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kenzicon Launch HN: Magnitude (YC S25) – Self-optimizing inference engine for agents

Wow, that's impressive.

kenzicon Launch HN: Magnitude (YC S25) – Self-optimizing inference engine for agents

How long does tuning take (on an M3 MacBook Pro for example)?

kenzicon GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price

Is it really 1/5 of the price if most people who use it are also losing 1/2 of their credits?

kenzicon Why browsers need a native API for open-weight models

The Web Models API is a proposal for letting web apps use specific open-weight models running on a user’s device through navigator.models. The goal is to make on-device open-weight AI free, private, predictable, and less dependent on cloud providers.

kenzicon MicroLLM Lab – Try 7 tiny LLM's in the browser

Interesting idea. I hadn't considered that. Thanks

kenzicon MicroLLM Lab – Try 7 tiny LLM's in the browser

Great question. Right now there isn’t a definitive answer, but it’s something that needs to be worked out. There would likely be a registry. The question is how to keep model IDs consistent: does each browser manage its own registry, or is there one shared across browsers?

kenzicon MicroLLM Lab – Try 7 tiny LLM's in the browser

Really cool project. Giving web apps direct access to on-device models is something I’m excited about, and it’s cool to see the different approaches.

I’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

kenzicon WICG Proposal for Browser AI API for Utilizing On-Device Models

The Browser AI API is a proposal for a new browser feature that makes AI models accessible directly on users' devices through the browser. By offering a simple API available on the window object, this approach would allow websites to leverage AI without sending data to the cloud, preserving privacy, reducing latency, and enabling offline functionality.

This is about empowering developers to integrate advanced AI into web apps—without needing heavy infrastructure—while giving users control over their data and the models they choose to run. Imagine a world where on-device AI enhances web apps in real-time, with no data leaving the device and no reliance on external servers.

The API would let developers:

Query available AI models on a users' device. Request user permission to access specific models. Create sessions with the models. Perform common tasks like text generation, embeddings, and chat. By running models directly on the user's hardware, we’re opening up new possibilities for AI-driven web apps while keeping things secure, private, and available offline.