Google has TPUs, a frontier model, a completely separate and lucrative revenue stream they can call on at will, and teams working on multiple different language modeling strategies simultaneously. Did I mention the vast and ominous data centers that already serve a significant fraction of the internet? If that ain't a moat, then what exactly is a moat?
I have _long_ said don't sleep on Google for precisely these reasons. They have the only vertically integrated AI stack, insane capital they can deploy, and attention and focus and phenomenal architects and engineers, and a pre-existing catalog of as much of the world's data as possible. Counting them out would be completely absurd.
It started to feel just a bit like they were potentially content staying in the effective-fast-cheap lane and ceding frontier models to frontier labs, but I don't think anyone seriously thought that Google was going to sit back and let this generational shift pass them by when they're so well positioned to remain on the top of the heap.
If anything, I thought that 4 was maybe coming up short or causing safety concerns that were forcing them to be a bit more cautious, but nothing packs a wallop like being able to launch ahead of everyone else's brand newest toys...
I agree on all except for your comment on attention and focus. They've seem to be very scattered in their deployment of AI for customers. Examples in point being the replacement of Google Assistant with Gemini, the AI Studio vs Vertex disconnect, and a crazy amount of coding tools and platforms (Duet, Firebase Studio, Studio Bot, etc).
Working through this as a consumer and enterprise customer has been a confusing experience, to say the least.
Strongly agree - their approach has been extremely scattered. But also, doesn't it seem like they're starting to consolidate? It kinda makes sense to approach things like this as a mega corp. Have internal teams try the same things in different ways and let the market pick a winner. Kinda like being a startup incubator.
A vertically integrated AI stack won't fix the misaligned incentives of google execs.
AI is strangling their other major business and they don't like that. Unless Google sacrifices that branch of income, they won't put their full force behind AI.
I'm curious -- in your view, what exactly is it strangling that could not be addressed by replacing google.com with a ChatGPT-like interface while integrating other Google free-by-ads tools nicely? Or is your point they wouldn't do that due to existing "siloed incentives"?
The ads in google search are ~55% of their revenue and ~70% of their profit. Will the LLM drive as much traffic to the ads as the current google search? Will it feel as organic to the users as the current solution, or will LLM hawking a product seem forced by the users?
I mean it sounds wise to not go all in on publishing expensive models when they can earn money with more efficient models while still not bleeding too many customers?
I've been lowkey rooting for them, not a fan of Altman, and I don't know if I trust Anthropic either, I'm not Google's #1 fan, but I think they can definitely innovate heavily in this field, they have a lot of key things as has been mentioned.
I'd add that we've seen how the leadership/reputation of different AI leaders, and with 2 decades of history with Larry and Sergey, they seem to come up on top as the most respectable.
Did they ever really abuse the power Google could have wielded?
I could be missing something, but for the most part they seem to just get down to building and pushing technology/science forward and avoid drama rather than welcome it.
> Did they ever really abuse the power Google could have wielded?
Plenty of times. Perhaps the worse is pushing Manifest v3 with no support for real ad blockers in Chrome. Not to mention no support for ad blockers in Chrome mobile.
Also, their stealing of newspaper content.
Their new push for AI summaries instead of actual search in their search product, stealing even more clicks from sites that actually produce information.
YouTube pushing Shorts to everyone, and now the weird text posts that you can't hide.
In general their gigantic push for ads everywhere all of the time.
Google, with the help of Facebook, destroyed the independent online publishing business. They made it impossible to maintain an honest publication and tunneled users to low quality websites until there's not much left of respect.
> Did they ever really abuse the power Google could have wielded?
The "Do no evil" never being an official slogan and people saying it's no longer true for the last 10 years or so, they're just really massive. They do mess up a lot, but when you're Microsoft, Apple or Google sized, its nearly impossible to get everything right all at once.
There are pictures of Sergey in the files, but they are rather milquetoast. He's just sitting next to David Brooks of the NYTimes. I don't think there's any evidence he's engaged in sex abuse.
The alternative would have been paywalls galore with subscription tiers for everything. Only rich people would be able to afford having subs for everything, while the poor would just get the most dirt tier scraps and wouldn't be able to afford many platforms.
Nothing would be "free", so google sub, news source subs, reddit sub, youtube sub, discord sub, instagram sub, FB sub, app stores are full of paid only apps, podcasts are all paywalled, all the ad supported stuff is subscription supported. Everything would feel like constant nickle and dime'ing you.
On the bright side, there would be no ads, and relatively robust privacy.
Ehh, the internet was worse before Google. Google actually became popular for having a nice blank page with only the search bar. Even the ads they had later were much cleaner compared to yahoo, altavista, lycos, aol and other firms of that time.
I am not rooting for them, I don’t own stock from either just that like GP I was sure by now Google would have eaten others’ lunch. I was expecting a Gemini 4 before Mythos/Fable and Astra just from what GP pointed out: a cash hose, data centers, good engineers. But I underestimated the investment others would keeping absorbing so started to lose confidence in my Google prediction. Let’s see how Gemini 4 holds up. Are we going to see a flurry of scientific and mathematical breakthroughs from it?
Please check Gemini's t and c, as the last time I checked when they had a good pro model (3.1) you couldn't turn off training on your data with a paid account .
Not to mention - they have the internet already indexed (they have a local copy), all books, and youtube. Beyond that, everyone "connects" to Gmail, but google HAS Gmail.
I don't know what to make of it, but from my experience, Gemini in Gmail is the worst AI integration for Gmail, just like Copilot in PowerPoint is the worst AI integration for PowerPoint.
I agree with you there - what I mean however is more about the vast amount of training data available to Google. Productwise - I have a feeling the 100x'rs that made Google Maps (and even Gmail itself) have moved on. They're going to need to do more than just tell an agent to add agentic features to Gmail
Recently there's been a lot of talk about how Google has fallen behind and missed the AI boat. Now today with Gemini 4 they're back in the boat. But give it a few months, people will be counting Google out again. This has been a repeating pattern for at least a couple years now.
The thing is, Google doesn't have to scramble and freak out every time the others do some impressive update, because they have stable income, the other two do not.
Kind of and kind of not. Their main resource of serving ads is getting legitimately eaten away. The route to getting AI to replace those ad dollars isn't clear and the capex to build it out is significant. Google has to manage a variety of assets that are currently lucrative but under threat. Yes they don’t have all their chips in one basket but it isn't clear that helps them in the race… it hasn’t so far.
their stable income is eaten away by the quickly rising income of the labs, they will be out of the race once the labs reach a certain threshold of income, rather sooner than later. Unless many people install Google surveillance anti-gravity thing on their system which I doubt
It wasn't that they were out of the running for a few months, it was a year and a half.
That's too long to be so far behind. This release looks like it puts them back in it but if they don't ship anything again for a year plus it's hard to imagine building on top of them and watching the world go by.
As others note, this is most relevant for us here, Google does not need to chase YC developers and the like. They can move more slowly, they have the size to do that. But it does suggest a lot of dysfunction given they have the world at their fingertips and couldn't seem to ship anything for a year.
Google aren’t back in the boat. They’ve announced that they have seen the boat, intend to swim over to it and will sail not quite as fast or as far as the other boats.
Google should be dominating, but instead all we currently have is a disparate collection of consumer facing apps and a flash model that’s fast, clever and expensive.
Muse and Dots are doing what Google should have brought out last year, with their resources and know-how.
Googles subscription offerings are so confusing, I didn't even know gemini spark was a thing. The Gemini brand means so much now.
Meta was genius in coming up with a new name and offering Muse for free to start. They can upsell you once you see the value. Meanwhile I have 3 existing Google subscriptions to different services and from what I can tell, paying for one of the all in one subscriptions that includes Gemini would cost me a lot more.
They are more focused on incorporating AI into their products, for better or for worse, but they could burn a whole lot of compute to train a model that competes for the #1 spot. Is that worth it to say you’re the (temporary) leader in AI? I doubt it.
I share the same sentiment. I de-Googled myself except for YouTube, but still wouldn't want my Gmail banned.
That's why I've gone to using open models, they are getting there slowly. A bit much of hand-holding but that's fine by me. If a customer of mine decides to use Google's models, I will have them sign a disclaimer that I'm not responsible of them getting insta-banned or similar. I just can't recommend it.
Large existing players are pretty notorious for screwing up their leads and trying to move in many directions at once, or go to hard into the wrong one. Based on Google's huge number of failed products and poor ability to maintain products outside of ads I am not yet sold. They are very good at buying out their competition, but what happens when their competition has enough money not to be bought out?
>
Then why have they been lagging behind OpenAI and Anthropic for most of the last few years, and only briefly been at the frontier?
One possible explanation: because Google is a little bit more frugal and focuses on how to make providing AI models financially feasible - combined with some willingness to burn money so that they don't strongly fall behind on their AI models.
On the other hand, OpenAI and Anthropic at least formerly concentrated on building and providing the best models that they could with concerns about financial feasibility taking a backseat.
Just to be clear: I do have the impression that by now (likely because of pressure from investors) OpenAI and Anthropic take these financial concerns more seriously, but nevertheless Google's vs OpenAI's/Anthropic's "DNAs" concerning on what to focus on differ.
Anthropic is a private company that is losing money hand over fist. Google is a profitable public company that doesn't have that luxury (at the scale Anthropic/OoenAI are losing money)
Google never really has to outpace the competitors (other than to have some relevance) but they have a very large group of business customers using them for business process work in Gmail, Docs, etc.
Clearly they will win when the models are close enough to frontier to be good enough, but are long-term cheap for buy. I.e. they will aim to make it a commodity.
In theory MS has the same opportunity (plus they have GitHub so, you know, dev eco system too) but seem be blowing the strategy.
Anthropic and OpenAI are having to race to the top on ability entirely to keep their name in the media and in front of us all (which costs: hence more recently trying to pivot away from model releases and more into controversy/danger). The main cost is in training and so this strategy is much much more expensive and this will play out either as a huge cost hike or a forced slow down in pace.
I believe essentially Google is betting on that & I think it's probably the right strategy.
> In theory MS has the same opportunity (plus they have GitHub so, you know, dev eco system too) but seem be blowing the strategy.
Yeah, they have Phi but offer it nowhere on CoPilot as far as I know, I can't even register for copilot, which is bizarre. They came out with "MAI" but... nobodys talked about it since, not sure if its even used by anyone? They're as bad as Mark Zuckerberg is about it.
I do appreciate both Microsoft and Google for releasing small models, unlike Anthropic and (not so) OpenAI.
Yes and no. Microsoft is likely looking at open weight models and going oh, this is just as good or better than we could do, without the training costs, and we simply are an inference commodity provider where azure already operates. Count us in.
I'm gonna need you to look at the capex obligations they've undertaken in the last 12 months. They are definitely not being frugal. If they are behind, its not for lack of spending.
I think they've legitimately been fumbling the frontier race, but fortunately with not too much impact to their profits.
See for example the exodus of talent this year, triggered by mismanagement and politics. They still have a lot of talent but they've lost a lot.
Also, competition with Google Cloud for compute resources, less urgency and focus than the competitors, and (strange to say) not as much user LLM behavior data to feed to RL for coding, work, etc.
But I think they will keep catching up and stay relevant for a good class of LLM use cases.
I don't know exactly why the talent left. But this talent couldn't produce a serious frontier model over the past 6 months. Several months after high profile departures, Google appears to have a high quality model again. Maybe the high profile folks were overrated at best, or a hindrance at worst.
> Then why have they been lagging behind OpenAI and Anthropic
Because they're not desperate. Slow and steady wins the race, at this rate all Google has to do is wait for OpenAI and Anthropic to exhaust themselves on aggressive training, then they can casually amble along right past them.
This is basically what people were saying about Microsoft versus Google and other upstarts in the early 2000s.
Slow and steady wins the race. How could they lose to something on the web, when Microsoft owns the web browser itself? Everything runs on Windows and IE. They can just relax and wait for competitors to exhaust themselves, then quickly build their own version. Isn’t that how Netscape lost. Etc.
Now Google is the new Microsoft, just like Microsoft became the new IBM.
> This is basically what people were saying about Microsoft versus Google and other upstarts in the early 2000s.
They would have been right if Google's marquee product was an Office Suite.
Google was the AI company before AI companies were a thing. The comparison with Microsoft and IBM are misplaced because they failed to capture new territory; ML/AI is Google's stomping grounds. The criticism that Google is bad at consumer chatbots is true, but that's not where the real future value lays.
I've never heard or read anyone saying this in the early 2000s. They had publicly stated their contempt of the web earlier, made fools of themselves when they realized their mistake and went all-in on it, and spent the whole decade lagging behind. The closest they had to an online success was Wizzes.
For some of us OpenAI is already the new Google. I prefer chatgpt even when I'm searching for web links. Google Search had already been deteriorating terribly even before the rise of LLMs.
Also because they are Google. Google being Google: unreliable (they could kill a product anytime), too much of a platform risk (all products in a single place, get banned and lose the company), lack of support unless you really pay a big bill (into the 7 figures), among other… things.
Incredible how the idea of Google being such bad choice has become so entrenched that people prefer the offerings of two companies that might not exist anymore in a few years over Google‘s similar offering.
Alphabet isn't just an AI lab, they're an ad company, a search index, a media distribution company, an email provider, office tool provider, a OS developer, a browser developer, a smartphone brand (Pixel), cloud provider, DNS, amongst a plethora of other services and goods.
OpenAI and Anthropic are AI business, if the AI market burst tomorrow, they'd be the first to flounder.
Google just has to keep pace in the AI space, they don't have to lead. Especially since whom is leading changes like two or three times per month non-stop for four or so years now, including small (by US standards) Chinese AI labs with a fraction of the money who keep pushing the tech forward every month while being open for now.
> Then why have they been lagging behind OpenAI and Anthropic for most of the last few years, and only briefly been at the frontier?
Because it's not an existential battle for Google. If OAI or Anthropic disappear from the absolute frontier for ~8 months the news cycle and churn will diminish them to the second rate. Google is processing near 4 quadrillion tokens every month, that's - I'm sure - significantly more than OAI or Anthropic, because Google is interested more so in their flash models and getting these competitive, which they are.
From a business perspective a frontier model does not make much sense anymore if you are not a startup. Neither for Amazon, nor for Google. Their clouds need models that are fast and perform well in their agent frameworks nothing were a frontier model excels at.
Most Google products even use flash lite underneath, so their frontier model is mostly used for distillation.
>
From a business perspective a frontier model does not make much sense anymore if you are not a startup. Neither for Amazon, nor for Google. Their clouds need models that are fast and perform well in their agent frameworks nothing w[h]ere a frontier model excels at.
A good consideration; just one point from my side: as far as I am aware (but I may be wrong), Gemini is not known to perform well in an agentic framework.
This is no contradiction to your other claims, quite the opposite: perhaps (or even likely) Google wants to avoid that their models become a commodity in some (agentic?) application where the middleman who actually writes this application gets a disproportionate of the money that the customer of the application pays for it.
Well at the moment we do not use Gemini in an agentic framework. But as said the flash and flash lite families are basically their driving force in some of their applications in Google cloud, like document ai and its ocr capabilities are probably better when it comes to business documents than any other (at least in perf to cost to speed).
We also drive Gemini lite in our application where customer can use it to generate simple automation, like an agentic framework but way way smaller scale. And while it struggles in more context heavy operations it still is a beast when feeding it one or two pdf documents and asking questions about them and it’s hella fast.
> A good consideration; just one point from my side: as far as I am aware (but I may be wrong), Gemini is not known to perform well in an agentic framework.
I used it for a month over the summer, right before they were going through the migration to antigravity. It was a fine workhorse IMO, no complaints from me.
> From a business perspective a frontier model does not make much sense anymore if you are not a startup. Neither for Amazon, nor for Google. Their clouds need models that are fast and perform well in their agent frameworks nothing were a frontier model excels at
I don't know , if it really finds all kinds of data center optimizations, quantum breakthroughs, helping make their workers smarter and more efficient - stuff an opensource model can't quite do - there's real economic value here no ? perhaps not worth dozens of billions but it could get there really fast.
> Then why have they been lagging behind OpenAI and Anthropic for most of the last few years,
The reverse could also said to be true. Google has models that run with search, producing usable results in well under a second. I suspect the world is consuming far, far more of those Google tokens then the tokens produced by OpenAI or Anthropic.
So why are OpenAI and Anthropic so far behind? They are serving a different market: the one that wants high intelligence / high cost tokens. Google is targeting the low cost end of the market - ie the commodity. That's where they've always played with search, email, docs and the like. That's were they are playing with AI too, and they are killing it.
We have very different opinions of the usability of Google's low-end models in search.
If anything, their search was the gold standard, and placing sometimes-wrong LLM results above them has hurt people's perception of both Google's search, and AI in general.
Google made a mistake in prioritizing speed over accuracy there.
Given the spend requirements to stay on the leading edge and the speed (and with low cost) that others catch up, the economics support a fast follower model unless you get some benefit from being a pioneer. So far nobody has received a permanent benefit from being ahead.
Chinese models are barely behind the leaders. Google can catch up anytime they hit the gas. I think they’re intentionally spending less, and when this crazy race burns out they can play their cards.
I think Google, mainly Demis, just made a bad bet that multimodal world models would be the key to unlocking massive progress. Anthropic made the bet that it would be coding, and they were right. OpenAI was originally betting on like hardware and trying to compete in the browser space (?) but was able to quickly pivot to coding due to their size. Google, on the other hand, is like an aircraft carrier, it takes a lot of time to course-correct.
That's one interpretation, but I think people are simply having amnesia of the past 2 years.
The better interpretation is Google completely commoditized and killed ChatGPT's initial chat product. If you think about it, Google right now has Gemini Flash running on single TPU instances at massive scale serving almost every android device. I use it every day and it's more capable than GPT-40.
This literally forced Anthropic and OpenAI to come up with new use cases and revenue streams such that now we think the product is actually agentic coding.
I use Gemini Flash every single day without paying a dime. It's the one LLM call on the most, but GPT-6 and Opus are the ones I use the most tokens on.
They havent. OpenAI and Antropic are now integrating with a plethora of apps, google has it from the get-go. Also, it may be important to point out that the transformer model (aka the hole llm thing) is a google initiative; Id assume they are not competing in the qualification series of AI (which is lets build a generic ai and get customers), but in the finals - they already have the customer base and the lock-in, they don't need to scale - just to cater. Cerebras and Google are probably the best safe bets in AI right now, and google does gave the tradition of being way ahead of the curve internally vs what is published.
Before 2025 yes. Currently not. YouTube implemented severe restrictions to scraping and downloading of videos. You can get away with maybe 5 videos, after that you enter a tar pit.
If you continue, you need to log in.
If you continue, the account is blocked in less than 30 minutes.
If you try to use cloud machines you are blocked before the first video. If you try to use known proxies, there are already tar pitted or blocked because everyone is trying.
I downloaded about a thousand videos (300gb) from YouTube this past week without logging in.
I used two IP addresses in a datacenter. Both were blocked after a few hundred videos, but the block expired after a day or so. It is not as hard as you make it sound.
Just make it too expensive. Wanna buy one internet link per hour to download videos. Or maybe rotate between source IPs (google will block the whole ASN ip block in less than an hour). Or maybe pay people to download videos for you? They can download maybe 20 in a day, for a week, because tarpit and blocks.
Google stands to lose enormous revenue from people not using search - and we already see traffic declines. It's truly an existential threat for them. Their competencies are in advertising, and if people are going to be using chatbots in future, they're going to have to advertise in their chatbot. That sounds awful to me, but maybe people will be cool with it?
Those are competitive advantages but a "moat" usually refers to being on top of the hill and able to keep anyone else from climbing. I think it's arguable whether Google is on top of the hill at all, and if they are they're sharing it with at least two other companies.
I don't think that other revenue stream is completely separate. It weighs on them as they need to think about tradeoffs. Classical search is going away sooner or later so they need to replace that with AI powered search.
Data centers are important but a few others also has them: Amazon, Microsoft, Meta. SpaceX will likely be in/at the top I AI dedicated precessing power in 2027 as well.
I don't see the moat. I see a company with a lot of other commitments that is not the best at delivering consumer facing products. They have some good cards but so do others.
Alphabet also has nearly infinite money to pour into this endeavor from their advertising enterprise, so much so that AI/LLMs could all fall apart and they would be happy to go back to selling mid-roll campaigns on youtube videos.
And yet, their models are often behind and the team is bleeding talent. A moat is not a compendium of intimidating features, it’s a matter of whether a company deters competitors and maintains a competitive advantage. So far, Google obviously does not have one here.
Amazing. Can they now go hire some really good information architects and designers and come up with a cohesive user experience please. They have the right to win here and if they can give me something that feels like Codex / Claude desktop I am sold.
Google wins.They have been on the frontier of ai for the last what 10-20 years (up until chatgpt)? You have the established company with tons of traininv resources at tgeir disposal from all their services and being the biggest search indexer, and also having the top minds in AI and computing in general.
Gemini wins and I said this since the beginning. Google wins in general. I never understood why they have not been the highest market cap companh for the last 10 years. And I despise google but its obvious.
Wait 1-2 months, Anthropic will come up with a shinier model and Googel will look obsolete again. I too struggle to see the moat - yes Google is able to serve their own A.I traffic but as far as I can see - at a loss. Prices keep going down because open source models.
We'll see.
> Wait 1-2 months, Anthropic will come up with a shinier model and Googel will look obsolete again. I too struggle to see the moat - yes Google is able to serve their own A.I traffic but as far as I can see - at a loss. Prices keep going down because open source models. We'll see.
Google makes AI profits, its in their breakdowns. And Google has been releasing models every few weeks now, they have a faster iteration pace than the competitors, so they fixed that, they wont be behind in coding models any longer.
> Google makes AI profits, its in their breakdowns.
What "AI profits" exactly. Their capex is through the roof. What they're actually earning is in cloud , their own AI is lossy for sure. Who is paying for Gemini? Not many people.
