Almost AGI? The latest AI models still haven’t shown they can beat humans at carb counting…
This is a follow-up to I asked AI to count my carbs 27,000 times. It couldn’t give me the same answer twice. The full preprint […]
LLM
The world’s first digital endo that asks AI to fix your AID settings, and why you should keep your money.
Ask once and you get an answer. Ask fifty times and you get eighteen different pairs of safety limits, a headline that flips one time in five, and an app that accepts them all. Inside the £4.49 app that turns your diabetes data into chatbot advice on your OS-AID settings.
Explore a Decade of Diabetes Insights with Diabettech AI
After 10+ years of documenting the diabetes landscape, Diabettech is launching diabettech.ai—a custom research tool designed to help you navigate a decade’s worth of articles and reports. Powered by an LLM interface, this tool allows you to “interrogate” the site’s data to find specific answers on everything from cures to n=1 observations.
Key highlights of the beta launch:
Targeted Accuracy: Built to stick strictly to Diabettech articles and comments to minimize “hallucinations.”
Research-Focused: Optimized as a precision tool rather than a standard chatbot to provide relevant article links.
Sustainable Design: Privately funded and optimized for efficiency to manage resource costs and query speeds.
Ready to dive into the archives? Visit diabettech.ai to start your research and share your feedback on the beta experience.
In Conversation with…. Carb Counting with AI: A Deep Dive into How Different Models Stack Up
In the dynamic world of diabetes management, anything that can help us accurately estimate carbohydrates in our meals is a game-changer. Imagine a future where […]
In conversation with… the questions
We provided a broad range of questions to the AIs we tested. They’re documented here and cover factual questions, wider information gathering, picture analysis and data analysis.
Read more to see what we went into.
In conversation with…. How effective are large language models at giving diabetes advice?
An experiment with Large Language Models. How well do they provide advice on diabetes issues?