Passengers ride in an electric Waymo full self-driving technology in Santa Monica
Allen J. Schaben | Los Angeles Times | Getty Images
Waymo, Alphabet‘s self-driving car unit, is having a relatively good couple of months – at least, compared to one of its key rivals: GM‘s Cruise.
Formerly known as the Google self-driving car project and now an independent subsidiary of Google parent-company Alphabet, Waymo has been operating in some capacity since 2009. Five years ago, the company launched what it billed as the “world’s first commercial autonomous ride-hailing service” in the metro Phoenix area, then last year expanded to San Francisco. The company soon plans to launch commercially in Austin, its fourth city, and also recently began test-driving vehicles in the winter weather of Buffalo, New York.
For much of this time, Cruise has seemed to be competing neck-and-neck: When Waymo raised funding at a $30 billion valuation in 2020, Cruise followed in 2021 with the same valuation. When Cruise began offering fully autonomous rides in San Francisco in the winter of 2022, Waymo followed in the fall. In August, California regulators voted to approve round-the-clock robotaxi service in San Francisco from both companies, making it the first major U.S. city to allow two robotaxi companies to compete for service “at all hours of day or night.”
Amid the news, Waymo’s chief product officer, Saswat Panigrahi, told CNBC that the self-driving car unit hasn’t seen a change in tone from regulators or a shift in the company’s public perception.
Obviously, Waymo seems to be performing better than some competitors. What, exactly, do you think you’ve been doing differently?
There are no shortcuts. I mean, this is not a question you’re asking an app or a web page, which is giving you an answer. This is a multi-thousand pound vehicle that’s moving through the physical world – yes, it’s an application of AI but a very different kind of application of AI. And there’s something to be said about time and experience and just rigor that no matter how hard you work, it takes time to do this.
So I would say that the amount of data you’ve tested yourself against – you could always test more, but the staggering scale of testing that has been brought to bear – I sometimes say that building the Waymo Driver is a hard thing, but it’s almost as hard to evaluate the Driver. The amount of simulation we have had to do… has taken a decade. It took Google’s level of infrastructure because even to simulate at that scale, as you and I are speaking right now, 25,000 vehicles in our simulator are learning to drive better. To bring that, you need incredible infrastructure capability because even if you had the AI capability, without the infrastructure, it’d be very hard to bring that skill to bear – a decade of investment into AI before AI was cool.
Compute infrastructure, to power those simulations?
Yeah, some of it is just raw scale of compute, how many computers can you bring to bear, that kind of thing. But some of it is also – think of the old-school video game versus how realistic video games have become now, that’s a metaphor for how things are. Let’s say we saw a person in Phoenix speeding at 60 miles an hour on a 45 mile-per-hour [street], and then imagine that we saw a very tight intersection in SF – can you realistically mix these two to challenge your driver to a harsher situation that may occur many millions of miles later in the real world?
[On top of that], being able to add rain, for example – all right, you’re safe enough when you’re driving through good weather, through this tight intersection with a speeding agent. Can you do that as well in rain? Can you do that at night? You can’t wait for the rain in real life to occur exactly when you want to push your system in that way, but being able to simulate rain requires that infrastructure but also enough algorithms and realism on top to be able to push this.
Can you get specific about how much compute that requires?
I have worked with pretty high-scale systems before Waymo, at Google and Ericsson, and this is a pretty staggering scale. But the only number I can tell you is 25,000-plus virtual vehicles driving continuously, 24/7, learning from each other, and [tens of] billions of miles in simulations. Think of how much you or I drive in a year – we drive, what, 10,000 miles in any given year…? Now think of billions of miles of experience – close to seven orders of magnitude difference.
Let’s talk about the shift in ridership over the past month. Have you seen an increase? Decrease?
Things are growing – to give you an idea, this year we have more than 10x’d [trips with public riders]… The ridership is increasing in both Phoenix and SF. We are well ahead of 10,000 trips [in each city] every single week… So it’s going well. We’re taking the time to respond to feedback and thoughtfully expand.
[Note: Waymo recently shared that Waymo riders took more than 700,000 trips in autonomous vehicles in 2023.]
Amid all the controversies, in recent months, what’s been the impact on public perception of your programs?
For riders, it’s just been an incredibly positive response. We look at their ratings, we look at their usage patterns, we look at what they qualitatively tell us, we speak to them in focus groups and all of them have been overwhelmingly positive…
On people we share the city with – communities, groups, like first responders, firefighters and so on – we’re continuously engaged with them. We’re listening to their feedback. We have trained more than 5,000 first responders in SF alone, multiple training sessions, and based on that have [brought] new features. For example, now we can signal intensities to firefighters that, “Hey, we’re about to make a U-turn and get out of this scene.”
Over the same period, have regulators’ demands of the Waymo team changed at all?
With regulators, we have a very open dialogue and submitted more data than they ever asked for… So it has been a very positive engagement with them, but no change in tone.
We were the first company that openly released our safety framework, the mechanism by which we test the performance of our system and how we determine when we’re ready to deploy, three years ago. We were also the first to release all of our collision data from the fully autonomous service… Those were all before any regulator asked us for something. And then yes, we do submit ongoing reports to them as well.
As far as your AI processes and how exactly things work – are you running deep learning on neural networks? Feeding in training data from simulations? Give me a rundown.
There’s a ton of AI that’s helping us detect a pedestrian, a child, a cyclist, a pedestrian on a scooter, a pedestrian on a scooter that’s motorized which is why it’s going much faster, an older person with a stroller they’re pushing. Being able to predict which direction the car that’s making an unusual curvature is going to jump in… being able to predict where different objects are going to be in the next few seconds.
All that is an insane amount of AI with a lot of specialization on the difference between how kids behave, versus how adults behave, versus how people on bicycles behave… Everything you can think of from deep learning, reinforcement learning, all of these areas, we are utilizing it in multiple parts of the system.
Most autonomous vehicles have remote operations teams. How does Waymo’s work?
I want to clarify that the driving is done by the Waymo Driver on the car – there is no remote person driving the car. You can think of it like air traffic control, in a way. Air traffic control doesn’t fly the plane, but the pilot may ask a question to air traffic control, “Hey, I’m observing a very anomalous situation here, what is the intent?” And there are very basic binary questions that can be asked that a person can respond to provide clarification when that’s not immediately clear from the scene.
For example, you could have a set of cones blocking a street, but there could be a large enough gap where you could go in, so it’s a bit ambiguous on whether or not you should go in or stop – that kind of a question can be asked and there’s an answer… And it’s designed to do the right thing even when support isn’t available.
What’s been Waymo’s biggest internal obstacle over the past year?
One thing I’ll say is definitely what has been interesting this year is bringing the cost down.
During past expansions, my impression has been that Waymo was looking for “Goldilocks cities,” and what I mean by that is cities that didn’t make it too difficult to roll out a driverless car service but were also challenging to some extent, such as a growing population or interesting road maneuvers but no snow or ice. When you’re on the lookout for your next city, what are you looking for – and what those cities might be beyond Phoenix?
You touched upon a key thing there. Phoenix has been amazing for us… If it’s really tight, you don’t need to see that far ahead, but when you are going at 45 and sometimes people are driving 50 to 60 miles per hour, you do need to see a lot further, anticipate objects, make unpredicted turns and so on. And what we found is when we went from Phoenix to San Francisco – the ultra high density of pedestrian narrow streets, double-parked cars, and so on – one thing we’re realizing is that every other good weather city in the United States, at least, and some internationally as well, is just a linear combination of the two. So if you take LA, for example, West Hollywood is a bit like the dense parts of San Francisco, but its paths to the suburbs are very much like Phoenix.
On the axis of weather, we’re now doing rain and fog… and then the next, eventually, will be snow… What we’re trying to make sure of is that we don’t go to a city just to rubber-stamp it, just to be able to say that we’re autonomous there.
Applied Materials shares sank more than 10% in extended trading Thursday as the semiconductor equipment company provided outlook for the current quarter that came in light.
Here’s how Applied Materials did in its third-quarter earnings results versus LSEG consensus estimates:
EPS: $2.48, adjusted, versus $2.36 estimated.
Revenue: $7.3 billion vs $7.22 billion estimated.
Applied Materials said it expects $2.11 per share in adjusted earnings in the current quarter, lower than LSEG estimates of $2.39 per share. The company said to expect $6.7 billion in revenue, versus $7.34 billion estimated.
CEO Gary Dickerson said that the current macroeconomic and policy environment is “creating increased uncertainty and lower visibility.” He said the company’s China business is particularly effected by the uncertainty.
The Trump administration’s tariffs could double the price of imported chips unless companies buying them commit to building in the U.S. Applied Materials makes tools for chip foundries to physically make chips, much of which currently happens in Asia.
Applied Materials said that it has a large backlog of pending export license applications with the U.S. government, but that it’s assuming none of them will be issued in the next quarter.
“We are expecting a decline in revenue in the fourth quarter driven by both digestion of capacity in China and non-linear demand from leading-edge customers given market concentration and fab timing,” the company’s finance chief said in a statement. He added that it expected lower China business to continue for several more quarters.
Applied Materials reported $1.78 billion in net income, or $2.22 per diluted share in the quarter, versus $1.71 billion or $2.05 in the year-ago period.
The company’s most important division, semiconductor systems, reported $5.43 billion in sales, topping estimates, and representing a 10% rise from last year.
Applied Materials was praised by President Donald Trump earlier this month after it was included in an Apple program to make more chips in the U.S.
Apple said it would partner with the chipmaker to produce more manufacturing equipment in Austin, Texas.
Lip-Bu Tan, chief executive officer of Intel Corp., departs following a meeting at the White House in Washington, DC, US, on Monday, Aug. 11, 2025.
Alex Wroblewski | Bloomberg | Getty Images
Intel shares rose 7% on Thursday after Bloomberg reported that the Trump administration is in talks with the chipmaker to have the U.S. government take a stake in the struggling company.
Intel is the only U.S. company with the capability to manufacture the fastest chips on U.S. shores, although rivals including Taiwan Semiconductor Manufacturing Company and Samsung also have U.S. factories. President Donald Trump has called for more chips and high technology to be manufactured in the U.S.
The government’s stake would help fund factories that Intel is currently building in Ohio, according to the report.
Earlier this week, Intel CEO Lip-Bu Tan visited Trump in the White House, a meeting that took place after the president had called for Tan’s resignation based on allegations he has ties to China.
Intel said at the time that Tan is “deeply committed to advancing U.S. national and economic security interests.” An Intel representative declined to comment about reports that the government is considering taking a stake in the company.
“We look forward to continuing our work with the Trump Administration to advance these shared priorities, but we are not going to comment on rumors or speculation,” the spokesperson said.
Tan took over Intel earlier this year after the chipmaker failed to gain significant share in artificial intelligence chips, while it was spending heavily to build its foundry business, which manufactures chips for other companies.
Intel’s foundry business has yet to secure a major customer, which would be a critical step in moving towards expansion and giving other potential customers the confidence to turn to Intel for manufacturing.
In July, Tan said that Intel was canceling plans for manufacturing sites in Germany and Poland and would slow down development in Ohio, adding that spending at the chipmaker would be closely scrutinized.
Under Trump, the U.S. government has increasingly moved to put itself at the center of deals in major industries. Last week, it said it would take 15% of certain Nvidia and Advanced Micro Devices chip sales to China. The Pentagon bought a $400 million equity stake in rare-earth miner MP Materials.It also took a “golden share” in U.S. Steel as part of a deal to allow Nippon Steel to buy the U.S. industrial giant.
Intel shares are now up 19% this year after losing 60% of their value in 2024, the worst year on record for the chipmaker.
Alexander Karp, chief executive officer and co-founder of Palantir Technologies Inc.
Scott Eelis | Bloomberg | Getty Images
Palantir‘s astronomical rise since its public debut on the New York Stock Exchange in a 2020 direct listing has been nothing short of a whirlwind.
Over nearly five years, the Denver-based company, whose cofounders include renowned venture capitalist Peter Thiel and current CEO Alex Karp, has surged more than 1,700%. At the same time, its valuation has broken new highs, dwarfing some of the world’s technology behemoths with far greater revenues.
The artificial intelligence-powered software company continued its ascent last week after posting its first quarter with more than $1 billion in revenue, reaching new highs and soaring past a $430 billion market valuation.
Shares haven’t been below $100 since April 2025. The stock last traded below $10 in May 2023, before beginning a steady climb higher.
Last month, retail poured $1.2 billion into Palantir stock, according to data from Goldman Sachs.
Here’s a closer look at Palantir’s growth over the last five years and how the company compares to megacap peers.
Government money
Government contracts have been one of Palantir’s biggest growth areas since its inception.
Last quarter, the company’s U.S. government revenue grew 53% to $426 million. Government accounted for 55% of the company’s total revenue but commercial is showing promise. Those revenues in the U.S. grew 93% last quarter, Palantir said.
Still, one of the company’s oldest customers is the U.S. Army.
Earlier this month, the company inked a contract worth up to $10 billion for data and software to streamline efficiencies and meet growing military needs. In May, the Department of Defense boosted its agreement with Palantir for AI-powered battlefield capabilities by $795 million.
“We still believe America is the leader of the free world, that the West is superior,” Karp said on an earnings call earlier this month. “We have to fight for these values; we should give American corporations, and, most importantly, our government, an unfair advantage.”
Beyond the U.S.
The U.S. has been a key driver of Palantir’s growth, especially as the company scoops up more contracts with the U.S. military.
Palantir said the U.S. currently accounts for about three-quarters of total revenues. Commercial international revenues declined 3% last quarter and analysts have raised concerns about that segment’s growth trajectory.
Over the last five years, U.S. revenues have nearly quintupled from $156 million to about $733 million. Revenues outside the U.S. have doubled from about $133 million to $271 million.
Paying a premium
Palantir’s market capitalization has rapidly ascended over the last year as investors bet on its AI tools, while its stock has soared nearly 500%.
The meteoric rise placed Palantir among the top 10 U.S. tech firms and top 20 most valuable U.S. companies. But Palantir makes a fraction of the revenue of the companies in those lists.
Last quarter, Palantir reported more than $1 billion in quarterly revenue for the first time, and its forward price-to-earnings ratio has surged past 280 times.
By comparison, Apple and Microsoft posted revenue of $94 billion and $76 billion during the period, respectively, and carry a PE ratio of nearly 30 times.
Forward PE is a valuation metric that compares a company’s future earnings to its current share price. The higher the PE, the higher the growth expectations or the more overvalued the asset. A lower price-to-earnings ratio suggests slower growth or an undervalued asset.
Most of the Magnificent Seven stocks, except for Nvidia and Tesla, have a forward PE that hovers around the 20s and 30s. Nvidia trades at more than 40 times forward earnings, while Tesla’s sits at about 198 times.
At these levels, investors are paying a jacked-up premium to own shares of one of the hottest AI stocks on Wall Street as its valuation has skyrocketed to astronomical heights.
“This is a once-in-a-generation, truly anomalous quarter, and we’re very proud,” Karp said on an earnings call following Palantir’s second-quarter results. “We’re sorry that our haters are disappointed, but there are many more quarters to be disappointed.”