331–340 of 379 posts
Here we are in 2026 and LLMs write like this all the time.
Ultimately it will be indistinguishable from a Q drop.
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The outcome is plausible. Open weights models though look like a tactical more than a principled play by Chinese companies to overcome the disadvantage and difficulties to access western markets. Two issues: 1. If market conditions change they might decide to close down like Meta did. 2. If as you said models keep getting more expensive to train, is an open weights strategy financially sustainable? edit: typo
I'm confident we will continue to see improvements in edge models at minimum. For example, Google has a vested interest in making Gemma as good as it can, because ultimately any edge inference is free for Google and they have a massive install base. It wouldn't surprise me if Apple eventually trained their own foundational models, and while it'd be surprising, I wouldn't be shocked if Apple also released open weight…
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It is a principled play by the Chinese. You would not have Xi showing up at AI conferences and speaking quite clearly had this not been the case.
To add to that, to me it seems that the idea is that open weights vastly accelerate dissemination into and practical application in the wider economy, which seems to be the goal. They don't seem to subscribe to the AGI/singularity silliness so prevalent in the West.
But if we compare what what was described in Neuromancer, vs how personal computing and the internet affected the world, we see basically very little overlap.
AGI Doomerism likewise has no basis in reality considering what LLMs have been shown to be capable of. Not saying they wont be transformative in some way or isnt already, but essentially the way these AGI prophets predicted things will go down will be completely inaccurate save for the vaguest tems (something bad will happen at some point, and AI will be involved)
Speculation: open models is what will kill Anthropic and OpenAI. Hyperscalers can run the models without a licensing fee. Apple can make them smaller and put them on the device. The frontier models are an edge and a liability. They're astronomically expensive to train. Without them, their models will fade into obscurity. Their marketing depends on people believing the models are meaningfully different, as people have…
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Are frontier models actually astronomically expensive to train? GLM 5.2 was trained on ~30T tokens, so ~10^25 FLOPs. Say you get B300's for $5/h (pretty high), and you get 50% MFU; that's ~$15M. Of course there's also a bunch of risk that the training itself goes badly, post-training, etc. But still, compared to the inference spend after, it's not that crazy.
Nobody spends 15M on inference only to check at the end that their money was wasted.
I am curious about what changed since GPT 4.5 and other unsuccessful attempts to train large models, compared to now.
Speculation: open models is what will kill Anthropic and OpenAI. Hyperscalers can run the models without a licensing fee. Apple can make them smaller and put them on the device. The frontier models are an edge and a liability. They're astronomically expensive to train. Without them, their models will fade into obscurity. Their marketing depends on people believing the models are meaningfully different, as people have…
Completely agree. Once I can reliably get open models doing what I am on Fable ultra I imagine I will switch for good. I am fortunate to have access to a decent bit of local RAM, 192GB of DDR5 at an OK speed. It is not enough and costs are well past absurd. In a few years time I envisage a setup that is sub $10k which can accomplish such tasks. The pace so far has been breakneck. That is all I personally need. That m…
Fable or GPT 5.6 Sol regularly hand off obviously broken features in my mobile app.
QA is the bottleneck.
If vision capabilities and understanding of motion improve significantly, perhaps the models can tell that a list is not scrolling correctly, or a transition not animating as it should.
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> The frontier AI companies are betting "the house" on them, and if they pay off they could, hypothetically, make them financially competitive. They are not betting the house, they are betting the American economy on it. When this crashes it will take everyone down.
I've been keeping my cash/stock ratio a bit higher than usual recently because I'm waiting for the bubble to burst. My "stock" side is mostly a company I work for that is riding the wave.
Lost me here - I was there - I worked on open sourcing communicator at Netscape and starting Mozilla. We were the one company that tried to own it all, but were out spent and out maneuvered by a more insidious company. This totally misunderstands the situation and the history. Plus the “our CTO” and “CTO letter” at the start was too pretentious. For gods sake; CTOs are just engineers that aren’t worth trusting becaus…
beautiful.