I coded a OpenMateo weather call into my python router, so I can type >>weather (city, country) and get live updates.
Failing that, you can search or API this https://openweathermap.org/
Or if you wanna go ultra-minimalist (and super cool)
https://github.com/chubin/wttr.in
https://wttr.in/
^^ if you just type that, it will give you the weather matching your current IP address. Else use /cityname
eg: wttr.in/London
I mean…you could just get them to deliver what you need :) Or try your local hardware store (if one still exists near you)
I wonder…does it need to be a real phone number, or can it be a virtual phone number that forwards?
You just need to authenticate once, right? Then you can drop the burner number and you’re clean?
EDIT: Yup!
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Same :)
I have no idea what that is, so let me look it up…
https://en.wikipedia.org/wiki/BonziBuddy
Huh; must have missed that one back in the day! Though I do recall the Homer Simpson that was like that, and e-sheep
You guys get ads? 😈
Actually I’m always surprised at how pervasive they are. I keep thinking the way my home infra is set up is normal and people are exaggerating about ads for lulz.
But every now and then when I jump on a unfiltered system I realise “No, no they are not”.
You’ll have to dig but it should be here
Feel sorry for yourself. Your ignorance and biases are on full display.
You’re over-egging it a bit. A well written SOAP note, HPI etc should distill to a handful of possibilities, that’s true. That’s the point of them.
The fact that the llm can interpret those notes 95% as well as a medical trained individual (per the article) to come up with the correct diagnosis is being a little under sold.
That’s not nothing. Actually, that’s a big fucking deal ™ if you think thru the edge case applications. And remember, these are just general LLMs - and pretty old ones at that (ChatGPT 4 era). Were not even talking medical domain specific LLM.
Yeah; I think there’s more here to think on.
Agreed!
I think (hope) the next application of this tech is in point of care testing. I recall a story of a someone in Sudan(?) using a small, locally hosted LLM with vision abilities to scan hand written doctor notes and come up with an immunisation plan for their village. I might be misremembering the story, but the anecdote was along those lines.
We already have PoC testing for things like Ultrasound… but some interpretation workflows rely on strong net connection iirc. It’d be awesome to have something on device that can be used for imaging interpretation where there is no other infra.
Maybe someone can finally win that $10 million dollar X prize for the first viable tricorder (pretty sure that one wrapped up years ago? Too lazy to look)…one that isn’t smoke and mirror like Theranos.
Funny how the hivemind over looks that bit enroute to stunt on LLMs.
If anything, that 90% result supports the idea that Garbage In = Garbage Out. I imagine a properly used domain-tuned medical model with structured inputs could exceed those results in some diagnostic settings (task-dependent).
Iirc, the 2024 Nobel prize in chemistry was won on the basis of using ML expert system to investigate protein folding. ML =! LLM but at the same time, let’s not throw the baby out with the bathwater.
EDIT: for the lulz, I posted my above comment in my locally hosted bespoke llm. It politely called my bullshit out (Alpha fold is technically not an expert system, I didn’t cite my source for Med-Palm 2 claims). Not all hope is lost with these things lol
The statement contains a mix of plausible claims and minor logical inconsistencies. The core idea—that expert systems using ML can outperform simple LLMs in specific tasks—is reasonable.
However, the claim that “a properly used expert system LLM (Med-PALM-2) is even better than 90% accurate in differentials” is unsupported by the provided context and overreaches from the general “Garbage In = Garbage Out” principle.
Additionally, the assertion that the 2024 Nobel Prize in Chemistry was won “on the basis of using ML expert system to investigate protein folding” is factually incorrect; the prize was awarded for AI-assisted protein folding prediction, not an ML expert system per se.
Confidence: medium | Source: Mixed
I remember discussing / doing critical appraisal of this. Turns out it was less about the phone and more about the emotional dysregulation / emotional arousal causing delay in sleep onset.
So yes, agree, we need studies, and we need to know how to read them and think over them together.
I don’t think it’s their information per se, so much as how the LLMs tend to use said information.
LLMs are generally tuned to be expressive and lively. A part of that involves “random” (ie: roll the dice) output based on inputs + training data. (I’m skipping over technical details here for sake of simplicity)
That’s what the masses have shown they want - friendly, confident sounding, chat bots, that can give plausible answers that are mostly right, sometimes.
But for certain domains (like med) that shit gets people killed.
TL;DR: they’re made for chitchat engagement, not high fidelity expert systems. You have to pay $$$$ to access those.
Very welcome :)
As it usually goes with these things, I built it for myself then realised it might have actual broader utility. We shall see!
Agree.
I’m sorta kicking myself I didn’t sign up for Google’s MedPALM-2 when I had the chance. Last I checked, it passed the USMLE exam with 96% and 88% on radio interpretation / report writing.
I remember looking at the sign up and seeing it requested credit card details to verify identity (I didn’t have a google account at the time). I bounced… but gotta admit, it might have been fun to play with.
Oh well; one door closes another opens.
In any case, I believe this article confirms GIGO. The LLMs appear to have been vastly more accurate when fed correct inputs by clinicians versus what lay people fed it.
Depends which bit you mean specifically.
The “router” side is a offshoot of a personal project. It’s python scripting and a few other tricks, such as JSON files etc. Full project details for that here
https://github.com/BobbyLLM/llama-conductor
The tech stack itself:
I have ASD; I made several tools that explicitly convert web sources to .md and JSON.
The shitty thing is, a lot of sites - even if they have stuff available in simple, beautiful JSON format, refuse to give public access to it. Notoriously, movie session times for local cinemas. That should be a simple look up…but no.
Oh well, at least cool shit like this still exists
https://github.com/chubin/wttr.in
https://github.com/scrapy/scrapy