https://www.reuters.com/business/media-telecom/openai-plans-...

Apparently they've declared a code red, because competition has got so hot. They're definitely going to do ads, but they may have to put it off. They can't afford ads at the moment ironically.

https://www.theinformation.com/articles/openai-ceo-declares-...

Pre-revenue gets weird when you're in the cuatro commas club.

"If you show revenue, people will ask 'HOW MUCH?' and it will never be enough. The company that was the 100xer, the 1000xer is suddenly the 2x dog. But if you have NO revenue, you can say you're pre-revenue! You're a potential pure play... It's not about how much you earn, it's about how much you're worth. And who is worth the most? Companies that lose money!"

I’m not advocating for it! But it’s real.

I agree that is what he is doing, but I can also justify adding fentanyl to every drug sold in the world as "making it better" from a business perspective, because it is addictive. Anyone who ignores the moral or ethical angle on decisions, I cannot take seriously. It's like saying that Maximizing Shareholder Value is always the right thing to do. No, it isn't. So don't say stupid shit like that, be a human being and use your brain and capacity to look at things and analyze "is this good for human society?".

To an MBA type, addictive drugs are the best products. They reveal people's latent preferences for being desperately poor and dependent. They see a grandma pouring her life savings into a gambling app and think "How can I get in on this?"

And he's right (and the sources he points out), that some bubbles are good. They end up being a way to pull in a large amount of capital to build out something completely new, but still unsure where the future will lead.

A speculative example could be AI ends up failing and crashing out, but not until we build out huge DCs and power generation that is used on the next valuable idea that wouldn't be possible w/o the DCs and power generation already existing.

I _kind of_ understand this one. You can think of a bubble as a market exploring a bunch of different possibilities, a lot of which may not work out. But the ones that do work out, they may go on to be foundational. Sort of like startups: you bet that most of them will fail, but that's okay, you're making bets!

The difference of course is that when a startup goes out of business, it's fine (from my perspective) because it was probably all VC money anyway and so it doesn't cause much damage, whereas the entire economy bubble popping causes a lot of damage.

I don't know that he's arguing that they are good, but rather that _some_ kinds of bubbles can have a lot of positive effects.

Maybe he's doing the same thing here, I don't know. I see the words "advertising would make X Product better" and I stop reading. Perhaps I am blindly following my own ideology here :shrug:.

I’d argue that AI apis are nearly trivial to switch… the prompts can largely stay the same, and function calling pretty similar

I see where you coming from, but that only tells half of the story.

I've been sporting the same model of Ecco shoes since high school. 10+ models over the years. And every new model is significantly worse than the previous one. The one I have right now is most definitely the last one I bought.

If you would put them right next to the ones I had in high school you'd say they are a cheap, temu knock offs. And this applies to pretty much everything we touch right now. From home appliance to cars.

Some 15 years ago H&M was a forefront of whats called "fast fashion". The idea was that you could buy new clothes for a fraction of the price at the cost of quality. Makes sense on paper - if you're a fashion junkie and you want a new outlook every season you don't care about quality.

The problem is I still have some of their clothes I bought 10 years ago and their quality trumps premium brands now.

People like to talk about lightbulb conspiracy, but we fell victims to VC capital reality where short term gains trumps everything else.

I became even better off when I installed an ad blocker.

That's obviously not true. It significantly favor those with more money.

"unquestionably"? Given that vast majority of ads are for harmful self-destructive projects or misleading or lying or make place where they got spammed worse... Sometimes multiple at once.

Spam alone (also advertisement) is quite annoying and destructive.

People aren’t collectively paying him between $3 million a year and five million (estimated 40k+ subscribers paying a minimum of $120 a year) just because he doesn’t have ads.

I realized that ads within context were going to be an issue a while ago so to combat this i started building my own solution for this which spiraled in to a local based agentic system with a different bigger goal then the simple original... Anyways, the issue you are describing is not that difficult to overcome. You simply set a local llm model layer before the cloud based providers. Everything goes in and out through this "firewall". The local layer hears the humans requests, sends it to the cloud based api model, receives the ad tainted reply, processes the reply scrubbing the ad content and replies to the user with the clean information. I've tested exactly this interaction and it works just fine. i think these types of systems will be the future of "ad block" . As people start using agentic systems more and more in their daily lives it will become crucial that they pipe all of the inputs and outputs through a local layer that has that humans best interests in mind. That's why my personal project expanded in to a local agentic orchestrator layer instead of a simple "firewall". i think agentic systems using other agentic systems are the future.

> But if "ads" are woven into the responses in a manner that could be more or less subtle

do you realize how much product placement have been in movies since...well, the existence of movies?

Why? It turns out that I try to read people who have a different perspective than I do. Why am I trying to read everything that just confirms my current biases?

(Unless those writings are looking to dehumanize or strip people of rights or inflame hate - I'm not talking about propaganda or hate speech here.)

You realize this “dumb blogspot” is written by the most successful writer in the industry as far as revenue from a paid newsletter? He has had every major tech CEO on his podcast and he is credited for being the inspiration for Substack.

The Substack founders unofficially marketed it early on as “Stratechery for independent authors”.

Your analysis concerning the technology instead of focusing on the business is about like Rob Malda not understanding the success of the “no wireless, less space than the Nomad lame”.

Even if you just read this article, he never argued that Google didn’t have the best technology, he was saying just the opposite. Nvidia is in good shape precisely because everyone who is not Google is now going to have to spend more on Nvidia to keep up.

He has said that AI may turn out to be a “sustaining innovation” first coined by Clay Christenson and that the big winners may be Google, Meta, Microsoft and Amazon because they can leverage their pre-existing businesses and infrastructure.

Even Apple might be better off since they are reportedly going to just throw a billion at Google for its model.

> spew out their nonsense theories

Discussing "innovator's dilemma" unironically is a fullstop for me.

It's likely they already make money on affiliates, but this is different, ads are product placement.

ChatGPT has recently been linking me directly to Amazon or other stores to buy what I'm researching.

Sure, but affiliate != ads. Rather, both affiliate links and paid ad slots are by definition not neutral and thus bias your results, no matter what anyone claims.

better product = inflicting more suffering while generating more revenue

Outside of experience and experimentation, is there a good way to know what models are strong for what tasks?

Non developers using Chatbots and being willing to pay is never going to be as big as the enterprise market or BigTech using AI in the background.

I would think that Gemini (the model) will add profit to Google way before OpenAI ever becomes profitable as they leverage it within their business.

Why would I pay for openrouter.ai and add another dependency? If I’m just using Amazon Bedrock hosted models, I can just use the AWS SDK and change the request format slightly based on the model family and abstract that into my library.

All google needs to do is bite the bullet on the cost and flip core search to AI and immediately dominate the user count. They can start by focusing first on questions that get asked in Google search. Boom

How is the number of users a moat when you are losing money on every user?

You need a way to test model changes regardless as models in the same family change. Is it really a heavier lift to test different model families than it is to test going from GPT 3.5 to GPT 5 or even as you modify your prompts?

For the most part, I don’t do chatbots except for a couple of RAG based chatbots. It’s more behind the scenes stuff like image understanding, categorization, nuanced sentiment analsys, semantic alignment, etc.

I’ve created a framework that lets me test the quality in automated way between prompt changes and models and I compare costs/speed/quality.

The only thing that requires humans to judge the qualify out of all those are RAG results.

checkout https://poe.com - it does the same thing. I agree with your assessment though, while you can get better answers from some models than others, being able to predict in advance which model will give you the better answer is hard to predict.

As the OP points out, Google is now selling TPUs to at least some corporate customers.

And it is “fair” that a company can gain market share while losing billions backed by VC funding?

Author isn't non-financial, but the "moat 2.0" doesn't feel right.

> More than anything, though, I believe in the market power and defensibility of 800 million users, which is why I think ChatGPT still has a meaningful moat.

It's 800M weekly active users according to ChatGPT. I keep hearing that once you segment paid and unpaid, daily ChatGPT users fall off dramatically (<10% for paid and far less for unpaid).

I would say that customer diversity may be a marker of past resilience, and likely results in moat.

Customer diversity says nothing about current or future resilience.

1. Seems to forget its context about 20/80 of results now. It used to be decent but now I may make only two prompts and it forgets the previous one noticeably more.

2. Results are noticeably worse, much more prone to "cheating" outcomes like generating some logic then = true to all results so it always finishes regardless of conditions.