There's going to be a limit to how much they can raise prices, because someone can always build out a datacenter and fill it up with open source DeepSeek inference and undercut your prices by 10x while still making a very good ROI--and that's a business model right there. Right now I'm sure there's a lot of people who will protest that they couldn't do their jobs with lesser models, but as time goes on that will get less and less. Already right now the consumers who are using AI for writing presentations, cooking recipe generation and ELI5 answers for common things, aren't going to be missing much from a lesser model. That'll actually only start to get cheaper over time.
Also for business needs, as AI inference costs escalate there comes a point where businesses rediscover human intelligence again, and start hiring/training people to do more work to use lesser models--if that is more productive in the end than shelling out large amounts of cash for inference on the latest models. [Although given how much companies waste on AWS, there's a lot of tolerance for overspending in corporations...]
Not sure how it all works out. Currently trillion dollar companies can't make a native app for platforms. Everything is just JS/Electron because economics does not work for them.
And here companies can make GW data center running very expensive GPUs for 1/10th of current prices. Sound little fanciful to me.
Now, I have this high-resolution shiny object that can near instantaneously get any information I want along with _streaming HD video to it_ *anywhere*.
15 years even feels like a stone age. I can't fathom what it has to feel like people in their 60s and 70s.
That's very close to a normal day in 1996. The biggest difference is I read the news on my phone instead of a physical newspaper. The news was not any more interesting or informative because of that. I guess I can also still do the loop reasonably well, but I'm a lot slower than I was in 1996 when I was a cross-country state champion.
My parents are closing in on 70 and I guess I can't speak for them, but I'm at least aware of the daily routines of their lives, too. Walk the dog, do housework, DIY building projects, visit kids and grankids. Seems much the same, too, with the biggest difference being they're now teaching my sister's sons to play baseball rather than me, but shit, one of her sons even looks like exactly the same way I looked when I was 7! The more things change, the more they stay the same.
But - now they are easier - I can read books on an e-ink screen and pretty much instantly find what I want to read next. I get my news on a phone. I used to watch TV/movies broadcast or on tape rentals. Now, I have just about everything I could ever want available - without ADs... those were such a time-waster.
What has changed is that I have access to MORE information than my local (or school) libraries could ever provide - in a variety of more accessible formats. Whatever tools I need to get "work done", I can find a myriad of free and open-source options.
But - the overall days and household family routines are the same - now, instead of reading a paper book while waiting to pickup my kids (or other family members) "back-in-the-day", I can read my device, or connect with my DIY communities online on my phone - or learn something new. I don't have to schedule life around major broadcast events, I can easily do many tasks while I am "out-and-about".
Friction has been reduced.
I am just over 50 myself and I agree with your points. Technology has changed but life is largely very similar to wear it was in the 90s. At least day to day. Attitudes are way worse now.
I always wonder the views of older people. My parents are very technology forward and have been my entire life so it is difficult to gauge how different life is compared to when they were growing up.
It's easy to hear "Oh well I only had 640kb of memory and typed programs out of a magazine I got in the mail!" and see as distinct from having 'unlimited' resources and the internet.
Your insight is good ("The biggest difference is I read the news on my phone instead of a physical newspaper") that life sort of stays the same but the modality changes. People still go to the store like they did in the mid-1800s but now it is by car.
I wonder what our "industrial revolution" will be where the previous generation lived (ie: out in the country on a farm) totally different lives to the current (ie: in the city in a factory). Maybe when space travel and multi-planetary living is normalized?
Since I was there (young, but there), I want to point out that this crosses three eras which all felt quite different:
1978: typed programs in from a magazine or loaded from a cassette (16kB, TRS-80)
1983: loaded programs from a floppy (64kB, Apple ][ and C64 etc)
1988: loaded programs from a hard disk (640kB, IBM PC and Mac).
Housework meant no laundry machine, no dishwasher, and possibly no vacuum cleaner. That means hand washing everything, and beating rugs with sticks and brushes to get the dust off of them.
I look at the life my kids live, and it's not so different to my childhood. The toys are similar, their housing is similar. Probably the biggest difference is the availability of content on demand rather than much more fixed TV schedules.
The big difference in the last 30 years hasn't so much been in the kind of middle class life you can live, but the number of people who live that kind of life. In the 90s 40% of people globally were living in extreme poverty. Now its under 10%. The kinds of lives the middle class live in China and Vietnam are closer to those of Europeans today, when even 30 years ago most people in those countries were living much closer to the way your dad grew up.
I wonder if AI will result in a step change of living standards? Perhaps along with robotics we'll finally get to do nothing at all at home? I'm not convinced it'll be quick though. Maybe another 30 years.
And at some point even frontier model costs will hopefully come down (if there is still a meaningful difference between closed and open source models at that point) as all of the compute that's being built out right now comes online.
It has been years now, of cash injections, investors can't keep feeding the beast forever.
That would be, even is, the smart thing to do.
In other words.
The bubble has burst. You're just in denial.
Deepseek API pricing is very low compared to Anthropic/OpenAI API pricing.
For many, the 300% difference in pricing may be difficult to justify, if the quality difference is very small. And there will be many tasks where the most expensive/the best model, is not needed. Currently many people end up using Opus 4.7/GPT 5.5 for many tasks without thinking about it.
I am not shilling China, this is just what is happening right now.
I think the Chinese government works differently than the US government. I think China has been subsidizing their electricity grid for decades and leading the world on sustainable electricity namely solar. While the us has let their infrastructure rot and laughed at government inefficiencies for about half that time. The US has data centers running on gas right now while waging wars blowing up gas infrastructure world wide. It would be comical if it wasn't an environmental disaster. Most of them have no hopes at even getting enough power in well established areas short term.
I realize what I am saying may come off as propaganda because the US holds net negative views on China so here are some links.
https://www.technologyreview.com/2025/07/10/1119941/china-en...
https://www.wired.com/story/data-centers-are-driving-a-us-ga...
I think because openai spent so much money upfront showing how it was possible to do this and laid out a product roadmap China got to get on board much cheaper and easier. I see no reason to not believe any of these companies when they say they didn't squander tons of money to do what they did because I don't know how openai has even spent all the money they have it's actually ridiculous to think about.
https://the-decoder.com/openai-adds-111-billion-to-its-cash-...
Unlike the us chinas focus is on research and sustainable building. China also has really good infrastructure for energy, etc. it is also to their advantage to drop 5 billion instead of 2 trillion and beat the us while turning a profit.
Chinas focus in ai is less flashy and because they are the biggest manufacturing super power in the world right now, it directly feeds their economy. They aren't looking for applications or to replace thought workers with slop bots, they have natural needs for this technology. Us manufacturers can't compete so they have to keep companies from selling their goods there see byd. China sees it as commoditizing their complement, the us is risking its entire economy and it's environment and resources, kind of scary.
If/when it gets to the point where it can replace a skilled worker, the service can be sold for close to the same price as that skilled labour. But the AI can run 24/7, reliably, and scale up/down at a moments notice.
There's not going to be much competition to drive prices down, the barriers to entry are already huge. There'll likely to be one clear winner, becoming a near-monopoly, or maybe we'll get a duopoly at best.
Yes, a lot of people (not me). Why? Well because that was the whole value proposition of these companies, relentlessly pushed by their PR and most of the media- rememmber it was something something Pocket PhDs, massive unemployment etc?
Based on what exactly? So far every time OpenAI, Anthropic or whatever has released a new top performing model, competitors have caught up quickly. Open source models have greatly improved as well.
I expect AI to be just like cloud computing in general - AWS, Azure, GCP being the main providers, with dozens of smaller competitors offering similar services as well.
I think the future of ai will be breakthroughs that let it run on commodity hardware, and the average person will not be paying for it from the cloud unless they want to be surveilled or are stuck on older hardware.
Right now I am running about what was a frontier model 1-2 years ago on a junk machine. Some people are running what was a frontier model 4 months ago on PCs and laptops that cost 5,000. In a year I think the landscape will be even better.
Even if SOTA models in the cloud are a few percentage points better, most work can be routed to local models most of the time. That leaves the cloud providers fighting over the most computationally intensive tasks. In the long term, I think models are going to be local-first.
(Unless providers can figure out a network effect that local models can't replicate).
Why on earth would that happen when everything else is moving into the cloud to tie it to ever-escalating subscription fees and prevent piracy?
Even with gaming, where running high-end 3D games in the cloud seems like madness and inevitably degrades the quality of the experience, they won't stop trying.
Why? There's an inherent efficiency advantage to scale, while the only real advantage for local models (privacy/secrecy) hasn't proven convincing for broader IT either.
The reason local models hasn't caught on is several fold. It's marketing to say your company follows the latest trend, and there's an inherent pressure to keep AI companies afloat so the economy doesn't entirely collapse. The other is, it wasn't until the last month that these models have caught up to frontier models. They just did, and they are more efficient and don't require a team of 500 to deploy.
Maybe in a world where these AI companies behaved with some semblance of ethics and user-friendliness they would be on even ground, but for anyone paying attention local models are obviously the future.
Because of nonexistent regulation. Just wait for it…
The legal situation in for example the EU is crystal clear, only that it will take some time to go though all court instances.
Even with overhead and scaling for peak use and a large profit margin, any company with an ounce of competition will be vastly cheaper than self-hosting. And for models you can run yourself, there will be plenty of competition.
Considering most of the cost of producing a model is the upfront cost rather than the running one, I kinda still do.
The point was never to produce 4 frontier models per company a year.