It's purely client-side aggregation. The entire "engine" is a single HTML file with vanilla JavaScript—no backend server required. When you type a query, it fires off parallel fetch() requests (using Promise.all) to public, CORS-friendly APIs like Algolia (for HN), Reddit’s public .json endpoints, and Wikipedia’s API. It then normalizes those JSON responses and injects them into the DOM. History and settings are just persisted in localStorage.
As per the name, it's Din Don Dan [1], from Konami's DDR (and included in other rhythm games by them). This is specifically the performance from DanEvo [2].
This particular version became popular from a guy absolutely killing it despite appearances [3], but personally I like this one [4] because it shows how you can dance to look good, or dance to score well.
Given the strong anti-science anti-GMO sentiment in Europe, the company probably will not even bother to try to apply for a permit from the European regulatory agencies.
When it comes to GMO plants, Europe is anti-science.
European Commission had a Chief Scientific Adviser, but they happened to choose a plant biologist for the role [1]. Then she dared to speak the scientific consensus about GMO plants (they're safe) [2] and EU decided to close the whole role [1,3] to get rid of her.
Oh, I'm looking forward of this client being available as a Flatpak although especially in this case some folks might prefer it to have it available via Snap :D
Can somebody explain how the workflow works here exactly? Is the LLM trained on SVG?
If so: could it hallucinate SVG properties or so?
Or is it a regular image generating AI that vectorizes raster images afterwards with traditional tooling?
I'm a noob in that field but I'm curious about potential risks. ;)
Does anyone know whether this would also be possible with Firefox, including explicit extensions (i.e. uBlock) and explicit configured block lists or other settings for these extensions?
And below in the README were the conditions set from the prompt (i.e. "use only NumPy (no deep learning frameworks)")