You can even not have any data layer all together. The only thing missing from a local LLM is knowledge of current medications by name if you want to just say whatever prescription you're following.

For sure, context rot is a problem, but that's also the easiest thing to control for in this case. If sensor data is relevant to you, having some code to process and reduce it to a dashboard you can read is always a good idea, independently of getting an LLM into the loop.

This becomes more complicated with data you can't really understand like results from blood tests, for example. But maybe you just don't summarize any of that.

What we can call a health advisor is not a doctor. In fact, depending on the model, it will actively point you to seek medical help.

I can read minds and they're thinking "we better get some money around here, otherwise we're still blaming the immigrants".

If they're not great, it's your fault /thread 😅

I believe right now it's also valid to ditch NVIDIA given a certain budget. Let's see what can be done with large unified memory and maybe things will be different by the end of the year.

can't have both

somebody do something any day now

no more fokin ambushes

I'm aware of it, seems cool. But I don't think AMD fully supports the ML data types that can be used in diffusion and therefore it's slower than NVIDIA.

it's most likely math

Congratulations Nintendo, you played yourself.