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Nvidia’s Power Play: From Robotaxis to Palantir Partnerships · Connecting the Dots

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  Today's tech news moves fast, but understanding
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  it shouldn't be hard. That's why Snarful Solutions
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  Group brings you Connecting the Dots, where we
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  break down what's happening in tech and why it
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  matters to you. Now, let's dive in with your
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  hosts. Welcome to Connecting the Dots. I'm Alex.
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  And I'm Morgan. Good to be with you today. It
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  is Wednesday, October 29th, 2025. That's right.
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  And before we jump into... the big tech stories
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  we're tracking. How about a quick look outside?
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  Sounds good. Here in Sacramento, it's shaping
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  up to be gorgeous, sunny, high around 80 degrees
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  Fahrenheit. Nice. Nationally, though, a bit more
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  serious, there are critical fire weather alerts
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  active for parts of Southern California and South
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  Texas. We're talking gusty winds, really low
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  humidity. So definitely stay alert if you're
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  in those areas. Yeah, good reminder. And elsewhere,
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  there's widespread rain and thunderstorms moving
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  from the Mississippi Valley up towards the Northeast.
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  Okay, shifting gears to the markets, what are
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  we seeing? Well, a slight dip yesterday, very
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  small. The Dow and S &P 500 both down about a
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  tenth of a percent. Right, barely noticeable
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  on the day, but the weekly picture is strong,
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  isn't it? It really is. Since October 20th, both
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  the Dow and the S &P are up a solid 3%, so good
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  momentum there. And Bitcoin, still holding strong.
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  Yep. Saw a little bump yesterday, about 0 .4%,
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  closed near $113 ,400. Still way up there. OK,
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  so the underlying trend seems, well, pretty optimistic
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  still. Agreed. Now, before we get into our Morningstar
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  report and connect those tech dots, a quick word
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  it out. OK, let's dive into the tech news. Right.
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  Time for the Morning Star Report. And it seems
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  like NVIDIA is kind of everywhere today. It really
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  does. Story number one. Uber is going big on
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  autonomous vehicles with Nvidia. Big is right.
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  They're planning to scale their global autonomous
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  fleet to 100 ,000 Level 4 vehicles. 100 ,000.
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  And starting in 2027, this isn't just a pilot
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  program anymore. No, this is about full scale
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  operation. And just to clarify for everyone,
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  Level 4 autonomy, or L4, that means the vehicle
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  drives itself completely under certain conditions.
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  Like within a specific geographic area, or maybe
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  only in good weather. Exactly. No human driver
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  needed in those approved zones or conditions.
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  It's the kind of autonomy you could actually
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  use reliably soon. And the tech making this happen
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  is NVIDIA's Drive AGX Hyperion 10 platform. Uber's
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  leaning heavily on it. Yeah, think of Hyperion
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  10 as like the central nervous system for the
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  self -driving car. Okay. It bundles the sensors,
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  the radar, lidar, and crucially the really powerful
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  computer chips needed to process all that data
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  in real time. It's a standardized package. So
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  it helps automakers or ride hailing companies
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  get L4 capable faster. Precisely. It's the foundation.
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  Uber's CEO, Dharakos Rishahi, even called NVIDIA
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  the backbone of the AI era. That's quite an endorsement.
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  But I mean, does relying so much on one company
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  for that backbone create a risk, like giving
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  up too much control? That's definitely the strategic
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  tightrope they're walking. But when you're talking
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  100 ,000 vehicles globally. Standardization becomes
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  key for cost and just, you know, making it work
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  consistently. Speed to market versus controlling
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  every little piece. Exactly. Their betting NVIDIA's
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  platform is the fastest, most reliable way to
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  get there. And their global plans show that urgency.
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  Right. They're testing robo taxis in Munich starting
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  in 2026 and working with a Chinese startup, Momenta,
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  for that. Yeah. Which puts them head to head
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  with Lyft and Baidu, who are also eyeing Europe.
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  Plus, they're already integrating Waymo vehicles
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  in places like Austin, Phoenix, LA. And expanding
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  in the Middle East, too, with partners like WeRide
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  and Pony .ai, Abu Dhabi, Riyadh. They're really
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  pushing everywhere. So 100 ,000 L4 vehicles,
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  that feels like the scale needed for autonomous
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  ride hailing to actually become mainstream, maybe
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  even cheaper than regular taxis eventually. That's
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  the goal, moving it from a novelty to a core
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  part of transportation and delivery infrastructure.
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  It's about operational scale. OK. Huge implications
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  there. Let's shift from vehicles moving themselves
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  to AI managing while everything else in a business.
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  Right. Our second story connects Nvidia again,
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  this time with Palantir. They're teaming up to
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  create something they call operational AI for
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  enterprises. Operational AI. Okay, so Palantir,
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  known mostly for government and defense work
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  historically. Yeah, they're making a big push
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  into the corporate world now. So what is operational
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  AI? How is it different from, say, the AI that
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  just analyzes data and gives you a report? Great
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  question. Think of it like this. Analytical AI
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  tells you what happened or predicts what might
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  happen. Operational AI does something about it.
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  in real time. Ah, so it's integrated into the
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  actual business processes, making decisions on
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  the fly. Exactly. It connects the AI brain directly
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  to the hands, so to speak. It takes action based
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  on the data instantly. And the partnership makes
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  this possible how NVIDIA brings the computing
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  power. Right. NVIDIA provides the muscle, their
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  CDX libraries for speed, their Nematron open
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  models for intelligence. Palantir provides the
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  structure. The structure being their ontology
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  and AIP platforms. What did those do? So ontology
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  is like the digital twin, the map of the entire
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  business, inventory, supply chains, operations,
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  everything connected. AIP is the AI engine that
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  runs on that map. OK. Nvidia's tech essentially
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  turbocharges that AIP engine, letting it analyze
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  vast amounts of data and make decisions like
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  instantly. Gotcha. Can you give an example? The
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  Lowe's case study is perfect. They've built a
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  digital replica of their whole global supply
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  chain using this tech. Okay. So imagine a hurricane
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  suddenly delays a shipment. Instead of waiting
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  hours for someone to figure out alternatives.
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  The AI system just reroutes everything automatically.
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  Instantly. Right. It simulates new routes, calculates
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  costs, adjusts orders worldwide, all continuously
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  optimized. That's operational AI in action. Wow.
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  And Palantir's CEO emphasizes keeping AI tethered
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  to reality, right? Using accurate data. Crucial
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  point, it can't just make stuff up. It needs
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  that solid, structured data foundation from ontology.
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  NVIDIA provides the processing power, Kalantir
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  provides the structured reality for the AI to
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  work with. So it turns data into immediate, actionable
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  intelligence. That's huge for logistics, manufacturing,
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  really any complex operation. Absolutely, a massive
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  advantage. Okay, so we've seen AI scaling in
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  vehicles, scaling in enterprise operations, both
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  heavily reliant on NVIDIA's tech. Which leads
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  us right into our third story. The geopolitical
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  angle. Yeah. Because this tech isn't developed
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  in a vacuum. Exactly. NVIDIA CEO Jensen Huang
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  was in Washington recently talking about the
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  delicate balance needed in the U .S.-China AI
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  competition. Yeah. Despite all the tensions and
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  the U .S. export controls trying to limit China's
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  access to advanced chips. Huang's message was
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  pretty direct, wasn't it? He warned that completely
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  isolating China's tech ecosystem isn't actually
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  beneficial for the U .S. long term. He said it
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  hurts us more. His argument is basically economic
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  tied to innovation. How so? Well, Nvidia's market
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  share in China for these advanced AI chips plummeted
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  from like 95 % down to basically zero because
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  of the restrictions. Wow, zero. That's what he's
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  saying. And that represents potentially billions
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  in lost sales, maybe $50 billion, he suggested.
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  And losing that revenue, he argues, means less
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  money available for the huge R &D investments
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  needed right here in the US to develop the next
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  generation of chips, like the ones beyond Blackwell.
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  So cutting off China might inadvertently slow
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  down U .S. innovation by starving companies of
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  R &D funds generated from global sales. That's
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  a complex loop. It really is. But at the same
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  time, Nvidia is making very public commitments
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  to the U .S. Like manufacturing the new Blackwell
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  AI GPUs in Arizona. Exactly. And building seven
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  massive new supercomputers for the Department
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  of Energy for defense and research. One with
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  Oracle uses 100 ,000 black wool chips. That's
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  a huge commitment to U .S. infrastructure. So
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  they're playing both sides, in a way, showing
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  U .S. loyalty while also arguing for access to
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  global markets. It's a tightrope walk. And then
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  there's the whole enforcement problem. Can the
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  U .S. actually stop these chips from getting
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  into China if they really want them? Yeah, you
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  hear reports about middlemen, smuggling networks.
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  I remember that mega speed investigation. Right.
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  It's incredibly hard to completely fence off
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  high value, easily transportable tech in a globalized
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  economy. So, the US government is trying to balance
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  national security, keeping advanced AI out of
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  China's military, with the economic reality that
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  US tech leadership relies on global sales and
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  massive R &D funding. That's the crux of it.
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  It connects everything. Innovation, supply chains,
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  national security, global economics. It's arguably
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  the biggest underlying story in tech right now.
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  Absolutely fascinating stuff. Okay, that wraps
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  up our Morningstar report for today. But before
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  we recap and give you our final thought, let's
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  SNARFL for 15 % off at SCONI .com. Okay, so let's
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  quickly recap the big themes we hit today. First,
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  Uber's massive scaling of its L4 autonomous fleet
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  100 ,000 vehicles plan. Yeah. Autonomy is really
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  moving towards mainstream operation. Second,
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  Palantir and NVIDIA joining forces to bring operational
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  AI to businesses, letting them manage complex
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  logistics like supply chains in real time, turning
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  data into instant action. Think Lowe's. And third,
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  The really tricky geopolitical situation in video
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  finds itself in balancing U .S. security concerns
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  and export controls against the need for global
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  market access to fund future innovation. The
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  Jensen Huang tightrope walk. It really feels
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  like AI is rapidly integrating into the physical
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  world. Cars, supply chains. If the tech hurdles
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  are falling, what's the next big challenge? Regulation.
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  public trust, managing the societal changes.
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  That's definitely something to keep watching.
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  Lots to think about there. Well, we hope connecting
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  those dots today was helpful for you. We're here
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  to help at SNARFL, so reach out on our website
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  if you have any more questions. That's a wrap
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  on today's top stories. Remember, tech doesn't
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  have to be complicated, and we're here to help
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  connect the dots. If you've got questions or
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  want to learn more, visit us at snarfl .com.
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  Thanks for listening, and we'll catch you next
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  time.