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.
Going from 5.5 Instant (which was noticeably bad) to 5.6 Luna is a big jump as well. OpenAI is probably the most prominent among the general public - an advantage in some respects but they're giving away a lot of free inference and thus have to use a pretty small model to do it.
I really don't see how they're going to be google here. The free tier is dominated by verticle integration and the platform that people use. Long term I imagine google wins the bottom of the market and I'd be suprised if they lost.
> People tell these models everything. You don't think a pretty unethical company can figure out a way to monetize that?
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 guarantee you're a lot easier to manipulate than you think.
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.
Even a long while ago it was estimated that every Google search cost google several cents (and that they made back 10 cents). Google also uses AI for search results. Thus its not inconceivable that openai can make money here.
I typed wrong I mean I don't see how they will beat google. Google is the only true vertically integrated AI company meaning they own price at the bottom margins with their own chips and models made just for them.
Google's public AI model lineup is pretty bad right now. Gemini 3.1 Pro is scoring worse than some mid-sized Chinese models at 1/20th the cost, and their Flash and Flash Light models are horrendously overpriced on task benchmarks compared to GPT 5.6 Luna or the mid-sized Chinese models.
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!
That doesn’t matter very much for the free tier market though. The game is to have something useable that is actually used, and that can be offered at sustainable margins. Google has significant advantages in those regards.
Ads work when you can server $.01 worth of ads to a user for $.0001 of server cost. I fail to see how you can make it work when doing LLM inference which is significantly costlier than web search.
I don't know where you get that from, but it's pretty easy to prove it wrong: with their daily active users count, OpenAI and Anthropic would have been profitable for years if that was true. Instead they are bleeding cash like no others and are still trying to secure another round of funding 4 years after becoming among the most heavily used apps in existence.
Whatever you think about Altman and Amodei, they aren't clueless idiots and if ads was all they needed they would have done that from the beginning.
>with their daily active users count, OpenAI and Anthropic would have been profitable for years if that was true.
No they wouldn't have. Low cost isn't no cost, R$D is expensive and there are a class of tokenmaxxing users well outside the median (e.g Agentic Coding).
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.
>OpenAI isn't profitable even if you discount R&D entirely.
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.
>Is refuted by the sentence that comes immediately before
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.
Google has multiple massive cost advantages over OAI: TPUs, free access to massively valuable data (search index, gmail, maps reviews/PO/ navigation, youtube, android etc.), lower talent costs, lower training costs, lower distribution costs (they can shove AI down our throats in so many different places), lower ad infrastructure costs (it will be a lot of work for OAI to recreate adwords), lower ad sales costs (OAI deploying an ad sales team will be a massive investment).
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.
Yes, Google has massive advantages, but I was shocked to realize that their infra advantage is not that massive when we found out they were paying SpaceX about a billion a month for compute, along with enough CapEx spend to turn their free cash flow negative, which inevitably hit their stock price.
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 are right to question that. I am basing that statement off of the many famous engineers that have recently left and were very highly paid. My guess is Google is ceding the frontier and the high salaries that go with it and letting Anthropic/OpenAI fight over the high priced talent that exit. The remaining non-famous engineers will not be able to command celebrity salaries. But this is just speculation and I don't have great evidence that the celebrity salaries are enough to meaningfully reduce overall talent costs.
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.
Agreed. One effect I had in mind was much simpler: if you are the cool new company, people will want to work for you and might even take a hit in salary to do so.
People still want to go to websites, but it is a rapidly plummetting number. Multiple souces are already reporting a sharp drop from referral traffic from Google search, largely because people just stop at the AI overviews. To the extent that some major sites (including Reddit, which has a content licensing deal with Google already!!) are considering blocking Google crawlers:
90+% of queries are probably so common/evergreen that, if a cheaper model made all the different language varients and ways of asking the question into one query, they could be cached quite effectively.
> 90+% of queries are probably so common/evergreen that, if a cheaper model made all the different language vari[a]nts and ways of asking the question into one query, they could be cached quite effectively.
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.
Sure, but you don't represent the average ChatGPT free user in that case probably. I regularly do super complicated queries that Pro spends ages replying to, but yesterday I also asked if chilis are toxic, or just unpleasant, for dogs, and if other species other than flamingos get colored by the food they eat.
OpenAI can very plausibly target ads far better than Google can.
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.
> 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.
When I look at my history with AI chatbots, 90 % of the conversations revolve around research-level problems in math and computer science. :-D
Yeah I can easily imagine the “AI for work” version never being ad supported and gradually capturing more of the value created. Thats a very different usage pattern.
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.
I recently saw some discussion about the CPC for personal injury lawyers being ~$200 on Google ads. Seems insane to me, but I’m totally disconnected from the advertising world. That said, depending on the conversion rates between chats and clicks, the math could be favorable for OAI.
More like LLMs are near commodity at the common tier the ones who wins are those who can inference the cheapest and google is easily thr best positioned to do that with many years of custom chip model optimization.
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.
I'm not sure people fully comprehend the trickle-down pop-culture/zeitgeist effects that LLM's are having/are going to have on humanity.
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.
Is that really accurate though? I use Claude in my software job but the majority of my friends do not use it at all. And I never use it for anything other than that either.
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.
We're all in our own personal bubbles and extrapolating from there as normal, but ChatGPT has some 800 million users, most of them outside the US. Countries like the Philippines and Thailand. I don't think they're all vibecoding the hottest new SaaS app but maybe they are.
Even the Philippines and Thailand are lower in per-capita usage compared to the US, most of the higher use are in Europe. Interestingly Australia & New Zealand are also pretty high, similar to Europe and far more than Asia & Africa in general, with the exception being Saudi Arabia (similar to US) and Israel (even higher than Australia). https://openai.com/signals/data
+1 to this. Many of my engineer friends don’t use AI even in cases where it could clearly help them. Not out of any principles stance but because they just don’t understand that it could speed up their work. It doesn’t help that the advertising surrounding AI hasn’t communicated its benefits well - either you’ve tried it and you get it or you just don’t know. I would imagine some early horseback riders in the 20th century probably felt similarly about the automobile.
Yes. Go to chat.com in an incognito window and ask it the same question that you ask 5.6-sol with thinking max, and compare. Depending on the question there is or is not a huge difference.
Also, remember the bulk of AI users are using free models, getting terrible answers, and wondering why people keep saying AI is going to take everybody's jobs away.
There was already thinking in free model though. They removed the option a while ago and made it automatic... But you could force by just saying "think hard" or whatever.
