Giving free ChatGPT users access to reasoning (the 'Think' toggle) will have a broader impact on the world than every new paid model and coding agent combined.
I assume research-level questions about scientific topics (with a focus on math and computer science) are not easy to monetize (yes, this is by far the most common kind of question to AI models for me). :-D
I can imagine some hypothetical scenarios, but I do believe that I have strong evidence that this is mostly not the case.
For example, I think I have already told the story how when I worked together with a person who is a business consultant (and thus salesman) told me that C-level executives are an incredibly easy sales target compared to me. For him, selling something to me was "ultra-hard mode", basically because I could immediately see through every sales tactic that he tried on me.
As I wrote in some parallel post:
"When I look at my history with AI chatbots, 90 % of the conversations revolve around research-level problems in math and computer science. :-D"
For quite a few of them, creating a decent answer involved quite a bit of thinking by the AI, so I assume they are not the easiest queries to answer, and the queries are too obscure to cache.
The median LLM query isn't significantly costlier than web search.
Whatever you think about Altman and Amodei, they aren't clueless idiots and if ads was all they needed they would have done that from the beginning.
No they wouldn't have. Low cost isn't no cost, R$D is expensive and there are a class of tokenmaxxing users well outside the median (e.g Agentic Coding).
> I don't know where you get that from
https://cloud.google.com/blog/products/infrastructure/measur...
https://epoch.ai/gradient-updates/how-much-energy-does-chatg...
I'm not talking about R&D.
> there are a class of tokenmaxxing users well outside the median (e.g Agentic Coding).
It wasn't a thing before last year and OpenAI wasn't making profit before that either.
> https://cloud.google.com/blog/products/infrastructure/measur...
> https://epoch.ai/gradient-updates/how-much-energy-does-chatg...
None of these support your claim.
Again, when you're here saying that the CEOs of the two biggest AI companies are basically idiots, nobody will take you seriously.
You said OpenAI and Anthropic would be profitable if the median query was as cheap as I say. I'm telling they wouldn't be because inference isn't the only cost these companies shoulder. R&D/Training is a very big part of costs. That you didn't mention it is irrelevant. R&D is the lion's share of costs - https://news.ycombinator.com/item?id=48550465
>None of these support your claim.
Yeah they do lol. Both those articles place the median query cost around the same as a Google search.
>Again, when you're here saying that the CEOs of the two biggest AI companies are basically idiots, nobody will take you seriously.
That's not what I'm saying and I don't see what's so hard to understand here.
> Research and Development: $19.18 billion. Loss from Operations: $20.92 billion
OpenAI isn't profitable even if you discount R&D entirely. Google search on the other hand has had ridiculous margin from the beginning, allowing the company to be highly profitable while financing significant R&D investment. These two businesses models are as different as it can be.
If ads were the solutions for profitability these companies would have used ads as their source of income from the very beginning.
They have a billion weekly active users, almost all free (Not Google search free. Free free) with about ~50M subscriptions. Of course they're not profitable even without R&D. Low cost isn't no cost. Take away the huge R&D and they become hugely profitable with a robust ad business like Google Search.
>If ads were the solutions for profitability these companies would have used ads as their source of income from the very beginning.
You've said this a couple times and it doesn't make any more sense the more you say it.
Just admit you're wrong about inference costs and move on.
> Take away the huge R&D and they become hugely profitable with a robust ad business like Google Search.
Is refuted by the sentence that comes immediately before :
> They have a billion weekly active users, almost all free (Not Google search free. Free free) with about ~50M subscriptions. Of course they're not profitable even without R&D. Low cost isn't no cost.
Please explain why have OpenAI been actively not trying to “hugely profitable with a robust ads business” for the past 3 and a half year then? Or at least make a profit that can cover some of there R&D expenses, instead of losing money from their operations?
> Just admit you're wrong about inference costs and move on.
Unfortunately I'm not. And again, none of your links above says otherwise.
No. "They're unprofitable while serving almost everyone for free" does not refute "they could be profitable if those users were monetized with ads." That's the entire distinction.
>why have OpenAI been actively not trying to “hugely profitable with a robust ads business” for the past 3 and a half year then?
Because "they didn't do it early enough" is not evidence. They may have prioritized growth, product adoption, subscriptions, or simply delayed ads for strategic reasons.
>Unfortunately I'm not. And again, none of your links above says otherwise.
They show that "LLM inference which is significantly costlier than web search." is unsupported. Imagine dismissing numbers over "but why no ads earlier".
Prioritizing growth? When OpenAI had saturated the market by year one and has only been losing market share for the past 18 months! Again that's basically assuming Sam Altman is a complex idiot. No board in existence will let you move away from the most obvious business model in the Silicon Valley if this model was the obvious solution you think it is.
> They show that "LLM inference which is significantly costlier than web search." is unsupported
It's not unsupported, the price per million token of frontier model is public, as well as the cost of running open source models, which gives us a rough idea of how much those frontier models cost to run, and it's significantly higher than what it costs to run a web search.
> Imagine dismissing numbers
But you're just making those “numbers” up: there's simply no cost numbers at all in these papers. They are just about energy, and you jump from there forgetting that consuming a kWh of electricity on a server from 19 years ago is substantially cheaper in capex than doing so on a H100, let alone doing so on newer hardware.
To expand: it seems inevitable that Google's SERP format will be replaced with a conversational / chatbot / agentic interface, which equalizes the playing field for all chatbot providers.
This is because you can stuff in much fewer ads into a chat interface compared to SERPs. (They could try stuffing more ads but that would likely just push users more to the competition who have a much lower baseline on which to show growth.) As such, Google would be forced to progressively nullify its own invincible firehose of ad revenue as they deprecate SERPs in favor of AI overviews.
There's no way OAI has a long term advantage over google in replacing the search engine experience.
Google's one major weakness is it will face the innovator's dilemma as their core search revenue gets cannibalized. But they seem to have been able to get their entire org to recognize that AI is an existential threat so at least that's a good sign.
A counter point would be OAI and Anthropic can pay with more equity that they can promise will go to the moon. But all the equity base compensation eventually dilutes earnings per share so it's not free once you go public and people start caring about that.
Then notice how many of the advantages you enumerated are directly related to their ad business. But the ad business itself is under threat. I just cannot see how they can stuff as many ads in an agentic interface as their SERPs. E.g. what's the net outcome of shoving AI everywhere if it's not going to be monetized nearly as well as their ads?
My point is, Google has finetuned their ad business and surrounding ecosystem to an extreme level to sustain this absolute firehose of cash (including antitrust and rig-bidding shenanigans they were literally found guilty of) but almost all of that is disrupted by the shift to chat interfaces.
I think Google will do extremely well as an AI chatbot / agent and cloud AI provider, but it will not be nearly as lucrative as the ad business they have to cannibalize to get there.
You’re painting a dichotomy that doesn’t exist and hasn’t for a good while.
Edit: I missed your final paragraph. I still disagree with this argument though, people still want to go to websites.
https://www.niemanlab.org/2026/07/search-traffic-has-decline...
https://www.techspot.com/news/113199-reddit-major-publishers...
Email is a good window but lots of people talk in more depth with a chat bot.
Search is a good “purchase intent moment” but people are telling a chat bot exactly what they care about in a purchase, rather than making indirect search terms and reading review sites.
> Search is a good “purchase intent moment” but people are telling a chat bot exactly what they care about in a purchase, rather than making indirect search terms and reading review sites.
When I look at my history with AI chatbots, 90 % of the conversations revolve around research-level problems in math and computer science. :-D
But 90% (99%?) of user sessions don’t require a huge amount of reasoning tokens or output; keep in mind LLMs are replacing search for single-turn answers.
Google is going to be able to push cost down further and for longer than anyone else. They also rightfully believe this is a company ending gamble if they fail they could be a second tier player for decades.
So better inference margins, far better operation experience serving cheap AI at massive scale, a massive warchest, and the fear of complete company irrelevence.
That's going to be one hell of a company to beat for free tier LLMs. Also chatgpt is impressive but it's notthing like google search quite yet. On top of that AI labs must use google's product for their AI.
They also own more data by an exponential margin. Anything but dominance of free AI on google's side would mean they are just so incompetent they deserve to fail.
There's no reason why Google's public stuff is this stale, overpriced and underwhelming. But at least until their next round of models drops, even calling them a "frontier lab" is starting to feel like a stretch. Which is weird!
Especially considering that in the 2010s they were The Big AI company, especially after buying out boutique shops like DeepMind.
Because everyone now outsources much of their thinking and researching to LLM's, our collective culture + brain is shaped in a cyclical manner by using them.
It's the mechanical homogenization of culture and groupthink.
TBH I don’t find it useful at all for personal use. It’s totally soulless for creative ventures and absolute dogshit at researching the things I want it to be good at (I.e. planning a vacation or finding new music).
All that combined with the social stigma makes me feel pretty skeptical that it’s some kind of pop culture shaping mechanism, at least not for a few more years.
That would explain a lot of the terrible AI/LLM takes online.
They took away the button a few months ago and are now putting it back.
Perhaps I should have said "proper access".
This could be the Opus 4.5 moment for normal humans.