61–70 of 88 posts
1833: first known case of "lose money on every sale but make it up on volume." Amazing. Birth of postmodern capitalism right there. https://barrypopik.com/blog/we_lose_money_on_every_sale_but_...
It was a joke back then, not a real business model
The subsidy is blatantly obvious when you compare the cost of self-hosting versus subscription, and the subscription is dramatically dramatically cheaper. The difference between Blue Apron and many AI tools is that the value add does exist. You can cut meal prep from your life, but by 2030, cutting whatever agentic code copilot exists by that point will be like cutting off your fingers for many workers and businesses…
In 2024 OpenAI generated some $3.5B in revenue and still lost like $5B. It means they spent something like $8.5B to run this thing [1]. They would have lost less money if they had been selling dollars at 50 cents. [1] https://www.cnbc.com/2024/09/27/openai-sees-5-billion-loss-t...
The bet is that the cost for delivering the same results will go down, through hardware or software advancements. This bet still seems reasonable based on how things have gone so far. Providers right now are willing to burn money acquiring a customer base, it's like really really expensive marketing.
The bet is that costs will go down enough so that ad-supported AI will become profitable. This is not a positive outcome, a large part of the article is about the evils of ad-supported.
I am somewhat baffled at the economic models of LLMs right now. Ever since MS decided to gift me a copilot on my desktop that appears to have no limits and is entirely servicable for a range of tasks I'm failing to immediately see the monetisation. I feel like even trying to game the LLM into creating product placement is a relatively complex feat that might not be entirely reliable. Some of the groups who spend the…
Monetization will come with agents that take action on your behalf (reorder dinner, find and buy a gift for your niece, make dinner reservations). Bots will take a cut of every transaction, and intake ads to steer recommendations.
I seriously doubt the vast majority of people would trust actual purchases to LLM agents that have the inherent feature of being possibly very inaccurate. If I have to review my orders, I would rather do those actions myself than having the extra step of having agents do it on my behalf.
Earlier quoted context omitted.
> the models I do use remain static and predictable Some people overload "local" a bit to mean you are hosting the model - whether it's on your computer, on your rack, or on your hetzner instance etc. But I think parent is referring to the open/static aspect of the models. If it's hosted by a generic model provider that is serving many users in parallel to reduce the end cost to the user, it's also theoretically a st…
I am bewildered to hear the sense of "local," in which I and engineers in my experience have for thirty years referred to things which are not remotely hosted, referred to as an "overload."
Anyone else here tried the same thing? Results?
So what exactly is the "AI lifestyle subsidy"? The article doesn't seem entirely clear on it seeing as the last line essentially asks this same question. Some friends and I have been taking advantage of cheap GPU time from a company trying to break into that space, and of course lots of AI tools are being sold below cost but is that really it? Compare "GPU time is cheaper" to the classical "$10 steaks delivered direc…
>So what exactly is the "AI lifestyle subsidy" The world's richest subsiding the real cost of offering AI services with the current state of our technology. Once it's clear the AGI won't come anytime in 20X, where X is under 40, money tap will begin to close
Honestly, I think that's quite generous. And I only phrase it that way, rather than more like "that X should be 99" because trying to predict more than about 15 years out in tech, especially when it comes to breakthroughs, is a fool's errand.
But that's what it's going to take to reach AGI: a genuine unforeseeable breakthrough that lets us do new things with machine learning/AI that we fundamentally couldn't do before. Just feeding LLMs more and more stuff won't get them there—and they're already way into the diminishing-returns territory.
Even if unintentional, pushing of products is already happening. If you ask any AI for a tech stack to create a web app you'll get recommendations for Vercel, AWS and co. This is going to be the new SEO
But yes it will be abused for advertisement as well.
I'm running an experiment--just cancelled my ChatGPT subscription and I'm going back to doing things the Hard Way. Which for me is Kagi. I want to see if there are noticeable effects and tradeoffs. Anyone else here tried the same thing? Results?
We all know search is broken, so not sure how a couple more tools on top of the same results are supposed to fix all woes.
I’ve found much more utility in researching models.