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The LLM usage will generate hundreds of billions of dollars in ad revenue, which will be wildly lucrative in terms of margins (not as good as Google search used to be). If GPT is a leader in that, they'll take a sizable share of that pot.

There's a lot more money in being Google -> consumer ads, or Amazon -> consumer ads, or Meta -> consumer ads, than there is in being Anthropic -> enterprise.

Just take a look at the enterprise. Amazon's ad business alone is already a better business than Oracle or SAP or Salesforce, with superior margins, and it's growing faster too.

And of course everybody knows the Google & Meta ad monsters.

The only question remaining is who is going to extract all those LLM ad dollars, how will that break out. Right now it's Gemini and GPT in the obvious lead, with Anthropic in third, and Meta & Grok nowhere to be found (permanent situation for those).

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>The LLM usage will generate hundreds of billions of dollars in ad revenue, which will be wildly lucrative in terms of margins (not as good as Google search used to be).

This seems like ... not the situation we are in. LLMs are great for coding now but their text generation capabilities aren't exactly capturing the masses or replacing their jobs yet. People are already tired of the deluge of fake content on the internet, it's not going to drive a second revolution in web ads.

The $20-200 LLM plans are all subsidized and aren't paying for themselves. Something has to give here.

LLM usage will largely replace traditional search, and that's stage one. To be specific, search will be consumed by the LLMs, it'll be merely an aspect of what they do for the user, and that'll include handling the more intricate details of the search, refining the search, understanding the results of search, etc. The age of the typical user handling any of that is about to end. Search will more be a feature of Gemini in the not very distant future, rather than Gemini being bolted onto/into search.

Fuller integration into the user's life will bring ever more ad opportunities (and it doesn't matter if the HN base hates that notion, it's going to happen regardless). That'll happen over the next decade gradually.

Shopping, home management, tasks (taxes, accounting, lifestyle, reminders, homework, work work, 800 other things), travel (obvious), advice & general conversation (already there), search (being consumed now), gaming (next 3-5 years to start), full at-work integration (gradual spread across all industries, with more narrow expertise), digital world building (10-15+ years out for mass user adoption). And on the list goes. It's pretty much anything the user can or does touch in life.

> To be specific, search will be consumed by the LLMs, it'll be merely an aspect of what they do for the user, and that'll include handling the more intricate details of the search, refining the search, understanding the results of search, etc. The age of the typical user handling any of that is about to end.

We already have the tech for that, why hasn't it happened? People are revolted by the AI results in Google. AI isn't going to make people use their computers more. It's not opening up a new consumer market. This is just making each search infinitely more expensive.

Who is revolted? I use the AI Google results every day when asking for specific questions, I rarely visit the webpages before anymore. Also Google already injects ads into conversations in the form of Google Shopping affiliate links.

>I rarely visit the webpages before anymore.

And what do you think this'll do for future LLM models that need to train on new content if web page traffic collapses?

I understand the concern but it's frankly not my problem as a user, that is for the authors and corporations to figure out. No one would (or should) blame car buyers for putting horse and buggies out of business, they're merely participating in the market as a consumer not the producer.

They won't figure it out. It's the tragedy of the commons.

Then that is how it will be, it's a self correcting problem in that if they don't figure it out, their models won't continue improving.

And web sites will collapse along with them. What do you think the 'corrected' state will look like? If you use the web it is your problem.

More people going into insular communities like discord or creating micro sites. Like I said it's a self correcting problem, either it is fixed or it's not. It's not my problem.

I find searching chatgpt.com and asking for sources, then visiting them, works much better than Google to find niche topics

Every year I ask the latest version of Chat GPT a basic facts question about rugby results. It almost always gets it wrong - even when it does web search and cites sources. Wrong scores, hallucinated matches, wrong locations - just gob smacking amounts of wrongness.

The latest "Thinking" version gets it reliably right but spent about 3 minutes coming up with the answer that 10 seconds of googling answers.

So I don't believe we are currently in a situation where LLMs are an effective replacement for search engines.

yep google ai results are old too.

Google is already dumping LLMs into search and it works well and is free.

It doesn't work well. The searches are wrong and uninformative much of the time.

Any examples of bad ones? I find them perfectly fine for my queries.

Search for anything mechanically car related and the results are terrible or wrong.

Do you have a concrete example I can reproduce? I searched for things like how to change the filter of X make and model and it seems correct, not sure if that's what you meant.

I'm not the person you replied to but I'm wondering which Google AI product you are referring to that you use for search which is so excellent that you need someone to find for you an example of it failing?

I think Google has several ai products with search features?

Which one in your experience "seems correct"?

I'm fascinated because I've never found any LLM to be particularly error free at search.

Google.com with the AI overview or whatever they call it now. It seems to source web page information for grounding so it's reasonably correct and doesn't hallucinate recently at least.

I played around with it and its better than it used to be but if you ask it something like

"Whats the name of the third book in the peripheral trilogy going to be" it just regurgitates some dumb reddit comment by someone who seems to be making things up.

There's no actual title that has been announced and the reddit post was not a reasonable bit of speculation.

The problem with these LLMs is they rarely say "the search results were not credible no response can be provided."

These days, Google AI overviews regularly add a qualifier to the effect of "... according to this comment on Reddit <link>"

That's basically a UX trick to entirely sidestep being held accountable for the results, but seems sufficient to notify the user about the provenance of the answer to adjust their grains of salt.

It works very poorly

You see it already with how many people use LLMs for everything these days. Google Gemini can also integrate with your other Google apps to personalize further, and Gemini already has product placement ads.

> The $20-200 LLM plans are all subsidized and aren't paying for themselves. Something has to give here.

Whats interesting to me as well as much as companies are pushing AI adoption, i have started to hear AI token spend limits enforced across a few companies, so its not entirely clear that b2b can make them profitable yet either.

If all the models reach good enough, then low cost provider would win. Gemini seems like a safer bet since Google controls more of the stack / has more efficiencies / cross selling / etc.

It’s not like “best” has won any other b2b arms race in the past.

In large part because most companies have a set budget for IT spend. Thats how “normal” profitable companies operate outside this cash burning bonanza that’s going on.

And in that reality one can’t just magically spend a bunch more on some fancy new thing, especially when said fancy new thing isn’t retuning value. So “token limits” and cost controls on B2B is entirely expected here.

> especially when said fancy new thing isn’t retuning value

I think this is the key element. Either they can't measure the value, or it's far far lower than anyone wants to believe, or both.

I think the problem is less that it makes some coding tasks XX% faster, but that the end to end of a SWEs roles tasks is only improved by some much smaller Y%.

If a CTO sets $10k/year spend limits on $500k SWEs.. they must not believe any of the hype.

The problem is that AGI fantasy aside, CTOs at companies are expected to deliver results today and tomorrow. Better to let somebody else hold the bag and train models, then once it finally works as advertised you can ease on the brakes.

>If all the models reach good enough, then low cost provider would win. Gemini seems like a safer bet since Google controls more of the stack / has more efficiencies / cross selling / etc.

Gemini is the best deal too. For $20: you get multiple quotas per day across the products (web, CLI, antigravity, AI Studio) 2tb of cloud storage, and you can family share the plan.

I don't know Gemini's pricing model in detail, but in general pricing doesn't generalize well between personal/hobbyist and enterprise use. Consumer pricing of variable costs is a balancing act, and most Gemini users aren't going to be anywhere near the quota; a company of 1000 can't always buy for $20,000 what 1000 random users with $20 personal plans are theoretically capped at.

Ultimately though in the long run.. They invented the tech, have a large cashflow generating business subsidizing R&D as well as sales, with network effect of existing B2B relationships.

Further they have their own TPUs, datacenters, etc on which to run their models.

Plus existing data they've squirreled away over the preceding 30 years from books, web, etc.

Just seems like a lot of efficiencies if its going to come down to cost.

> The $20-200 LLM plans are all subsidized and aren't paying for themselves. Something has to give here.

Expert systems were amazing. They were not cost effective.

There might be another bitter lesson to be had here, and unless the accountants start talking we're not gonna know any time soon.

Google launched in 1998 and were running ads by 2000. Considering how much more access to adtech product talent there is for OAI a quarter of a century on, what explains their hesitation to pick that route and make billions? After all they had billions avaiable to acquire designer bauble maker Jony Ive's company.

The first AI company to cram their product full of ads will get roasted over the coals for it. My guess is they're all playing chicken and waiting to be the second to do it. I'd also guess that they're all already thinking about ways to introduce it that will generate the least backlash.

Google could do it in 2000 because their search was legitimately so much better, and also because their ads were comparatively more relevant and unobtrusive than modern ads. In comparison, LLMs are relatively similar in performance unless you're picky enough that you're probably already paying and thus wouldn't be in the ad-supported tier.

That said, I wonder if ads are even lucrative enough to move the needle relative to how much training costs are increasing with each generation.

People forget it took Google years of frog-boiling to get us to where we are now.

The first AI to insert blatant ads will be dumped for some other model overnight. Look at the Copilot "backlash" over their "product announcements".

Yep. Finally someone who knows how to think straight.

Google built up immense surplus and ate into it slowly.

OAI can't suddenly start cramming Ads as it fights to survive. Im sure they are employing questionable tactics to keep users hooked. Won't really work on a large enough user base to make the economics viable given the competition they face.

“The LLM usage will generate hundreds of billions of dollars in ad revenue”

And yet every attempt to extract even minimal ad revenue has been canned to date as something nobody wants with AI providers retreating in failure.

I don’t doubt that there’s “some” ad revenue to be had but there’s little evidence that ads are going to save the day here.

These exact words were said tens of thousands of times about Facebook (am old enough to remember those discussions :) ), “no way they can monetize on mobile” (this was the most fun).

rules are simple, if you have Xbn or XXXm users on your system, you will make big bank in ads eventually

At that time, Facebook provided a free service without any real competitors. The masses will switch to Meta AI or Gemini or Claude at the drop of an ad that annoys them enough.

Gemini, GPT and Claude will all have ads on the consumer side. They will go together in quasi lock-step into the ad future, because that money is gigantic and they're going to need it.

The masses will have no say in the matter. Just as they had no say in the matter with Google's ads getting ever more intrusive, or cable prices previously, or streaming prices going perpetually higher in the present, or YouTube ads, or anything else. Consumers will have no say in the matter, they'll take it and that's that.

With only three relevant competitors (maybe Mistral in Europe), there will be nowhere to flee the deployment of ads.

amazing this is even a debate, we have now decades of this across everything that reaches enough users, it is a certainty as much that the Sun will rise tomorrow morning. as probably many people here on HN I am designated computer-fixer for all my family so any family gathering I have to look at someone's computer about something. years ago I started checking whether browser(s) anything ad-blocking in place and I am 0 for million by now. while HN crowd might be theoretically pushing back on ads (even with like "I won't use this if there are ads" nonsense) general public is so used to ads that I sometimes feel it is welcomed change when some new service etc gets ads. I remember the first time I saw an ad on Amazon Prime Video and my daughter and I were like "no f'ing way!!!" and my wife was like "oh, ____ is on sale this weekend, cool!" :)

It's tempting to look at trends and assume there must be a rule behind them, but it's also intellectually lazy. Please do the hard work of justifying your stance like GGP did.

it is a simple stance - if you have a product that is used by hundreds of millions of people ad monetization strategy will be found cause there are people a lot smarter than you and me that will get it done. here’s intellectual challenge - find a business with comparable number of users to openai which is not swimming in ad revenue - one will do

Snapchat

Total Quarterly Revenue (Q4 2024): $1.55 billion in total revenue, with $1.41 billion coming from advertising

Basically all their revenue is ad revenue and not too bad

A counterpoint is that there are many products with significant usage that fail or never attempt advertising monetization. They just increase the cost of the product.

Such as?

I apologize, but I thought it was self-evident. The majority of enterprise professional software.

I would argue that comparing OpenAI to social media companies is an awful comparison. A much better comparison would be to Microsoft Office.

I thought we were talking about search or social media companies failing to capitalize on advertising which I haven't seen. OpenAI is much closer to Google than it is to Office.

I could see that argument, but the economics of the two are so different. I just don't see how using an LLM can be sustainable for search, but could see it as an enterprise model.

For several early years search was thought to have no great business model (banner ads and similar). And then it did.

GoTo.com -> Google -> $$$

It will not be lucrative if the hundreds of billions of dollars in ad revenue cost the providers trillions in compute. That's still the big question.

I think this is the right question. My search/chat is now 50% ChatGPT, 30% Google, and 20% Gemini. I have no idea the business implications of this.

For that matter, I don't know the bandwidth and compute cycle tradeoffs between traditional search and AI.

> Just take a look at the enterprise. Amazon's ad business alone is already a better business than Oracle or SAP or Salesforce, with superior margins, and it's growing faster too.

You can say the same about AWS and then prove the b2b case instead of ad case as well

AWS is legitimately a giant and it should be considered in enterprise broadly. It's infrastructure more than enterprise software of course, which is where Anthropic is at. Anthropic is not trying to host the world's databases and services (at present anyway). Anthropic will however help you write software to compete with Salesforce, Oracle, SAP, et al.

Google's ad business remains far larger and more profitable than AWS. And the advertising segment is drastically larger than the segment AWS is in. Just Google + Meta = nearing $600 billion in ad sales. Amazon will soon have their own $100 billion in ad sales.

I guess the question is how many more $100B of ad sales slots are available, aside from just stealing share from incumbents (who already took it from traditional media channels over last 20 years).

At some point someone needs to add value to the real economy, not just take an ad tax off the top.

I don't think advertising is entirely a zero-sum game (there is real value to everyone for steveBK123 to learn of a product that actually solves a real need or saves money, etc) - but it has to be something akin to it - the economy can't support five hundred trillion dollars in advertising spend.

Not interested in a service with ads throughout my workday, which is why I switched to Anthropic.

Billions in projected revenue is nothing but hype/cope. Google and Meta got their edge because their product was offered for "free" to the masses.

absolutely not the case. there isn’t a single nerve in human brains that goes “oh imma tolerate ads cause this shit’s free but if I pay a few bucks no way” - if the product you use has utility to you, you will tolerate ads provided no other acceptable alternative. not to tell you something you don’t already know but anthropic is getting ads, eventually, it is a given. so while today you may have an alternative (arguably better even if no ads in the equation) at some point you won’t have an alternative (other than running local) and you’ll tolerate ads. the thing with LLM ads is that companies can make $$$$ from “ads” you don’t see, i.e. I can (not now but in the future) companies to push my product, e.g. claude is setting up architecture and proposes upstash (which I own and am paying anthropic a lot of money) instead of any competitor. or even more silently adding dependencies on my NPM library which has free and commercial offering…

Yeah sure, but for me the common man OpenAI doesn't add any value that Claude, Gemini or Meta AI doesn't also provide.

If they want to out-ad those companies to the tune of billions, I'll go with the least annoying. OpenAI hasn't earned any loyalty.

to me and you sure, but what do you reckon how many of their MAU are just people for whom “AI” is ChaptGPT? 90+%?

Anthropic is already an ad - for Anthropic. The uniquely "friendly" personality of their user-facing AI chatbot is far from accidental.

hm not sure I follow - the anthropic is selling itself to users that are already using it by being friendly to the users?

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