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Considering everything is metered by the token I can't see why that would be true? Like, if you use a reasoning model you are either using more of your quota or straight-up being charged more directly. It shouldn't change anything meaningfully.

Heh I'm not quite so adversarial as the last half of your statement, especially since I think companies go through lifecycles during which their initial growth tends to produce more social value than they capture and so I wouldnt want to interrupt that - yet But yes it's premature atm

(Tongue planted firmly in cheek) if only there were a trustless decentralized mechanism for assuring service (preferably in TEEs) and a means to do global payments between providers and consumers

of course it's not just about jobs

frankly i’m already impressed by the models i can run on my phone. knowledge is an issue, but their ability to perform purely language-related tasks isn’t really all that far off the big models at all

You can run a decent model on 16 gigs of ram on a M series Mac now. Building agents is a lot like web dev, request response and doing things in between. I have enjoyed working with the smaller ones, it’s interesting what can be done.

one underappreciated fact is that there are like 100 “neoclouds” out there right now that you can go to and run open weights models

I think the cognitive load required to make something that conforms to your firms expectations will still require people regardless of how efficient these models are. Similar to how outsourcing your core product never really works I agree the future is less concentrated tech talent

This would essentially displace the saas industry and distribute the jobs outwards, and - you know, hopefully - lead to a better software industry, because shrinkwrapped software from megafirms sucks anyway

I'm definitely seeing the most utility with these things in "building myself bespoke and odd little software specifically for my little freak brain." Generalizing that to other people and explaining why I made those choices would be a LOT more complicated.

So I was thinking about this a little bit, and in particular about the opensource community and ecosystem. I'm starting to think that interfaces and governance are places where there's potential leverage for people to carve out their own economic space, or at least exert leverage.

It has made products for others and the barriers are not in the LLM but the human side of the equation. Strong systems thinkers can do it already and chainlink for example has many users

As a user experience/product designer, all I can say is: same as it ever was. The wonderful thing about programmers is they think unlike 95% of the population—the problem is that when they design software and its UI, they think unlike 95% of the population.

Universities too. I work as a developer for a mid-sized state university and we do a lot of custom work that would otherwise be prohibitively expensive and ill-suited to our situation.

"They will be able to do anything you can think of/speak/express." At that point SaaS becomes a triviality and we are dealing with the same type of problems we always have: "managing conflict and resources."

We’ve been interested in a hardware co-op model across the board, including regular compute/cloud stuff. Still in the recurring idle thought phase.

I've had similar thoughts www.newscientist.com/article/2516...

I expect the models will become commodities. Open ones are not that far behind. I see the risk as that the companies de-skill huge numbers of people who become dependent on the convenience of their systems. Then the prices will start going up and the companies will manipulate their users.

this is really cool, we could use Tailscale to hook up different exo instances. Network hops wouldn't be very good for long running compute, but still worth trying it out

Yeah it’s an interesting concept @scoiattolo.mountainherder.xyz

This may become a necessity. Again, if models become "super intelligent" whatever the heck this means and there are only like 3 providers ... that is very very bad under the current conditions. We need to hedge ... but all the talent is concentrated there.

More than just running open models, there is an opportunity to provide small models trained for a specific task. Agents defined for a specific task, do not need a general purpose LLM. They can use a task specific model. This reduces training and inference costs.