Google Has the #1 AI Model but the Stock Just Fell 12%

Google now has the number one AI model in the world. Gemini 4 Carbon tops the Artificial Analysis Intelligence Index two weeks after Gemini 4 Argon, and Google Cloud revenue more than doubled to $30.7 billion. So why did Alphabet stock open down nearly 12%? Search, the business that pays for everything, grew just 12% and fell below half of Google's revenue for the first time as AI Mode answers more questions and earns less per query. Add a quiet change to how Google charges advertisers, the exits of Jeff Dean and Demis Hassabis, and a paper loss on SpaceX, and the market isn't buying the comeback. Ejaaz thinks it's wrong.

We also cover Genie 4, Google's new world model, which uses the cheaper Gemini 3.8 Flash as its planner; Microsoft offering buyouts to 60,000 employees, its own AI teams included; SK Hynix selling out its memory through 2029; and China's STAR 50 tech index falling more than 40% since June.

==
Timestamps
00:00 Google Has the #1 AI Model
01:58 Gemini 4 Carbon
03:51 Earnings: Cloud Doubles
04:39 Why the Stock Fell 12%
05:13 Search Drops Below 50%
06:29 $200 Billion in Capex
07:27 Can You Trust the Benchmarks?
08:19 The Ad Auction Change
09:42 Ads in AI Chat
10:29 Google's TPU Customers
11:55 Jeff Dean and Demis Hassabis
12:42 The SpaceX Loss
13:23 Genie 4
16:03 Microsoft's 60,000 Buyouts
18:40 SK Hynix Sold Out Through 2029
19:41 China's Tech Stocks and Final Thoughts

#ai #google #gemini #stocks #earnings

==
AlphaSpace by Yahoo Finance: A Professional-Grade Investment Platform Built for Everyday Investors.
👉 https://finance.yahoo.com/about/promos/gold/alphaspace/?ncid=100003571

Creators and Guests

Host

Ejaaz Ahamadeen

Investor & Host of the Limitless AI Show. Former Product at Coinbase and ConsenSys

What is In the Loop AI?

Exploring the frontiers of Technology and AI

It's official. The number one AI model in the world doesn't belong to Anthropic.

It doesn't belong to OpenAI.

It belongs to Google. They released Gemini Carbon yesterday.

And according to the benchmarks, it's the number one against any other model

that exists out there. Now this is very interesting because Google for the last

six to nine months have been trailing pretty aggressively.

They haven't been able to put out a capable model. And finally, it looks like they have.

But that's also the exact reason why their stock is plummeting.

It's down 12% at the time of recording because AI has started to cannibalize

their main business search. Google makes all of their money through advertising revenue via search.

And now everyone is choosing not to go to Google. They're choosing to go to

AI models like ChatGPT, Claude, and Gemini.

And we were able to get into the numbers this week. Google reported their earnings

as well as a host of other companies which reported record cloud revenue,

so selling all their compute to AI companies.

And despite this, it was still foreseen as a bad thing by investors.

And so we're in this weird conundrum where companies like Google,

Microsoft, Meta, and all the hyperscalers are investing hundreds of billions

of dollars in a very capex intensive industry such as AI,

hoping to generate a lot of revenue, proving that they're generating a lot of revenue.

And the market still thinks it's quite bearish. It's this weird conundrum.

Microsoft is thinking about laying off 60,000 people. I'll get into that.

And a host of other companies, including stock markets that don't even exist

in the West, the Chinese stock market is down 40%.

So the number one question is, have we reached the breaking point?

The markets, despite all the good news, despite all the good numbers,

despite all the traction, still thinks it's bearish.

Anthropic released their S1 this week, and the numbers were a surprise to many

people. They're making a lot of revenue at a very lean rate,

but the market doesn't agree. There's something fishy going on.

And so I want to get into all of this on today's Roundup episode brought to you by Qualcomm.

So let's start with the model the new gemini model is called carbon and they've

released it two weeks since their last model which is again unbeknownst to google who have taken so

long to release even one frontier capable model now they seem to be churning

out every other week so what's this model even good at well when it comes to

general intelligence it scores 59 on the artificial intelligence index which

is like the best measure to kind of see

how it performs against all the other models, which rates it as number one currently.

Now, what it's also good at is long horizon tasks and cybersecurity.

This is a smart strategic move from Google because of all the cybersecurity

incidents that we've seen.

Just over the last week, we've had something called Black October,

which is the worst 48 hours in internet history, where basically a bunch or slew of hacks.

Caused by AI agents, and we don't know who's behind it, has been orchestrated

across the entire world across various different platforms and the underpinnings of the internet itself.

Just yesterday, we recorded another episode where Anthropic apparently got hacked

and people got into their Slack and was able to expose a bunch of different secrets.

The point being is we've reached a period where AI models, whether they're old

or new, are capable of breaking into very secure and reliable software or things

that we thought were secure and reliable.

And so for Gemini or for Google to come out with a model that is the best at

it currently ranked is a very smart move.

Now, of course, you look at cybersecurity, you look at general intelligence,

there's one other bucket that's super important.

Coding. How does it measure against the best coding creators in the world, which is Anthropic?

The answer is it still comes in second. Claude Opus 5.5 is the best one and

will probably remain to be because Google's kind of struggled to put out a good

coding model. Okay, so that's the model.

What does that mean for the actual market reaction to this and also Google's earnings?

Like how is the actual core business doing? Now, at an initial glance,

it all looks quite positive. Sundar announces that, hey, Google's hit for the

first time ever half a trillion dollars in annual revenue run rate.

And our cloud business, which is their business of building up compute and providing

it to different types of customers that want to use that compute,

the most recent business being AI, which has driven up their revenue, has broken a record.

They've brought in over $30.7 billion over the last quarter,

which is up 103% from last year.

And this has been consistent over the last couple of quarters this year,

to the extent where they're probably going to hit $120 to $160 billion ARR for this single unit.

By any means, if you were just to look at this company in that lens,

you would be super bullish about Google.

So why then has the stock dumped over 12% in the opening hours of this morning?

There are two reasons. The first is their core business, Search.

Its revenue has started to slow down. The expectations were about 17% growth.

They only achieved 12%. And the exec

team basically attributed this to AI cannibalizing their search business.

Now, the reason why this is such a big deal is the majority of money to date

has been made via search and advertising.

That's how Google keeps majority of its capital afloat and for the first time

ever search now accounts for less than 50 percent of google's revenue first time in history

and so people are questioning is this a good thing or a bad thing now the optimistic

lens of this is oh no that's just because google's compute product is growing

so aggressively the one that i mentioned earlier that's making around 30.7 billion

dollars in three months absolutely impressive.

But the negative view of this is that a slowing down of search revenue is a

precursor or a sign or signal that AI is eating into the main core product.

And I think about a personal experience that I have when I used to use Google

quite a bit every single day to kind of ask my questions and search for information.

And recently, I've just been relying on my Claude or ChatGPT

or Muse or any other AI product that I can get my hands on because I just feel

that it's more intuitive, it knows me and it's going to give me a much more

effective answer it can effectively

outsource all the searching scrolling clicking on links trying to figure out

what information i'm looking like in a singular chatbot

and i think that's starting to affect a much wider scope of google's customers

and the wider world so the big question mark that people have is

how on earth is google going to compete with this well google's answer is pretty

clear in my opinion they're spending the most amount of money.

I think it's upwards of $200 billion either this year or committed to next year

to build out their TPUs, their own version of GPUs, compute to train and inference

their own models and to kind of like sell.

So the idea is they're doubling down on the AI business.

The idea here is if they are able to build frontier models, which their announcement

this week of Gemini Carbon proves, whatever this new world looks like where

people choose to go to AI models to send their search queries,

Google will still be able to capture.

But I think people are questioning whether they'll be able to actually compete

competitively against the likes of Anthropic, OpenAI, and maybe even Meta if

we want to throw them into the equation.

And so that's why I think people are being very cautious here because Google

hasn't yet proven that they're able to do this. This is the first time that

we've had the changing of the guards where search revenue is slowing down whilst

another business unit kind of steps up.

And I have to say the skepticism to a point is actually justified.

So far, Google's kind of had a history of releasing these models.

Releasing the benchmarks that show that it's a good model and then in practice.

It's not actually quite that good and so people are obviously questioning this

new gemini carbon release thinking

i don't know if i care enough about this i'll just continue using claw to chat

gpt even if it is better is it materially better but don't take my word for

it people who have been paying google hundreds of millions of dollars to date to

use their search ad revenue product are claiming that the product quality has

gone down recently. Let me give you a fun anecdote here.

Google basically pioneered advertising on the internet, and it has been the

primary way to make money on the internet. You have ads pop up on different

websites or on content profiles like this.

And so the idea here is Google is the monopoly in this case.

And one important mechanism that they pioneered is called a second auction mechanism.

So let's say company A offers $1 for an ad placement.

And company B offers $5.

Now, typically, you would take the highest bidder. But what Google does is they

see the highest bidder and they say, okay, I'll give it to you,

but I'll only give it to you at one cent more than the lowest bidder. So $1 plus a cent, 101.

And so why Google decided to do this is they wanted to incentivize advertisers

to actually give their genuine highest bid and not get screwed over because of it.

And so this drove the ad business as it is today to the multi-billion dollar

business that Google has. So it's a fantastic model. It's worked really well.

What's happened recently, however, is they've gone back on this.

Instead of just charging a penny more, they charge the full price of the highest bid.

And so people or their customers who have been very loyal to them feel quite short-changed.

And on Google's perspective, you could probably think that they're doing this

short-term strategy to boost up their numbers artificially in order to show

that, hey, listen, the business is good, when realistically, it's not actually good.

If I was in Google's position, I would just own it and say, listen,

things are slowing down, which is what their C-suite exec team has admitted to.

But we're doubling down on the new version of what this is going to look like, AI.

We haven't started to really lean into putting ads into AI. And there's a good

reason behind it because ChatGPT, although they have ads, isn't really cumbersome.

Anthropic doesn't have ads. And they committed to saying that they are never going to have ads.

So the idea here is that Google can't take the first step before or these other

companies that are arguably ahead of them will end up saying,

hey, listen, we have a free product. We don't have any ads. You should just use ours.

Google kind of needs to eat the cost and loss for now to not risk losing existing

customers and bringing on newer customers.

So there's going to be a tumultuous period, in my opinion, where Google is kind

of needing to tread very carefully, figure out what the new ad model looks like,

as well as put out frontier models.

That is a lot of pressure. Now, one thing that they're absolutely excelling at is selling compute.

Most recently, Apple has rumored to be buying more TPUs from Google.

Apple has a huge cash reserve balance to train their own foundational frontier models.

They've also got that partnership with Google where I think they're paying Google

a billion dollars a year to get access to Gemini, which is an absolute bargain,

but that's a story for another day.

And the rumor that broke this week is that OpenAI is reportedly going to be

buying TPUs from Google.

This is a big deal because typically OpenAI has rented TPUs from Google.

Now they're buying, they're investing more heavily as a diversification to NVIDIA

GPUs. The reason why TPUs are such a big deal, by the way, is that NVIDIA has a monopoly on GPUs.

And Google and their TPUs are the closest thing to eating into that market share,

to being a viable competitor.

And Anthropic, OpenAI, Meta have all committed to buying versions of these TPUs from Google.

So I would expect to see the cloud revenue go up, up, and up.

I think over 50% of their cloud revenue was from TPU sales. So it's just a very

impressive feat. And the last thing I'll say about their AI business is...

Remember, Google are kind of like the forefathers of this entire business or industry.

They were co-authors on the Transformer paper.

They were OGs in building out infrastructure, their version of TPUs,

which was like a decade-long love child experience, which took a lot of time and a lot of risky bets.

So they have all the talent, or rather they had all the talent.

Over the last couple of months, some of their key players, Jeff Dean left to

start his own startup because he didn't feel like Google was providing him with

the adequate resources or freedom to go do the thing there, which was such a shame.

And then Demis Hacibus, the former CEO of DeepMind, stepped down to take on

a new role because, well, we don't know what.

So Google is in this very weird growing period where it's new management,

it's a new team, it's a new model, we haven't been able to access the model,

we don't know how good it is.

The changing of guard with losing their key market share on search to this new

AI thing, a lot of it is unproven.

But I'm not ruling them out because I think Google is a fantastic company and

half a trillion dollars ARR is just absolutely insane. So I think the market

is unfairly valuing them and.

We'll see if my prediction is right. Oh yeah, and I missed one other thing.

Another reason why the market is tanking is because they missed on their earnings,

specifically around EPS, earnings per share.

And the reason why is not affiliated to any of Google's businesses.

It's affiliated to their investments. They are one of the largest stakeholders

or were one of the largest stakeholders in SpaceX before it went public.

I think they owned around 14% or something ridiculous like that.

And obviously when it IPO'd, stock pumped. and then it kind of dumped and it's

now reached around the level I think it's around $135. I'm not quite sure.

But the idea here is they've taken a loss on the balance sheet and they have

to report it on their earnings.

So that's affected EPS in addition to such.

Now I want to end the news on a more positive note, which is they released another

model and this is arguably my favorite one.

Google developed these things called world models. They're basically AI models

that are really good at creating physical simulated realities.

So imagine you're stepping into a GTA game or some kind of world simulator.

And the thing about Google's products, Genie 4, the one that they just released is...

It is so hyper-realistic. It's almost like you're watching a YouTube video and

it's just completely artificially created.

I mean, look at some of these demos. You have one of a guy on a motorbike and

you can see someone typing in saying, I want the other motorbikes to overtake

me. I want the traffic lights to turn green.

And you'll notice that you can hear certain sounds that generates.

You notice that you can actually speak and interact with other people in the

world. There's this great example from Ethan, Ethan Mollick,

I believe, who created this game, this neolithic, neo-gothic game.

He asked to spawn a beaver that walks up to him and talks to him.

And it happens in an instant. And the beaver talks, it has a voice,

it generates all artificially. Now, what's interesting about this product is

the AI model powering it is obviously great at video generation, images, etc.

But it's Gemini 3.8 Flash. An old, cheap model is powering this brand new wonderful experience

and the reason why i wanted to mention this is i'm noticing a trend which is

the best or some of my favorite ai products today or this year

have been these things that aren't powered by the frontier ai models i don't

quite know what to make of this but i just wanted to point it out because i

think there's been an assumption historically that the best ai models

give you the best ai experience and certainly we've seen that with coding,

solving math and whatever that might be.

But I think there's a new bucket or sector opening up where the consumer apps

don't have to be powered by the best models.

They could be powered by open source models or cheaper frontier models that

unlock a new experience.

Imagine just because it's cheap, it doesn't mean it's bad. It means that you

can spend more tokens to do crazier things like generate realities in an instant

and be able to hear, speak, and interact with things.

Imagine what this means for applying it to gaming or applying it to movies or

applying it to simulated realities, but you need to train robots or whatever that might be.

These are all applicable things. And my big bet of the year and the next couple

of years is that world models actually end up competing pretty directly with

LLMs. We'll see if that pays off. Okay, so I want to get into a few final thoughts

on today's episode brought to you by Qualcomm.

Now, next story, Microsoft had their earnings, but that's not the focus point of this week.

The focus point is them potentially laying off 60,000 people,

which is 25% of their entire workforce, including their AI teams, in the name of AI CapEx.

It should free up around $70 billion that it will spend to buy more NVIDIA GPUs,

set up new data centers, and fuel the AI beast. This is a questionable move

because Microsoft has spoken the benefits of AI for so long.

I believe Satya has even said that like, listen, this should lead to a transition

of roles and jobs, not actually loss of jobs.

And we're seeing kind of the opposite thing take place here.

Now, I understand why they're doing it. CapEx is very expensive and you need

to kind of keep the business, especially as large as Microsoft, as lean as you can.

They spent around $130 billion this year. I think they're going to do the same next year.

But what's crazy is they're also making that same amount this year.

So the question is, are they allocating resources in the most effective way does it make sense

the other thing that struck me is i can't believe they're getting rid of their

ai teams now i know that microsoft has a major financial stake in open ai and

other such ai providers i know that they've been very open to allowing more recently

other ai models to live on their platforms they've become model agnostic they

got into a kind of like a bad fight with sam ottman and chad gpt and they were

like okay cool we'll become agnostic but they were also working on their own

frontier models i believe the models were called mai and a host of other things.

One thing has been pretty clear. They have not been able to catch up.

Google was behind and now they've been able to catch up. Microsoft has failed

pretty much the entire time. I don't know whether this is because they have

a lack of high quality researchers. They're indeed hard to come by.

But this kind of seems like they're hanging up the towel. They're like, okay, cool.

We'll just become one of the number one near cloud providers.

And if you look at their recent earnings, they've absolutely crushed it,

specifically on Microsoft Azure.

Google Cloud still beat them, but it's still a good business.

But it seems to be like they don't care about building their own AI models right

now. And it's just interesting to see and kind of worrisome to see about people

potentially losing their jobs. Now the buyout presumably is around six months plus more.

And so they're not doing this for cheap. It's obviously worth the cost to them,

especially as the cycle becomes more CapEx heavy and intensive.

And that's the other thing.

Google is committing around 200 plus billion dollars for next year.

Microsoft is doing a similar figure. Meta's committing the same figure now.

We're seeing this growing trend of we're just doubling down on this AI thing,

especially when companies' cash balance sheets are going into the red.

We'll see how all of this plays out. The final story I'll give you is that the

earnings aren't just a Western thing this week.

They're crushing it in Asia as well. SK Hynix, which is the number one AI memory

provider, slam dunked it. Their revenue is up, I think, 328% year over year.

This is important because for a number of quarters before this,

people have been calling the end of the AI memory trade.

And what is clear is that not only is that false, but two, memory is sold out

through 2029, which means three years ahead of where we are today,

two and a half years, people are still buying up memory.

The craziest part about this is around 50% of those contracts are long-term

contracts, which means that all these customers who are committing to the memory

years ahead have paid upfront likely 50% of the cost.

So you have this memory provider, which is very well financialized,

that are building even more higher capacity as quick as they can,

but they can't sufficiently provide to the demand that they're seeing.

Now, you might think that this is bullish for Asia in general.

It's not. China's stock market has tanked 40% since its June highs.

And people are thinking that this might be a precursor to the AI trade and AI bubble in the US.

Certainly, we've had figures like Ken Griffin, Elon Musk called the top of the

AI bubble. I think yesterday I saw Snowflake's co-founder and CEO say the same thing.

So again, we're reaching breaking point. That's the whole theme of this entire

episode and this entire week is

despite all the good news, despite all the record earnings, despite all the

crazy numbers, the S1 filings, yada, yada, yada, people still think that this

might be a bearish turning point for AI because.

It feels almost too good. And I can't say that I disagree with them too much.

I don't have the answers right now. All I can do is look at the fundamentals.

Now, I'm very optimistic on this show, and I will continue to do so.

I think a lot of easy takes to have on AI is just assume the bear case and that

gets more views. I don't care for that at all.

I truly feel in my heart of hearts that AI is going to revolutionize and change the world.

It might just take more time. And right now we are overcapitalized.

We might be taking on a little too much leverage. And honestly,

I'll an episode to this next week. But I still think ultimately,

we're directionally ending up in a good place. And maybe we see some healthy

consolidation in the meantime.

Thank you so much for listening to today's episode. If you're listening to this

on YouTube and you aren't subscribed, please subscribe, turn on notifications,

do the same thing on Spotify, Apple or wherever you're listening to it.

Our socials are also linked below.

And yeah, that's today's episode brought to you by Qualcomm. Thank you.