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The AI Revolution: Winners, Losers, & The Future of Tech | The Real Eisman Playbook Episode 27
Dan Ives argues the AI build-out is a new industrial revolution, with infrastructure spending paving the way for enterprise and consumer adoption.
The Real Eisman Playbook · Steve Eisman
- Dan Ives is a tech analyst at Wedbush Securities.
The best minutes
- 22:55Big tech can fund AI spending before adoption scales5 min
- 39:12Palantir turns customer data into operational decisions5 min
- 44:47Data center power needs make nuclear a key AI betPro pick 5 min
Also worth watching
- 7:48AI is making IT services and software growth harder4 min
- 19:20Standalone AI models may need a larger platform to compete4 min
Skip the four-minute Eightco/Worldcoin discussion and both sponsor breaks.
Full analysis · 5 min read
Real Alpha · Nov 8
Dan Ives says $350 billion in big tech spending supports AI
- Ives ties big tech's $350 billion in yearly capital spending to the AI buildout.
- Steve Eisman restates the cash cushion as $1 trillion, but neither figure proves customer returns.
- Budget against production use, not spending alone, and watch sales friction and power approvals.
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Read the rest of the analysis
6 sections, the 5 other voices it tests Ives against, and what it means for you. Every episode we cut gets one.
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Cash cushions the buildout, but does not prove returns
Ives put big tech capital spending at $350 billion a year and said its balance sheets held over $1 trillion. Eisman restated that as a trillion dollars in combined cash.
That is Ives's distinction from the dot-com era. He said many firms then had weak models and relied on venture capital. The comparison supports a limited conclusion. Cash-rich platforms can keep building before AI revenue spreads. Spending alone does not prove an imminent funding stop.
But cash is a funding source, not a customer return. It does not show each server, model or power project earns its cost.
Ed Zitron offered a countercase on The Diary Of A CEO in August 2026. He said big tech finances AI customers whose spending justifies more data centers. That does not refute Ives's balance-sheet point, but makes circular financing a separate risk from insolvency.
On a16z Podcast in October 2026, Andy Jassy said Amazon's $220 billion in CapEx still left demand unmet. His example supports demand-led investment, but Amazon's figure is not comparable to Ives's aggregate.
Ed Zitron · The Diary Of A CEO · Aug 27AI infrastructure spending is fueled by circular financing
Andy Jassy · a16z Podcast · Oct 23Customer demand guides Amazon’s AI infrastructure spending
Our read
Ives establishes capacity to spend, not proof of returns. The case still needs customer demand, cash conversion and utilization to bear it out.
Adoption remains the buildout's biggest unproven link
Ives said only 3% of US enterprises were going down the AI path, calling adoption early. He cited healthcare, insurance and pharmaceutical use cases, then forecast consumer applications later.
Those examples matter, but the transcript gives no savings, payback periods or deployment counts. For example, a deployed workflow beats a model demo, but still needs a budget owner and measured outcome.
Cal Newport said on Prof G Markets in October 2026 that enterprise investment was heavy but ROI remained mixed. On Prof G Markets in November 2026, Tom Lee called innovation remarkable while saying use cases still needed real markets.
Their later assessments do not show Ives is wrong. They sharpen his burden of proof. Growth in spending is not necessarily growth in value delivered.
- CNCal Newport · Prof G Markets · Oct 9Enterprise AI adoption is real but harder to turn into ROI
- TLTom Lee · Prof G Markets · Nov 4Lee says AI differs from past bubbles while innovation continues
Our read
The adoption figure makes Ives's growth story a forecast, not a settled result. For operators, the test is whether pilots become production systems with measurable returns.
Incumbent software faces a sales problem before churn
Ives describes the pressure as a sales problem, not immediate mass abandonment. Salesforce and Adobe have sticky installed bases, he said, while incremental new sales get harder.
His CIO example is blunt. AI vendors get meetings, while non-AI vendors go to the back of the line. That suggests budgets can shift before existing contracts unwind.
Incumbents must show that new AI features win budgets or defend renewal pricing, not just point to existing customers. Take Accenture, which Ives said had 20% of its consultants focused on AI and was pivoting quickly.
He offers no comparison of billable hours, project margins or displacement. That omission matters because services firms can sell AI transformation even as routine delivery faces pressure.
Our read
The near-term signal is whether AI takes share of new spending, not a sudden churn wave. Track net-new bookings and expansions separately from renewals.
Palantir gives Ives a concrete enterprise use case
Palantir is Ives's clearest example of AI turning enterprise data into action. He said customers had struggled for years to use their datasets, despite bringing consultants into the problem.
His insurance illustration was hypothetical, not a named customer result. Software might flag rates as off by 20% or 30%. That distinction matters because a vivid use case is not published ROI.
Ives says Palantir's AIP commercial opportunity extends beyond its government base. He described customer referrals rather than a direct-sales force, as companies sought help putting data to work.
That account makes deployment friction the central test. Can teams connect messy data, trust recommendations and change operations? For example, finance should ask what action changed and what cost fell, not count AI features.
Our read
Palantir illustrates what a useful enterprise deployment could look like, but Ives's anecdote does not establish repeatable returns. Buyers need operating results, not just a compelling demo.
Power could move the bottleneck beyond chips
Ives says data-center growth will outstrip grid supply and require six to eight times today's energy. He sees nuclear as a major answer and Oklo's small reactors and fuel reuse as a potential fit.
That is a forecast, not a deployed power solution. Ives acknowledged Oklo has zero revenue today and framed approvals and buildouts as the next evidence.
His claim that more data centers are under construction than active came without a count. He also said definitions vary. Still, power availability is a genuine constraint in his argument.
Alex Bores said on Prof G Markets in November 2026 that investors may be pricing strict data-center limits. He expected a pause and clearer rules, not an end to US growth.
Our read
Ives's nuclear thesis depends on approvals becoming projects and projects becoming operating capacity. Watch reactor approvals, sites and supply contracts, not announced data-center plans alone.
His stock map depends on forecasts beyond today's results
Ives says he is not valuation-sensitive and looks three to five years out. That horizon helps explain why he backs companies whose current spending or earnings may not yet reflect his expected opportunity.
Ives believes Tesla could be two years away from some federal approval for full self-driving. He also believes Oklo's reactors could become widespread in the US within three to five years. The episode supplies no outcome data to test those timelines.
Ives is a Wedbush analyst and Eightco chairman, a company he describes as a treasury vehicle for World tokens. Eisman described Ives's AI-30 ETF as a basket of AI-related names.
The show closes by disclosing that hosts and guests may hold positions in discussed stocks. That is context for weighing Ives's enthusiasm, not evidence that any particular forecast is wrong.
Our read
Treat Ives's stock map as a set of owned forecasts, not independent proof of adoption. Test each against milestones, customer economics and the speaker's stated time horizon.
What it means for you
- Track paid deployment. Separate production systems from pilots, then measure recurring spend, time saved and the workflow that changed. Ives's adoption figure makes conversion more useful than demo counts.
- Set a return hurdle. Compare infrastructure spend with utilization, contracted demand and cash returns. Ives's balance-sheet point supports capacity to invest, but does not establish project economics.
- Measure software sales. Track net-new bookings, expansions and renewals separately. Ives sees new sales under pressure while installed bases remain sticky.
- Gate power plans. Ask which approvals, sites and supply contracts must land before a data center can operate. Ives's Oklo case remains a forecast with zero revenue today.
What to watch
- Whether enterprise AI pilots become production deployments with measured returns.
- Whether infrastructure spending is matched by customer demand and utilization.
- Whether nuclear approvals lead to operating capacity at data centers.
Send this to the CFO and product leader setting next year's AI infrastructure budget.
Watch the minutes around 25:49 where Ives gives the spending and cash figures.
Written by Real Alpha from the episode's transcript and the other moments it links, then checked against the transcript. Quotes are the speaker's exact words.
Minute by minute
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Read it with Pro, 7 days free- 1:46World ties identity to tokens
Ives says Eightco’s World investment is an AI authentication play, not just a token strategy. He says iris scans are processed by the Orb and then deleted, while users receive a World token in the app. He cites 15 million sign-ups and says advertisers and social platforms could pay for authentication as the network grows.
- 6:07AI reshapes tech winners and losers
Ives calls AI a fourth industrial revolution, with enterprise adoption driving spending now and consumer use growing later. He sees pressure on IT services and consultants, and says software companies such as Adobe and Salesforce face harder incremental sales as buyers prioritize AI. He argues their installed bases remain valuable, while Oracle built up its AI stack earlier.
- 12:09Apple needs an AI offering
Ives says Apple’s 1.5 billion iPhones give it a major role in consumer AI, but he thinks the company needs proprietary models to keep users and outperform. He says Apple has lost talent and is unlikely to build the answer internally, pointing instead to a deeper Google Gemini partnership or an acquisition. He also criticizes Apple’s bureaucracy and lack of product innovation.
- 19:20ChatGPT and Perplexity lead
Ives calls ChatGPT and Perplexity the leading AI products, while saying Gemini could rise to third place and eventually second. He argues Perplexity will need a partner because a company built around a model alone cannot sustain itself in the next stage, where data matters. He says Apple and Google both have reasons to deepen their relationship.
- 23:07AI spending differs from dot-com
Ives cites $350 billion in big-tech capital spending this year, compared with an earlier expectation of $280 billion, and says big tech holds more than $1 trillion on its balance sheets. He contrasts this with dot-com companies that had loss-making, venture-funded business models. He says only 3% of U.S. enterprises are on the AI path so far and argues that real use cases show adoption is still early.
- 27:12Regulation slows European AI
Ives blames European regulation and privacy concerns for slowing AI adoption and says startups are leaving for the United States, Asia and the Middle East. He says a startup may have to prepare an 800-page document for approval. He contrasts Europe’s caution with AI investment in Saudi Arabia and the UAE.
- 39:12Ives sees Palantir expanding commercially
Ives says Palantir analyzes large amounts of data for government agencies and commercial customers, citing an insurance example where it could identify mispriced policies and customer segments. He says its AIP product is gaining commercial use through customer referrals, without a direct sales force. He sees the company as a potential trillion-dollar business, while Eisman notes its high valuation.
- 44:47Ives sees Oklo powering data centers
Ives says data centers will need six to eight times more energy than they use today and argues nuclear power will be essential. He describes Oklo as a small-reactor company that can reuse nuclear material. His thesis is that reactors will be built alongside data centers, though approvals and construction remain milestones.
- 49:01Ives favors two China AI names
Ives says his AI 30 includes just two Chinese companies: Alibaba and Baidu, which he considers AI winners. He argues investors should have some China tech exposure, while acknowledging the risks. He says his travel and network in China help inform his view.
Published Sep 29, 2025.
Transcript · 44 min read
The Real Eisman Playbook, hosted by Steve Eisman, with Dan Ives.
Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there. Where the podcast’s audio and the video part ways, some times are a minute or so off.
Talk to me about what's going on in the world right now. Some like myself that's covered tech my whole career. We are in an unprecedented build-out of essentially the next layer of the way humans are going to interact and enterprise is going to interact. I think everybody would agree this is a revolutionary period, but in revolutions there are winners and there are losers. Let's talk about Apple. Elephant in the room is AI. It all is waiting on when they finally double down on Gemini partnership and actually give us something that's going to be the catalyst for Apple going forward. When Trump does these meetings with big tech CEOs, he said, what's the biggest constraint?
It's power. You think tremendous number of data centers going to be this little nuclear reactor powering the data center. That's our thesis. Let's talk about Palantir for a second. What does Palantir do? Palantir's work with every three-letter agency in the U.S. They can mine their data in a way that basically no other company in the world can mine data. But where they're going on the commercial side, oh my God. Because now they're taking that technology. That is going to be the magical solution in terms of AI. Hi, it's Steve Eisman, and this is another episode of The Real Eisman Playbook. And today, I have Dan Ives of Wedbush Securities, the tech analyst.
Welcome, Dan. So excited to be here. So I just want to point out one thing. We are both bullish on the market. You know, when I go on CNBC these days, they call me Happy Steve. But I think the difference between our backgrounds can be expressed in our fashion. So I come from the financial services background. I'm wearing a sports jacket, a little podcasty, but yet stayed. And you're a tech analyst in the wild, wild west, hence the outfit that you're wearing. But at least the sunglasses, I took them off. Thank you for taking off the sunglasses. So let's start with what happened this week. So I'll tell people who don't know, there's a company called 8co.
Read the whole transcript
Stock price was $1.45 on Friday at the close. And Monday morning, they announced that Dan Ives, my guest, is now the chairman of the company. The company raised $250 million in a private placement, I think, at $1.45. And then 8co was going to go out and buy a cryptocurrency called WorldCoin. So the stock proceeded to go straight to $80. that went to $40 and has corrected over the last couple of days, but it's still considerably higher than the $1.45. By the way, congratulations. Thank you. Thanks. But explain to me, because one thing I read about is that OpenAI has created, Sam Altman has created this device that gets to authenticate you by looking at your eyeball.
And then somehow a cryptocurrency shows up. Explain how that works. Yeah. And look, and I take a step back, like I wouldn't have done this venture if it was just a token strategy, like a typical, you know, you see many of those cookie cutters coming out. I mean, to me, I view like everything Sam's built with world, I view it as an AI infrastructure play because in the future, especially in a robotic world, bots everywhere, you're basically going to have to identify as a human and that's going to become more and more important. But you need true authentication. And I believe what they've built with World in terms of iris scanning technology, they're miles ahead of what anyone else has built.
You know, 15 million have already signed up for it, and it's going to about 100 million over the next year. But in terms of – to put it all together with the token, you know, obviously ACO buying World in terms of our treasury vehicle. Okay, so I bring the orb in, you sign up, Steve gets, so all of a sudden you put your eyeball in, you know, it basically scans it. That data is in the orb for basically a second, and then that data leaves the orb, goes to your world app. The data in there disappears forever. Now it's actually in your app. You get a token, a world token, as part of that. Just for putting your eyeball in.
It's very similar. It's like the PayPal model in the early days, right? $20 to start a PayPal account. I see. So now all of a sudden you have a token. Now, if you look today, 15 million have gone down that route. That token strategy, the way that the token trades, okay, world, it's all based on this. Now, in the future, look, the goal is that we took about 100 million. I mean, we believe it's ultimately going to be billions because- But how does the token have any value if you're getting it for free? So at first it's free, but now the token is, you know, if you look like in Japan, the second biggest advertiser in Japan, uses world as a way to scan relative to making sure that they're humans, not bots. You see it actually use cases on social media. I believe in the future you're going to have social media that are ultimately going to pay a fee to actually have authentication from a world user. Our view is advertisers are going to pay for this.
So it's a good example of you build the network, the use cases then form. And then the token has value. And then the token has value. So I don't view it necessarily as, quote, unquote, a store of value today. My view is it starts off, it's an AI tech authentication play. Okay. Then as now you're up to $15 million. But AECO is just going to own the token. Exactly. The authentication is done by his company. That's by Tools for Humanity. So that's separate. Got it. But it's all based on the token strategy. It is our view that this is something that's going to, as it expands and you start to see a network, it has value in terms of not just the token, but with the network effect and ultimately the monetization in the network.
And that's why just like, you know, Sauer's done on Bitcoin, Tom Lee's obviously done it on ETH, you know, through Bitminer. Bitminer is an investor in our venture because of the relationship with Ethereum. Okay, let's take a step back. Sure. We're at a cocktail party. Yeah. I've never met you. You tell me what you do. I know some of what's going on. I read the newspapers. I read some research reports, but I don't know anywhere near what you know. Talk to me about what's going on in the world right now in a couple of paragraphs. Like, give me your sort of gestalt. I would tell you, as someone like myself that's covered tech my whole career, it is truly a real fourth industrial revolution that's happening we're living in it and and it's my view that um when it comes to the ai revolution it's transforming enterprises today that's where the spending is right but in the future it's consumers so i when you say what's happening today i view it as like this is it's not just the tech ball market because it's my view we're in a tech bull market for the next two or three years at least but we are an unprecedented capex build out of essentially the next layer of the way humans are going to interact and enterprise
is going to interact so i i would equate it to like vegas being built in the 50s it's set you built dubai being built where there's no building that's essentially what we're doing when it comes the AI infrastructure. Okay. So let's say at a high level, I think everybody would agree this is a revolutionary period, but in revolutions, there are winners and there are losers. The winners right now are very, very obvious. These are the people who are building up the infrastructure. Obviously, it's NVIDIA. Who are Weave? Is anybody involved in kind of the hardware-y space?
“I think the biggest potential losers are IT services companies.”
Look, that's why, why is Apple underperformed? Because the reality is, is one of the biggest pours out for the last 15 years that they, it's about Michael J. Fox back to future movement, right? You know, it's like they continue to be focused on like iPhone this, we tweaked it. What's your AI strategy? Is it Gemini? Are you going to buy Perplexity? You can be on the outside looking into the biggest industrial revolution that we've seen in the last 50 years. That's the issue. That's why it's like cool kids table. Then there's the table like back toward the kitchen and stuff. And that's the issue right now in terms of tech.
Let's talk about Apple. What are your thoughts here? I mean the criticism is there's no AI strategy. But on the other hand, any AI product that comes out that the consumer is going to use, it seems to me, has to work out some deal with Apple. It's paying to play with Apple. You've got to pay a toll on the highway, and that's Apple, right? So the reality is the reason we're bullish on it and continue to be is the install-based unparalleled, you have 1.5 billion iPhones, the monetization opportunity. At the end of the day, the consumer AI revolution, one way or another, goes through Cupertino. But it comes down to, like, Apple stock, I believe we get to $270, $280 without AI.
Where is it now? $235. Okay. But the issue is that for this thing to actually outperform, because it's been a huge underperformer, you need them not just to collect the tolls on the highway in terms of the services or on the app store. You need them to have true models built into their phones that are proprietary to make sure Steve, Jane, Jim doesn't leave. And I think that's where they've been – they've significantly underestimated it. They've lost a lot of talent internally. There's a better chance of me playing Ryder Cup Bethpage September than anything happening internally at Apple. It has to be external.
And look, clock short – So then they have to buy something extra. They either have to buy a perplexity or – And that's why Google, I think fundamentally, they were waiting to see what happened in the DOJ situation to see if that got cleared up. Clearly, that was a huge win for Google. And now Sundar and Cook could do another candlelight dinner to get to figure this out and actually get this deal done. Interesting. Okay. What do you think the conversations are like internally at Apple now about what's going on? Look, there's a part of Apple that's run like a motor vehicle in New Jersey. Meaning?
Meaning in a bad way, like the bureaucracy, the red tape, it's run like a municipality. And that's part of the problem, right? Is it really? I had no idea. That's been a huge part of the problem at Apple is that innovation has really lacked, right? Like in other words, like for a company where there was the car, where there was autonomous, different. The reality is, is that the product innovation has been lackluster. You have the biggest install base in the world, but every time you go to an actual Apple event the last few years, you're trying to drink a Red Bull not to fall asleep. How was the phone?
They had the new phone meeting. How was it? It was at? I honestly needed two cappuccinos to watch it. Two. Doubles each? Doubles each. Just to actually watch it, right, from Joe and the Juice. It was that boring. It's just good because the reality is it's going to be fun. Like on a scale of 110, the product cycle is probably an 8.5. OK, it's street underestimating numbers that that's enough where I think just given the install base and what we're seeing in China to be a catalyst. But it's elephant in the room. Elephant in the room is A.I. You like, you know, it's like for someone like myself that goes to, you know, around the world with tech, you can't just say, OK, we're everyone else is playing this game.
we're not playing that game. So now it all is waiting on when they finally double down on Gemini partnership and actually give us something that's going to be the catalyst for Apple going forward. So let's go back to something that you said that why is innovation, like what happened to Apple that the innovation has lacked? Because we were talking before the show about Patrick McGee's book, Apple in China. And Dude. The way he describes how Apple moved all its manufacturing to China and incredible manufacturing and innovation, logistical genius. One thing he said, which was interesting, he said that what Apple did in China is they're not making, let's say, a million Fords.
They're making a million custom-made Ferraris in China. That's how incredibly innovative they've been. And yet that manufacturing innovation has lacked in product innovation. Why? Product, but also it's like they're very focused on like privacy. Like in other words, they're not like a tech-centric company in terms of like willing. Like if you look, it's like Meta, willing to make big bets, lose on it. Like I'd say like Metaverse, but then obviously hit massive home runs like AI, like what Meta's done. I think everything's slow there to come. even on content, like the content strategy. How long has this been like this, you think?
It's been like this, I'd say probably for the last three to four years, but the impact you haven't really seen just till the last one, two years, because look, biggest strategic mistake they ever made was not acquiring Netflix. I'm saying just go back to the history. They underestimated content. They underestimated the AI buildout. They've never done acquisitions, right it's like we could do it better but they're anti-acquisition but the reality is it's almost like it's like a kid in uh high school or whatever kid that plays baseball you're a legend at seven you ate you 11 in your town 12 eventually when you start playing club and you go to perfect game in atlanta at 15 you that's where clock strikes midnight when you see the other kids from california and hawaii whatever the point is like that's what happens to apple And it was like, they hit a point where it's like, innovate, they hit a ceiling.
Others were so much better. And guess where developers went? They didn't, they left Apple. If you're a 22 year old coming out of engineering school in the United States, you're going to OpenAI. You're going to Palantir. Right. You go, you're going to perplex today. Apple, it's like, you don't want 12 meetings to decide what type of, you know, food you want. So it's a bureaucratic nightmare in a way. And look, and I'd say to some extent. Hi, Steve Eisman here. The most successful businesses in the world share one secret. They know exactly where every dollar goes, what to cut and where to double down.
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Points can be redeemed for flights, hotels, lift rides, a future housing payment, and much more. Turn one of the most unavoidable payments in your life into the most rewarding. Find the card that's right for you and apply at joinbuilt.com slash eisman. That's J-O-I-N-B-I-N. lt.com slash eisman. Use our link so they know we sent you. Terms apply. Subject to approval and eligibility, billed cards are issued by Column N.A., member FDIC, pursuant to license from MasterCard International Incorporated. The reason in 22, the reason Google, the most AI engineers in the world were at Google. When you look at DeepMinds and everything else, DeepLabs, So you go back to OpenAI, Altman, it was Nadella was the only one willing to make the bet and understand the importance.
And Microsoft, that was the bet of the century that they made in OpenAI. That could have easily been Google. But the problem there is that the bureaucracy was there, engineers were leaving. And that's where the whole thing, Google missed that first part of AI because it was really run. And I think they recognize it was run like a municipality, right? The red tape. Next thing you know, it's like you feel like there's going to be a Kodak sort of camera somewhere or some Xerox machine. And I think that was the fear. They quickly changed that philosophy, did layoffs, brought other people in, and now Google's winning again.
But they went through that phase in 23, 24, where finally, and that's where Sundar and everyone came in. And they're like, look, we got to rip the Band-Aid off and change this whole thing.
“you cannot sustain in this next stage just being a model-driven company.”
But, but it also just speaks to now, it's like, you cannot wait. Because a lot of times I can invest from an investor perspective. Like CapEx is not sustainable.
“you only have 3% of the enterprises in the US that are actually going down the AI path today because it's so early.”
Like when you go over there and talk to people, like why is Europe nowhere? And it's a huge frustration because like I speak at a lot of these events there and like every startups, they're leaving in droves. They're leaving Europe to come to the United States. Either U.S., Asia, Middle East. And why are they leaving? Because of the privacy issues. You can't essentially do anything there. If you actually have a startup, you got to write like an 800-page document to actually get approved from some municipality, which gets approved by government. The problem is that when the privacy and the scared level of AI in Europe, you're going to have small African countries that you've never heard of ahead of Europe.
Because that's the scary thing that's happening there. And that's why, like, from an innovation perspective, the world's going ahead. Just like Middle East, think about it. Look what's happened, Saudi, UAE, across the board, and Europe is basically being like, okay, we're focused on the VCR. I think the way they're going, you can maybe have some blockbuster videos stores that might start to be built in Europe. I mean, I know there's only one in Alaska. I understand what you're saying. What do you mean blockbuster videos? They're going back to the 1990s. Europe is. Yeah. I mean, Europe is like a back to the future moment.
That's how over-regulated they are. It's the regulation, the red tape, worry about privacy. That's why if you're a startup, you're leaving Europe. That's why you see, I mean, investors right now, what European tech stock, where are things being listed? London Stock Exchange? There's companies that they would have could hit a three wood to the London Stock Exchange. Where are they listed? New York Stock Exchange or NASDAQ? So the problem is it's just the reality of what's happening in this world. Let's switch gears and let's talk about Tesla and Waymo. So I had Itai McKaylee on my show, and he's bullish on Tesla.
But as I listened to him, he basically said that Waymo has a much more belts and suspenders, autonomous driving with the sensors and everything. And so Waymo can start to be in big cities. But that Tesla has chosen a route of just cameras and that he doesn't think that they, at least at this point, have the. ability to do autonomous driving in big cities. And so I didn't ask him on the show, but when I thought about it, I thought that's kind of like a real weakness because the money is going to be in big cities. So let's talk about Tesla to begin with. I find it amazing that peak earnings of Tesla were 2022 and where the earnings are going to be this year is like 60% lower than they were in 2022. It's a testimony to the belief in Elon Musk that the stock is actually flat over that period, but it certainly doesn't look great. Give us your thoughts on Tesla.
Where are they in autonomous driving? What has to happen to this company to make it better? They're losing market share to China. Let's talk Tesla for a while. And I think for us, most people know us for Apple in the early days and really Tesla in the early, right in terms of identifying that because it's my belief that tesla is the most along with NVIDIA disruptive technology company in the world like in the future because look the reality is like when you look at the future for them is about autonomous and robotics so when it comes to like losing share deliveries numbers coming down and it's a huge frustration of the bears right in terms of Tesla is that the whole future for Tesla, the whole growth, it's all about physical AI, autonomous and optimist on the robotic side. When it comes to autonomous, see, my view is way more $200,000, $230,000 cars. They're essentially in five cities in the United States.
That's how much the cars cost because of the incredible technology that they have all over of the car so how much does that car cost two to 230 000 wow so now look will that come down over time yeah they're not scaling like you know i'm saying the real waymos are cool it's cool to tell your friend dude i was in scottsdale i was in a waymo is really that's great like take a facebook picture but the reality is like who's gonna own autonomous it's gonna be tesla's world everyone else paying rent. Relative to the scale producing these cars at $30,000, they're going to have millions of autonomous vehicles.
But how do they get over the fact that it doesn't seem nearly as good? Or they don't use LiDAR. I mean, it's cheaper, but it's cheaper for a reason. But I believe Tesla, it's a whole different data model because you have 10 million Teslas out there. Their model is non-LiDAR. So it's camera driven. As someone like myself that spent a lot of time in Austin, in the robo-taxis, and obviously that's going to continue to get deployed around the United States, I believe they're going to be able to do it non-LIDAR. And I was like, I believe they're going to be doing- And how do you do it non-LIDAR? Camera set.
If you look at how Tesla's done it, look, go back years ago. You can't build an EV like that. You can't actually build a car that's actually going to- You can't build a supercharger network. Musk and Tesla, their whole existence has always been, you can't, that can't, same thing. Because I believe it's going to be a data-centric model, the way that they ultimately build this out. What do you mean a data-centric model? Because it's all based on the AI from the data, from the technology that's been built into the algorithm. It's not just camera technology. You think it's camera plus AI software?
It's from AI software. And that's why ultimately what's going to happen is like, they're going to actually, own a big piece of xai which i think will happen in november what's xai xai is musk's ai technology company okay okay so i just view the future that tesla is going to continue to innovate more and more in autonomous the interventions which basically is a fancy term for I appreciate it. a human has to get involved in terms of, you know, getting on the wheel or taking control are going to, I think, get to the point that you're going to have more and more regulatory approval for what I view as true level four and, you know, ultimately no wheel, essentially, technology. Level four means no driver. No driver. Right.
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and Ramp corporate cards block any out-of-policy spend before it even happens. That's why some of the most valuable businesses in the world like SpaceX, Shopify, Visa, and Stripe cut their expenses by 5% with Ramp. A business owner I really respect uses Ramp, and they say they love it. Invest in your growth. Get on Ramp. New customers get $250 off at ramp.com slash eisman. go to ramp.com slash eisman ramp.com slash eisman so look is that coming today no is it coming tomorrow but i believe like in the next few years that is within reach well so what has to what has to happen in terms of technology for tesla to get to that point because until then this is not going to be rolled out all over the place you need to have in terms of full self-driving yes you have to get to a point that the technology is so good that it hits a regulatory threshold that then from a federal perspective and ultimately the state, they say- That's good.
That's good. How far away do you think we are from that? I believe we're two years away. Two years away. I think we're two years away from starting to get some sort of federal approval on what I view as true FSD for Tesla. Full self-driving. Full self-driving. Now, like, look, the scale obviously has to get there, okay? You got to get robo-taxis to ultimately 35, 40 cities around the United States. You know, that's something that's going to need to happen. Waymo, look, because it's our view, like, we're much more neutral. We were bullish on Uber. We're much more neutral and negative on Uber because it's my view over the years that Tesla will ultimately dominate that opportunity.
the economics on ride sharing are going to come down significantly that's gonna be major pricing pressure for uber lyft because the way it's ultimately going to work is if i have an uber and i live in new jersey and i'm here right now in new york city when i put my uber into the network my uber right now my tesla could be driving around new jersey picking people up making money because 94% of the time, you don't use your car. And then I make sure it's back in my driveway by 6 p.m. It's made 500 hours driving people around. So people have a little side business. Of course. It's no different. That's what you think is what Tesla's going to do.
It's like me and you buying a medallion. So is that an Uber business or is that a Tesla business? That's a Tesla business. That's a Tesla business. So that's what, and look, that'd be like me and you buying a medallion for a taxi service. Right. So it's the same concept. And that's where my view is termed like physical AI. And that's why when you look at everything Jensen talks about, physical AI, autonomous. What is physical AI? Physical AI means physical devices, physical action machines that use AI. That's robotics, humanoids, autonomous. I understand. So if we're two years away, let's say you're right.
Let's say two years from now, it's clear that Tesla is level four. In our world, two years of freaking eternity. So what happens to Tesla between now? Forget about robo-taxing. Let's talk about the fundamentals now. What happens to Tesla over the next couple of years? Because the tax credits are going away to buy EVs. Are the earnings going to go down to the 50%? I don't think they're going down to the 50%. I mean, I think you have some stabilization from margins. Some of the demand destruction started to stabilize in Europe. You have new models that come out, I think, probably over the next year.
But the reality is, like, look, it's the most – if I've covered whatever, 100 public companies. Like the most emotional bull bear debate out there will always be Tesla. The bears would be like, oh my God, they missed earnings again, 20%. The bulls would be like, robo taxis are now in 15 cities. By the way, having run hedge funds, I have to say, if I was an analyst and I had pitched Tesla as a short, okay, and I had said to my boss, I am super confident that the earnings are going straight down. And that four years from now, the earnings per share will be 60% lower than it was in 2022. Let's short the stock.
And it all happened exactly as I said, and the stock is flat. I'm going insane. Well, that's why. But that's why I could tell you, like, as someone that lives in, like, the institutional world, but also on the retail world in terms of private client, well, speak so much to retail. you know webbush and others what i think this market what's been so frustrating for many is like from the palantirs to the NVIDIA's to the tesla's to many other names where a lot of times investors have been if they've done their work on the negative side they've actually been right in terms of sometimes their thesis in terms of numbers but what they've missed is what's coming what's coming. And I think that it's been a very, look, you've obviously lived it for decades. I think that's been the most difficult thing for stock picking. If you're very valuation centric, it's been a very, very, look, it's been a very brutal years for many of those investors if you
“They can mine their data in a way that basically no other company in the world can mine data.”
So when I think about the trillions of dollars that's going to be spent, I view Palantir as like they are going to be, and they're a household, I believe they're a trillion dollar market because it might be the commercial business.
What's the market cap now? I mean, 300 billion or something. Okay, so you think this could be still a huge stock. And even though it's so big, how do you justify, it's 80 times. times earning, it's eight times revenues. My view, like everyone knows this for like the last 25 years or whatever, I've never been a valuation sensitive tech analyst because my view is like, I look out three, five years, if I believe and I do all my work and look, you know, over 3 million air miles later, the point is like traveling the world. Like that's the other thing. Like there's many, they're the smartest guy in the world wearing the Peter Millar on Metro North and they go to san francisco twice a year so the point is like for me that travels like asia four times a year all around the world go i i feel like a huge advantage for me is like been seeing it boots in the ground so that is actually been a huge way is that a lot of the bears when they're in hibernation mood they can't see ai in their spreadsheets let's talk to a small company that
“You need six to eight times more energy than you have today to fuel these data centers. It's not going to be the grid.”
Let's talk a little bit about some of the other stocks while I got you. You have a couple of China companies in your 30. You got BABA. And Baidu. You got Baidu. like how do you like know what's going on in China you're one of us living here in the United States you go to China you make a tour around like see I would be uncomfortable me personally I would just be uncomfortable having anything in China in my portfolio because I just figure I can wake up tomorrow morning the Chinese government does something I don't know what the hell's going on if you're not part of the party in terms of the communist party Look, first of all, I go to China a few times a year.
So the point is we have a pretty good network that I think we built there. So my view is like, okay, there's a reason I don't have 10 Chinese companies in R30 and we only have two. By the way, so I'm going to say Dan has a product. It's an ETF. It's the Dan 30. Yeah, it's the ETF. And Dan Ives 30. It's basically AI related. And the second, third, fourth derivatives. Right. But see, Steve, to me, it's like, to the opposite, what you're saying is like, I feel like you have to have some exposure to the China tech market. Because when we think about the AI revolution, it's not just going to be all US centric.
So to me, when I look at BABA and Baidu, those two specifically, they're the AI winners to me in China. Is there risk? Of course there's risk. but i believe they will be key to ultimately that that builder that we see in china but there is risk but also that's why like that's why like we're in asia we'll be in asia next month like that's why it's a huge piece i think it's been like a big different share for us to be honest i think it's very easy when you live in a more of a cocoon like environment you get caught up in sentiment and stuff like that but then all of a sudden like when you're in China when you're in Taiwan when you're in Vietnam when you see it a lot of times like that's probably been like some of our biggest like aha moments like there have been times like I've there were times in like 22 23 I'd be like traveling and like stocks are selling off especially I'll be sitting there in like Taiwan everyone's like dude this is that things are selling off this is like a bubble yet i'm going around to the different fabs being like oh my god demand's like 15 to 1 right so that's where it's like let's talk about mongo db for a second yeah what does mongo db do why do you like it because my thing about like palantir mongo db is right here i mean they are basically
a data-centric model that's Let's go. Not as good as Palantir. Not as good as Palantir, but here's the difference. Like, they're a consumption model. So what that essentially means is, like, the more you ingest, the more that they make. Mongo's issue has been they've been waiting. So when you think about the AI bill, it's, like, chips, hyperscalers. If there's, like, an Eisenman-Ives, it's, like, building it out, building it out. The use cases, the consumption happens later because you have to build it. But Mongo has been weighted. If you look at Mongo, it was actually like the stock was like underperforming a lot.
Now, as everything's been built out, like this last quarter, bam. Snowflake, bam. Because now the mind- Now people need the data mining. They need the data mining. I see. So that's why- And they can't all use Palantir. You can't all use Palantir. And then when you look at it, that's why our whole view is like of the second, third, fourth derivative. You have to view this as like, okay, it's like you have to almost like follow the kind of breadcrumbs and you can't just stop here you gotta be okay then who gets it here like g vernova is a name that we're bullish on me too no i've owned it for a while but g like nebesis is another like you know that we're bullish on so it's it's trying to figure out the breadcrumbs talk about breadcrumbs one stock that i was the most surprised about that's in year 30 is spotify like why i mean i mean i use spotify but what's that got to do with the whole ai story i mean Because to me, it's really around, like, the AI piece in terms of how – look, Apple's in there.
Like, Apple's not – because in my view, like, how they're ultimately going to monetize AI from a consumer perspective. They're going to be a use case when it comes to AI, Spotify. How? Well, because I think AI is going to be used in terms of, like, preferences, in terms of buying habits, in terms of data that will ultimately be used from an advertising perspective. So I view it very similar as how like AI, like Amazon's going to be using AI in a lot of similar capacities. It's a view of where AI is going, not where it is today. But that's also in a consumer perspective. It's like you can look at meta, but then like look at like where Apple, look at how, you know, like Alibaba would be a good example in terms of how that's going to be mined.
Dan, that was great. No, thank you. This is a great conversation, and thanks just for having me. I'm a huge fan of you. I really appreciate your time. I'm a huge fan of you. It's great to be here. Thank you. This podcast is for informational purposes only and does not constitute investment advice. The hosts and guests may hold positions in stocks discussed. Opinions expressed on their own and not recommendations. Please do your own due diligence and consult a licensed financial advisor before making any investment decisions.


