Yes, fair point. I was trying to use the same comparison we are currently having between closed weights and open weights and their time gap. If there might be a similar time gap to what is possible with ordinary equipment.

Yes, a small open model that can run on today's hardware and that compared to a historic SOTA closed model with all in. What time difference do we think?

Thanks, yes, I meant even ordinary retail PCs, not specialized GPUs. At some point in time in history, SOTA closed models were at a level that compares to todays open models that can run on ordinary hardware.

Retail PCs will probably never catch up to even the open‑weight models (the full, non‑quantized versions). Unless there’s a breakthrough, they just don’t have enough parameters to hold all the information we expect SOTA models to contain.

That’s the conventional view. I think there’s another angle: train a local model to act as an information agent. It could “realize” that, yeah, it’s a small model with limited knowledge, but it knows how to fetch the right data. Then you hook it up to a database and let it do the heavy lifting.

Maybe the industry adapts too and the future PC is AI-ready out-of-the-box. Because people demand that.

Yes, I meant ordinary hardware which you find at home, like a current MacBook Air or equivalent Windows desktop. There must be a time frame when early SOTA LLMs were at a level that compares to open models that can run on ordinary hardware. But it's more like years rather than months. My rough guess would be 2-3 years. Which still would be amazing if we could get OPUS 4.5 quality within 2-3 years on an ordinary computer.

I don't know if you'd consider this ordinary, but a single Mac Studio M5 Ultra 512GB (or even 256GB) V/RAM seems pretty sweet.

I love the spec, but it is like 5x or 10x a Macbook Air I mean really ordinary, Personal Computer in broad sense - not dedicated LLM kit.

I think there are also implications for governments and states. Imagine when all this is done without human involvement, you want to have your legislation machine and AI ready to remove all the friction. In the future, states who are getting that will have a big advantage. Today, everything is designed to interact with humans, and even governments need to rethink that.

That’s what DOGE should have done

I found the creative idea interesting - like the humanoid robots who do not have front or back - it is always both. So they do not need to turn around.

got it - corrected.

Thanks.

The trap in my view is that they think they "do something AI" (the AI Adoption) and by thus completely miss the point that in 2-3 years "AI Native" might be a thing. I see that in companies or at conferences, they are proud of what they have achieved and how good it works. Which makes them kind of blind on what is really coming, the tsunami that's just building up, requiring a complete re-think of what an organization looks like.