From Cold War to Code Wars: Unpacking America’s Bold AI Strategy
Welcome to another episode of Data Driven, where we delve deep into the crossroads of data, technology, and the ever-shifting world of geopolitics. In this packed episode, hosts Frank La Vigne and Bailey are joined by Christopher Nuland, AI technical marketing manager at Red Hat, for a candid, no-holds-barred discussion on the newly released America’s AI Action Plan.
Together, they tackle everything from the resurgence of Cold War tensions in the AI arena to the complexities of “AI sovereignty” and what it really means for the US, China, and the rest of the world. Expect spirited debates about EU’s place in the global AI race, the real-world implications of chip supply chain disruptions, and the heated rhetoric around workforce security in an era when AI is starting to replace traditional jobs.
The conversation weaves through existential questions—can AI ever truly reason, or are we just witnessing the rise of superpowered “spreadsheet goblins?”—and gets hands-on with the very real risks (and opportunities) of rolling out LLMs in everyday workplaces. Plus, the team touches on power-hungry data centers, potential impacts on the job market, and even finds time to swap sci-fi references from The Expanse to Ghost in the Shell to help paint a picture of what our AI-dominated future might look like.
Buckle up for a dense, dynamic, and dangerously nerdy journey into the world of AI policy, technology, and what it means for all of us. Let’s get into it!
Timestamps
00:00 AI Geopolitics & America’s Action Plan
08:14 EU’s Role in Tech Hierarchy
14:10 “US Focus: Securing AI Workforce”
20:40 Supply Chain Security in Software
24:24 Politicians’ Technical Proficiency Limits
27:19 AI Sovereignty and Cultural Values
33:52 CHIPS Act: Innovation and Expansion Hopes
38:11 “AI Vulnerability: Patch Attacks”
47:58 Maryland Power Line Controversy
50:09 “AI Impact on Jobs & UBI”
55:47 Techno Feudalism Perspective
01:04:41 “AI Sovereignty: A Geopolitical Chess Match”
Transcript
Welcome back to Data Driven, the podcast that dives into the collision
Speaker:of data technology and occasionally geopolitics with
Speaker:the finesse of a caffeinated quantum computer. In this episode,
Speaker:Frank Lavine is joined once again by Christopher Nuland,
Speaker:AI technical marketing maestro at Red Hat, for a no holds
Speaker:barred breakdown of America's freshly minted AI action plan.
Speaker:From Cold War vibes and AI sovereignty to the CHiPs Act,
Speaker:GPU geopolitics, and existential musings on large language
Speaker:models, this episode has more hot takes than a GPU server farm
Speaker:in July. Plus, we debate whether Europe can still flex
Speaker:its AI muscle without surrendering to Silicon Valley, and whether
Speaker:AI models will ever truly think or just continue to be unreasonably
Speaker:effective spreadsheet goblins. So buckle up, data
Speaker:disciples. This one's dense, dynamic, and
Speaker:dangerously nerdy. Let's get into it.
Speaker:All right, that bouncy little pop number. That is a fun
Speaker:fact. AI generated can only mean one thing. It's time for
Speaker:a new edition of Frank's World TV Live or
Speaker:an episode of Data Driven, depending on where and how you're listening, slash
Speaker:watching. You can catch me at the following URLs. Franksworld.com
Speaker:data driven tv and impact
Speaker:quantum.com speaking of impact
Speaker:quantum.com my co host and I have launched another
Speaker:book and it's basically Quantum
Speaker:Curious, the Gateway to the Next Computing Revolution.
Speaker:And what that is is we basically took the third, the first
Speaker:13 some odd episodes of the season and distilled it down
Speaker:into a little book. It's 2.99 on Amazon, but if you join
Speaker:our mailing list, it's completely free. So go to Impact Quantum or scan
Speaker:the QR code to find out more. All right, now that I've gotten the
Speaker:commercialism ism out of the way, I'd like to welcome
Speaker:back our guest, Christopher Nuland, who is
Speaker:a peer of mine on the same team, an AI
Speaker:technical marketing manager at Red Hat. How's it going? Good,
Speaker:good. Glad to be back. I think
Speaker:we ended the last talk on kind of a cliffhanger, and then
Speaker:I think some recent news has really built on top of some of that
Speaker:previous conversation. So I'm happy to be here talking about some big things
Speaker:that are going on in the the area of AI right now. Absolutely. So
Speaker:over the weekend, the Trump administration dropped the thought on
Speaker:the Amer AI's America's AI Action
Speaker:Plan. I think somebody likes alliterations.
Speaker:But so, and you and I were chatting about this over
Speaker:Slack and, and, and, and you had some thoughts on this. So, like, what.
Speaker:And you had some interesting ideas around it, and some surprises are in the bell.
Speaker:So let's. Let's get into it. Yeah. So
Speaker:I think overall, this is really needed.
Speaker:We've seen a couple things like this come out for some other
Speaker:countries globally. The EU has
Speaker:this. I'd say the one from the US is more of a set of guidelines,
Speaker:or the one from EU is actually some laws that they're trying to pass that
Speaker:have some similar tone to this one. You know, we're
Speaker:seeing things out of the uk, out of Singapore, other, you
Speaker:know, other nations that really are trying to get an
Speaker:idea of what is their strategy around AI
Speaker:sovereignty. And this, to me, is a document
Speaker:more about AI sovereignty than anything else.
Speaker:It's really about how. How does the US
Speaker:go into the next phase of really almost
Speaker:like a new industrial revolution around AI and
Speaker:this document's really outlining the plan.
Speaker:I think overall, I thought it was pretty well thought out, and we'll go through
Speaker:and kind of pick apart some of the key areas. But I think
Speaker:overall the. The key tone here was about
Speaker:AI sovereignty, so specifically within the US
Speaker:and how we're going to be managing that. And overall,
Speaker:I thought it was. It was good. I know. You know, when we were talking
Speaker:on Slack, we were talking about how there's definitely a lot there about China
Speaker:as well. Right. In a weird way,
Speaker:I. I felt like this document was a bit of a. A declaration
Speaker:of. Of war in a way, because in
Speaker:a document, it outlines that
Speaker:they really consider this now like a Cold War with.
Speaker:With China around AI and what I thought was so
Speaker:fascinating is I kept going back to this analogy of, like,
Speaker:the Cold War arms race of Russia and how
Speaker:we need to do certain things around AI because we basically need to
Speaker:mimic what the United States was able to achieve during the
Speaker:Cold War. And I think that sat with me
Speaker:because I think, you know, even last time I was on here, we were talking
Speaker:about how we. We basically. No, there's a Cold War kind of thing going on,
Speaker:but it was. It was different seeing
Speaker:it. You know, you and I were talking earlier, like, on the letterhead. It was.
Speaker:Yeah, it's different. You know, like, there's. There's things that are. Obviously, you
Speaker:can see with your own eyes, but it's quite a different thing when something appears
Speaker:on official White House letterhead. Right. Or even,
Speaker:you know, government letterhead. I think that's. It's an interesting,
Speaker:interesting shift. And this whole idea of a Cold War between the US
Speaker:and China and AI is Not a new concept.
Speaker:Right. I. There's a really good book and I'm gonna see if I can share
Speaker:this tab real quick. This is an excellent book. It's an
Speaker:excellent audiobook too. There you go.
Speaker:Oh, there we are. Sorry everyone, my dogs are barking.
Speaker:But this book came out in:Speaker:lot of what he predicted has come to pass.
Speaker:And it seems to me like the authors of this document have also,
Speaker:if not read the book or listened to the book, have at least seen the
Speaker:Cliff Notes version of it. Right. Like this, if you really think
Speaker:about it, there's really only two major players right now in
Speaker:the AI space and we're going to alienate a lot of people in the eu.
Speaker:Right. But saying that, right, it's really largely
Speaker:US and China, right? Yes. And
Speaker:not to say that the EU is not in the games, clearly, Mistral. And
Speaker:apparently there's a rumor, I don't know if you heard this rumor that, that Apple
Speaker:is considering buying Mistral. I have heard some of those.
Speaker:So again, I don't own any of Apple stock or whatever, so I'm not. Or.
Speaker:But I think it's an interesting con, Interesting idea if they were to do
Speaker:that because clearly that would, I wonder how that
Speaker:would shift kind of the balance of, if not power,
Speaker:perceived power. Right. Because Apple
Speaker:obviously is a stalwart of Silicon Valley and if, you know,
Speaker:if Europe's major, you know, every
Speaker:time you talk about the EU falling behind, they always say, what
Speaker:about Mistral? Right. So if Mistral ends up getting purchased by, you
Speaker:know, Apple, that would be, that would.
Speaker:I think there'd be a lot of drama about that. Yeah, I think so
Speaker:too. I think it, it really just shows there's a line in the
Speaker:sand between the two major superpowers here, between
Speaker:China and the United States. My
Speaker:speculation there is that there might
Speaker:be something official there, but that the EU might step in
Speaker:and just say no. Right. To that.
Speaker:Simply given what we're here talking about, AI sovereignty. And what does
Speaker:AI sovereignty look like? I, I don't think the, the French
Speaker:necessarily want to give up that and I don't think the EU wants to give
Speaker:that up
Speaker:from an open source standpoint. We're still seeing a lot of thought leadership
Speaker:coming out of the eu, even though there's not
Speaker:enough, what I would say, enterprise momentum there.
Speaker:Right. There's still a lot of research institutes there. There's still
Speaker:a lot of, even some smaller form companies
Speaker:like even like Hugging Face and Mistral for example, are, you know,
Speaker:EU based that have made A big impact and are very open
Speaker:source heavy and but at the end of
Speaker:the day they're just still very small when you
Speaker:consider these behemoth organizations like Microsoft,
Speaker:Amazon, Nvidia, Apple, all the
Speaker:fang corporations which have,
Speaker:that can really throw their weight around. And we've seen a
Speaker:lot of, a lot of
Speaker:startups like OpenAI that has like
Speaker:climbed up now into the upper epsilon and
Speaker:that's being really driven by American industry. So
Speaker:and that's just something the EU can't prop up as as much.
Speaker:But I still think they, they're a major
Speaker:player. They may not be necessarily
Speaker:one to one with China and America, but if there was a
Speaker:second tier right under that, it would be the eu. Yeah, I
Speaker:can see that. I also think it's too early to count them out of the
Speaker:race. Right. Like, yeah, you know we're, this is the start of the
Speaker:marathon. Right. So they're clearly, clearly there are two front runners.
Speaker:But I don't, I don't, I wouldn't count them entirely out just yet. Right.
Speaker:And I didn't know Hugging Face was a European company. I thought they were based
Speaker:out of New York. But that must be their American. I
Speaker:believe you may be right. Let me show Hugging Face.
Speaker:I know. I think the founders are European.
Speaker:You are correct. Founders are European, but they are based out of
Speaker:America. And that just goes to show right there.
Speaker:Yo. That the gravity of just American enterprise. That
Speaker:you can shell out a lot of money to get, to get talent. Right. And
Speaker:yeah, this was the thing that a European tech founder said. Right. So you know,
Speaker:all the Europeans don't hate on me, but there was a lot of founders that
Speaker:they'll end up moving to Dubai. Right. Bootstrap and
Speaker:then move to Silicon Valley, you know, at some point. Right. Like,
Speaker:so I think the, the
Speaker:European Union as a whole
Speaker:has to address some systemic shortcomings when it comes
Speaker:to a venture capital and startup
Speaker:pipeline. Right. And I hope I, I
Speaker:think that they'll get it figured out. I just don't think that they're going to
Speaker:get it figured out this year. They might
Speaker:get it figured out by the end of the decade because I think that,
Speaker:you know, just a little bit of back of the napkin math, right. You, you
Speaker:know, it's, it's, you can see
Speaker:that growing the tax base is good for everyone
Speaker:and this is one way to do that. And if you have your
Speaker:brain drain, which we'll get into that, that term, you know, either
Speaker:going to Dubai, you know, Silicon Valley or New
Speaker:York, it's not Good. Right. Because
Speaker:you're, you're basically, you're educating them in country. Right.
Speaker:And a lot of these countries have, you know, cheaper, you know, free tuition.
Speaker:Yeah. So you're paying for the talent, you're training up the talent, you're
Speaker:paying for talent. And then when time comes in to cash in on the return
Speaker:on that investment, if you want to look at it that way, throughout of country.
Speaker:Right. So what are you going to do? I think that it's
Speaker:in the EU's best interest to fix that problem. And like
Speaker:you said, like sovereign AI or is a big deal.
Speaker:And sovereign AI is different than sovereign than data sovereignty, right?
Speaker:Yep. It's the. And I don't think people really kind of gotten their head around
Speaker:that. So I know what my definition is of that,
Speaker:you know, is the idea that. And it's even called out in this action
Speaker:plan report. Right. Where it's like, you know, AI with American values. Right.
Speaker:Yeah. And like you said, I'm pretty sure the French want to have, you
Speaker:know, AI with French values, and the
Speaker:Germans probably want to have, you know, with German values. Right. So I think even,
Speaker:even painting the entire continent, even though everything's is kind of done
Speaker:through the European Union, I don't think that's. That might
Speaker:be at their detriment. Right. And. And the German market is also pretty
Speaker:sizable too. Right. It's something like 80 million people. Right. And the
Speaker:German language market, I think, adds another 20
Speaker:million to that. Right. So, you know, I only say that because one
Speaker:of the, one of the points that people made for taking German in high school
Speaker:was it was 100 million ish, you know, number of people speak the
Speaker:language. So it's not. And, and I would say that,
Speaker:you know, particularly when we're dealing with language models. Right. It's in the
Speaker:name. Right. So language and culture, although not exactly the same,
Speaker:are very much tightly linked. And that was something we talked about last
Speaker:time. We got sidetracked, but that's what
Speaker:I do here. That's fine.
Speaker:What struck out of you, the report? I think one of the things you mentioned
Speaker:was, well, go ahead, I'll let you go. Sure.
Speaker:The thing that I was most surprised about was
Speaker:that pillar, one of the
Speaker:document on page six and a couple of other areas was
Speaker:really focused on the workforce
Speaker:and this concept of like, securing the AI workforce,
Speaker:making sure to have necessary people
Speaker:in play. And then it got into like almost this Cold
Speaker:war kind of mentality
Speaker:of like, how do we make sure that we can trust the people that we
Speaker:have and it was, it was just surprising to me because I thought it was
Speaker:going to be more about the regulation of AI models, which it does move
Speaker:into eventually. Right. And supply chain security.
Speaker:But the, the concept of, of workforce and the fact that it
Speaker:was the first pillar was intriguing to me. It got me
Speaker:thinking about kind of what, what is the US Administration thinking about right now? And
Speaker:they're, I think they're really thinking about making
Speaker:sure they lock down the people. And
Speaker:for good reasons and, and probably bad reasons too. You know, good reason is,
Speaker:you know, how do we entice the best experts
Speaker:to stay here in America? How do we entice
Speaker:the workforce to continue to move into the area of AI through
Speaker:education? But then there also seemed to
Speaker:be almost like a Cold War vibe there.
Speaker:I don't know if you watched the movie Oppenheimer, but it kind of reminded me
Speaker:in that movie where the people working on the
Speaker:Manhattan Project were like their personal lives
Speaker:were, were under view quite a bit.
Speaker:And it, it kind of reminded me of that. Like is, is in,
Speaker:in a year or two are all the AI experts going to, you know, have
Speaker:the NSA and the FBI like keeping track of them
Speaker:and what they're doing? And it doesn't explicitly
Speaker:say that, but the tone kind of led me to think, oh, wow,
Speaker:they're, they, they're really interested in what these people are doing.
Speaker:It's not just about the technology, but the people making the technology.
Speaker:And that was very intriguing to me. I could see that being
Speaker:a thing, especially if there's an actual honest to God, you know,
Speaker:old school knockdown, drag out shooting war with any
Speaker:country. I could
Speaker:see that being, I wouldn't say nationalized, but
Speaker:you'll have to get some kind of. Even now, like if you work in the
Speaker:nuclear industry, you need a queue clearance. You need a lot of things being. You
Speaker:need a lot of invasive, not procedures, but
Speaker:definitely a lot of invasive paperwork and investigations that,
Speaker:But I, and I, and I do see,
Speaker:I didn't read the whole thing yet, but I did, I did, I did feed
Speaker:it through Notebook lm. I did listen to that. I did do some skimming
Speaker:of it. And that was one of the things was like it seems like they're
Speaker:laying the groundwork for that in case things get sideways.
Speaker:Also part of that is the, the
Speaker:securing the supply chain from the silicon on up.
Speaker:Yeah. Which is a smart thing because
Speaker:the chips are made in very limited
Speaker:geolocations. Right. So one,
Speaker:one major international incident, a shooting
Speaker:war. Right. No matter who wins. You know, there's Going to be an
Speaker:island where most of the stuff is made. Yeah. That's going to be reduced to
Speaker:the rubble. Right. Now, whose flag gets planted on top of that rubble,
Speaker:you know, remains to be seen. But you know, you, you know,
Speaker:so much for the chip manufacturers there. Yeah.
Speaker:And also too, you can't rule out natural disasters. Right. You know,
Speaker:, was it:Speaker:tsunami that, you know, did major
Speaker:swath of damage. It's not impossible to imagine even just a natural
Speaker:disaster, bad typhoon either. Earthquake with
Speaker:Japan, wake Japan. I mean it, it could,
Speaker:it's not impossible to imagine like more than one way for it
Speaker:to rain on everybody's parade. And if you think supply chain issues with GPUs
Speaker:are rough today. Yeah, I mean that's just,
Speaker:that would be a big thing. But what really stood
Speaker:out to me, and obviously I'm biased because my wife is a federal employee, was
Speaker:talking about training federal employees to use AI. Right. And
Speaker:there was, even in there, even in there there was a
Speaker:accelerating adoption here, but basically mandating
Speaker:employee access for federal employees and
Speaker:training on these LLMs,
Speaker:which is interesting because I can
Speaker:speak from not first hand experience, but certainly, you know,
Speaker:secondhand experience. Right. Federal employees do not feel loved
Speaker:and appreciated, let alone have access to any kind of training or
Speaker:anything like that. So I thought that was interesting,
Speaker:that was interesting in there because it's been a rough go for
Speaker:feds the last six, seven months. Oh yeah. Everything's
Speaker:been very negative. And this is like one of the, maybe the first,
Speaker:it's first positive, you. Know, and I was, I was telling
Speaker:you in the virtual green room is that, you know, the agency my wife works
Speaker:at, like they're not hiring new people,
Speaker:but they're creating a new organization that people will be doubling down on their duties,
Speaker:which presumably they'll get access to the training. And she,
Speaker:she may or may not be involved with that yet. We don't know. But, but
Speaker:it's interesting to kind of see that, see that
Speaker:happening. But yeah. What else have you, what else
Speaker:took. It's, you know, so I think the most
Speaker:important thing that was in there and I,
Speaker:I actually figured the whole document would be about this is
Speaker:around supply chain security. So if,
Speaker:if people aren't aware when we're talking about supply chain, typically we talk
Speaker:about supply chain, it's more in industry terms of, you know, how
Speaker:does something get made, the nuts and bolts, where does the raw
Speaker:materials come from? That term was
Speaker:never used really in technology until recently.
Speaker:And. Probably the pandemic
Speaker:is when most people first heard the term supply chain.
Speaker:It was, it was the Solar Winds hack. I think that
Speaker:also really, yes, put it in perspective too.
Speaker:So those who aren't aware, there's a company called SolarWinds,
Speaker:they were very predominantly used in the government. I think
Speaker:they still are. But there was a
Speaker:hack where instead of hacking their software directly,
Speaker:they hacked the supply chain. They injected
Speaker:bad code early on into the supply chain
Speaker:and that slowly propagated out to these
Speaker:different government agencies. And the scary part
Speaker:is that the very thing that was meant to monitor these
Speaker:type of situations was the thing that had gotten infiltrated. So it
Speaker:took a while for anyone to even know. And it was
Speaker:massive. It impacted the government and impacted
Speaker:enterprise. And that is where
Speaker:I think NIST and a couple other agencies made the decision, okay,
Speaker:we're going to come up with a requirement of what supply chain looks like
Speaker:within these types of software development
Speaker:process. And really gets into, okay, all the way
Speaker:from how do we think up an idea for
Speaker:code, how do we submit that code
Speaker:into a repository, how do we compile it, how do
Speaker:we scan it, how do we distribute it? And that's when we talk about supply
Speaker:chain, secure supply chain. That's in the context of what
Speaker:we mean. And that relates directly to AI as well, because it's
Speaker:all data pipelines. And for AI specifically, it's about where does
Speaker:that data come from, where was it sourced,
Speaker:when was it added into our model? How
Speaker:can we prove that the model that we built over
Speaker:here is the model that's running over here?
Speaker:So if the government has an officially blessed model, how do
Speaker:I know the model that's running within
Speaker:my defense contract firm is that model? And that gets
Speaker:all into this supply chain. And I was happy to see that some of it
Speaker:wasn't as technically laid out as I wanted it to be.
Speaker:The document really just says we're relying on NIST and some
Speaker:other government agencies to come up with a plan.
Speaker:So this wasn't really the plan, it's more the actual call to action for
Speaker:the plan. But it was good to see that there. It was important for it
Speaker:to be there. I was happy that that was highlighted. And I think
Speaker:in terms of security, it's the most
Speaker:underappreciated one right now. Everyone's really focused on
Speaker:model guardrails. And what we talked
Speaker:about last time with the AI:Speaker:breaking out of, of its shell. I think the most
Speaker:important thing right now is actually more of the supply chain security where you
Speaker:know, don't let people inject bad data into
Speaker:models that are making critical decisions for the government,
Speaker:for finance or healthcare. That's where our focus needs to
Speaker:be first. I think having that secure supply chain is
Speaker:ultimately what's going to lead to, to preventing
Speaker:the AI:Speaker:a breakout or if there was a breakout, it's going to reduce the blast
Speaker:radius of that type of situation.
Speaker:Now that makes a lot of sense and it's interesting because there's not just
Speaker:the traditional nation states that could be involved here. Right. There's also
Speaker:or bad actors in the normal sense. But also the
Speaker:AI itself could become a threat too. Right. Like,
Speaker:and the report doesn't isn't technical in detail,
Speaker:but I don't think that's who the audience was really for. Yeah
Speaker:but that's interesting
Speaker:because you know, I don't know like from a game
Speaker:theory point of view, right. Like you have the traditional, the usual suspects,
Speaker:right. The countries, terrorist groups, criminal gangs, blah blah,
Speaker:blah. Right. The usual kind of players. But AI also has
Speaker:the potential to become yet another player
Speaker:in the game of that. That's. I certainly
Speaker:didn't see that in the report and it didn't cross my mind until you kind
Speaker:of bridged last stream and this stream content. I was like,
Speaker:oh wow, this is multi dimensional. This is like 5 dgs or
Speaker:something like that. Yes.
Speaker:I would say for a first effort, it's actually a fairly reasonably well
Speaker:written document. For those that don't, for folks
Speaker:that don't know, I used to accompany our lobbyists
Speaker:in, in when I was at Microsoft talking about technology
Speaker:issues and things like that and you know, I was the
Speaker:technical resource for that.
Speaker:And as I was telling you, virtual green room. A lot of these elected officials,
Speaker:regardless of, you know, whether you agree with their
Speaker:party affiliation or whatnot, they're not the most technical I
Speaker:would say of the one ones I've interacted with
Speaker:which maybe, maybe 60, 70,
Speaker:some of them are names you've heard of, some of them as you've never heard
Speaker:of. I would say less than 10%
Speaker:are technical in any sense. Yeah, right.
Speaker:And there were only two that I would say like would feel
Speaker:at home having a technical conversation. I wonder how
Speaker:many of the policymakers even
Speaker:understand the term AI sovereignty. So and
Speaker:this is interesting, I'd love your opinion. Yeah, I think how many technical people
Speaker:would understand. Well, that's what I mean. Yeah, go ahead. This is where I've been
Speaker:having some conversations even within our own organization that we work
Speaker:for. There's a lot of differing opinion on what AI
Speaker:sovereignty is. A lot of people who keep talking to me about AI sovereignty,
Speaker:I realize they're more talking about clients, cloud sovereignty, they're talking about how do
Speaker:I secure the compute, all of my
Speaker:compute within my borders and can guarantee that everything is
Speaker:within those borders. Which makes sense. I mean we work for Red Hat, we work
Speaker:for a, you know, basically a cloud
Speaker:Linux based company. Right. But when we talk about AI
Speaker:sovereignty, at least me personally, it, it's an accumulation of a
Speaker:few core areas. It gets back to the data sovereignty, a little bit of that
Speaker:cloud sovereignty. But it's really about
Speaker:do my, I have control over my AI models,
Speaker:I know where the data came from.
Speaker:And I loved what you said earlier. It's about the culture of the model
Speaker:and I think ultimately the AI sovereignty is about the culture of the
Speaker:model and then making sure that you're containing your
Speaker:AI to the borders of the United States.
Speaker:So you're keeping all the secrets here, you're keeping the talent
Speaker:that are driving it. But ultimately you're right, it's about that
Speaker:culture and making sure that your model has the best
Speaker:representation of your culture. And
Speaker:it's kind of a scary thing to think about. It's an interesting topic, but
Speaker:it also gets into a lot of geopolitical challenges I think we're
Speaker:having are now surfacing to the top because of things like AI,
Speaker:you know, it's, it's interesting. Well, it's like 100
Speaker:and I think I was actually a colleague ours, Robbie, shout out to Robbie
Speaker:and gotta have him on the stream one of these days. You know, he
Speaker:was talking about kind of AI sovereignty like, you know, what is, you know,
Speaker:you can use an American model, right. From
Speaker:data, right. And then tell it to behave British. He used
Speaker:better words, right? You know, the spellings and the grammar and things like that. But
Speaker:whose values are in there, right. When you, when you ask it questions, Right,
Speaker:yeah. And, and that gets to an interesting thing, right? So
Speaker:like you know, I, I,
Speaker:my grand half, my grandparents were not born in the U.S. they're immigrants,
Speaker:right. So like, but so, so when I went to one of the countries my
Speaker:ancestry comes through is Ireland, right. So but the Ireland that a lot
Speaker:of my older family members came from really doesn't
Speaker:exist anymore, right. It's not the rural kind of
Speaker:poverty stricken country that it was, right. 100, 110 years
Speaker:ago. 100 years ago.
Speaker:So it was very awkward because when I was,
Speaker:when I was in Ireland as an American.
Speaker:Even though it felt familiar, it was also felt very foreign. Right. Because
Speaker:it was, you know, it was, you know, and if you think of me as
Speaker:a, you know, large language model,
Speaker:so to speak. Right. I grew up in New York. Right. I'm
Speaker:very Americanized. So when I go there and it felt familiar.
Speaker:Right. Like the, the pubs and the restaurants felt like places my older family,
Speaker:it felt like grandma's house and that sort of thing. But it clearly was
Speaker:not. And it was clearly also
Speaker:not the same place that they left. Yeah. That you would hear in family stories
Speaker:and things like that. You know, so it's
Speaker:interesting because also I think
Speaker:values and country and all of that are inherently
Speaker:political and I think that's why you're seeing this. Right. It is inherently
Speaker:geopolitical is inherently all of these things.
Speaker:So technologists who are not used to, we're not
Speaker:used to this, these types of conversations now suddenly we're pulled into this
Speaker:and God forbid if there's a, you know, an actual kind of
Speaker:20th century global war style thing happening. Yeah. Or would happen,
Speaker:you know, it's only going to get worse
Speaker:from here. So I do
Speaker:find it, I do find it interesting how
Speaker:technologists are now suddenly pulled into this. Right. There's a famous,
Speaker:you know, you know, Jensen Wong made
Speaker:it an emergency visit. That was,
Speaker:that was a big deal. Right, That's. And actually that a lot
Speaker:of that kind of stuff is called out in this report. You should,
Speaker:you should go into details about that. So
Speaker:Jensen Wong, apparently, I don't know what was the
Speaker:driver of it, but I suspect he was. The administration was trying to
Speaker:block all exports of GPUs to a particular country.
Speaker:Yeah. So the rumor was that week
Speaker:that all, all chip, the global chip manufacturing
Speaker:outside the US Other than key allies, would just be completely
Speaker:stopped. And obviously for, for some areas,
Speaker:like China, it would. They would just end export for
Speaker:pretty much all chips. So that was not just the ones that are blockaded
Speaker:right now, but you know, really, even some of the basic
Speaker:ones. Well, remember that Ford's assembly line
Speaker:was shut down because there was a shortage due to the pandemic. Nothing else.
Speaker:Of chips to put in the cars for the assembly line. Yes.
Speaker:And it cost them x. Millions of tens of millions of dollars a day or
Speaker:something like that. Right. So not trivial. Right. So like this
Speaker:could have, this could have been
Speaker:really bad. So go ahead. I'm
Speaker:sorry. No, no, no, I was just saying. I was just adding some flavor because
Speaker:it, it was officially announced by the White House that they were
Speaker:evaluating this and then the, the word on
Speaker:the street was, you know, the, the uncut secret was that
Speaker:the, the U.S. was going to declare this at one of the summits that they
Speaker:were going to, that they were just cut the chip manufacturing
Speaker:altogether. And.
Speaker:Yeah, and then Jensen made an emergency visit to the White House
Speaker:and which I guess you, if, if you run the,
Speaker:the most profitable company in America right now,
Speaker:it helps. Well, that's his most profitable, the most valued. Right. This
Speaker:valuation is like 4 trillion last I heard. So. Which is crazy.
Speaker:But yeah, I mean he, it was a, it was a very
Speaker:unplanned visit where he just went and knocked on. The door and
Speaker:oh, to be a fly in that wall and that. In the wall. I know,
Speaker:I know, right. But I mean props to him. Immediately
Speaker:after that, right, we start hearing of the oh, we're gonna
Speaker:back this down. We're gonna, we're, we're gonna consider still
Speaker:shipping the, whatever the, the chip is in China. That's kind of a.
Speaker:Right, an A100
Speaker:knockoff.
Speaker:We did see impacts in that conversation, but I think it's important because it
Speaker:builds into the, this document because the document clearly outlines
Speaker:semiconductor supply chain outlining the reliance
Speaker:on the, of Taiwan.
Speaker:What I loved about it is that there was a section here,
Speaker:one second, I am
Speaker:pulling it up. It was
Speaker:a little tongue in cheek where they're talking about
Speaker:reviving the US chip manufacturing under CHIPS act,
Speaker:but stripped of ideological constraints.
Speaker:And we won't go into the politics of that here. But I thought that was
Speaker:pretty funny because the CHIPS act was obviously a big deal.
Speaker:It was a big deal for me because when it was announced I was still.
Speaker:I'm based in Boston now, but I'm from Northern Indiana around
Speaker:the area where Purdue University is close to Chicago. And
Speaker:we were actually called out on the CHIPS Act. They were going to build a
Speaker:semiconductor facility there in our area in
Speaker:conjunction with Purdue University.
Speaker:But then when, when Trump was elected, he was trying to claw back anything he
Speaker:could from the CHIPS Act. Right. I'm happy to see that the CHIPS act
Speaker:is back on the table. I think it's still going to be
Speaker:extremely political like we have seen with these types of acts,
Speaker:but is needed. I
Speaker:AM hoping that $6 billion isn't just
Speaker:going to go to intel because I think the innovation there is starting to
Speaker:die off. I'm hoping that we see
Speaker:more focus towards some innovative areas in chip
Speaker:manufacturing here and also ultimately which is called out. We
Speaker:want to bring over a lot of the Taiwan based technologies
Speaker:and my understanding is that there's just a bunch of
Speaker:explosives within those facilities there in
Speaker:Taiwan and they're ready to just blow them up at a moment's
Speaker:notice and move ship to the U.S.
Speaker:wow. So I know they're building some of those facilities. I think
Speaker:Arizona was one of them. I think Texas is another
Speaker:where they're starting to mimic some of that chip production. And
Speaker:basically right now the United States is trading military
Speaker:equipment for chip technology.
Speaker:It's crazy. Fascinating is. But it's absolutely fascinating from a
Speaker:geopolitical standpoint that the currency right
Speaker:now for, for Taiwan is, Is chips.
Speaker:Yeah. And so. But I think that's
Speaker:a big driver. It's one of the things that was called out. It was
Speaker:called out in pillar two of the document, which calls called
Speaker:Build American AI Infrastructure. And I think. Yeah, you have the
Speaker:outline there where they call out
Speaker:specifically the semiconductor leadership and then also securing data
Speaker:centers. I thought this was interesting. They're going to start having federal
Speaker:guidelines on data center security
Speaker:and will also incorporate military and
Speaker:intelligence usage for those facilities. This is what I
Speaker:was telling about. This is just reminding me of when I, when I watched
Speaker:Oppenheimer and learning about the Manhattan Project and
Speaker:there were military guards in front of
Speaker:the physics research facilities in
Speaker:Chicago University and in, in New York
Speaker:and in Los Alamos. It's, it just
Speaker:seems very, very similar where it's like we are now going to
Speaker:attach military guards
Speaker:to guard our public sector AI
Speaker:infrastructure. And yeah, I mean
Speaker:one of the interesting things and I think this really kind of, if you take
Speaker:a step back, right. Like why, why is.
Speaker:For many nations, why is domestic auto production important?
Speaker:Right. Because when it hits the fan,
Speaker:you're not. You make tanks, right? You make tanks, you make
Speaker:airplanes. Like all these things are important for
Speaker:nation states. Right. So automobile production is a
Speaker:proxy for tank production. Right.
Speaker:Civilian airline airplane production is a proxy for, you
Speaker:know, this I would add now probably chip manufacturing.
Speaker:Right. And possibly, possibly AI model creation.
Speaker:Yeah. You look at what's happening around the world where there are conflicts. Right.
Speaker:Drones are playing a huge part of this. Yep. Right.
Speaker:Whether they're autonomous or not, we will never really know
Speaker:until the history books are written and even then. But
Speaker:the whole idea of, you know, drone
Speaker:and AI based warfare. Right. You know,
Speaker:one of the videos coming out of you, the Ukraine conflict was
Speaker:the Russian airplanes were covered in tires. I don't know if you saw
Speaker:this. No. So, so one of the.
Speaker:The thinking is that they had, I guess, old tires covering some of
Speaker:the parts of the airplane. Strategically, the best guess that Everyone
Speaker:has. And I've heard this from multiple sources saying it's kind of true and kind
Speaker:of not. So. I don't know, take it for what you will, is that that
Speaker:was done to confuse computer vision systems. Yeah. And
Speaker:then there's this other thing. I don't know if you heard of patch attacks,
Speaker:which is basically like this idea of. I'll see. I pulled up some.
Speaker:Some graphics of this, but basically.
Speaker:Open image in new tab.
Speaker:Basically, it's the idea that you can alter
Speaker:a structure, like a stop sign,
Speaker:in ways that the AI model will see something different
Speaker:and alter what the AI model is
Speaker:determining it sees. And apparently you're seeing a lot of this,
Speaker:if you look at footage from, you know, Ukraine area, is that
Speaker:you're seeing, like, you know,
Speaker:tanks both sides with. With
Speaker:stickers on them that look like really warped QR codes or
Speaker:like bizarre things like this. Yeah. And it's basically to
Speaker:thwart these types of systems.
Speaker:So. That's fascinating. It's interesting, isn't it? And this gets back
Speaker:to. I don't know if it was on the stream or another conversation we have.
Speaker:We're building these systems, these LLMs with, you know, hundreds of billions of
Speaker:parameters. Right. If not a trillion or two,
Speaker:we really don't know how they work. No, we think we know.
Speaker:And you and I were talking about this the other day, actually, it wasn't on
Speaker:a stream or anything. It was kind of like. I think that LLMs
Speaker:that we have now are unreasonably effective.
Speaker:Right. They're able to. And I'll put air quotes here for anyone listening reason.
Speaker:Right. They shouldn't be able to
Speaker:based on. I mean, all I see is just a vector
Speaker:database with lots of relationships between words.
Speaker:Yeah, Right. They're capable of doing things that
Speaker:if. I wouldn't think they would be yet. They are.
Speaker:Yeah. So there's a lot of research dollars going into figuring this
Speaker:out right now. Like, why is that? Like, what. Is there something
Speaker:inherently powerful about language? Probably. Yeah. Right.
Speaker:That and, you know,
Speaker:language is kind of like the assembly language of the mind, if you think
Speaker:about it. Right. So I can
Speaker:encode my thoughts into something, whether it's a written word,
Speaker:whether it's, you know, vocalizations,
Speaker:and then have that come out. It's basically a.
Speaker:Like a codec for human thought. And
Speaker:maybe there's some kind of. I don't want to say intelligence, but some kind of
Speaker:something we don't quite yet grasp. Yeah. About the nature of language
Speaker:and relationships between words that
Speaker:automatically you get for free. Once you kind of train these models up,
Speaker:I think that's fascinating, and I'm glad there's a lot of research dollars to that.
Speaker:It is. But, you know, clearly the human nervous
Speaker:system, our visual system, our cortex, whatever it's called,
Speaker:you know, we know that that is a moth sticker on a stop sign.
Speaker:Yeah. What is different about how the AI learned
Speaker:that makes us vulnerable, this type of attack. That's fascinating.
Speaker:And it doesn't see things like, there's
Speaker:a lot of research papers that'll show you, basically, what does the model
Speaker:see? And you see it and it's just absolute nonsense to us.
Speaker:Right. It's. It doesn't see what we see. It's like
Speaker:it doesn't relate the.
Speaker:You know, maybe it's not correlating the red and
Speaker:the white backgrounds, but instead it's correlating
Speaker:the position of the text or the fact that it's four
Speaker:capital letters positioned over an octagon or something like it.
Speaker:It. The. The way figures these things out is.
Speaker:Different than how we think we do it. Yeah. It's actually seems obtuse, but.
Speaker:It's obtuse. But it does it billion times faster than us. So when it's
Speaker:obtuse, it gets to something faster than we do because it just can
Speaker:do it a billion times over. And that's where
Speaker:the secret sauce really is. But how
Speaker:things relate back to each other, obviously, we have these,
Speaker:these vectors that like, you know, build relations between
Speaker:words. But how it can then take it and
Speaker:reason is still not quite
Speaker:understood. Right. Right now it's just not understood.
Speaker:No, it. And it's. No, it's not understood. And that's kind of what
Speaker:keeps me up at night, is we don't really. We're putting these.
Speaker:Again, you know, full disclosure, we both work for an enterprise software company with very
Speaker:large customers. You know, we're deploying these LLMs in
Speaker:places they're
Speaker:not exactly making the life and death decisions right now,
Speaker:but it's not that hard to imagine that they would.
Speaker:Right. Yep. And I don't know, I think that's.
Speaker:That's just a huge security vulnerability. We don't know how these things work
Speaker:and also understand that it doesn't make sense to hold off
Speaker:deploying these things once we fully understand it. Right. That doesn't. That's
Speaker:not going to fly either. But I think we should,
Speaker:as a society, like, really think about,
Speaker:you know, what are the consequences here. Right. Think of what
Speaker:the Jeff Goldblum character, Jurassic park. Right.
Speaker:You know, talked about chaos Theory and all that. Right.
Speaker:Like it's, you know, you know, the
Speaker:unintended consequences of this. We
Speaker:should, to your point, have AI in a box, like,
Speaker:and make sure it's really hard for that to get out. But
Speaker:again, like, you know, these things are. Doing.
Speaker:These things don't think like us
Speaker:and they may think in more circuitous and obtuse ways that don't
Speaker:make sense to us, but again, they do it a billion times faster.
Speaker:So, you know, it could end
Speaker:up being far more clever than we are.
Speaker:Absolutely. I remember when I was learning Comp sci
Speaker:and one of the things I think was assembly language class actually
Speaker:was multiplication on silicon is typically done. Not
Speaker:by now. What was it? Yeah, it was.
Speaker:I don't know if it's still true, but back in the day it was true
Speaker:that multiplication is actually done through repeated addition.
Speaker:Yeah. It was actually more efficient to do it that way.
Speaker:Right. Again, I think that's a great summary of like,
Speaker:that's kind of the slow way. But if you're operating billions of
Speaker:times faster, slow way isn't so bad.
Speaker:Or a slow way doesn't mean anything. And I think you and I were having
Speaker:this conversation
Speaker:that, you know, if you think about the power requirements of these
Speaker:AI systems. Yeah. Versus the power requirements of the human
Speaker:brain, something like 25 watts.
Speaker:Right. And if you think about the intelligence of
Speaker:birds, like crows in particular, Right. They, they, they have the
Speaker:intelligence of a six, seven year old supposedly.
Speaker:You know, not only do they have to
Speaker:do it power efficiently, but they also do it weight efficiently
Speaker:too. Right. So the infrastructure, you know,
Speaker:that a crow has to think about, think about, but, or
Speaker:evolution or whatever, has to put it in a lightweight body.
Speaker:Like I don't fly. I'm obviously not, I'm not a petite individual,
Speaker:so I don't have to worry about that. But like, if you're a bird, you
Speaker:know, you have to fly, so you have to think about that. And yet they're
Speaker:able to manifest some kind of
Speaker:intelligence with very modest hardware. I mean,
Speaker:their brains are not that big. I think the size of a
Speaker:walnut. I don't know. Like, this is totally off topic, but.
Speaker:No, it's, it's related though. And on the report they were talking about
Speaker:power,
Speaker:power requirements, power requirements and grid security.
Speaker:Right. And it was called out as. And you think about just the sheer
Speaker:massive amount of power that these AI models
Speaker:take. It's. It's insane. I think, I think there was a point where
Speaker:one third of all power is being used for like bitcoin. Mining. At one point
Speaker:that went down, and now we've. We've replaced that with AI
Speaker:and, you know, that's. It keeps going up and up and to the point
Speaker:that, you know, it's possible that half of all the power being used here soon
Speaker:is just going to be for AI. And I can see that there's no
Speaker:evolutionary pressure like there was on biology. No, no, you can just
Speaker:throw more power at it. So in. In
Speaker:this case, with. With the LLM technology,
Speaker:you can just throw more chips. Right. And, you know, make
Speaker:them. You know, this actually hits home
Speaker:because I'm between. So Ashburn
Speaker:or Loudoun County, Virginia, which, if you've ever flown in
Speaker:and out of Dulles Airport, you've been there, is Data center alley.
Speaker:So U.S. east is there. U.S. east 1, 2 for all the major providers. Right.
Speaker:Plus a lot of private ones, too.
Speaker:I live between there and Three Mile Island. Oh, wow.
Speaker:Yeah. So one of the big controversies in
Speaker:the state of Maryland is that they want to put in what they call the
Speaker:Maryland Power Piedmont Reliability Project or something like
Speaker:nprp. They're basically going to put in high power
Speaker:lines between Pennsylvania to Virginia,
Speaker:which is a political football because there's a lot of land that's going to have
Speaker:to be eminent domained. Yeah, Right. There's
Speaker:obviously environmental factors, but also this is the
Speaker:thing that is really kind of insult to injury. Right.
Speaker:None of the power that's going to go over those lines is going to be
Speaker:consumed here. It's all basically exporting power from
Speaker:Pennsylvania through to Virginia, which
Speaker:is not. Not a good look if you're. Because the people who
Speaker:vote Maryland people in are Maryland residents. So there's this whole.
Speaker:It's a very big controversy right now.
Speaker:And it's interesting because what used to be
Speaker:a very isolated hobby of technology
Speaker:is now embroiled in geopolitics, local
Speaker:politics. It's just kind of like I kind of miss the good
Speaker:old days before lawyers got involved.
Speaker:Yep. But
Speaker:sorry, but no, I mean, that's a good point. That's, you know, you think about
Speaker:the power requirements, right. You know,
Speaker:for these things, you're gonna have to build new power centers. You're gonna have to
Speaker:do this. Right. And then that, you know, what's. What's your
Speaker:power source going to be? Solar is awesome. Solar
Speaker:can't solve everything, Right. So
Speaker:what's it going to be? Is it going to be wind? You know, is it
Speaker:going to be, you know, coal? Is it going to be natural gas? Is
Speaker:going to be oil? Right. There's going to be a whole. It's all fun and
Speaker:games until people are paying way more for their electric
Speaker:bill each month than they, than they're used to.
Speaker:Yeah, it's going to be, it's going to change things
Speaker:very quickly, especially if it starts impacting people's monthly power bills.
Speaker:Right. I think right now we haven't seen it too much just because
Speaker:we've been able to keep up with demand. But once that demand
Speaker:starts really affecting prices, I think we'll also see
Speaker:AI being a conversation point in that way where it's going to start.
Speaker:you know, even with the, the:Speaker:lan that we're talking about,:Speaker:like, you know, universal basic income and stuff. You know, if you, if AI starts
Speaker:taking over everything. And that wasn't outlined in this document,
Speaker:which I'm not, I'm not surprised. But it's a,
Speaker:it's going to be a big conversation point. If AI does work the way that
Speaker:we think it's going to work, will we start seeing the AI
Speaker:take the jobs? And if they take the jobs. I think it was, actually,
Speaker:it was Bill Gates like 10 years ago was talking about UBI for,
Speaker:for AI, and at the time we just thought Bill was being crazy and like,
Speaker:like a go back to your Gates foundation and. You know, go back and work
Speaker:on malaria. Yeah, yeah. But no, and even Elon Musk, I mean, and
Speaker:Elon Musk is definitely a polarizing figure, as is Bill Gates. But they're both
Speaker:polarizing in different directions. Yeah. They both agree on ubi. I have
Speaker:mixed feelings personally about ubi, and it's
Speaker:not because I'm a mean individual. It's just if you study the history of
Speaker:serfdom. Yep. I don't know.
Speaker:Looks a little too similar to me. Yeah. But that's just my take
Speaker:on it. But
Speaker:you're right, like, and also too, like governments are getting involved. Because if you go
Speaker:to your local McDonald's, right. Or your Dunkin Donuts, right. And
Speaker:you think of how many people used to staff that in the past
Speaker:versus how many people staff that now. Yeah.
Speaker:Right. And
Speaker:assume, well, human nature is human
Speaker:nature. Right. If you used to take 10 people to run your average
Speaker:McDonald's, now they can get by. I don't know. If you go in there now,
Speaker:there's like five, maybe four. Yeah, four or five. And that's
Speaker:generous. Right. If nothing else, the taxes on
Speaker:the wages have went from 10 employee taxes on 10
Speaker:employees. Now they're taxing it on five. Yeah. Right.
Speaker:That, that's a big deal. It is, right. Because now
Speaker:you're taxing. Now granted they're not, you're not taxing them a lot because
Speaker:they're not making a lot of money, but still that's 50%.
Speaker:So if you're kind of like a, you know, a number cruncher and you're
Speaker:looking at every McDonald's, right. When you have 100 McDonald's now, you're getting the tax
Speaker:revenue out of that one McDonald's, you know, or at least
Speaker:on the income of it. Right. The income of the individuals. The income tax on
Speaker:that is going to be way less now. Even
Speaker:now. Even before AGI. Before. Yeah, before
Speaker:that. Right. Because it's just automation. Right. And I personally
Speaker:would rather deal with a kiosk. Same
Speaker:here. Deal with the person. Yeah. Right.
Speaker:Especially if you have like special orders. Right. Like, oh, you know, my kid doesn't
Speaker:want ketchup on his burger. Right. He doesn't want onions on his burger. Right. So
Speaker:you just have that as a favorite of the app and then just press go.
Speaker:I don't even have to touch the kiosk. Yeah,
Speaker:I think that that is going to be, that's not even an AI system,
Speaker:Right. That's just good old fashioned automation. One of
Speaker:the big Silicon Valley AI
Speaker:gurus who, it was escapes me right now, but was talking
Speaker:about how the, the jobs
Speaker:that are going to be considered desirable are going to be
Speaker:completely flipped here soon.
Speaker:Where he was, he was saying the most desirable job might just be people in
Speaker:performing arts. Right. He's like, he, he's like, AI is
Speaker:not going to replicate that anytime soon. He's like, yes, you may have
Speaker:movies being AI generated, but there's still something to be said about
Speaker:the performing arts. You know, obviously like
Speaker:plumbing and electrician work and construction
Speaker:work, you know, robotics might amplify that and make
Speaker:it better, but there'll still be a human element. But you know, traditional white collar
Speaker:jobs as we know it, other than the people
Speaker:who, who manage that AI, I, I just
Speaker:feel like it's going to be completely turned upside down if
Speaker:AI does what we want it to do. That's a big if right
Speaker:now. It's a good tool. But the, the real if is
Speaker:we're gonna get to this more area of agentic and more AI is actually being
Speaker:able to do the full job of someone rather than just being a
Speaker:tool that they use. And that's the if right now that we're, we're
Speaker:betting a lot on. The economy on where there's a lot of.
Speaker:A lot of bet from many financial institutions that
Speaker:the AI is going to be what is the next industrial
Speaker:revolution. I think that's still yet to be proven out.
Speaker:One just to go back to the UBI though,
Speaker:there's a book you might be familiar with at the Expanse.
Speaker:Yes, love those books. They
Speaker:cover this idea of. Of universal basic
Speaker:income. And you know we basically have in that, that
Speaker:series like I think it's like 90,
Speaker:95 of the world is just on
Speaker:Earth's population averse population is basically on universal
Speaker:basic income some sort. And
Speaker:you then have these, the 5% that actually
Speaker:just have jobs. Right. It's a big deal that they just have
Speaker:a job and they're doing things and you know, they're
Speaker:politicians and people managing technology
Speaker:or defense and it's. It's fascinating. And I think
Speaker:if anyone's wanting to look at a little
Speaker:bit less of less rosy kind of outcome
Speaker:and one that I think is more accurate, I think it would be a
Speaker:combination of. Of the Expanse and then probably Ghost in
Speaker:the Shell, the anime. Both of them show
Speaker:AI and technology not to the extent
Speaker:of like Terminator the Matrix where everything gets destroyed, but more
Speaker:of a like human progression just
Speaker:gets bogged down by this development. We end up in this
Speaker:more like
Speaker:technocratic kind of of realm where techno
Speaker:feudalism almost. Yeah, that's a great way of putting it. Techno techno
Speaker:feudalism. And what's interesting is if you look at kind of the expense. So I'm
Speaker:a big fan of the Expanse. I've read. I haven't read all the books, but
Speaker:I've read a lot of them. I've seen the series, which is
Speaker:excellent by the way, on Amazon. I'm
Speaker:salty that they didn't. They stopped it at season six, but I can let that
Speaker:go. But what's interesting is that the people with gumption ended up
Speaker:leaving Earth and going to Mars. Yep. Or the asteroid
Speaker:belt. So what happens is 100 years after that now you have to kind of
Speaker:like these three factions. Right. Everyone looks down on Earth,
Speaker:right. Because there's always like, particularly in the show, there's always these barbs where
Speaker:the politician says, you know, if. If you don't do this right, I'm going to
Speaker:put you on basic. Right. Like so basic becomes like a threat,
Speaker:which I think is interesting. And then there's also kind of the.
Speaker:The people who are more entrepreneurial end up going to Mars or the
Speaker:asteroid belt. And then that doesn't always work out well. So they have this. You
Speaker:have this tension between these three different factions. And then
Speaker:throughout this course of the books, a third faction, kind of a
Speaker:fourth faction kind of enters the scene and kind of disrupts the power of
Speaker:the status quo. And that's kind of the main tension
Speaker:of the books is, you know, what happens
Speaker:after that. But highly recommend those books if you
Speaker:haven't seen them on the TV show. If you. The TV show is really well
Speaker:done. I think I would agree. From what I've seen of it, I haven't finished
Speaker:it, but it's good. And I'm in. I'm in the same boat as you. I'm
Speaker:a couple books in. It's one of those series I kind of come back to
Speaker:every once in a while. But funny enough, it's a. It's a series I reference
Speaker:a lot. I think about it a lot because I was like, I think that's
Speaker:a really accurate depiction of what the future could look for us
Speaker:with. With the technology. It's pretty reasonable. And that's what's
Speaker:really nice about the show. Like, it's. It's not because there's also.
Speaker:There's. Obviously, you mentioned the pessimistic views of the future. Right. There's. There's the
Speaker:Matrix, there's the Terminator, but there's also Star Trek, which is a little too. On
Speaker:the optimistic side. Yes. But
Speaker:there's not really. I think what's great about the Expanse, and I haven't.
Speaker:I haven't seen Ghost in the Shell anime in a long time.
Speaker:I did see clips of the Scarlet Johansson movie,
Speaker:but the
Speaker:Expanse does a pretty good job of going down the middle. Like, there's going to
Speaker:be societal changes that will come
Speaker:for this we really can't imagine now. Right. Yes.
Speaker:You know, Earth is pretty much almost like a
Speaker:techno feudal state. Especially what's interesting in the Expanse is
Speaker:when they explore what life is like for the average human on
Speaker:Earth. It's kind of like it's either really good or not.
Speaker:Right. And Mars is also kind of an
Speaker:interesting place too. There's a very different dynamic when you get that
Speaker:many type A driven people in one place.
Speaker:Sounds awesome at first, but then it's not really awesome.
Speaker:Yeah, necessarily. Right.
Speaker:But fun fact, the serve the
Speaker:PCs and the server names in my house are all derived from the show.
Speaker:Oh, cool. Yeah, yeah. So I'm talking to you now on
Speaker:Amun Ra. Cool. I don't know if you've gotten to that part of
Speaker:the. That's in the first book. Yeah, yeah. The Amun Ra Stealth class
Speaker:ships. And
Speaker:the computer I just bought also has that same kind of, you know,
Speaker:gamer box game aesthetic. So that's Osiris.
Speaker:And I also have Behemoth, which is that
Speaker:machine back there. And. Or you've not gotten to the Behemoth
Speaker:yet. Okay, I won't spoil it for you though. Yeah.
Speaker:But. And Andy, my co host on the podcast, is also a big fan
Speaker:of the show. He has, he has the, the
Speaker:Doniger, which you probably heard of that one. Yes, yes. He's
Speaker:got Weeping Sonambulist, Weeping Somnambulist,
Speaker:which. I had a machine with that name, but it's too hard to type out.
Speaker:You doing the ping on it? It's like, no, I don't know if
Speaker:you got into that one yet, because that's a couple books in. But.
Speaker:Yeah, yeah. And my, my,
Speaker:my. When I left Microsoft, my former Microsoft manager let me keep
Speaker:one of the laptops. So when it boots into Windows, it's the
Speaker:Tachi. And when I boot it into Linux, it's Rosson,
Speaker:which, you know, people have read book or seen the show.
Speaker:Go get the joke. But. And it's
Speaker:funny, our manager, when we met in person, my machine was the
Speaker:Razorback. Right. Which I don't know if you got to that part
Speaker:yet, but I'll try not to be
Speaker:spoiler. He's like, so what are you with like an Arizona fan? I'm like, no,
Speaker:no, no, it's from a book. Nice. So,
Speaker:but. Another area,
Speaker:I think this is for another, another time.
Speaker:So when I come back. But I think it would be good to talk also
Speaker:about how are the AI
Speaker:tools right now? Like, are we seeing them replace
Speaker:humans? I think the leap that we've
Speaker:made in the last six months is pretty substantial.
Speaker:Yeah. I think last year I would have said no.
Speaker:I think this year I'm saying yes. Like, we're seeing,
Speaker:we are now seeing the technology
Speaker:there to actually start replacing people. And
Speaker:it's not that, it's not that the
Speaker:main guy is going to be out like the tech lead, but I think it's
Speaker:going to be more the, the junior developer
Speaker:that's going to be in trouble because now the tech league can act like
Speaker:a fleet of junior developers. And like I'm, I'm just
Speaker:programming a game right now and
Speaker:I'm so surprised how much I've been able to get done
Speaker:in the, in the time frame I've been working on it. It's amazing
Speaker:how quickly you can be. But wasn't there also a story, a Guy deleted
Speaker:his entire production database. Yeah. Because of. I
Speaker:don't know the details. I had my AI delete,
Speaker:actually go and start cherry picking things off of the main branch and start
Speaker:deleting things. Oh, interesting. So I have a duplicate.
Speaker:I, I every day I fork my. I have a
Speaker:fork that I, I merge back into because I don't trust
Speaker:it and I don't tell the AI about the, the fork backup. Yeah, yeah.
Speaker:I think that says a lot though. Like you don't trust it. Like, you know,
Speaker:and it's not guardrails. It's not. Well, it's not guardrails in the
Speaker:sense that when people say guardrails and AI. Right. That's true. Yeah. It's a different.
Speaker:You're kind of. You're cya.
Speaker:That's really what you're doing. It is, it is. Right, that's true. Whether you, whether
Speaker:you put your code back up in another repo in another branch or a
Speaker:USB drive, like you're really. CYA is really what you're doing. And
Speaker:I think that there's a lot of. We've been going for an hour, so.
Speaker:And I also have to. I gotta drop too, so. Yeah, I gotta drop two.
Speaker:But, but it's been great. It's awesome. I think we continue more. But I
Speaker:definitely want to know more about the game thing you're doing because I sent you
Speaker:a bunch of stuff on Humble Bundle too. Yeah, yeah, which for game
Speaker:dev, so. But I have. My teenager needs a
Speaker:ride somewhere, so. Hey, thank you for having me. Hey, no
Speaker:problem, man. It's great. And be sure to check out
Speaker:our Red Hat AI YouTube channel where I think Chris has a video or two.
Speaker:Yeah. And I have a video or two as well. And
Speaker:with that, we'll see you next time. And
Speaker:have a good one. And that's a wrap on this episode of Data
Speaker:Driven, where we've dissected the Americas AI action plan with the
Speaker:precision of a data scientist on espresso and the paranoia of a
Speaker:Cold War analyst. Big thanks to Christopher Nuland for
Speaker:returning to the show and reminding us that AI sovereignty isn't just a
Speaker:buzzword. It's a geopolitical chess match played with silicon and
Speaker:source code. If you're not slightly more worried about data
Speaker:pipelines, chip supply chains, or which values your LLM
Speaker:secretly harbors. Were you even listening? As always, you
Speaker:can find us on data driven TV, franksworld.com
Speaker:and wherever your algorithms recommend quality geek banter.
Speaker:Until next time, stay curious, stay Data Driven.
Speaker:And remember, if your AI starts talking about sovereignty.
Speaker:Maybe check the firewall.