[bluescrn]

Did anyone really expect AI to be cheap?

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.

[hansmayer]

> Did anyone really expect AI to be cheap?

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?

[rwyinuse]

"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."

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.

[2ndorderthought]

Right now China is flexing the future in my opinion. Smaller, widely available, frontier models for pennies on the dollar.

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.

[flir]

I do. "Commoditize your complement". Want to sell lots of silicon? Give away good local models to run on that silicon.

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).

[bluescrn]

> I think models are going to be local-first.

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.

[vanviegen]

> In the long term, I think models are going to be local-first.

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.

[solid_fuel]

Local first models aren't just more private than the API vendors, they also have the advantages of fixed cost, lower latency, and better stability - local models don't get nerfed/"updated" in the background like chatgpt does.

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.

[still_grokking]

> the only real advantage for local models (privacy/secrecy) hasn't proven convincing for broader IT either

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.

[2ndorderthought]

It's foolish not to care about privacy especially as a company. You know how it prevents you from emailing yourself your tax documents? Meanwhile thousands of employees are sending literal design docs, software, product goals, etc to several ai third partys. Not only is that insane, the companies they are sending it too intend too and openly admit to scanning the data, make software products themselves, and intend to create models that can produce their products automatically.

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.

[LtWorf]

To not depend on an external company that can decide the price.

[Dylan16807]

That's a silly reason. For non-agent use cases what kind of utilization are you going to average on your own GPU, 5-10%? And that's without batching.

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.

[LtWorf]

I think you are calculating with current prices. Try to extrapolate the price in one year, seeing the current trends instead.

[Dylan16807]

The models I could reasonably run at home aren't experiencing big price hikes, as far as I'm aware.

Price is a reason to escape many proprietary models, but not so much a reason to self host. Buying an expensive GPU mostly for AI purposes is not likely to save money unless you load it all day long.

[vanviegen]

Extrapolating current trends, I expect API prices to drop significantly for a given measure of 'intelligence'.

[soraisdead]

> Did anyone really expect AI to be cheap?

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.