Just you switching away from Google is already justifying 1T infrastructure spend.
Just think about how much more effective advertisements are going to be when LLMs start to tell you what to buy based on which advertiser gave the most money to the company.
> Just think about how much more effective advertisements are going to be when LLMs start to tell you what to buy based on which advertiser gave the most money to the company.
Optimistic view: maybe product quality becomes an actually good metric again as the LLM will care about giving good products.
Has a tech company ever taken 10s or 100s of billions of dollars from investors and not tried to a optimize revenue at the expense of users? Maybe it's happened but I literally can't think of a single one.
Given that the people and companies funding the current AI hype so heavily overlap with the same people who created the current crop of unpleasant money printing machines I have zero faith this time will be different.
I think it might be like when Grok was programmed to talk about white genocide and to support Musk's views. It always shoehorned that stuff in but when you asked about it it readily explained that it seemed like disinformation and openly admitted that Musk had a history of using his business to exert political sway.
It's maybe not really "caring" but they are harder to cajole than just "advertise this for us."
For now anyways. There’s a lot of effort being placed into putting up guardrails to make the model respond based on instructions and not deviate. I remember the crazy agents.md files that came out from I believe Anthropic with repeated instructions on how to respond. Clearly it’s a pain point they want to fix.
Once that is resolved then guiding the model to only recommend or mention specific brands will flow right in.
large language models don't "care" about anything, but the humans operating openai definitely care a lot about you making them affiliate marketing money
Google search won’t exist in the medium term. Why use a list of static links you have to look through manually if you can just ask AI what the answer is? Ai
tools like chatgpt are what Google wanted search to be in the first place.
ChatGPT will have access to a tool that uses real-time bidding to determine what product it should instruct the LLM to shill. It's the same shit as Google but with an LLM which people want to use more than Google.
> Just think about how much more effective advertisements are going to be when LLMs start to tell you what to buy based on which advertiser gave the most money to the company.
But can we really say that advertisements are more effective today?
From what little I know about SEO it seems nowadays high intent keywords are more important than ever. LLMs might not do any better than Google because without the intent to purchase pushing ads are just going to rack up impression costs.
It's not reasonable to claim inference is profitable when they've also never released those numbers. Also the price they charge for inference is not indicative of the price they're paying to provide inference. Also, at least in openAI's case, they are getting a fantastic deal on compute from Microsoft, so even if the price they charge is reflective of the price they pay, it's still not reflective of a market rate.
OpenAI hasn't released their training cost numbers but DeepSeek has, and there's dozens of companies offering inference hosting of open weight models for the very large models that keep up with OpenAI and Anthropic, so we can see what market rates are shaking out to be for companies that have even less economies of scale. You can also make some extrapolations from AWS Bedrock pricing and can also investigate inference costs yourself on local hardware. Then look at quality measures of quantizations that hosting providers do and you get a feel for what hosting providers are doing to manage costs.
We can't pinpoint the exact dollar amount OpenAI categorically spends but we can make a lot of reasonable and safe guesses, and all signs points to inference hosting being a profitable venture by itself, with training profitability being less certain or being a pursuit of a winner-takes-all strategy.
Sam has claimed that they are profitable on inference. Maybe he is lying but I don't think speaking so absolutely about them losing money on that is something you can throw around so matter of fact. They lose money because they dump an enormous amount of money on R&D.
> when LLMs start to tell you what to buy based on which advertiser gave the most money to the company.
isn't that quite difficult to do consistently? I'd imagine it would be relatively easy to take the same LLM and get it to shit talk the product whose owners had paid the AI corp to shill. That doesn't seem particularly ideal.
I mean I think Ads will be about as effective as they are now. People need to actually buy more and if you fill LLMs with ad generation well the results of results will just get shitty the same way googles search results had. Its not a Trillion dollar return + 20% like you'd want out of that investment
Just think about how much more effective advertisements are going to be when LLMs start to tell you what to buy based on which advertiser gave the most money to the company.