Here's Who's Winning the Global Fight for AI Talent

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Tracy Alaway
Bloomberg Audio Studios podcasts Radio News hello, and welcome to another episode of the Odd Lots podcast. I'm Tracy Alaway. And I'm Joe Wiesenthal. Jo, have you watched the three body problems? No, but I really want to, and I didn't read the book, so in case you're gonna ask that I didn't.

Joe Wiesenthal
I wanna do that too, but I intend to at some point. There goes my carefully crafted intro where we talk about the three body problem. Okay, well, this will work well, as everyone knows, except for Joe, there's sort of two types of people in the world when it comes to the three body problem. There are those who see it as an allegory for climate change. So humans coming together to unite against a common threat, which in this case, since you haven't read the book, is an alien civilization.

Alien civilization. I did. A friend of mine this weekend told me, like, two plot points. Okay, good, good, good. Yes.

Tracy Alaway
Okay. And then there are also those who see it as sort of an allegory for the trade or tech war between the US and China. So the idea that humans are going up against a much more technologically advanced opponent, and in this scenario, I guess Earth is China and the aliens are the US. Well, today we are firmly in that second camp to talk about us China rivalry in tech, and in particular, one area of tech, AI. Right.

Joe Wiesenthal
So obviously, AI, AI, AI. Everyone talks about it all the time. We don't really know where it's going to go, but we know a few things in the meantime, which is that people are spending money like crazy on chips, but they're also spending money like crazy on talent. And anyone who is capable of doing sort of cutting edge research in AI, from what I can tell based on articles I write, like, they basically just get to pick where they want to work and basically pick their salary. There's a great article in the information a couple of weeks ago about Facebook hiring top researchers without even doing an interview.

It's like, if you know this stuff, someone will hire you and pay you a lot of money. Yeah. And I have so many questions in this space. So first of all, like, who is an AI talent? Or what is an AI talent?

Tracy Alaway
Where do they come from? Is it the same as being a software engineer, but you have a slight, slightly different area of expertise? I really don't know. And then secondly, I'm kind of curious how fungible the jobs are from what you just said and the fact that companies are hiring without interviews and things like that, and that demand is so strong, it seems like you can just do AI anywhere, whether it's China or the US or somewhere else in the world, or whether it's a specific company versus another one. But so many questions on this AI talent war, I guess you could say.

Joe Wiesenthal
Totally. And there's two things. So a, I sort of consider myself a bit of an AI talent because I think I'm pretty good at coming up with chat. GPT, you are actually listeners. I have learned a lot from watching Joe enter his proms, and I still find it incredibly endearing that you say please and thank you.

Well, it's important for when AI becomes sentient that they're gonna remember who said please and thank you. But beyond that, there's this other element, and you already sort of alluded to it, but it's clear that for whatever reason, countries feel like AI, almost as if it's a commodity. There must be some every country, or there's this narrative being pushed by the industry, and maybe it's just a narrative to sell chips or subscriptions to the OpenAI APIs, et cetera. But there seems to be this narrative that every country must have some sort of homegrown AI strategy or data center or something. Like, something about this technology seems to engender political and nationalistic anxieties.

Tracy Alaway
Yes, I think that's absolutely true, and we're back to sort of the three body geopolitical tension point. But I am very pleased to say that we, in fact, have the perfect guest to talk about all of this. We're going to be speaking with Damian Ma. He is the managing director at Macropolo, which is the think tank at the Paulson Institute, and they publish something called the global AI talent tracker. So actually keeping track of where AI talent is coming from, how much there is, and where it's going.

So, Damian, thank you so much for coming on. All thoughts thank you so much. It's great to be here. How long have you guys been doing this? Talent tracker, and what was the genesis cause for me?

Chat GPT and all the chatbots seem to have come out of nowhere almost basically a year ago. So how did you get an early start on tracking AI? Well, the original conception is that we thought a little bit hard about, you know, what would you need to have a robust AI ecosystem or an AI industry? And we thought there were three key pieces. You need, obviously, compute power, so things like chips and the infrastructure, and you need, obviously, a lot of training data.

Damian Ma
Data is obviously everywhere now. And we thought the last piece that people haven't thought too much about is human capital, because it is a very human capital intensive area, and discipline, because it's highly complex and complicated, and you need highly trained people to be able to do it. So we thought, nobody's really looked at the human capital side of things. Is there a way to do that? And so we sort of found this one conference that's widely known in the AI community as one of the most prestigious.

And so we looked at papers and researchers that went to that conference. This was back in 2020, during the pandemic, was when we first launched the initial tracker that gave us our idea. That's a proxy for sort of the top 20% of global AI talent. So this is not all AI talent. This is not everybody in the world, but this is really sort of what we might call the cream of the crop top 20%.

And within that, there's also the top 2%. So we're looking at really kind of the elite people, which is probably the type of people that's being fought over most fiercely because people want the top talent. Real quickly, what's the conference? It's called newer ips. It's a conference that's held, I think, every year, but we didn't track it every year.

We tracked in 2020, and then we did it again, and we looked at the 2022. We were trying to see had there been any changes after the three year pandemic to see if there were different mobility patterns. This is a conference that's mainly focused on neural networks, large language models, so a lot of things that are currently really pushing the frontiers of a generative AI. So we thought that those are the kinds of people that would probably want to work for the Googles at OpenAI's and buy dues of the world. And so that seemed like a good sampling.

Again, we don't pretend that this is comprehensive, but it is sort of the elite 20% sample. Just real quickly, since you say you're able to distinguish between the top 20% and the top 2%, how do you do that part? I mean, it can't just be people who attend the conference. How do you sort of grade or figure out who is this specific ultra elite AI engineering talent? So we looked at authors whose papers got accepted, and within that acceptance, there's a oral presentation.

You don't get accepted to oral presentation unless you're really, really good. So there are only about 2% of people that got accepted at oral presentation. So that, to us, was sort of the proxy for the 2%. This kind of leads into what I was wondering, which is, what makes a really good AI engineer? Like, what is it that would lead them to be someone who presents at a conference like this?

I mean, Joe just said, you know, he's a really good, prompt engineer, so. So they would let me present. Joe, I'm sure your invite's in the. Mail, like, really curate the question as well. But I think that's a really good question.

Tracy Alaway
Just curating the questions, right. It's like actually coming up with the natural language models and things like that. Okay. Yeah. So I think it's a really good question, and I'm not sure.

Damian Ma
The distinction is huge. I think the foundation of AI is all computer science. Most AI people would call themselves computer scientists first and foremost, or people that have a lot of mathematical training. And in fact, I think some of those people, I think back in the two thousands and 2010s, were the same people that got attracted to big finance, right, and went to build algorithms for trading desks. Those are probably a similar type of people.

Now they're just doing AI. And the AI specific apply part is being able to train large amounts of data and being able to write out algorithms. But those are the things that you would get from computer science training with a bit of added AI specific component to it. And I think the neural networks thing is probably one distinguishing characteristic is trying to really figure out how do you make the computer mimic the human brain in a way, but fundamentally, it's just mathematics, quantitative computer science. All those things eventually can become AI scientists.

Joe Wiesenthal
So there's a certain type of person who is seeking out the hardest or maybe most lucrative sort of real world math problem or computer science problem at any time. Maybe in the two thousands, they were going to Wall street to figure out the best way to create new securitized products and derivatives. In the 2010s, they went to Facebook and Google to figure out the ways to pack the most number of ads on a smartphone or get you to click on them. And now apparently they're going into AI research. So let's start with, like, what the data shows.

Big picture. When you started, first started collecting the data in 2020, where were they coming from and where were they going? A lot of them came out of China in the United States in 2020. That was pretty clear. Most of them ended up in the United States by far.

Damian Ma
And we're still seeing that in our latest update in 2023. Although I would say the big surprise was that China has done a really good job, really ramping up its domestic supply of top AI scientists. So they're producing nearly half of the world's top tier AI scientists now, and many of them are actually also staying in China. And the reason is, I think it's pretty simple, is that China is obviously been focusing on its own AI industry. And as we already said, people go where the jobs are.

And if you look at the major economies where they're focused on building out AI industry opportunities, it's probably the United States and China. And if you look at Europe, Europe actually, I think punches way below its way in terms of having an AI industry. And so they don't tend to attract as many top tier AI talent as China or the US. And if you look within top us institutions where top AI talent work, it really is almost a chinese american duopoly. Chinese origin and american AI scientists are 75% of the top AI talent within us institutions.

Tracy Alaway
What are the factors that would go into, say, a computer scientist who has been educated in China, and they're surveying the different opportunities available to them. What are the factors that would go in to them making a decision like, are there immigration considerations? I imagine pay and renumeration would have to factor into that. How easy is it for them to switch from China to the US? I think the skills and the training is fairly similar if you come out of a top program, whether it's Tsinghua in China or Stanford in California.

Damian Ma
I think the key, from what we're seeing, one key indicator of where people end up for work is really where they go to graduate school. That's probably not a surprise. If you're going to do your master's or PhD somewhere, you generally start to search for job opportunities near you, around you, unless you happen to be in a country in an area where there's not a lot of opportunities post graduation. And of course, when you're considered an elite AI talent, you generally have a terminal degree, usually a PhD, but at least a master's. So I think where you choose to go to graduate school is really important, and we see that in the data, too.

Those who come to the United States or graduate school, by and large, tend to stay in the US to work unless there's some very lucrative opportunity that attracts them back home or somewhere else. But generally, there's a bit of a path dependence between graduate school and staying in that country to work. There has been a lot of anxiety for years in the tech industry, where you see CEO's and leaders complaining that the US immigration policy has made it too hard to keep talent who has graduated in the United States. And there's this idea of like, hey, if they're going to come here for education, why are we not reaping the benefits of this US educated talent? It does seem like from your data that still many are staying in the United States, but the numbers have changed since 2020.

Joe Wiesenthal
Yes. Yes, they have, you know, gone down a little bit. We didn't go into really exploring exactly what happened over the last three years, in part because I think many people realize the pendenning years have been a little strange, whether it's for economic data or just general mobility for people where people work, how people work. So there's going to be a lot of distortions in those last three years, but there has been a relative decline, especially among the asian talent. It's not just China.

Damian Ma
India has also done a better job retaining its own top tier AI talent. South Korea, interestingly, that's not on our data set yet, but we're about to publish regional South Korea, they've retained 90% of their talent. They've not let anybody leave, and they've been really good at doing that. And places like France have actually done a very good job on retaining their talent. So I can't say definitively what the reason is, whether countries have stepped up their game to retain domestic talent, or there's been other things that happened in the pandemic that's triggered it, or there could be immigration challenges and so on.

I think maybe in the future when we do the next iteration, we will have more clarity to see the pattern. So I'd be a little hesitant to give definitive conclusions at this point.

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Dot choosestream. Stifel Nicholas and company incorporated member SIPC and NYsE Tracy. If France does a really good job keeping their talent, who will fill the niche of blowing up trading desks with exotic derivatives? If all those ecole polytechnique and sciences poe graduates go into AI instead? Yeah.

Tracy Alaway
Yes, it is always a french person working in equity derivatives with a mathematics degree. You are absolutely correct. But on the degree topic. So I hadn't realized that in China. And Damian, I think this factoid was in one of the reading materials that you sent.

But chinese universities have launched more than 2300 undergraduate programs since 2018, when the Ministry of education designated AI as a separate major. That's distinct from computer science. So, first of all, how common is that that you would get the separation between computer science versus AI? Is that the standard in other parts of the world, or is it still relatively new? And then secondly, presumably this is part of China trying to build up its domestic AI talent pool and eventually its capabilities in this area.

What else is it doing on that front? Yeah, so that's why, one of the reasons we think that China has really seen this boom on top AI talent is you have just kind of a graduating class in 2022, if you started in 2018, some of them are graduate students, some of them are undergrads. So they've really pushed really hard to grow the AI talent. But now not all of them are the top 20%. But I think China looks at it as a way that they're going to need a lot of AI specific technicians.

Damian Ma
China's not really thinking about AI in the generative AI sense, I think there are definitely some startups and folks pursuing things like chat, GPT, chatbots. But my understanding is that China is probably going to focus much more on industrial applications of AI, manufacturing, robotics, probably healthcare, biotech. I'm going to bet that's going to be a huge application for China. And I think for obvious reasons, generative AI is probably not as copacetic with the governance system in China ultimately. And I think that's a pretty clear thing that I think everyone knows.

But I think they're really looking at how to apply artificial intelligence to energy, to industry, to advanced manufacturing or things like climate. That's where China is really focused on it. And I think they feel like they need a lot more people, not just to cream of the crop, but sort of, you know, middle level technicians, people that are just familiar with being able to like run data or to run Python or to just check all the data. So I think they're viewing AI as a very wide, expansive way of creating certain jobs. Yeah, I can't imagine China's ambition here is to have like 5000 different chat bots.

Tracy Alaway
Like there is clearly a tendency towards industrial sort of real world applications of this technology. On which note, do you think there's currently enough places for AI graduates or specialists to actually go within China? Because in some respects it feels like this might be a very hot degree. People are being encouraged to do it, but at the moment companies aren't necessarily at the same sort of level. It feels like there's sort of a mismatch in the evolution of this at the moment.

Damian Ma
I think you're absolutely right. So we've seen these kinds of bubbles before that the new hottest sector in China, everyone goes there because they think that's where the opportunities are. And then China already had what we would call a college bubble for the last ten years. And that's why you have really high youth joblessness in China, though. The way I think about how China works in that respect specifically is that there are basically two different cycles in China.

There is a policy induced cycle and then there's an actual market cycle that comes after that. So right now we're in sort of this policy driven. Like you guys got to come in and we really like AI, we're going to create all these programs and you should just get AI. And then parents are like, whoa, well that seems like a good new thing. And that's what the government's promoting.

So all my kids that are going to do computer science, they're going to add the AI component to it. So that's sort of the policy induced cycle. And then after that, once the bubble happens, it will kind of eventually get into a market cycle where it'll correct a little bit, and then people will be like, oh, well, actually, we probably now have an oversupply of a lot of these middle AI technicians that will have no jobs. What are we going to do with them? We don't know.

So I think this is a pattern that happens in China a lot, and I wouldn't be surprised if it happens with the AI talent pool as well. So there's a lot of interesting threads to pull on already in this conversation, and I want to return to the non chatbot applications of AI, like how can we make better robots and factories and drug discovery, et cetera. But I want to ask another question. So, okay, all these new institutions or graduate programs have been launched in China, and more and more universities, universities offering degrees in AI or computer science or related fields. In my mind's eye, if I imagine what a top AI researcher, I imagine maybe they have a PhD from MIT or Stanford or something like that.

Joe Wiesenthal
When you look at the institutions in China, has there been any sort of broadening out of the number of schools that are capable of producing either those top 20% or top 2% talent beyond just the sort of like, handful of schools that we've for a long time understood as the elite schools? There have been a little bit. And when it comes to Asia specifically and China, I think they have eleven of the 14 top AI institutions in Asia. But in terms sort of, you know, just top in general, China has climbed quite a bit. Places like Zhejiang University, Shanghai, Jiaotong, which are not your traditional names that you would hear.

Yeah, I've never heard of either. It's not PKU, it's not Tsinghua. And interestingly, this is interesting. You entrant into 2022, Huawei is actually one of the top 25 institutions for AI researcher globally. So they've invested a lot in hiring top AI talent, for obvious reasons.

Tracy Alaway
Oh, this is actually exactly what I wanted to ask you next, which is you mentioned Baidu as well, earlier in the conversation. But in terms of domestic destinations for AI specialists, is the idea here that a lot of the existing Internet companies in China, that they're going to devote more development and more resources to this particular technology, as we've seen here in the US, but also that maybe some of those big, like, consumer Internet companies, the ones that had a very rough few years during Xi Jinping's big crackdown on disorderly capital expansion, that they're going to pivot as well. So I think that's basically correct. Baidu, as far as I'm concerned, has basically become an AI company, and I think they made that strategic change many, many years ago. And one of their big focuses is, I think, like Tesla, autonomous driving, and no one has really been able to crack that.

Damian Ma
I think that's sort of the AI frontier that everyone's really focused on is how to solve vision, right? Because everyone's now focused on how to solve language, which is what generative AI. And a lot of the products we see today is kind of language based, but vision is a really tough nut to crack. And Baidu is the one in China that's really been trying to solve it. And I'm not sure their progress is any better than Google or anybody else.

But in terms of some of the software companies like Alibaba, Tencent. Tencent has been doing a lot of AI investments, and obviously Biden's, there's been a lot of that. But what we're also seeing, we did a recent piece where we looked at where chinese vc money has been going, venture capital, whether venture capital is going to a lot of these places, but in fact, venture capital actually has invested less in software in the last few years, but actually invested more in hard tech hardware. So similar things like the advanced manufacturing side. So I really think in the next few years we're going to see a lot of money, private and public, going into these advanced manufacturing, hard tech side of things that will have AI applications.

And I think there'll be some startups in China that probably we haven't heard of today that's going to put a lot of money into AI, but the big guys are doing it. But Baidu is probably the one that's the most prominent in trying to solve the sort of autonomous vision problem. And they will be a big employer in China for sure, for AI talent. So going back to the other industrial applications of AI, like already, there's this just tremendous anxiety in the US and Europe about whether there's any way to catch up with China's sort of advanced manufacturing prowess, whether we're talking about cars, whether we're talking about batteries, whether certainly whether we're talking about certain types of chips. Should the US be concerned, perhaps, that here chatbots are the shiny new thing and everyone wants to work on a better chatbot?

Joe Wiesenthal
And in the meantime, China gets even better at sort of automated factories, particularly, I imagine, with better vision technology that factory floor robots could be safer or could be more agile, et cetera. Do you see a sort of further widening of the nature of the US China competition as a function of where the AI talent is going? I'm not sure I can give you a very satisfying answer. I guess the way I would think about that, something that would be emblematic of both advanced manufacturing and AI applications, software and hardware. I think the key for both countries, and I think all countries, is probably going to be in robotics.

Damian Ma
That's sort of the new frontier of whether it's the Optimus humanoid robot. China's got, I'm guessing like half a dozen robotics startups already. So if one country, one company succeeds in that arena and is able to really blend that hardware and software and make it work and commercially viable, I think that could send a lot of strong signals about the relative capabilities of each country. Are you going to start a robotics talent tracker? Robots that's going to involve a lot of supply chain.

So it's a little tougher than just looking at the people. You got to bring in the chips, you got to bring in the engineers, the mechanics. So it's more than just the AI scientists when it comes to robots, but interesting, for sure. So one thing I wanted to ask, because you're looking at this world very carefully and sort of watching what people are doing and saying, but what is the language that I guess policymakers in China are using around AI talent? Like, what sort of statements do you tend to hear?

Tracy Alaway
And I'm thinking back again to that famous disorderly capital expansion phrase that Xi Jinping deployed when he was cracking down on things like the education sector and consumer Internet companies and stuff like that. But how is this whole dynamic, this talent war, couched among policymakers? I think it's natural, and it's given that no country generally likes brain drain, everybody wants to have brain gains. And I think that, rhetoric aside, the actualization of that and how you set up your own country, how do you set up the environment and incentives, compensation, all sorts of things. The thing about top tier talent in any arena, but particularly in computer science and these sort of frontier technologies, most of that talent, I would imagine, would want to be in the most competitive and dynamic industries.

Damian Ma
That's where they probably feel the most comfortable. That's where they want to make a difference, that's where they want to make an impact. And obviously the compensation, all that stuff follows that. But I think they want to have the freedom to do the best cutting edge work possible. So I think having dynamic industry is really important.

And so I'll bring up the Europe example again. Europe doesn't seem to have that, which is why they've consistently been sort of underweighted when it comes to attracting top tier talent. And if you look at the UK, which has been the main place in Europe, where most top tier AI talent work, but in UK, most of them work for Google, DeepMind, which is a us company, right. Having that industry is, I think, really, really important. And so in our current debate about regulating AI and industry, I think it's going to get controversial, it's going to get testy.

We all know that, we all can see that, but I think we have to think about if countries want to attract the top tier talent, they want to work in the most cutting edge, dynamic thing where they can do the coolest, the most transformative stuff possible. And if that's in America, great. But if China does that, maybe it's China. But right now, China still mainly relies on its own domestic talent. They're not really importing much foreign talent either.

So to me, I think having that industry is really, really vital.

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Joe Wiesenthal
Nicholas and company incorporated member SIPC and NYSE. What are us universities doing? I imagine a high schooler graduating in 2024 probably way more than four years ago or even one year ago, are saying like, oh, yeah, well, this is what I want to do. I want to work in AI or something in this realm. Have we seen an expansion of what us universities are offering or capable of offering?

Has there been that sort of supply side capacity increase here to take advantage of what is almost certain an increased interest in this industry? Well, did you see the WSJ piece yesterday where all the Gen zs are becoming plumbers and electricians? Oh, I did, yeah. A return to trades. Yeah.

Damian Ma
I mean, you know, frankly, if I were 18, I might consider that route. But my understanding is that a lot of the top tier technical schools or things that have a technical school reputation, whether Stanford, Caltech, MIT, Carnegie Mellon, I mean, they definitely have AI programs. I don't know if it's to the extreme volume that China has offered in a span of two or three years, but they've definitely added those. But again, the foundation really is computer science. So I think if you go in and study computer science or some sort of mathematics foundation, that's going to get you into AI one way or another, much easier than if you just go straight into sort of AI, because you can't really think about AI without having any foundational knowledge from CS or mathematics.

Tracy Alaway
This might be a weird question, but it's related to the idea of people choosing to become plumbers or plasterers or whatever it might be. Do you sense a sort of, like, note of caution among potential graduates in the sense that a lot of people in recent decades were encouraged to go. Go into coding and become fluent in python or rust or whatever it might be? And now we've seen the rise of AI, we've seen models that can actually write your code for you, pretty much. And a lot of software engineers are currently a little bit worried about their job security and the outlook for their skills.

Does that impact the potential AI talent pool at all? Like, is there a sense that, okay, I can get into this, but then maybe in ten or 20 years, the AI is just going to be developing itself, right? Self learning models are already a thing, so why get into it at all? Oh, yeah, that's a tough question. Can AI be so good that it doesn't need any human input anymore?

Again, I've been watching the three body problems, so a little bit of a. Sci-Fi I don't know. I can't see that far into the future. But what I will say, I guess kind of a more realistic near term future. I think we said earlier that if AI is able to really solve human language, which is obviously a big indicator of human intelligence, and that seems to be a lot of where the efforts are, large language models and trying to figure out how to mimic human language, human thought through language, I would say one of the areas that's probably going to be in trouble a lot is translators.

Damian Ma
That whole area seems like it's going to be probably, for lack of better term, disrupted quite a bit. Or if you think about somebody that needs to do research in different languages, maybe in two or three years, I can read Japanese as easily as anyone else, just get it quickly translated on some AI software, and I can be pretty fluent in reading Japanese. That doesn't mean you shouldn't be studying foreign languages. There are a lot of intellectual benefits to that. But I think as a research tool and as the ability to kind of use it as a way to understand the world, once AI really gets to that point, there are going to be a lot of, I think, disciplines like translation, interpretation, those kinds of things.

It doesn't seem like there's going to maybe be a huge need for that sort of stuff. So in the earlier part of the conversation, you know, we talked about three necessary components to have a domestic AI industry. One is talent, one is sort of infrastructure, and then the other one is just the pure compute. And, you know, we see companies like Facebook like they tout as an advantage. We just acquired so and so many h 100s from Nvidia and we're spending $10 billion.

Joe Wiesenthal
And I kind of get the impression that having a lot of computing power is a recruiting tactic and that if you're a top AI researcher, you want to be at the place that has the most advanced sort of raw computing capacity. We know that there's a lot of restrictions on some of the cutting edge semiconductors going into China, and Jensen Wong of Nvidia has talked about this and the constraints there for a potential talented AI researcher, maybe from China or studied in China, does that factor into it? The fact that at least for now, it looks like still without question that the US institutions, whether we're talking about meta, whether we're talking about Amazon, Microsoft with OpenAI, have the most computing power to play with, for lack of a. Better term, that could certainly be one attractive factor. But I can't remember where I read it, but I was shown an interesting survey on one of the chinese social media sites where apparently our AI talent tracker got some traction in Chinese.

Damian Ma
And so a bunch of AI people in China weighed in. And if I remember correctly, don't quote me on it, but I think one of the main things that stood out was that one of the things that really attract that kind of talent is the research environment where they're able to have the freedom and the ability to have free thought and be able to kind of pursue things that they think are really interesting, that are really worthwhile. So that stood out to me as a really important factor beyond the compute of prowess and beyond compensation, obviously. But I think it seems like, at least, I think the United States still seems to really have that culture by default, and I think that's a really important ingredient that people shouldn't forget about again, I just think top tier talent tend to want to be unencumbered, unrestricted, because they want to pursue things that they think are really, really, really interesting and groundbreaking. And that's just the way they work.

And so you got to give them that environment to work in. All right, Damien, that was such an interesting conversation. Thank you so much for coming on. Odd lots. And it is the global AI talent tracker, and you can look it up online.

Tracy Alaway
It's got some really good charts and sort of interactive elements that you can play around with. So thanks, Damian, for coming on and walking us through the latest work that you've been doing. Thank you so much. Great talking to you.

Jo. That conversation answered a lot of questions for me. It was just interesting to talk about the patterns that we're seeing play out. I think it's kind of funny that in many ways, like, this is a new technology that everyone is excited about, but it's kind of playing out the way a lot of stuff has played out historically, where the US has a lead at the moment, and then China is rapidly on its heels and trying to build out its own capacity, and then Europe is in the background publishing thought pieces and new pieces of regulation about it. It's kind of funny.

Joe Wiesenthal
It's exactly right. I'm really interested in this idea that, you know, I do think that in the US, if you say AI at this point, either people think about the text generators or the image generators, which are amazing, but this idea, and we've been, and I think we're doing some more episodes coming up on it, but, like, there's also a lot of excitement that, like, there's more to AI than just human language. And we talked about it a little bit on the food automation episode, the idea that, like, if robots could sort of have the same framework where they're fed tons of data and then make better decisions so their arms aren't swinging or a slight deviation on the assembly line doesn't disrupt them, then that could be incredibly powerful if they had enough training data about all of these different scenarios that they face. And so it's interesting to see that China, which seems to be leading the world in many ways in terms of sort of electrical engineering capacity, that's also in alignment with where a lot of the AI researchers are going. Yes, absolutely.

Tracy Alaway
And I know I brought it up a number of times now, but that's why the consumer Internet crackdown was so interesting to me, because China explicitly said, like, we don't want all this money pouring into another new online retailer. We have enough of those. Why don't you take that money and invest it in chips or something tangible like that? And so I do think we are seeing that tendency right now, that focus on like real world applications, industrial applications, manufacturing, that you don't necessarily see in the US and other places in the west, because as you know very well, Joe, it's fun to play around with the chat bots and become the public face of this entire new technology. So that's probably one area where China does have an advantage.

But the other thing, I think so, first of all, Damien talked about the brain drain aspect of it and the idea that, well, a lot of China AI talent does end up in the US because they go to university in the US and then they stay there and there's demand for their services, et cetera, et cetera. Although maybe that will change soon. But then the other thing I was thinking is you brought up that question of compute power and whether or not that's sort of a carrot for AI developers. I also wonder about data and data restrictions in China and what data sets they're playing around with specifically for the large language models, but maybe for other things as well. That could maybe be a competitive advantage.

If you're really interested in this area, maybe you want to go to a place that has bigger and more wide ranging data sets, like Damien was kind of alluding to. Totally. The other thing I think is really important to watch. I remember like 2025 years ago, you know, when the number of, if you just looked at the raw number of people graduating with an engineering degree, it was exploding in China, and there was a lot of sneering in sort of western publications. It's like, oh, these are trash degrees.

Joe Wiesenthal
Yeah, people graduate with a degree in engineering, but it's pretty mediocre talent and not really that good. And we sort of have to take some of these numbers with a grain of salt. I get the impression that's changed dramatically a lot of these schools. And so the fact that there is, you can sort of come up with this objective measure of talent, which is who gets to speak at these big conferences. And if there is a broadening out of the number of degree granting institutions that are represented in that top 2% or top 20%, that strikes me as like a very important trend to watch.

And so these universities in China that, you know, I'm not familiar with any of them, but if there's like, you know, beyond just the sort of the equivalence of the MIT or Stanford are also contributing to that elite, that strikes me as a very key indicator to watch. Absolutely. And neural information processing systems, conference organizers, if you're listening, Joe's interested in going, so send him an invite, please. Yeah, I'll demonstrate some of the great poems and songs. No, I've done some.

And I had AI come up with a new verb tense for me. It was very impressive. So I come up with creative stuff. Oh, that's interesting. You didn't tell me about that one.

I didn't want to bore you with all my. It's not boring. All right, all right, I'll show you, I'll show you that one. Wait, have you started using Claude? Yeah, I love Claude.

Tracy Alaway
It's better, right? There's something about it, I don't know objectively about it, but this is also another interesting question. So while we're talking about this, this is like another interesting thing I'm wondering about, which is, what if it turns out that some of the sort of moats that we associate with software do not end up applying as well to AI? No, absolutely. Yeah.

Joe Wiesenthal
So it's like, I like, for whatever reason, because I like the interface, I like the way the nature of the language it speaks. I started using Claude a lot more in a way that I could never just imagine, say, like going back and forth between, like once I used Google in 2000, I never like, went back to Yahoo after that, you know, or something like that. I've been using Google ever since. It does make me wonder whether like, it'll turn out that a lot of institutions with sufficient talent, with sufficient compute, can kind of do the same thing, and switching costs aren't that high. Yeah, I was wondering about this as well, because the premise of this entire conversation was there's like a war going on.

Tracy Alaway
People are trying to develop their AI capabilities really fast because first one wins, kind of. But it does seem like some of these programs, like the motes, might not actually be that high. And once you crack like one level, it might be kind of fungible in other ways. I don't know. I guess it'll, it'll be interesting to see.

Joe Wiesenthal
Definitely. All right, shall we leave it there? Let's leave it there. This has been another episode of the all thoughts podcast. I'm Tracy Alloway.

Tracy Alaway
You can follow me. Racial away. And I'm Joe Wiesenthal. You can follow me at the stalwart. Follow our guest Damien Ma, he's amienix, and also check out his AI talent tracker at Macropolo.

Joe Wiesenthal
Follow our producers Carmen Rodriguez Armenarmon, Dash O. Bennett at Dashbot and Calebrooks Cale Brooks thank you to our producer, Moses Andam. For more odd lots content, go to bloomberg.com oddlots where we have transcripts, a blog in the newsletter, and you can chat about all of these topics 24/7 in the Discord discord, GG oddlots, and. If you enjoy oddlots, if you like it when we have these conversations over artificial intelligence, if you want a live demonstration of Joe's prompting of chat, GPT or Claude, then please, please leave us a positive review on your favorite podcast platform. And remember, if you are a Bloomberg subscriber, you can listen to all of our episodes absolutely ad free.

Tracy Alaway
All you need to do is connect your Bloomberg account with Apple Podcasts. Thanks for listening.

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Here's Who's Winning the Global Fight for AI Talent

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1: Introduction

2: AI Talent Dynamics

3: Guest Introduction - Damian Ma

4: Educational Influence

5: Industrial and Generative AI

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