The text is too small and it's way too dense with information in general. Considering how simple this product is to use, it's kinda crazy that I have to scroll through over a page length of (mostly useless, AI-generated) information before getting to the actual interface.
Also what is going on with the footer (why does it link back to the site itself, why is it telling me to "serve over HTTP").
>What is 2+2?
Answer
> To find 2 + 2, we need to add 2 to both sides of the equation.
> 2 + 2 = 4
> So, 2 + 2 = 4 + 2.
Brilliant
LLMs produce semantically correct sentences, not factually correct statements. Have we forgotten this so soon?
> what is 2+2?
> 3+3? 4+4? 5+6? 7+8?
> Reply ~18000 0 ~10 min 2 By : 1-1: I'm a beginner. 3x2 is my best option, but if you're not sure about the other options then just go for it and try againI’ve been working on a related proposal called the Web Models API, which explores a browser standard for an API that runs open-weight models on-device. Would love your thoughts: https://www.webmodels.dev
My take on this concept: https://github.com/willaaam/gemma-4-E2B-webgpu-vision
> "2+2 is 2."
Otherwise, a very neat demo. As others have said, the UI is VERY confusing, way too much stuff going on.
(It's a little bit slow at the moment - you have to wait a few seconds for the models to load - as it's currently on the HN front page. The server is on a 1 gigabit unmetered network connection so it can serve all the weights - around 600 megabytes - to one person every few seconds, there are several concurrent users now.)
What version of Firefox are you using and what is your operating system and graphics card, please? Can you also try it without WebGPU? (Reload the page and uncheck "Prefer WebGPU" and try a prompt.)
1. Add 1 tablespoon of water to the water bath. 2. Place the tub into the water bath and let it sit for about 5 minutes. 3. After 5 minutes, remove the tub and let it cool down. 4. Now, fill the tub with water and let it sit for about
uhmm completely unusable ?
Useful applications include sentiment analysis, text classification, entity extraction, etc.
They certainly can be useful, but you shouldn't compare them with LLMs such as Opus or Fable.