cool idea, I like the round globe too, now with 3D rendering in the browser being trivial on modern devices, there’s no excuse for choosing compromising 2D projections of the globe.

[0]: https://en.wikipedia.org/wiki/Null_Island

> The last option is to use “Hybrid Transport”, where you scan a QR code and connect via Bluetooth simultaneously to the computer. Whilst this option is secure and works in theory, reality is plagued with edge-cases where connections fail or Bluetooth is straight-up unsupported.

at least in Apple land, if you try to sign on on a device that you don’t own (let’s say a work laptop where you’re not signed in to your apple id) it’ll give you a QR code to scan with your iPhone and it’ll do faceID on your iphone then do some bluetooth handshake to use your passkey on the other device. I’m not sure if this is Apple exclusive or if android/windows/linux would be able to do the same

So far feels smarter than Bonsai 1 27B, it’s slightly larger than the Q1_0 quant. Super exciting stuff :)

That said, system prompt (which to your point also comes from the human) matters a lot too. For example a coding harness that doesn’t a have a plan mode will keep trying to write underbaked ideas to code instead of working with the user on the plan. That said, a “system prompt” can also be the first prompt you send to the agent in a vanilla chat window, so I do like your point about the user being the real harness

I’ve been thinking more about how this deterministic + agents style could work, it’s kinda like the analogy of factories in the 1800s going from the central shaft to electric motors on each desk (where the central shaft in this case is a chat window, and the motor on a desk is calling the llm api from wherever you want just like a normal api call)

Of course, maybe in a few months the agents would just be reliable enough to do the shell part on their own too, but we’ll just have to wait and see

I see disk maxing out at 400 MB/s, this disk should be able to hit 1GB/s (it hits that eg when verifying the check sum of the weights), so there might be some optimization to be done there (I’m guessing it’s because the weights access is not pure sequential reads but involves some randomness depending on which expert)

[0]: https://en.wikipedia.org/wiki/Null_Island

To actually add something to the discussion though: I guess getting LLMs to control robots is cool, but would potentially have more severe consequences than pure software since it interacts more with the physical world

> AnkitAI/Parable-Qwen3-4B-Claude-Fable-5-GGUF

you’re telling me you managed to fit Fable 5 into just 4B?