Everything else is optimizing the targetting data in some kind of behavioral way to get better intent data or to reach the right users.
I have no idea where something like Chatgpt stands on that axis, it has actually very little attention (in hours per day) for most people and I am not sure that it has enough intent signals.
Lots of potential to game the results there. If that is enough to sustain the business is another question.
I'm having trouble seeing the difference. They both capitalise on attention, i.e. eyeballs. And they both try to predict what you're likely to click on so they can show you the most-relevant ads.
When you use Facebook you get ads for things you are looking for in a broad sense, they just happen to figure out what you are looking for via fingerprinting and spying on all your web and app activity (to the maximum extent allowed by platforms and regulators).
Google, of course, also does this in addition to looking at your currently active web search.
Google looks at both your current search/browse activity and gathered data (the gathered data being especially important for all the very many Google-served Ads off of google.com)
Facebook also looks at your current search/browse activity and gathered data.
The only real difference is Facebook search is universally entirely worthless so far less of that signal gets used relative to more passive snooping.
Emarketer’s data finds that standalone chatbots like ChatGPT,
Microsoft Copilot app, Google AI Mode, and Amazon Alexa for
Shopping (formerly Rufus) in U.S, will generate less than $1
billion in ad revenue this year, and just $5.41 billion by 2030.
Just because there are no ads now does not mean there never will be. Google search was run without ads for the first years too.
When you used google 10x a day, you saw, at a minimum, 20 ads/day. How many ads are you seeing when you babble all day long with a chatbot?
There is also way more competition between chatbots than there was between search engines after Google started leaning into ads. Which strengthens the Khan-Esayas hypothesisis "that data privacy constitutes a key parameter of non-price competition in the market for" consumer tech [1][2].
[1] https://yalelawjournal.org/pdf/e.710.Khan.805_zuvfyyeh.pdf
[2] https://www.researchgate.net/publication/327111419_Privacy_a...
You wouldn't see any of them, because you'd not be aware of the invisible bidding war over which products the bot recommends.
That's assuming a user with no ad-blocker which is an ever diminishing number of users
Google serves ads on search, maps, YouTube, android apps, amd all websites using Adsense or video ads
So its not really much to do with the technology or how good it is, but the stories their salespeople can tell. And I guess the story isnt good/convincing enough
From search or from adsense? That's very different. People place adsense banners on their websites which has nothing to do with search.
If GPT can maintain or grow usage, the ad dollars will be there given the enormous scale. There is a hundred billion dollars plus worth of advertising waiting in the LLM space. It would be surprising if Facebook doesn't contract for example, losing ground to LLMs on advertising over the coming decade.
Also it’s basically free for Google to show you a sponsored result but embedding one in a ChatGPT response actually costs money (assuming they’re part of the generated response).
Lastly I will bet you one Stargate datacenter that Meta has thought about LLM-based advertising, and if there’s any low hanging fruit there it’s already been tried
It depends on the economics and usefulness of the tool. Google Search got away with it because it was useful AND trading zero cost of usage for ads was worth it for most.
Whether LLMs can get away with it seems very unclear now as they don't seem as popular as search engines.
Google got away with filling their products with ads because "data privacy constitutes a key parameter of non-price competition" and Google had a monopoly when they started loading up on ads.
If OpenAI were the only AI game in town, they'd be running ads.
[1] https://www.researchgate.net/publication/327111419_Privacy_a...
Anecdotal evidence that I observe is that people stopped using google and only ask LLMs nowadays for their everyday queries.
They somehow need to corner many billions of business meanwhile chinese labs reckon they'll have fable class models by end of the year. [0]
That does not leave a lot of room for mistakes. I reckon they'll get government to block chinese models just like the US car industry did with EVs.
https://www.tomshardware.com/tech-industry/artificial-intell...
This is more or less already the case. Not that they're blocked, but... it may limit who you can work with and what insurance companies will cover you.
Look at Zuckerberg. He may have been good as a founder, but if he didn't have super voting shares, and if Meta's cash flow from their ad business wouldn't mask how poor his strategic decision making has been, he would have been pushed out as CEO years ago.
The only actual product was "Loopt", some bs location sharing app that nobody used or ever heard about.
tldr is: They either get a successful IPO to stave off bankruptcy for a couple more months, or they're going to be bankrupt by the beginning of next year.
That said, $2T was spent during GWOT with another $8T in veteran care, DHS, interest in debt.
Current AI spend this year is expected to be $2.59T (chips, infra, etc)
...that's not how bankruptcy happens. What is this guy's background?
Assets on a balance sheet are held at book value. You can absolutely run GAAP losses that exceed net assets without running into bankruptcy, particularly if you're granting (and having employees exercise) options.
The critical measures are cash in and out and debt-like obligations. None of those metrics point to OpenAI going bankrupt this year unless they do something really fucking creative. (Which, to be clear, is Altman's M.O.)
If we assume a 2026 revenue of 23B (Q1 2026 revenue x4) and costs of 70B (2025 costs * (2026 revenue / 2025 revenue)), even those 25B in cash reserves won't mean much. And this napkin math even ignores their debt obligations. So either they raise money in the range of 50-75B this year (actual money, not datacenter vouchers), or ...
[0] https://www.wheresyoured.at/exclusive-openai-financials/
If all those costs are cash costs, sure. When OpenAI gets non-cash investment, and it "burns" that investment on compute, that should be counted as a GAAP expense. Yet it doesn't touch cash. (It would destroy a unit of compute asset. But again, book versus market value can mess with how that works intuitively.)
Similarly, if you're granting lots and lots of options they're going to generate lots and lots of compensation expenses (and thus losses) as they vest. These aren't cash expenses, however.
Not to mention that being "on pace" is usually a term that means "keeping pace with".
An endless forest of mirrors reflecting no one but the user.
“An analyst thinks OpenAI may miss its 2030 ad revenue target by 90%” is what the article says.
I'm not surprised the iteration we're seeing now is perceived as failing: on the few remaining screens where ads are still present for me, they're between highly irrelevant to flat out repulsive. There are a few brands I will never touch with a long stick, purely as a result of their disturbing, disgusting ads -- again, charitably, a negative-sum game.