Even in my non-SWE job, paying $100/mo for my current $20/mo plan would still be a no-brainer.
I don't think there is much concern about open models either. Compute is constrained for the foreseeable future, and money is what will determine who gets it. Nevermind that the US will likely block Chinese model imports or China will block exports at some point. The cold war has already begun here.
Most people shouldn't open their mouths / write anything re. valuation TBH.
Just look at software over the last 20 years. People pay based on the value they receive, not the cost the produce or serve it. That fact is literally is the backbone of tech, and why it has been an absolute money machine.
I think the worst case scenario for the labs is current (or next gen) SoTA models reaching a point where cheap consumer hardware can fully run them. But the labs practically have a monopsony on compute, and getting the kind of long context current models thrive on out of 16GB GDDR6 is gonna be a trick.
Another bozo who read a intro microeconomics textbook, learned a fancy word, and doesn't know how to apply it! LOL.
Wow you people on here are really funny.
The average American family won’t be willing to pay more than a Netflix subscription.
I think in five years, it will only be power users that use a model in its raw form - everyone else will mostly consume using wrapper apps.
We still have 2billion+ people offline. Looking at global population is the wrong reference frame for selling a $100/mo service.
I think more realistically we'll have something like the Google/social media US-vs-world profit split of 40-50% US vs rest of world combined. Even those numbers can work out but then I don't see tremendous growth.
But the sector valuation is already priced for wholesale workforce replacement or massively expanded productivity and AI platform providers taking a lot of that pie for themselves.
With corporate profits already near all-time highs with respect to GDP, who is going to buy all those new products (from expanded productivity ) if all the gains only go to OIA and Anthropic employees?
It's an interesting time.
At the investment scales being discussed, CUDA/architecture and other advantages do not matter - you could spend 1 billion on building a new chip architecture. The ram/fab inputs have been a commodity market for years. Heck, even the model bottleneck doesn't seem real when it's only 1-4 billion or less to get a state of the art model.
At some point the compute bottleneck will be relieved, you can see NVidia hedging their strategy with both open models and on-device chips targeted for local inference. The 200 dollar a month plan will absolutely be taken over by local hardware in the future.
There is competition everywhere, and it is intensifying and catching up, not fading away. Open weight models are becoming more common, both within the US as well as elsewhere. Treasury secretary Scott Bessent just praised Meta's open weight models.
There is demand for AI at all different price points, and as all models at all price points become more capable, it seems that increasingly developers are seeing the most expensive ones as specialized tools, not daily drivers.
Compute/memory may be constrained for a few years until production capacity catches up, but this does not mean that demand for cheaper and open weight models will go away, else it would already be happening. Anthropic would like to sell an expensive Ferrari to everyone on the planet, but 99.99% of those people have no need for anything more than a Yugo.
DeepSeek recently said that their super-low pricing let's them recoup the cost of the hardware it runs on in 10 months, so there is evidentially plenty of profit to be had over a projected 3+ year lifespan of a "GPU".
Some in the AI industry, or breathing the same air (Dwarkesh) project that limited GPUs will only be used to serve the most expensive models with the highest profit margins, but it is just not what we are seeing. If the only LLMs available were ones at Opus/Fable price points then the GPU scarcity would disappear since the demand at that price is just not there. It's remarkably like trying to fill all the seats on a plane - you can fill a few at 1st class prices, but most of the plane better be coach if you want to sell all the seats.
For a GPU, "selling all the seats", keeping it busy 24x7, is critical to profitability since the primary cost to serving is the GPU which has a limited lifespan.
There is a clear trend of popularity and price.
For example, here we have Fable 5 at $3.14/task vs Kimi K3 at $0.84/task, with very little difference between them in coding capability (and this isn't even a coding/agentic fine tune of Kimi).
https://artificialanalysis.ai/models
We now have models like Qwen 3.8 27B, small enough to run locally, with coding capability similar to Opus 4.5 based on challenging tasks like the Anthropic Kernel challenge.
I think we are rapidly getting to the "good enough" stage of LLMs, just like we did long ago with PCs. A cheap PC/LLM is all you need for 99.9% of normal use cases. Maybe nothing can touch whatever latest greatest models Anthropic and OpenAI have when it comes to solving Erdos problems, but most developers are working on problems more like the Anthropic Kernel challenge in complexity (or in fact typically way simpler ones).
A large portion of the US construction capacity is now engaged in building data centers, priorities you know. Who knows what else will be a favorite tomorrow but it's unlikely to be properly built housing.
I don't know where the 5% of world population came from, because that's clearly not just professionals or people making a lot of money. That's Uber drivers, and retirees in the developed world or tech workers in Asia making <$10000/year. Those don't look like great markets. This needs to be 2x higher value than their cell phone and internet that they might spend $300/year on today (that's a new iPhone every 3 years on an ATT plan). It's not like it can replace their plan, because they need that connectivity to use it!
Who's getting this value other than SWEs? There aren't 40 million SWEs and I don't see them spending over $6000/year. If their business does, it still has to pass on the cost to consumers and/or fire SWEs.
Are there 100 of them? That would be 2 billion customers.
I think current investment to date is ~$1tn and revenues are ~$100bn so you'd only need the growth to keep up a short while longer for the current lot to pan out.
Why on earth do data centres need to be built from cashflow???
There's a reason why a company like Stripe can stay private far longer than Anthropic or OpenAI can.
These AI companies have taken in all the capital from private investors and are still losing hundreds of billions and have no choice but to hype up the IPO and dump some of the stock at a purposefully inflated valuation to retail investors.