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.

What part requires perfect precision?

If you want to parse sensor data, you do it in code before the LLM sees it.

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.

chat is this socialism

no more fokin ambushes

For some weird reason, in my country it's easier to order a Beelink or a Framework than an HP. They will sell everything else, except what you want to buy.

Remind me of what are the downsides of possibly getting a framework desktop for christmas.