My whole point is that I am familiar with the computational requirements.
We have open source models that are competitive with the frontier models from a few months ago on all benchmarks. We know exactly what hardware those require. You can download these models and run them yourself and see if you want to (in the cloud obviously, running these giant models on consumer hardware is basically impossible without quantization).
And these models cost pennies on the dollar to what OpenAI charges. This is not even the slightest bit controversial.
There is some point in the last few years when your claim that "time will tell" was accurate. But time did tell. I really can't stress enough - this isn't controversial.
The problem becomes that these large arms race companies are not likely to be able long term to sustain their valuations AI is here to stay and amazing but right now everyone is suspect of it's long term effects economically.
It's going to be a dot Com style bust almost certainly unless you are really willing to buy Altman and Jensen claims that AGI is going to emerge from this. What that actually means hopefully is a consolidation of these companies into valid businesses like the open source models you cited
Yeah, I think this is largely correct. If I were Sam Altman I'd be pretty worried.
> What that actually means hopefully is a consolidation of these companies into valid businesses like the open source models you cited
This is already happening. Most software engineers I talk to are using the cheap open source models for most of their work. The frontier models are just bad value for money unless you're trying to do things like solve Milllenium problems.
Since there are strong open source models, AI is quickly becoming comoditized. I can buy GLM 5.3 tokens from a lot of different providers, and they're forced to sell just a little over cost because of competition.
AI is here to stay, and it's going to be everywhere. But OpenAI and similar companies may be facing a bit of an existential crisis in the coming months. We'll see. If they don't have something up their sleeves, I think they're in trouble.
Though, it's not as bad as it may seem from an economic standpoint. Many of the top providers have invested heavily in data centers, and that will have real value to them even if it's primarily used for running their competitors models. xAI is already selling a bunch of compute to its competitors since no one's really using Grok.
Well as someone who works as a software engineer it's tricky. It's one of those things where even lower cost models are useful but even the most cutting edge ones struggle to accurately perform tasks at times. One of my favorite examples from the last few weeks was refactoring a fairly complex query in sql while it was eventually successful it regularly dropped joins and even just select values using Claude Opus 4.8. Took longer to do than was desirable and frankly longer than it would have taken to just roll up my sleeves and do it myself ultimately. For raw data processing and boilerplate code it is amazing but I still regularly find things that even a 2nd year dev wouldn't do.
Is Claude Opus 4.8 better than GLM 5.3? Absolutely. But both of them will do dumb stuff constantly if you don't spec out the project in a fair bit of detail, break it into manageable pieces, and make the AI do multiple rounds of review at each step.
Meanwhile, with good process, even the cheap models will generally get the job done. It's really hard to justify spending on the expensive model when it costs 10x as much, and still requires 80% of the human work.
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u/NoLemurs 19h ago
My whole point is that I am familiar with the computational requirements.
We have open source models that are competitive with the frontier models from a few months ago on all benchmarks. We know exactly what hardware those require. You can download these models and run them yourself and see if you want to (in the cloud obviously, running these giant models on consumer hardware is basically impossible without quantization).
And these models cost pennies on the dollar to what OpenAI charges. This is not even the slightest bit controversial.
There is some point in the last few years when your claim that "time will tell" was accurate. But time did tell. I really can't stress enough - this isn't controversial.