Lawfare Archive: Kevin Xu on the State of the AI Arms Race Between the U.S. and China

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Be smart, get wise, download the wise app today, T-Sensee Supply. I'm Sarah Lowell Rich, intern at Wallfare with an episode from the Wallfare Archive for June 21st, 2020.

On June 12th, and Thropic abruptly cut off access for all users to the Mythos 5 and Fable

5 Artificial Intelligence models to comply with the Trump administration export control directive preventing access to the models by any foreign nationals. Notably, the directive also prevents foreign employees of anthropic from working on the models, but eventually hindering research and development of the U.S.-based models. For today's archive, I chose episode from December 9th, 2024, in which Kevin Fraser sat

down with Kevin Jew, founder of Interconnected Capital, to examine AI competition between U.S. and Shrine. The discuss the two countries' different approaches to AI development and how export controls could impact their efforts. It's the Law Fair podcast. I'm Kevin Fraser, Senior Research Fellow in the Constitutional Studies Program at the University of Texas at Austin, an entire bell fellow at Law Fair.

Join by Kevin Shoe, author and founder of the Interconnected Newsletter. There has been probably to your point, Kevin, an over-emphasis on keeping China from having the stuff that we have, as opposed to spending more time thinking about investing in our own industrial base, to build more of the stuff that we need and want here on our own. Today we're talking about the state of the purported AI arms race between China and

the U.S. following the recent announcement of updated export controls. There's a lot of myths and truths out there about China's AI ambitions and its AI capacity.

“So I think before we dive into some updates about what we're seeing the Army say, what”

we're seeing the Air Force say about their concerns about China's use of AI, can you give us a sense of your understanding of China's current AI capacity?

Let's save our conversation about China's AI goals for a second.

Let's focus first on what are its actual capacities when we think about the sophistication of its models, vis-a-vis, let's say kind of our leading frontier models here in the U.S. when we're thinking about open AI or anthropic or something like that. So I think it's helpful for folks to understand a little bit of the historical context of AI in general right between U.S. and China. There is the pre-jet, chatGPT pre-general

to the AI era of AI. That was very kind of a hot topic already. And then we are now in the post-chatGPT post-gen AI world.

“So I'll kind of separate those two things real quick, right?”

So pre-chatGPT China has already been advancing in now we call it traditional AI or traditional machine learning in a very meaningful way in terms of using big data to do predictive analysis for all sorts of consumer product, whether it's Fintech, whether it's e-commerce. And that has been very much seeped into its kind of manufacturing industrialization base as well when it comes to robotics, when it comes to supply chain management.

And these are all things that one has a lot of data being generated. And two, the lifeblood of any AI capability or capacity as you call it is still very much relying on both the quantity and the quality of data, which again pre-chatGPT China has had a lot of already. And so did the U.S. we weren't necessarily behind in a lot of ways.

It's just that these two superpowers have been kind of coming close to net connect when it comes to traditional AI application, if you will, pre-chatGPT.

everybody who works in technology because for people who don't follow the GPT or the open AI journey, it came out of nowhere essentially.

“And actually a lot of the I think has to do with COVID as well.”

The most meaningful GPT model for me personally, having worked in technology for a little while it now was actually GPT-3, which was launched in the middle of 2020 in the middle of COVID, when the world was still being confused about whether the world was going to end or not. But GPT-3 came out with already very capable coding abilities.

And a lot of programmers and nerds like myself are already looking at the autocomplete ability

of GPT-3 as a model, which has actually moved into the first meaningful AI application, which

is GitHub co-pilot, which is the coding assistant product that was launched actually technically a few months before, chatGPT came into the world. And I think when chatGPT came on the scene, a lot of technologies in China were also caught by surprise. As much as they were doing to do traditional AI, they were completely kind of flabbergasted

but the ability of generative AI to be able to do this. So there was this huge kind of rush, like kind of a gold rush, of VC funding, of state back venture funding into a bunch of AI model companies, both startups, which we can talk a few of them about, but also within the large technology companies in China, like Alia Baba, you know, ten said, by do what have you, all of their internal AI divisions have started

making AI models, right? There's this term called 100 model war in China in the last couple of years, where everybody in the realm is making AI model, everybody knows it's not sustainable, but everyone's rushing towards this next moment of technology inflection, which again has a lot of mirror images in Silicon Valley as well, there's all kinds of AI models companies that were funded in the last couple of years and a lot of them are being kind of absorbed.

So, you know, when you talk about AI capacity, I think there's a lot of weaknesses to the Chinese system when it comes to making generative AI applications in particular that we can dive into, but there are also a few advantages, maybe, that China can take to their own liking if they want to kind of advance past the US, but right now, my personal estimation is that China in general is still like a year to maybe year and a half behind a state

of our models in the US, but that gap is kind of always shifting depending on which

day you ask the question.

“And I think it's important for folks to know that Stanford recently released a report”

suggesting that the US wasn't indeed ahead of China with respect to AI capacity. China was number two, the UK was number three, and they said, you know, it's still a competitive space with respect to all of these different nations, and I think as you point out, Kevin, myth that love to tackle right off the bat is you hear some people speculate that the only thing going in China from an AI perspective is stealing meta's lava model.

And they're not even stealing it because it's open source, but there's this narrative out there that China's just relying on meta's lava model, which is open source as opposed to something like cloud, which is offered by anthropic, which is a closed model. And you help readers break down that myth, or perhaps there is some truth to it. How much is China relying right now on the US for making progress on AI?

I will call that a half myth.

“I think the part of it is true is that meta has released probably the most capable model”

in the open world, right? I think technically we call them open waste models, not open source model. And I know that's a bit of a semantic difference, but at least we're a lot of people in the open source, where like myself, whatever meta has opened is not, where we consider open source, because there are three major components to any model.

You have the weights themselves, which is basically the probability estimates of any given

input output in the model. And then you have the actual data that went into the training of the model. And then you also have to code the mathematical functions that make up architecture of the model, right? And so far, most of the quote unquote open models have only opened the weights, not the

architecture/code, nor the training data, or the input data to train the model. And those two things are arguably way more important than the end result of the weights themselves. Now with that said, I do think a lot of Chinese companies have been very quick to deconstruct Lama every time a new version has been opened, right? And this notion of stealing is a bit of a sort of a padding ourselves in the back when

the information is completely open.

And that's very much a value-normed within the open source community globally. Is that when you open source something, it's therefore the taking, right? There's no my homework that you are now stealing to a Seor test using my open source code so to speak, everybody is just taking whatever is open to iterate on, to build upon, to use for your own good if you want to, but also to build on top of each other.

That is kind of the most sort of healthy positive some way of understanding open source as a development, a technology building process or development model, if you will, right?

“So that's what I think is sort of the half-met part.”

I think the other half-met, and this is something that's a bit more newsy perhaps, is that

over Thanksgiving weekend or over Thanksgiving week, rather, we have seen two Chinese AI companies come up with reasoning models. This is not matching Lama anymore. This is matching OpenAS01 thinking model, right? This is sort of the next stage of AI model advancements, if you will.

They have match or come close to matching the capability of O1 model and O1 is not open source. It's very much close hold of black box, yet given whatever we know about O1, two Chinese companies have been able to get close to replicating its capability. One is DeepSeek, which is actually a hedge fund that is doing AI modeling building, the other one being Alibaba, and they're actually both planning on open sourcing

or open waiting their O1 equivalent. So they are even going a step ahead as far as giving the best stuff they have for free into the open versus kind of state-of-the-art model development in OpenAI or in Swapek or Lama or what have you. So the dynamic is changing literally week to week, and is very fast enough to watch this competition

or race or however you want to frame it. What's startling, too, is seeing the discrepancy in the approaches used by China and the US with respect to leaning more into open source models, which we're seeing in China, versus the US seemingly wanting to champion and embrace a closed approach. So if we look at the national security memo, for example, that was issued by the Biden

administration a couple months ago, there was a big emphasis on making sure the various defense agencies were capturing and helping cultivate the latest models offered by OpenAI or in Thropic and helping encourage that innovation from firms that have traditionally been producing closemox. And a big rationale has been, we want to make sure no adversary in particular China

“can access that same technology. What's the rationale behind China taking the alternate approach?”

Really trying to champion this, as you pointed out, grandma's fighting grandma's over the latest model, seeing all of these hundred different models fight one another for dominance in the open source space. Why is China leaning into that approach given its broad ambitions that we can talk about

in a second? So historically, China has had a pretty long relationship with open source dating

other way back into the early 2000s. A lot of its companies embrace open source at that time already, as very much a way to catch up quickly, right? In its kind of lagging positioning, very vis-a-vis US technology in general, you have some of the largest companies like Alibaba and others literally building their infrastructure stack on open source technology the time to weed itself from paying for the proprietary equivalent of again US technology vendors. And I will say at that

point, it was very much this classic kind of taking and building to catch up relationship when it comes to open source. Now fast forward to probably around, I was four years ago, open source

“as a term has become a fairly key component in China's kind of technology slash industrial policy”

overall. One document that was interesting was about three years ago or four years ago, the Ministry of Industry and Information Technology, MIT, which is one of the kind of the governing bodies in China that regulates much of its technology industry has fused the term open source into one of this policy document and one of the goal or guidance that it has given to its industries, that it hopes that China will be able to produce two to three open source projects of global

recognition by year 2025, right, which is, you know, around the corner. And this was again all

embraced, not only as a way to catch up, but perhaps, and this is me speculating, also as a way

to project China's technology power, almost in a weird soft power sort of way, like we're very okay with producing and making technology in the open, give the way to the world, let everybody and anybody who wants to use a database or an AI model or some random data engineering, you know,

“library that you need to build your cloud infrastructure, use a open source package that just was made”

by Chinese, you know, organization or company when they started, right. So that has been a positioning for a while. And in the AI context, more recently, I think when the four minister of China visited the UN, during the UN, they were talking about kind of AI policy and what does AI mean for China's foreign policy, I think open source was also mentioned as a component

of how China wants to be a critical leader in the AI conversation world and promote AI's adoption

particularly in the global south, right. So it's a very interesting contrast, as you mentioned, kind of in between the way open source has been used as a piece of foreign policy or the measure industrial policy versus how the U.S. is currently viewing it, which is a bit more kind of closed hold. And we're talking on December 2 which is the day that the Bureau of Industry and Security announced its updated export controls here in the U.S. trying to diminish Chinese

“access to key components in developing and further researching AI models. And a lot of that hinges”

on the idea that China is following a similar strategic approach as the U.S. with respect to developing and advancing its AI capacities. So with respect to trying to diminish China's access to certain chips with respect to enlarging the number of blacklisted companies that can't receive certain chips from various U.S. manufacturers and U.S. allies, are these export controls even being updated and expanded? Do you see them as being very efficacious with respect to trying to

slow China's development of AI? So obviously, Kevin, as you mentioned, we're recording on the day when the export control or the new round drop. So all of us will follow this topic closely or literally still going through the hundreds of pages of legal leads and conditions and exceptions as we sweep. So, Kevin, you know I'm a professor, so I have to give tough assignments. Exactly. I code called people and you're getting code code, you know, it's just it's happening.

“So to respond to your code called question, based on what I've seen so far, I think both the”

previous round, which was in October 2023 and this current round that we're talking about right now, have very much been focused on limiting the hardware and the ability to produce the kind of hardware that China needs to advance as a generative AI capacity or capability visa via the U.S. And one of the most notable additions to today's or the most recent update is a high bandwidth memory, right? I think anyone will follow the hardware conversation of AI knows that

high bandwidth memory, in addition to very powerful GPUs from the video or AMD, are the key

ingredients to producing the kind of computation capability needed to train larger larger larger models, which the assumption still is that as the computation scales, as the size of the model scales, so well the capability of the model proportionally. This is becoming a bit of a hotly discussed topic in the AI world right now, so we won't get into who's right, who's wrong because frankly nobody knows, but I do think that the newest round of expert control is very much

focused on the next layer of hardware capability that needs to be restricted from the U.S. perspective. And this is both the actual kind of selling of the end product, the memory, but also a lot of the equipment that will go into possibly allowing China to produce themselves. And we're getting into a lot of interesting territories as well because we've seen Chinese chip fast being able to say produce a seven nanometer capability chip despite the assumption that the previous round of expert control

was more than enough to keep them from being able to do so, right? And if you dig into the details of these lithography equipment, you also find that all their generation lithography equipment that China was still able to either procure or keep from, you know, before expert control

chips, a bet with poor yield, right? So the conversation basis is they can make it, it's just a matter

of how much they can make it within the time frame they need to be able to scale up this capability. And now we're going to come up with another round of sanctions that will keep them from being

“able to do that in the future, right? And I think all this is also based on the assumption that”

the transformer model, right? The T part of TGPT is the answer to AGI. And if it is, then I do think and I have said this public before that our current kind of set of U.S. expert control measures

has been tough enough and I think to your question efficacious enough to keep China kind of reasonably

behind, depending on how you define reasonable, whether it's a timeframe or, you know, versioning or whatever, so that we have this like maybe sizeable, maybe not comfortable, maybe sometimes uncomfortable lead to keep going with this AGI race, right? And I don't think the assumption should ever be that with this expert control, China would just actually lie down flat and give up. I don't think that's ever been the goal of these policies, maybe some people

had hope that would happen, that's certainly not happening, giving everything is happening with

“Huawei and whatnot. But I think that is where we're going. So that is kind of the current understanding”

of the expert control. And I will say one last point on the late breaking topic is that I do think the kind of global alliance of expert control is falling apart a little bit. We all know that there's a lot of important equipments being made from Japan, from the Netherlands, from other parts of Europe, that are very much in the chip making supply chain. And previous rounds of expert control has had a decent enough traction with ally governments. So we all kind of stand in the same

alliance, so to speak, when it comes to executing that, because if the US is the only one doing this, it really doesn't matter, right? And right now, based on reporting so far, it hasn't looked like the Japanese government or the Dutch government is going to kind of follow step-by-step with what the US government has released so far, maybe that would change in the coming weeks. But if that kind of alliance does not become as kind of lock step as it used to be,

then I do think the expert control as is intended will become less effective over time. With LPP, with online shopping, no, just one thing. In Trieden, Varat and E. Pishish Lachten, all of that was a new stuff. Also, streamed up the 226th Unii, the new stuff will house up the dragon and all the series from Game of Thrones, newer of HBO Max. And Kevin just said, really zero in on that.

Would you say that part of the reason we may see diminished willingness to step in line with the US base export controls is just the fact that China is a huge market. And if you can tap into that market, that's a, that's a lot of dollars on the table. If you're producing, let's say in Japan

“or in South Korea, if you want to expand your market right next door, it's hard to follow the”

party line set by the US. Is that good understanding or are there other factors? I think the profit motive, and the size of the market is one part of the equation. I think the other part of the equation is the national security justification to all this expert control overall that the US has kind of placed on itself as the burden of proof. If you well, the party to really tell the rest of the world how important these sets of restrictions are to their own security.

Like how does, how could this benefit Japan's national security? How can this benefit

a little bit of a tougher conversation. And if you kind of project forward into a Trump administration where the definition of international alliance is very different, that you say, from the Biden administration, then whether a country doesn't matter how long standing of a relationship we've

“had with this country has been able to follow along so far in terms of expert control. I think”

this is one of the pieces of the puzzle or perhaps one of the chips on the bargaining table that these countries will have to keep there, right? When it comes to negotiating tariffs or negotiating some other sorts of things with the Trump administration before just kind of following along in lockstep with the United States, whether they sign up to the national security argument or not, while being lobbied by their own company. And some of them are their own national

champion. These are not some itty-bitty little small business associations lobbied them. These

are the most important technology company in their respective country, whether Tokyo Electron,

whether it's ASML, they're very powerful and they ought to be very powerful voice in the way any government makes their policy. And of course, they're making a lot of this very much geared towards being able to maintain at least some level of predictable access to China being a huge market. I don't think these companies are completely ignoring national security implications. I don't think they're exactly that naive, but it's got to be a balancing act as opposed to every

year the stuff I just earned the five years ago that I was going to ship off to sell. It's just all of a sudden I can sell to a quarter of my market. And that is a very difficult way to do business even under the best circumstances. You don't have to get an MBA to agree with that statement,

“all right. That is a that is a tough one. And I think you'll be pleased to know from a cold calling”

perspective, you definitely get a check-plus, which is the five stars on my grade sheet. That's

something I never got in law school. So I appreciate that. Oh gosh, yeah, you had all high honors.

We know that you all age agents here. So I'm keen to know on that national security angle, another key narrative is that China is racing ahead to militarize AI and to integrate its AI into military operations into weapon systems. We see, for example, concerns raised by the Secretary of the Air Force that AI is going to be a core component of China's potential invasion of Taiwan. As soon as 2027, we see a lot of national security experts raising concerns about the need for the

U.S. to lead in AI because China is going to race ahead. Recently, I've read about the fact that China is seemingly isn't embracing the need for a human in the loop with respect to the use of AI in a lot of these weapon systems, thereby allowing them potentially to use AI in more risky situations or with greater speed. So this whole narrative about China's emphasis on AI being a core component of its national security goals, where are we on the truth mythscale there? Are we dealing with

another half truth or are our pants on fire? What are your thoughts? So first of all, I want to

caveat by saying that I'm not a military expert. I spend more time doing investing. So I'm much more of the business tech guy, if you will. But of course, the military conversation is looming very large in the AI safety part of AI conversation. One thing I do want to note is that during the very last meeting between Biden and Xi, this is on the silent of the APAC summit in Lima, the two leaders committed to keeping a human in the loop when it comes to launching nuclear weapons.

So there's that one. So this is a very important but kind of under-reported commitment.

“That, frankly, on the one hand, it feels very dumb common sense. Like, of course, you should”

have a human in the loop before launching a nuclear weapon, right? Yet, we are in this very interesting AI world where that may not be a case. So to put perhaps some existential fear aside for people who are listening, I do think both of you United States and China, and any well-meaning state actor with nuclear weapons, will or should sign on to some sort of commitment that AI will not be the only component that decides the launching of a nuclear weapon, a human will be in the loop,

right? So that's number one. I think number two, a lot of the AI conversation when it comes to militarization has been wrapped up into drones. And of course, that is another application of AI, and it has been

conversation as far as I'm concerned. China has, of course, also been leading in kind of the commercial

civilian drone industry with companies like DJI and a bunch of others, where when the US has been largely actually a consumer of these products, as opposed to also a maker of these products, right? Which is kind of bananas if you think about it from our own natural security perspective, and I know that a lot of people are waking up to this, where we have our own drone companies now, but they're still relying on Chinese components to make the drone. So there's a whole lot of

“supply chain that you need to untangle to completely kind of domesticate or kind of homegrown your drone”

industry. If they're used for the purpose of military application, right? And if you separate those two things, the only sort of real AI conversation, the context of military that I've heard, is one, of course, is the offensive, right? Use drones to fight the worst that we would have usually sent humans to fight. Thus, less human die, at least our own human die, but our enemies human could still die with the drones that we use. So very dark, but, you know, that is the AI

conversation when it comes to offensive. The other side of the AI conversation, that's frankly a lot more benign, but that gets wrapped up into the conversation. It's just that, hey, now we have all these really cool large language models, foundation models, that we can perhaps apply to better manage the supply chain and operational back office processes of the Department of Defense, of the Army, of the Navy, or the equivalent of that in the Chinese side. So the procurement

and the operational side gets a little bit more efficient. That is just, you know, optimizing your back office, right? So that's not in my mind inherently military, but it's serving an organization

“that does military things. So I think, before we kind of get to wrap up by the militarization of”

AI, whether it's in China the US, we should separate the end use cases first and then think about

what are the safety consequences, whether it's for a country or globally speaking that we need to be aware of. Speaking with your business tech guide hat on, I'm wonder if you were the AI's are, which we may soon have, according to recent news reports under the Trump administration, if you were the AI's are, knowing that the transformer approach to AI development may not be the end-all deal with respect to winning the proverbial AI race. Do you think that the sort of

widespread embrace of competition seemingly in China trying to incentivize as many different companies as possible to develop as many different approaches to AI is maybe the better long-term strategy with respect to achieving AI or do you think having key identified national champions, let's say an open AI or anthropic, and really investing as much as possible in those companies is a better

“tactic, wearing your business investment and kind of tech acceleration hat. I think if I were an”

AI's are for a day here in the United States with the pro innovation hat on, it's an open question, whether transformer is the end-all beyond model, even though there's a lot of capital being devoted to this direction already, and I think one, I would be very lightweight on the set of regulations that I will put on our best companies, whether it's Google, OpenAI, Microsoft, the startups, what have you, and that's one of our key advantages quite frankly vis-a-vis China, where the Chinese

best companies doesn't matter how innovative, doesn't matter how capable, doesn't matter how well funded they are, are living under a much more heavy-handed governing system overall. I'm all sorts of things, even the most banay thing about releasing a next version of a new chatbot with a new model I just came up with that has like 30% incremental performance gains, but it's now a different version and now need to go through the regulatory system to get some kind of approval or at least

registration, at least some kind of hurdle, right, to even release this product to the consumer to

get some feedback, right, and under that environment, chatGBT would have never been released in the first place.

ChatGBT can only happen in the way that it did because it lived in the United States or started in the United States. It couldn't even do what it did in Europe, right, or other sort of more like-minded regime, if you will. So that's kind of point number one, because if the transformer is not the end answer, I would like, you know, US companies to figure out what is the next thing that

I do think AI safety is a legitimate concern and one template that I would kind of as the AI ZAR replicate or scale out is, I think what Enthropica is doing with our nuclear kind of energy commission here in the United States, which is that every time Enthropica came on with a model, they're going to work with these very important key regulatory agencies that holds the keys to

these world destroying weapons or capabilities first, to have a very close red team in relationship.

You know, let these experts test out this new model first to make sure it isn't inadvertently creating nuclear weapons, which is where everyone's fearing, right? You can just get an instance of

“cloud and now you can create nuclear weapons, which is kind of silly to begin with, but that's what”

people are afraid of. Then that's removed that risk once and for all with the right expert within the government to do so. And I would suggest frankly, every country to do that for their own sake. Before you release the next model, making sure all of these kind of existential, if not low probability risk are being kind of removed first, before we release it to the consumer, to do more positive, more productive, more interesting things with AI. That's sort of the way

I would think about it. I mean, pretty strong pitch for AI's arc, Evan. I gotta say that wasn't bad. So when we're thinking about some of the other myths or key things, you think more folks should know and understand about China's AI capacity and ambitions. Are there any outstanding myths or truths that you really want folks to know about? I think one thing I would, let me be two things, one of just that Chinese open source as a force is becoming more and more recognized around the

world. The US used to dominate open source contribution when I was working at GitHub and working with

open source organizations. The US also always dominated a chart when it comes to the amount of contribution.

And we still do. But China has been catching up very quickly. It is by most measures number two

“in the world. I think Germany and the UK kind of battles out number three depending on the project.”

Right? And that is a, I think net net good thing for China to actually produce and give more and not just take more. And I think there's a good way to encourage that without a lacking that into too much military or kind of national security geopolitical related conversations because for the most part, code is just code and they're just very utilitarian tools to build things. Right? And China's becoming much more of a contributory, not just a take of that. And the second thing I would mention

is, and this is more of an observation than an opinion, there is actually no AI institute or AI

safety institute in China as far as I know. You know, we are standing one up in the US, you know, Japan, Singapore, South Korea, a lot of countries standing up these AI-SIs, right? We had a summit of source of these institutes in San Francisco and not a lot of long ago. China was not present as far as I'm concerned. And one of the reasons China as a country actually does not have a singular body that quote unquote does AI safety. And that's a very interesting phenomenon to kind of maybe

peer into what does the Chinese leadership at least think about the danger part of AI versus the productive part of AI. There are a lot of turf battling within different government agencies right now to be the Chinese AI institute owner or safety institute owner. But that's still like a TBD kind of a development. And I think that's very instructive in terms of thinking about perhaps for whatever reason the Chinese government doesn't think the AI safety is

nearly as high of a priority. Among all their priorities they have to tackle as we think over here or we think they should have over there. And that's something that we should think about when it comes to the overall global conversation with the AI safety. It's not to say China's in care of AI safety. But as far as the positioning this concern, it's still something that they are trying to figure out what they should do domestically and how they want to project those views to the

rest of the world. One final question with respect to both the ambitions of China and the U.S. I think there are some concerns, count me among those who who have this concern, that the perpetuation that we are engaged in, AI armed race might distract us from other potential AI use cases, right? We've seen that the creation of an armed race like in the Cold War can lead to important advances in technology that later have downstream consumer impacts that are positive,

“you know, that's how we got the microwave, that's how we got the computer arguably.”

You can point to all these positives as a result of competition in innovation. But do you

we may experience a delay, delay in the realization of more productive AI use cases or

“societally beneficial AI use cases? I think it's mostly positive for my perspective. I think”

whether you take the race or the competition literally, slash seriously or not, it has in the United

States, first of all, really revamped the conversation around energy sustainability and security,

right? Like nuclear power is making a comeback. There's a lot more embrace for nuclear technology overall from a civilian use case and that has very much been powered by the need for AI infrastructure build out because of the power hungryness of the GPUs that needs to go into it. And that could probably be also a good catalyst to upgrade our smart grid overall, our entire energy infrastructure,

“so I think net net that's probably a good thing. Now, when it comes to distraction and I don't know”

if I can tag this to the AI competition per se, but I do think maybe an over-obsessiveness with

keeping China away from getting our chips capability, whether it's equipment or software, or, you know, actual a product, has gotten a little too much attention. We're talking about expert control today, but you know, what also happened today is the resignation or some actually room to say a push out of housing or who's the CEO of Intel, right? So he resigned over the Thanksgiving holiday as well and that is just like more start on the wound of a really

a really national champion in the United States that has really not gotten enough together and is continuing to flounder in my opinion. And if we don't build up that capacity to just make our own chips and to use that as a way to boost other parts of our industrial capacity when it comes to

“making an electric vehicles or batteries or all these sorts of other stuff, then I think there”

has been probably to your point Kevin over emphasis on keeping China from having the stuff that we have as opposed to spending more time thinking about investing in our own industrial base to build more of the stuff that we need and want here on our own soil. Well, you've certainly given us a lot of things to keep track of. I think the implementation of this latest round of export controls will be fascinating to watch who may be appointed as AI ZAR of course will give us a big sign about

where AI policy may be headed under the next administration and of course keeping our eyes on China and its own developments. A job for many people including you Kevin so get ready for being cold called once again at some point but for now we're going to have to leave it there and have you on down the road. Thank you so much for having me. The law fair podcast is producing cooperation with the Brookings institution. You can get ad free versions of this and other law fair podcasts by

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Jen Pacha and your audio engineer this episode was known as Ban of Go Romeo. Our theme song is from

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