Well, at least for me: no thanks.
Depends who 'we' is - I've seen plenty of non-tech people in the real world begin to use ChatGPT as a primary information source rather than the web (rightfully or not!)
I suspect that 'we' might not be the true early adopters here, similar to how quite a lot of the most technical users in the 80's thought GUI's were a waste of time.
I don't think that's really what people are talking about when they talk about 'agentic' PCs.
You not envisioning use for it is just a past bias. You can't know that. You can't because we haven't yet reached the point where the OS is fully useful when controlled with AI.
We don't see the same obvious applications of AI because nobody has developed a proper user interface for it. We're stuck with voice, chat, and dumping documents onto it. The current pro-AI stance is basically "fuck the user and fuck interfaces".
But for marketing, “artificial intelligence” is fine. And better than LLMs being called “AI”
To be fair, I find the term to be as contrived as “performant”
Scandalous!
The most likely outcome is the world in the children’s cartoon “Thundarr the Barbarian”. People living in the collapsed ruins of the past society, belief in magic, etc.
A post-apocalyptic hellscape, essentially.
I fully expect that local models models that are comparable to current frontier models in performance will appear in the near future. Additionally, a lot more can be done with the harness as well, which in my opinion is an under-explored territory right now. For example, ATLAS does some clever tricks in this area https://github.com/itigges22/ATLAS
I started working on my own harness and also notice a significant improvement in model capability with it https://dirge-code.github.io
Apple seems to be one of the few companies to have realized that the future is likely local, and they've been focusing on optimizing hardware for that while everybody else seems to still be stuck in a model as a service paradigm.
> I started working on my own harness and also notice a significant improvement in model capability with it https://dirge-code.github.io
You should mine your session logs for examples of scenarios that demonstrate this improvement. If you can characterize it in a time series metric, like tokens/feature, as you applied improvements, then you're offering a receipt.