機，所以修讀了一門關於人工智慧的線上課程。 Dr. Robert Davidson, an emergency-room physician in Michigan, says the pandemic has cast “a glaring light on the shortcomings of our public health infrastructure.” So he is pursuing an online master's degree in public health. 密西根州急診室醫師戴維森說，疫情「使我們公衛基礎設施的弱點顯而易見」，所以他在修讀線上公衛碩士學位。 Children and college students aren't the only ones turning to online education during the coronavirus pandemic. Millions of adults have signed up for online classes in the past two months, too — a jolt that could signal a renaissance for big online learning networks that had struggled for years. 在新冠肺炎大流行期間轉而接受線上教育者，不限於兒童和大學生。過去兩個月，數以百萬計的成人也註冊參加線上課程，這令人驚訝的事實可能意味苦撐多年的大型線上學習網路即將再起。 Coursera, in which Gupta and Davidson enrolled, added 10 million new users from mid-March to mid-May, seven times the pace of new sign-ups in the previous year. Enrollments at edX and Udacity, two smaller education sites, have jumped by similar multiples. 古普塔與戴維森註冊的Coursera，從3月中旬到5月中旬增加1000萬新用戶，是去年同期新增註冊人數的七倍。edX與Udacity這兩個規模較小的教育網站，新註冊人數也以類似倍數暴增。 “Crises lead to accelerations, and this is best chance ever for online learning,” said Sebastian Thrun, a co-founder and chairman of Udacity. Udacity共同創辦人兼董事長史朗說：「危機導致改變加速發生，這是線上學習業未曾遇過的最佳良機。」 Coursera, Udacity and edX sprang up nearly a decade ago as high-profile university experiments known as MOOCs, for massive open online courses. They were portrayed as tech-fueled insurgents destined to disrupt the antiquated ways of traditional higher education. But few people completed courses, grappling with the same challenges now facing students forced into distance learning because of the pandemic. Screen fatigue sets in, and attention strays. Coursera、Udacity和edX近十年前出現，嘗試與大學合作推出線上課程而備受矚目，這類課程名為「大規模開放線上課程」，簡稱「磨課師」。這種課程被描述為獲得科技支持的反叛者，意在顛覆傳統高等教育過時的授課方式。不過，很少有人能修完課程，這些人窮於應付的挑戰，與目前因為疫情被迫遠距學習的學生一樣。長時間盯著螢幕造成疲勞，而且注意力難以集中。 But the online ventures adapted through trial and error, gathering lessons that could provide a road map for school districts and universities pushed online. The instructional ingredients of success, the sites found, include short videos of six minutes or less, interspersed with interactive drills and tests; online forums where students share problems and suggestions; and online mentoring and tutoring. 不過這些線上企業透過反覆試驗來調整，並且積聚了可供被迫線上授課的學區和大學參考的知識和經驗。這些網站發現，線上授課成功的要素包括：短片時間不超過6分鐘，穿插互動練習和測驗；設立線上論壇，讓學生提出問題和建議；並提供線上指導和輔導。 A few top-tier universities, such as the University of Michigan and the Georgia Institute of Technology, offer some full degree programs through the online platforms. 有幾所頂尖大學，如密西根大學和喬治亞理工學院，透過這些線上平台提供一些正式學位學程。 While those academic programs are available, the online schools have tilted toward skills-focused courses that match student demand and hiring trends. 這些線上學校雖提供學術性學程，卻更傾向開設符合學生需要和雇用趨勢的技能課程。 The COVID-19 effect on online learning could broaden the range of popular subjects, education experts say. But so far, training for the tech economy is where the digital-learning money lies. With more of work and everyday life moving online — some of it permanently — that will probably not change. 教育專家指出，新冠肺炎可能會使線上課程熱門科目範圍變得更廣。不過到目前為止，針對科技經濟提供的訓練課程，才是數位教學業的金雞母。隨著更多的工作和日常生活轉移到線上進行，有些是永遠轉到線上，這種情況大概不會改變。Source articles: https://paper.udn.com/udnpaper/POH0067/354879/web/

Blockchain vs crypto currency, WiFi vs Ethernet connection to router, how much bandwidth is enough (looking at required data rates), actual vs theoretical download speeds (always lower), Profiles in IT (Sebastian Thrun, autonomous vehicle pioneer and founder Udacity), innovation according to Sebastian Thrun (an experimentation and learning process), and a new approach to AI (thinking with analogies). This show originally aired on Saturday, May 7, 2022, at 9:00 AM EST on WFED (1500 AM).

Blockchain vs crypto currency, WiFi vs Ethernet connection to router, how much bandwidth is enough (looking at required data rates), actual vs theoretical download speeds (always lower), Profiles in IT (Sebastian Thrun, autonomous vehicle pioneer and founder Udacity), innovation according to Sebastian Thrun (an experimentation and learning process), and a new approach to AI (thinking with analogies). This show originally aired on Saturday, May 7, 2022, at 9:00 AM EST on WFED (1500 AM).

In this episode our guest is Noor Siddiqui, founder and CEO of Orchid. Noor explains her mission behind Orchid helping couples achieve parenthood and healthy babies through genetic risk and single cell testing. We dive deep into the history of reproductive technology. Noor takes us along the journey from old days where birth control was obscene and controversial, to modern days with ultra high resolution genetic testing systems for couples, advanced embryo screening for families going through IVF and single cell sequencing. Understanding genetic risk impacts your lifestyle, your choices and can change the course of any possible diseases. Testing before your child is conceived gives you the best chance of mitigating risk. Couples can safely reduce their future children's genetic risk for the most common diseases and avoid suffering from similar conditions they have dealt with during their own lives. SUPPORT US ON PATREON: https://www.patreon.com/rhyslindmark JOIN OUR DISCORD: https://discord.gg/PDAPkhNxrC Who is Noor Siddiqui? Noor Siddiqui is the Founder and CEO at Orchid, a reproductive technology company which measures genetic predisposition to disease helping families have healthier babies. Before Orchid, she founded Remedy, a digital health company that helped doctors get instant answers from specialists. Noor received an M.S/B.S in Computer Science from Stanford, taught a class there on Reproductive Technology, and did AI and genomics research with Anshul Kundaje and Sebastian Thrun. Topics we touch: Welcome Noor Siddiqui to The Rhys Show: (00:00) Throughline that connects Noor's work / From Thiel fellowship to biotech: (02:50) Learning about interests & becoming more sincere to them: (04:07) Hyper about Orchid: (05:41) A teenager wanting to make “baby making” better : (07:10) Gene therapy vs. IVF/Alzheimer & different perspectives: (13:13) Couple report/method & sequencing tool : (18:06) How Orchid works: (21:24) Associations that are being done: (23:28) Embryo report/screening, how IVF works & sequencing : (26:36) Initial PCR amplification with lots of cells vs with only 5 cells: (33:20) Mentioned resources: Thiel Fellowship: https://thielfellowship.org/ Illumina: https://www.illumina.com/ Connect with Noor Siddiqui: Linkedin: https://www.linkedin.com/in/noorsiddiqui/ Web “Noor Siddiqui”: https://noorsiddiqui.com/about/ Twitter “Noor Siddiqui”: https://twitter.com/noor_siddiqui_ Web “Orchid”: https://www.orchidhealth.com/ Twitter “Orchid”: https://twitter.com/orchidinc

We're carrying on with last week's format as I'm sharing with you some of the core segments from a master's course I've been teaching on the Secrets of Silicon Valley at a university in Barcelona. In this course I am presenting the methods and systems of success that can be replicated anywhere in the world to disrupt any market and achieve success. And yes, I mean anywhere. In this course I have brought in the smartest people I know and asked them for their own secrets of success. This week we'll be talking to Dave Clarke about firing, hiring and finding what you love, as well as some crazy stories from his exceptional career. Let's go… Dave Clark has had what some would describe as an unbelievable, or even unattainable career, having worked with some of the world's greatest entrepreneurs to help them transform their moonshot goals into reality. He has worked with Richard Branson on the Virgin Galactic space program, with Travis Kalanick at Uber and Larry Page and Sebastian Thrun at Kittyhawk. He's now a general partner at EXPA, helping more entrepreneurs make their dreams come true. As you can probably imagine, he has plenty of crazy stories to tell! I'll let Dave share the details of how he ended up on this wild path with you… --- Send in a voice message: https://anchor.fm/ann-hiatt/message Support this podcast: https://anchor.fm/ann-hiatt/support

Read the full transcript here. Why has there been such an explosion of progress in genomics recently? What's the right way to think about how genes affect the likelihood of experiencing certain health outcomes? How can people mitigate genetic risks for their potential children? What sorts of moral obligations (if any) do parents have to mitigate potential genetic risks for their children? How does Orchid's focus differ from other companies in the same space? What is "junk" DNA? What percentage of our genes are identical to our siblings, to other humans, and even to other animals?Noor Siddiqui is the Founder and CEO of Orchid, a reproductive technology company. Prior to Orchid, Noor was an AI researcher at Stanford where she worked on applications of deep learning to genomics with Anshul Kundaje and computer vision applied to medical imaging with Sebastian Thrun. Noor has spoken internationally about her work at the intersection of technology and medicine at events like Milken's Global Conference, WebSummit, and Kaiser Permanente's Executive Leadership Summit. Her work has been covered by The Washington Post, Forbes, TechCrunch, among other outlets. Noor is also a recipient of the Thiel Fellowship, a grant program spawned by Paypal founder and Facebook board member, Peter Thiel, supporting breakthrough technology companies. Noor earned her M.S. and B.S. in Computer Science from Stanford University. Follow her on Twitter, connect with her on LinkedIn, visit her website, or email her at noorsiddiqui@orchidhealth.com. [Read more]

Read the full transcriptWhy has there been such an explosion of progress in genomics recently? What's the right way to think about how genes affect the likelihood of experiencing certain health outcomes? How can people mitigate genetic risks for their potential children? What sorts of moral obligations (if any) do parents have to mitigate potential genetic risks for their children? How does Orchid's focus differ from other companies in the same space? What is "junk" DNA? What percentage of our genes are identical to our siblings, to other humans, and even to other animals?Noor Siddiqui is the Founder and CEO of Orchid, a reproductive technology company. Prior to Orchid, Noor was an AI researcher at Stanford where she worked on applications of deep learning to genomics with Anshul Kundaje and computer vision applied to medical imaging with Sebastian Thrun. Noor has spoken internationally about her work at the intersection of technology and medicine at events like Milken's Global Conference, WebSummit, and Kaiser Permanente's Executive Leadership Summit. Her work has been covered by The Washington Post, Forbes, TechCrunch, among other outlets. Noor is also a recipient of the Thiel Fellowship, a grant program spawned by Paypal founder and Facebook board member, Peter Thiel, supporting breakthrough technology companies. Noor earned her M.S. and B.S. in Computer Science from Stanford University. Follow her on Twitter, connect with her on LinkedIn, visit her website, or email her at noorsiddiqui@orchidhealth.com.

Florida State Senator Jeff Brandes joins Grayson Brulte on The Road To Autonomy Podcast to discuss the big idea and why Florida is the perfect environment to operate autonomous vehicles.The conversation begins with Senator Brandes discussing his experience serving in Operation Iraqi Freedom as a transportation officer. During his time in Iraq, Senator Brandes read Capitalism and Freedom by Milton Friedman. This book had a profound effect on him and changed the way he sees the world, chooses to govern, and propose legislation.Operating convoys in Iraq also had a tremendous impact on Senator Brandes. One that would lead to one Senator Brandes Big Ideas a Florida State Legislator.It would be a lot safer if I did not have to have soldiers in these convoys and they could operate autonomously. – Florida State Senator BrandesAs an incoming State Senator in 2012, Senator Brandes wanted to distinguish himself from a great class of legislators. To do this, he reached into his past experience and embraced a Big Idea – Autonomous Vehicles after watching Sebastian Thrun‘s Google's driverless car TED Talk over a dozen times.There is one big idea in every area of public policy. – Florida State Senator BrandesTo make this Big Idea a reality, Senator Brandes reached out to Google and sought their assistance. The legislation which made testing autonomous vehicles on public roads legal passed unanimously and HB 1207 was signed by Governor Rick Scott in 2012.HB 1207 laid the groundwork for what Florida has become today, the Capital of Autonomous Vehicle deployments and commercialization in North America.Florida has the best laws on the books as it relates to self-driving. We have the best laws on the books as it relates to ride-sharing. – Florida State Senator BrandesInnovative companies have a long history of moving and expanding their operations to Florida from California partly due to regulation. This trend started in earnest when Walt Disney began acquiring land in the 1960's to develop Walt Disney World.Today, history is repeating itself as innovative autonomous vehicle companies such as Argo AI and Luminar are operating in the State. They are creating high-paying jobs and having a positive impact on the economy.You have to be competitive globally, not just amongst the States. What can we do to remove the barriers? Florida has the perfect environment to operate these types of vehicles. – Florida State Senator BrandesWhen you combine Florida's tourism industry with frictionless mobility services, magic happens.Florida is a mobility story as much as it is anything else. Whether it be Henry Flagler or Walt Disney. These are all mobility stories. – Florida State Senator BrandesFrom autonomous mobility to space flights, Florida is leading on innovation. Florida is also leading on issues such as criminal justice reform. It is an issue that Senator Brandes has championed as it is a big idea.Senator Brandes shares the story of how he first became interested in criminal justice reform. It's a powerful heart-wrenching story. A story that leads Senator Brandes to take a leadership position working on solutions that will have a positive impact on society.Another issue that is impacting businesses and schools today is COVID-19. Senator Brandes has filed legislation to protect health care providers, businesses, and schools from COVID-19 liabilities. The conversation evolves into a discussion about Governor Ron DeSantis' decision to open schools and the long-term positive impact on children in Florida.It was the best decision [Governor Ron DeSantis] made since the beginning of COVID. – Florida State Senator BrandesWith schools open, businesses open, companies are flocking to Florida in droves. The trend did not just start with COVID, it just accelerated. The trend began when Argo AI chose Miami as one of the autonomous vehicle test cities in 2018.We have created this environment where technology can thrive and where the taxes are of a lower nature. Where it's a strong incentive to consider relocating here. – Florida State Senator BrandesWrapping up the conversation, Grayson and Senator Brandes discuss the major mobility changes they see happening in Florida over the next ten years. Including how the State is preparing for the transition to electric vehicles and how safely evacuate individuals' electric vehicles during a hurricane.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Der DAX erreicht neues All-Time-High und auch in den USA ist die Tendenz an den Börsen positiv. Besonderes Aufsehen hat eine Falschnachricht rund um Tesla-Gründer und CEO Elon Musk erregt, der letzten Freitag kurzerhand für tot erklärt wurde. In der Story des Tages durchleuchtet unser Stammanalyst Pip die globale Flugtaxi-Branche. Besonders im Fokus stehen die beiden deutschen Player Lilium Aviation und Volocopter. Lilium wurde unter anderem von Frank Thelen finanziert und soll demnächst per SPAC an die Börse. Die tiefsten Taschen hat das amerikanische Flugtaxiunternehmen Joby Aviation, das bisher bereits 800 Mio. US-Dollar eingesammelt hat. Das tiefste Netzwerk hat Kitty Hawk, das vom deutschen Sebastian Thrun gegründet wurde, der zuvor das Google Team für autonomes Fahren aufgebaut hat. Insgesamt eine Branche mit vielen Chancen aber auch vielen Risiken. Es gibt viele spannende Ansätze, wer sich am Schluss durchsetzen wird, ist aus heutiger Sicht noch unklar. Diesen Podcast der Podstars GmbH (Philipp Westermeyer) vom 09.03.2021, 3:00 Uhr stellt Dir die Trade Republic Bank GmbH zur Verfügung. Die Trade Republic Bank GmbH wird von der Bundesanstalt für Finanzaufsicht beaufsichtigt.

By Walt HickeyWelcome to the Numlock Sunday edition. Each week, I'll sit down with an author or a writer behind one of the stories covered in a previous weekday edition for a casual conversation about what they wrote.This week, I spoke to Alex Davies, the author of the brand new book Driven: The Race to Create the Autonomous Car. It's just out as of last week and is an enthralling read about the events that led us to the present-day state of the art of autonomous vehicles.I've been looking forward to this book since it was announced, and it doesn't disappoint: from the iconic if shambolic 2004 DARPA Grand Challenge to the legal battles that threatened to tear the industry apart, the creation of this tech could change the world. It's a great story.For the first time, I recorded one of these to be podcast-quality so you can actually listen to the interview up top. Let me know if you enjoy that, and maybe I'll do more of them!The book is Driven: The Race to Create the Autonomous Car and can be found wherever books are sold, and Alex is on Twitter at @adavies47. This interview has been condensed and edited. Unless otherwise indicated, images are from DARPA. Podcast theme by J.T. Fales.Alex, you are the author of the brand new book, Driven: The Race to Create the Autonomous Car. You cover all about transportation, you cover all about vehicles and you've also covered a lot about the technology that goes into them. There's been a lot of talk about driverless cars recently, you were talking about how this is a really long journey. How far back have we been working on driverless cars?I think the people first started talking about the driverless car right around the time people came up with the car itself. The car was a great invention for all sorts of reasons but one thing people noticed very quickly was that when you got rid of the horse, you got rid of the sentient being that would stop you from driving off a cliff or into a wall if you, the human driver, stopped paying attention. You see these stories from the ‘20s and ‘30s of people coming up with ways of remote-controlling cars using radio waves. And in the ‘50s, you start seeing programs from General Motors and RCA working on embedding electric strips into the road, which obviously didn't work for various reasons, that would help guide a car along the highway. You see examples from the 1939 and 1964 World's Fairs in New York where GM is talking about, "oh, cars that will drive themselves and you'll have these things like air traffic controllers saying, okay, your car is clear to go into self-driving mode," or back then they would have used the word autonomous.Ford Pavilion, 1939 World's Fair, via Library of CongressSo, the idea itself is really old but technologically, I think you've got to date this work from the ‘70s, ‘80s and ‘90s. That's when you first start seeing the technology that undergirds the way we think about building self-driving cars today, which is not by following any kind of radio path, nothing built into the infrastructure and the system, but the basic idea of giving the car the tools it needs to drive itself the way a human operates a car. You've got three basic buckets: one is you have to recreate a human's senses, so that's where you see things like cameras, radars, LiDAR sensors, giving the car the ability to see the world around it. You have to replace what a human's arms and legs do or hands and feet, really, and those are just kind of servo motors built into the car that give the car the ability to turn the steering wheel or pump the gas and brakes. And, actually, in today's cars, that's all done purely over software, it's not even really mechanical in there anymore. And then the last, the really tricky thing is how do you replace the human's brain? The step between the senses and actually carrying out the decisions you need to make.I start my story with the 2004 DARPA Grand Challenge. I give a little bit of the history of the robotics and artificial intelligence research that happened before it. But for me, the Grand Challenge is really the starting point. DARPA is that really kooky arm of the Pentagon that is basically charged with making sure the U.S. government is never surprised on the technological front. It came out of the Soviets launching Sputnik, which really shocked the Americans to hell, and they're like, “okay, we need an arm of the military that's just going to do the kooky kind of far out stuff.” So DARPA, a lot of big hits — the internet, GPS, stealth bombers. Some not so great moments — DARPA was instrumental to the creation of Agent Orange. Whoops.Oops, yeah no, don't want to do that one.That one, not so nice.Look, they're not all hits, they're not all hits and that's okay. We are friends, we have been friends for a while now. I feel like you have told me the story of the 2004 DARPA Grand Challenge many times, as this deeply formative event, not only for self-driving cars but also robotics and Silicon Valley and how government can work together on different things. Do you want to go into what went into creating this event and kind of what happened at it? Which I feel like is a very, very cool story that I imagine is a solid chunk of the book.It is a solid chunk of the book. It's also, personally, my favorite part of the book. To me, this is really the heart of the story. DARPA was tasked with helping the U.S. military develop autonomous vehicles and the basic thinking there was that vehicles were a way a lot of soldiers got hurt, especially in the early 2000s, as we were starting to get mired down in these wars in Iraq and Afghanistan. We wanted autonomous vehicles so soldiers didn't have to be in vehicles that were being hit by IEDs, so you could send cars by themselves on convoys and dangerous missions, and basically, it was to save the lives of the troops. DARPA had been funding all sorts of research into autonomous driving for decades by this point and the guy running it, DARPA director Tony Tether, was frustrated that he just wasn't seeing the kind of progress he wanted to see, it just felt like one internal research project after another.So, he said, “do you know what?” DARPA had, at the time, a relatively new power to give out prize money and he could give out up to a million dollars without needing congressional approval. So, he created a thing called the DARPA Grand Challenge with a $1 million first prize. It was a race for autonomous vehicles across the Mojave Desert in California. You would go from this real dusty little town called Barstow in the California Mojave Desert to just across the line to Primm, Nevada, which is a pretty sad town because it's the least driving you have to do from California to legally gamble in a casino. If you're like, “I don't have the energy to drive the extra 45 minutes to Las Vegas,” you go to Primm.Oh no.And so, Tether's original idea, very briefly, it was we're going to have the cars go from Los Angeles to the Las Vegas Strip and they'll go on the freeway. And the guy at DARPA who was actually in charge of putting on this race was like that is completely insane, you can't do any of that. These robots don't work, we don't even know what they're going to look like. So, they ended up doing it in the desert, which made more sense for the military application anyway when you think about what your driving in the Middle East would be like. But the key part of the challenge was that it was open to anybody, this was not just Lockheed Martin and Boeing and Carnegie Mellon University, the big contractors who had been doing this kind of work. Tony Tether just said, “anybody who can build a self-driving car, we'll bring them all to the desert and we'll do this big race.” And so, you see this wide range of characters who come into this.I think, foremost among them, interestingly, is Anthony Levandowski, who at the time is just about 23 years old. He's an graduate student at UC Berkeley and he decides he really wants to be in this because he loves robotics, even though he doesn't have a ton of robotics training. He's like, “I'm going to build a self-driving motorcycle.” So, that's his idea. You've got the big players like Carnegie Mellon and that's where Chris Urmson, who becomes Anthony Levandowski's great rival once they're both at Google years later, comes in. Chris Urmson is a big player, Carnegie Mellon is the robotics powerhouse in the world, probably the best roboticists in the world and have been doing tons and tons of self-driving research over the decades. They field this team as a powerhouse of a team and you've got this guy, Red Whittaker, who's the old roboticist there.This is amazing.I have been yelled at by Red Whittaker more times than I care to remember. Really!He's just very cantankerous, he's an ex Marine, he's now 70 years old, he's well over six feet, he's 250 pounds, the guy is built like a redwood and he's just always yelling. And he builds robots, someone pointed this out to me once, he builds robots that look like him, in a sense. They're always these enormous, hulking things and for the Grand Challenge, they built this Humvee. And Red Whittaker, someone told me, he has this penchant for saying really bombastic things that sound crazy and don't actually make any sense. So, he once told someone, this project, it's like a freight train, you've just got to grab on and it'll rip your arms off.It sounds terrible.When he told me this, it's like, what does that even mean? But he has this incredible talent for really developing young engineers. And Chris Urmson is among his many proteges who are now pushing this technology into the world.And so, you have this collection of wacky racers, gathering to win a million dollars from the Defense Department in the desert. And the first one is 2004, what happens at the first one?It is a disaster. The 2004 DARPA Grand Challenge is supposed to be a 142 mile race through the desert, 15 teams get out of a qualifying round and make it to the final round. If you looked at the qualifying round, vehicles were smoking and shaking or they couldn't even start at all or they were just driving into every last thing. And then the race in the desert itself, wasn't all that much better. It got off to a great start, Carnegie Mellon's Humvee, Sand Storm, was first off the line, it shoots off into the desert. So, it's doing okay, the first couple of vehicles get off the line okay. And then you get through the bottom half of the field and it becomes a comedy of errors. You've got one little bathtub shaped thing that goes up onto the tiny ridge just on the side of the trail where it's raised and flips over and lands upside down.You've got one that drives 50 yards out, does an inexplicable U-turn and drives back to the starting line. We've got one, one just veers off-road into barbed wire and then can't find it's way back. You've got this thing from OshKosh that's a 14 ton military truck, a six wheeled thing, it's lime green and it's got a tumbleweed, like a bush thing in front of it. And its detection system says, this is an unmovable obstacle, but then another tumbleweed shows up behind it and so, it just starts going forward and backward and forward and backward like Austin Powers, trying to turn around. And then, even Carnegie Mellon's vehicle, which is doing well and is seven miles into the race, it's going around a hairpin turn, it goes off the edge of the road a little bit and it gets hung up on this rock. It gets, basically, stranded like a whale on a beach. It's raised up to the point where its wheels can't get any traction anymore. The robot brain doesn't know this and it's just spinning its wheels, spinning its wheels at full speed until the rubber is on fire and smoke pouring off this thing. And DARPA has to show up from a helicopter. They hop out of the helicopter with the fire extinguishers, and it's a complete disaster.And the thing that DARPA had really hyped up, they're like, “this is the new innovation, we're going to save the lives of all these troops.” And so then, reporters come after Tony Tether and he meets them, he meets the reporters who are waiting at the end line, at the finish line, which is roughly — it's 142 mile race — 130 miles away from the closest car. The Outcome.Carnegie Mellon did the best, it went 7.4 miles. Anthony Levandowski's motorcycle makes it into the final round, mostly as a stunt. It did horribly in qualifying, but the DARPA guys are like, “this thing is so crazy, it really embodies the spirit of what we're trying to do, so let's just bring it to the race anyway.” It's not like it can win, its gas tank doesn't hold enough gas for it to go all the way to the finish line.So, Anthony brings it up to the starting line, hands it off to a DARPA guy who kind of holds his hand on it until it goes, motorcycles starts going, he takes his hand off and motorcycle instantly falls to the ground. Anthony had forgotten to turn on the stabilizing software system before it started.That will get you.And so, one of his lessons for the next year was make a checklist.The cool thing about this is that it's an utter fiasco, it's how you always tell it. But then everybody who was there for this fiasco, they stuck around and they went, in many ways, to kind of form the current self-driving industry. Do you want to talk about that seed, what it has turned into since?Yeah. So, very quickly, what's great about the Grand Challenge is that it brings all these people together, and it pits them against this problem that everyone had kind of dismissed as impossible. So, what happens is DARPA does the 2005 Grand Challenge 18 months later, and the 18 months really prove to be the difference in that teams that weren't ready at all for the Grand Challenge, for the original one, are ready 18 months later. They've learned much more about how this works. And so, the 2005 race is a huge success. Stanford, led by Sebastian Thrun, comes in first place, Carnegie Mellon second, five teams finish this big race through the desert. Then DARPA follows it up with the 2007 Urban Challenge, which pits the vehicles against a little mock city, where they have people driving around and all of a sudden they have to deal with traffic and stop signs and parking lots and all of this stuff.What you really get from the Urban Challenge is the sense that this technology seems, suddenly, very possible. And by 2007, this is a big media event, it's hosted by the guys who did MythBusters and Larry Page is there, and he shows up in his private plane full of Google execs, and it's like, look at this future of technology. About a year later, Larry Page wants to build self-driving cars. This is actually something he'd looked at as an undergraduate or a graduate student and then his thesis advisor said, “well, how about you focus on internet search instead?” And it worked out pretty well.It worked out okay, I think, right?I think he did fine, that's what I thought. He decided I want to get back to self-driving cars. He'd been at the Urban Challenge and been like, “I can see how far this technology has come,” so what he did was he went to Sebastian Thrun, who had led Stanford's team through the challenges and he was already working at Google, he was a big part of making Street View happen. Along with Anthony Levandowski, who Thrun had met through the challenges and he's like, “oh, this guy's nuts but he's really talented and he's a real go-getter.” So, he brings him on to help them do Street View and then Larry Page says, “okay, now build me a self-driving car.” Sebastian Thrun says, "okay, well I happen to know the 12 best people on the world at this technology, I met basically all of them through the DARPA challenges."He has this meeting at his chalet in Lake Tahoe, at the end of 2008. And he brings together a dozen people and it's Anthony Levandowski and it's Chris Urmson and then people like Bryan Salesky — names that are now really the top tier in self-driving cars. And he says, “Google is going to build a self-driving car, we're going to have something that looks a whole lot like a blank check and I want this team to be the one to do it.” And that becomes Project Chauffeur. They become this really secretive project within Google, they go forth over the next couple of years, and they make this incredible progress in self-driving cars. And this is the story of the second half of the book: how this team it comes together and then how they ultimately come apart because as soon as they have to start thinking about how to make a product, how to commercialize this technology and the reality of money and power within the team become real wedge issues.Within them, you see rivalries, especially between Urmson and Levandowski, who are fighting for control and fighting for the direction of the team. Ultimately, things kind of break apart and what you see over time is as people leave and as this technology starts to look a lot more real, everyone splinters off to do their own thing, and this was what I call Google self-driving diaspora. Chris Urmson leaves to start Aurora. Bryan Salesky leaves to start Argo. Dave Ferguson and Jiajun Zhu leave to start Nuro, Don Burnette leaves to start Kodiak, and Anthony Levandowski, of course, leaves to start Otto, which is acquired by Uber, which is the genesis of the Uber-Waymo huge self-driving lawsuit.Considerable amount of litigation that I believe is ongoing to this day, yes.So, the litigation did end, fortunately for everyone but the lawyers, I think. Uber and Waymo ultimately settled and then, weirdly, about a year after that, the Department of Justice charged Levandowski with criminal trade secret theft to which he ultimately pled guilty, and a few months ago he was sentenced to 18 months in prison, but he will not start his sentence until the pandemic is over.So, it definitely seems that this is still very much seen as the start of something, and you have covered a lot of this industry. What's kind of the state of the art now and where are things kind of moving forward?Well, fortunately for the industry, all of these personal rivalries, I think, have largely cooled off. And I think the book is really a history of how this got started and how these people pulled this technology forward, and then kind of came apart at the seams. But now what you've got is something that looks a little bit like a mature industry. You have Waymo with its program in the Arizona suburbs of Phoenix, and it's starting to really take the safety drivers out of its cars in earnest. Cruise, which is also a focus of the book, which is part of GM and also backed by Honda, is moving to take the safety drivers out of its cars in San Francisco, a much more dynamic environment, as it moves to start a self-driving system there. Self-driving trucks are looking much more serious than ever before. Argo AI, which has partnered with Ford and Volkswagen, is moving towards starting a taxi service, a robo-taxi service in Miami.I talk about the Gartner hype cycle where, I think, from 2014 to 2017 or so, we were really at peak hype, totally inflated expectations where everyone said, “your kids will never have to learn how to drive.” Chris Urmson is saying, "my 12 year old son will never have to learn to drive a car," and I'm pretty sure the kid's got his learner's permit by now. Those inflated expectations burst a little bit as people realize just how hard this technology is. But I think where we are now, on that Gartner hype cycle, is on what's called the slope of enlightenment, where people are getting more serious. Even if they haven't cracked the problem yet, I think they have a really good sense of what it takes to crack the problem, which, it turns out, is a lot of time, an incredible amount of money and at least 1,000 very talented engineers.Whole lot of lasers, a very sympathetic governmental oversight structure in a suburb of Phoenix. We have the ingredients for the solution, right?We could make it work. And so, I'm still optimistic about it, I still think the technology can do a lot of good. I think what people are figuring out is how to right-size this technology. People are figuring out how to actually apply self-driving cars in a realistic way, and I think the cooler projects out there are companies that are working on making self-driving shuttle cars for senior living communities, these big areas in Arizona and Florida, they cover 1,000 acres and people need to get around but can't necessarily drive anymore. And where the driving environment is pretty calm, that's a great use case. The trick right now is to figure out where you can make the technology work, and then the next question will be where can you actually make money off of this? That one I'm less bullish on because the economics of this, I think, are going to be pretty tough to crack.I mean, we're closing in on the end of this one, but DARPA seeded a little bit of the initial funds, it seems, for a lot of this research. Is that still an application that people are looking into or getting folks off the road in places that are dangerous?The army is still working on that, and I think those projects are still ongoing. But the initial push for DARPA was a line in a congressional funding bill from the end of 2000, it was one of the last things Clinton signed into law. And it mandated that by 2015, one-third of all ground vehicles, I think it was military, be unmanned, which was completely insane.How did we do? What's the number?I mean, maybe we've got three vehicles. That stuff hasn't panned out so much. But my favorite thing, one of the first people I managed to track down for this book was the guy, the congressional staffer who got that line into the bill. And I told him, I was like, "oh, I'm researching this and I would just want to ask you about why you put that in there and what your thinking was." And he goes, "Oh, did something come of that?"That's amazing.I was like, “yeah, I don't know, an industry that's predicted to be worth $7 trillion.”And what also came of it is Driven: The Race to Create the Autonomous Car by Alex Davies. Alex, where can people find the book? You can find this book, basically, anywhere online, it's available through Amazon, Barnes and Noble, your regular booksellers. It's out in hardcover January 5. You can also get the audiobook, you can get it on Kindle. Get it however you like, I just hope you enjoy it.My Twitter handle is @adavies47. You can find some of my work on Business Insider, where I'm the senior editor for our transportation desk.Ah, excellent website, very, very good website. If you have anything you'd like to see in this Sunday special, shoot me an email. Comment below! Thanks for reading, and thanks so much for supporting Numlock.Thank you so much for becoming a paid subscriber! Send links to me on Twitter at @WaltHickey or email me with numbers, tips, or feedback at walt@numlock.news. Get full access to Numlock News at www.numlock.com/subscribe

Learn why Udacity (Founder & Executive Chairman) and Kitty Hawk (CEO) Sebastian Thrun believes job skill training and education needs to be a basic human right in every country, and how AI will help us get there. See omnystudio.com/listener for privacy information.

I am thrilled to announce this weeks podcast guest: Prof. Sebastian Thrun Brief overview: He is a Stanford professor, founder of Google X, built the first self driving car, won the Darpa-Award for it, started the online-academy Udacity and is now building autonomous planes at Kitty Hawk. Wow. Can you tell why I highly admire him and how excited I was when I won him for my podcast? We talked about the car nation in Germany, how competitive we are in the AI and software world, Stanford vs. TU-Munich, why Sebastian is striving for a brain-computer interface, why he has built the leading online university Udacity and how to tackle machine learning as a modern CTO. He also explains why he eventually comes up with a Bluetooth-connected Smart-Bra next.

Kitty Hawk is shutting down its Flyer program, the aviation startup's inaugural moonshot to develop an ultralight electric flying car designed for anyone to use. The company, backed by Google co-founder Larry Page and led by Sebastian Thrun, said it's now focused on scaling up Heaviside, a sleeker, more capable (once secret) electric aircraft that […]

If you could press a button to merge your mind with an artificial intelligence computer—expanding your brain power, your memory, and your creative capacity—would you take the leap? “I would press it in a microsecond,” says Sebastian Thrun, who previously led Stanford University's AI Lab. Turning yourself into a cyborg might sound like pure sci-fi, but recent progress in AI, neural implants, and wearable gadgets make it seem increasingly imaginable.

Kitty Hawk reveals its secret project, Heaviside The aviation startup has been working on the quiet electric aircraft for two years Sebastian Thrun is waving a device in his hand with an excited, almost gleeful expression on his face as he trots from a makeshift aircraft hangar toward the secret project that Kitty Hawk Corp. has been working on for nearly two years.

Sebastian Thrun is our first guest. He is an incredible computer scientist. One of the inventors of self-driving cars, now working on flying cars. He is the founder of a company called Udacity. It is an incredibly interesting company helping people to acquire skills for the jobs of the future. Sebastian was really the pioneer of the whole movement we've seen for what's called Massive Online Open Courses (MOOCs) which is online distance learning. There is so much more to unpack with Sebastian in this episode. Let's dive right in. Learn more about your ad choices. Visit megaphone.fm/adchoices

Since Stanley Kubrick's 2001: A Space Odyssey introduced the prospect of Artificial Intelligence (AI) with the spaceship computer system HAL, the world has had a rollercoaster relationship with the idea - from hope to hype, and everywhere in between. Have we "unleashed the demon" with AI, or does the potential of deep learning and machine learning for improving health outcomes far outweigh the fear factor? Duncan Arbour, Senior Vice President, Innovation with Syneos Health Communications, takes us on a fascinating journey through the progression of AI, its application in healthcare and touching on its potential impact on biopharma companies, healthcare providers, investors and the industry as a whole. But what about the perspective of the patient - up till now, the missing component in healthcare's AI conversation? To answer this question, Arbour shares the findings from a new Syneos Health report, Artificial Intelligence for Authentic Engagement: Patient Perspectives on Healthcare's Evolving AI Conversation, based on a survey of 800 patients regarding their expectations and concerns around the potential role of AI in diagnosis, treatment and support in their day-to-day lives. Also referenced in this episode: The Gartner Hype Cycle Google alum Sebastian Thrun's paper on melanoma diagnosis through machine learning in the journal Nature Geoffrey Hinton's comparison of radiologists to Wile E. Coyote IBM supercomputer Watson versus cancer The General Data Protection Regulation in the EU Investment opportunity for AI in the healthcare sector The "Speak Easy" study on the potential for voice assistance to build relationships Amazon, JP Morgan and Berkshire Hathaway plan to form their own health care company See our full list of podcast episodes here. The information, data, and other content contained in this podcast and any associated articles, sponsorships, advertisements, announcements or other communications are provided for informational purposes only and should not be construed as professional advice of any kind, on any subject matter. The content of the podcast contains general information and may not reflect current legal developments, verdicts or settlements. Moreover, the content is not guaranteed to be complete, correct, timely, current or otherwise up-to-date. Syneos Health reserves the right to make alterations or deletions to the content at any time without notice to you.

Educator and entrepreneur Sebastian Thrun wants us to use AI to free humanity of repetitive work and unleash our creativity. In an inspiring, informative conversation with TED Curator Chris Anderson, Thrun discusses the progress of deep learning, why we shouldn't fear runaway AI and how society will be better off if dull, tedious work is done with the help of machines. "Only one percent of interesting things have been invented yet," Thrun says. "I believe all of us are insanely creative ... [AI] will empower us to turn creativity into action." Hosted on Acast. See acast.com/privacy for more information.

Educator and entrepreneur Sebastian Thrun wants us to use AI to free humanity of repetitive work and unleash our creativity. In an inspiring, informative conversation with TED Curator Chris Anderson, Thrun discusses the progress of deep learning, why we shouldn't fear runaway AI and how society will be better off if dull, tedious work is done with the help of machines. "Only one percent of interesting things have been invented yet," Thrun says. "I believe all of us are insanely creative ... [AI] will empower us to turn creativity into action."

مستدفر يستضيف اليوم علي الصيبعي لنتحدث عن الذكاء الإصطناعي وتعلم الالة, وعن عقلية “أول سعودي فعل”, وعن أمكانية عمل السيارات الذاتية في العواصم العربية. وصلات الحلقة الدروون الذاتي المشكلة في بعقلية “الأول” تعيين وزير الذكاء الصناعي في الإمارات تغريدة الدكتور أحمد نبيل قصة السيارات الذاتية عبر العقود تحدي داربا للسيارة الذاتية سيباستيان ثران موقع ماستودون البديل لتويتر

Machine learning is everywhere, it's used on email, Netflix, social media and for driverless cars. In this episode, Katie Malone gives an introduction to machine learning. Katie is a data scientist in the research and development department at Civis Analytics. She is also an instructor of the intro to machine learning online course from Udacity along with Sebastian Thrun.