Live data from Hacker News

AI subscriptions are a ticking time bomb for enterprise

thestateofbrand.com

161–170 of 426 posts

Re: AI subscriptions are a ticking time bomb for enterprise

#161
post #79

Every AI subscription is a ticking time bomb for the frontier provider; within a few years we will be running local models as good as today’s frontier models with almost no cost burden. The floor will fall out of the enterprise market for all the frontier companies.

The economics of local AI just doesn’t make sense. A model like Opus is - supposedly - something like 5T parameters, which is likely something like 3TB of GPU memory. Local models never reach the % utilization that cloud providers have (80%+), and they’re always going to be much better than local models for this reason.

Running local applications is less efficient than thin clients to the cloud generally, not just in LLMs. The trick is that you can get to the point where it's effective enough, and affordable enough, that the control and availability factors become dominant.

Re: AI subscriptions are a ticking time bomb for enterprise

#162
post #50

Even if they are momentarily losing money it’s important to note the value add they are providing. If you increase the price, the value is still astronomical in comparison. Companies need to find a way to leverage local models in tandem with frontier models to offset the costs. It’s all about targeting specific workloads with the appropriate AI. These tools are not sentient beings they are tools that need to be prope…

You could use "git clone" or Wikipedia for free. If you mean the value of propagandizing gullible people, yes, there is "value".

Search costs aren’t trivial and, prior to LLMs, being able to find the piece of information on Wikipedia or software on GitHub that solved your problem took time, a lot of time if you weren’t an expert and unfamiliar with the jargon.

Re: AI subscriptions are a ticking time bomb for enterprise

#163
post #5

I’ve said this before on HN, but there are two things that make me optimistic that we won’t see a big rug pull where price-to-capability ratio skyrockets relative to today: * People keep finding ways of cramming more intelligence into smaller models, meaning that a given hardware spec delivers more model capability over time. I remember not that long ago when cutting edge 70B parameter models could kinda-sorta-someti…

Exactly.

Competitive pressure prevents a rug pull.

In a competitive race, each breakthrough gets copied or illicitly distilled or whatever. That means the frontier models are deprecating assets and the mark up tokens should get smaller and smaller.

Now bigger models are more expensive to run inference on, but today's models, or equivalent ability and size models, shouldn't go up in price.

5.5 is 4x the price, but 5.4 still exists, so its not rug pull, but a big more expensive to run and hopefully more valuable model.

Re: AI subscriptions are a ticking time bomb for enterprise

#164
post #7

Earlier quoted context omitted.

There are plenty of various providers on OpenRouter serving very large Chinese models like GLM for a fraction of what OpenAI/Anthropic. Presumably they are making a profit. It’s unlikely that Claude is proportionally that bigger and more expensive to serve so profit margins on inference must be pretty decent

Do we know they are making a profit though? They could be subsidizing use to build market share the same way. They might not have billions, but at the volumes they are selling maybe they’ve got the cash to do it. Even if they are “profitable” how many Uber drivers are “profitable” because they aren’t correctly calculating asset depreciation. Maybe these guys are doing the same thing. Maybe it’s a lot of people who al…

> subsidizing use to build market share the same way

To an extent maybe, but that market is almost entirely commoditized already. Besides Cerebras and maybe Groq (which already charge a slight premium) all the other providers are more less interchangeable.

> Maybe it’s a lot of people who already had GPUs for crypto mining

I’m not sure the type of GPUs that were most popular for crypto are at all useful for LLMs?

Re: AI subscriptions are a ticking time bomb for enterprise

#166
post #79

Every AI subscription is a ticking time bomb for the frontier provider; within a few years we will be running local models as good as today’s frontier models with almost no cost burden. The floor will fall out of the enterprise market for all the frontier companies.

I disagree. No one will want to use second rate models when the frontier models reach a specific level of capability. Enterprise will keep paying.

No one? When free means I get 95% of the capabilities of something very very expensive, you bet your bottom dollar many many people will choose free.

Re: AI subscriptions are a ticking time bomb for enterprise

#167

Earlier quoted context omitted.

> within a few years we will be running local models as good as today’s frontier models with almost no cost burden Based on what? The RAM requirements alone are extraordinary. No, running large models on shared, dedicated hosted hardware at full utilization is going to be vastly more cost-efficient for the foreseeable future.

Local modals are 6 months to 18 months behind frontier. Even if the performance of a cloud model is faster, it's clear that local is catching up.

> Local modals are 6 months to 18 months behind frontier.

I wish this was true but it is not. And I am working on open source models so if anything, I would have a bias towards agreeing with you.

Frontier closed models (GPT/Claude) are gaining distance to everybody else. Even Google, once the king.

Your claim is a meme coming from benchmark results and sadly a lot of models are benchmaxxed. Llama 4, and most notably the Grok 3 drama with a lot of layoffs. And Chinese big tech... well they have some cultural issues.

"Qwen's base models live in a very exam-heavy basin - distinct from other base models like llama/gemma. Shown below are the embeddings from randomly sampled rollouts from ambiguous initial words like "The" and "A":"

https://xcancel.com/N8Programs/status/2044408755790508113

---

But thank god at least we have DeepSeek. They keep releasing good models in spite of being so seriously resource constrained. Punching well above their weight. But they are not just 6 months behind, either.

Re: AI subscriptions are a ticking time bomb for enterprise

#168

Earlier quoted context omitted.

I would readjust your convictions. We are only 2-4 years away from consumer grade immutable-weight ASICs.

We are discussing how rapid development has been, and now you want to freeze your model in silicon?

If the silicon costs $200-300 and the company throws it away every two years that’s cheaper than a subscription.

Also, how many companies will just buy an M6/M7 MacBook Pro with 32GB+ of RAM in a couple of years and get “free” AI along with the workstation they were going to buy anyway?

Re: AI subscriptions are a ticking time bomb for enterprise

#169

Earlier quoted context omitted.

> within a few years we will be running local models as good as today’s frontier models with almost no cost burden Based on what? The RAM requirements alone are extraordinary. No, running large models on shared, dedicated hosted hardware at full utilization is going to be vastly more cost-efficient for the foreseeable future.

>running large models on shared, dedicated hosted hardware at full utilization is going to be vastly more cost-efficient for the foreseeable future. That is only true right now because hundreds of billions of dollars are being burned by these AI companies to try to win market share. If you paid what it actually cost, your comment would likely be very different.

No, it's economies of scale and I don't understand where anyone is coming from that thinks they'll be better off buying their own hardware, why would you get a better deal on MATMULs/watt than the cloud providers ?

Re: AI subscriptions are a ticking time bomb for enterprise

#170

Earlier quoted context omitted.

Do we know they are making a profit though? They could be subsidizing use to build market share the same way. They might not have billions, but at the volumes they are selling maybe they’ve got the cash to do it. Even if they are “profitable” how many Uber drivers are “profitable” because they aren’t correctly calculating asset depreciation. Maybe these guys are doing the same thing. Maybe it’s a lot of people who al…

also, it's very much possible that the chinese companies get heavy investments from the state. Since it's very hard to get this info we have no idea wether they really make a profit or not.

The R&D is of course subsidized but a lot/most(?) of these inference providers are not Chinese
Post reply on HN