Why do you think it would be worse? I’m seeing more local software, more things freed from SaaS jail, people reverse engineering proprietary drivers, etc. On top of that the barrier to entry for emergency networks like Meshtastic and overlays like Iroh is lower than ever.
We have local models capable of a lot right now and it’s only getting better every day. The hardware requirements are not great, but not absurd either - you can still share community resources, like when you need a lathe, there are people around with garage workshops.
First of all, the baseline is not great, so if things needed for users are whatever-local-LLM-ed by people with a general idea of what is going on instead of previously being blocked on lack of energy to do it properly, and the quality is above the pre-LLM corposlop (not always a high bar), it might still end up an overall improvement.
But the point you make is important regardless of this balance.
I would say that in terms of usefulness without fixing the code by hand the last few months have been a large change for local-ish models, and maybe in a few months there finally is a model that is reasonably local (good speed on 8 GiB RAM + 16 GiB system RAM + NVMe, dunno — I run on iGPU which shifts balance weirdly), and also not useless for generating single-usecase applications without looking at code at all.
LLM+diffusion image generation seems to be run by power users (sure, you need to install something then go download a plugin and install it correctly than go download a model and put its pieces into correct directories, the learning curve is there) who do not know any programming quite a lot.
Probably once it gets the same in terms of result-tier/performance/requirements for mini-app-gen as for image-gen, in a few months it starts approaching the same situation in terms of usability, harnesses included. Without harnesses Ollama is already pretty friendly, I think.
Why do you think it would be worse? I’m seeing more local software, more things freed from SaaS jail, people reverse engineering proprietary drivers, etc. On top of that the barrier to entry for emergency networks like Meshtastic and overlays like Iroh is lower than ever.
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… all dependent on a SaaS for construction and, more importantly, likely all future maintenance. Fun!
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We have local models capable of a lot right now and it’s only getting better every day. The hardware requirements are not great, but not absurd either - you can still share community resources, like when you need a lathe, there are people around with garage workshops.
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Those local models are essentially only used by people who know how to program in general, so this adds very little.
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First of all, the baseline is not great, so if things needed for users are whatever-local-LLM-ed by people with a general idea of what is going on instead of previously being blocked on lack of energy to do it properly, and the quality is above the pre-LLM corposlop (not always a high bar), it might still end up an overall improvement.
But the point you make is important regardless of this balance.
I would say that in terms of usefulness without fixing the code by hand the last few months have been a large change for local-ish models, and maybe in a few months there finally is a model that is reasonably local (good speed on 8 GiB RAM + 16 GiB system RAM + NVMe, dunno — I run on iGPU which shifts balance weirdly), and also not useless for generating single-usecase applications without looking at code at all.
LLM+diffusion image generation seems to be run by power users (sure, you need to install something then go download a plugin and install it correctly than go download a model and put its pieces into correct directories, the learning curve is there) who do not know any programming quite a lot.
Probably once it gets the same in terms of result-tier/performance/requirements for mini-app-gen as for image-gen, in a few months it starts approaching the same situation in terms of usability, harnesses included. Without harnesses Ollama is already pretty friendly, I think.
score 1 · canonical