Snapmaker U1 owners — that high-pitched whine from the right panel during printing?
It’s air being pulled through the cavities between the 3rd and 4th filament slots.
I made a passive activated carbon filter that drops the noise and cleans the air a bit. The 3d file is open source (MIT).
Don’t lower fan power though — overheating risk.
Anyone else dealing with this? Other quieting mods you’ve tried?
Today we release 𝙻𝙵𝙼𝟸.𝟻-𝟸𝟺𝙱-𝙰𝟸𝙱, the largest 𝙻𝙵𝙼𝟸.𝟻 family member. It is an efficient local model for laptops and PCs to work through multi-step tasks inside popular agent harnesses.
> 24B total parameters, 2B active per token
> Context expanded to 131K tokens
> A 128K-token vocabulary
> 33T pretraining tokens
> It is a reasoning model
> Very easy to fine-tune and customize
> Performs competitively with Qwen3.6-35B-A3B, a model with ~50% more total and active parameters, on agentic and tool-use tasks.
> Open base and post-trained weights on @huggingface 🤗
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Snapmaker U1 owners — that high-pitched whine from the right panel during printing?
It’s air being pulled through the cavities between the 3rd and 4th filament slots.
I made a passive activated carbon filter that drops the noise and cleans the air a bit. The 3d file is open source (MIT).
Don’t lower fan power though — overheating risk.
Anyone else dealing with this? Other quieting mods you’ve tried?
Decision models in llama.cpp are now available
The `/v1/systemone` endpoint is available in the latest llama builds. Use it to do Jev-style inference locally, efficiently and privately. Multiple open models are supported with more to come.
https://t.co/D3MUi78kXn
hermes desktop works well on jetson thor. i thought it was not gonna work for aarch64 linux but it does work. looks better than the builtin cli and dashboard interfaces.
Introducing CUDA Rust!
CUDA Rust lets you write GPU kernels natively in Rust, not just launch them from it.
Two paths: cuda-oxide for SIMT kernels compiled to PTX, and cutile-rs for Tile-based programming on stable Rust. Both can catch aliasing errors at compile time.
Technical blog: https://t.co/5mYSRnQkBB
thought "need need"
worked for a while before it indefinitely repeats itself.
dont know if the quantization went wrong or the model. same llamacpp starting arguments worked fine for qwen 35b and orin35b
Once I learn how to drive Hermes Agent, a cheaper/weaker model inside that harness often feels “good enough” compared with paying for the frontier lab model that tops DeepSWE 1.1
Using a coding agent makes my mind feel foggier than pairing with a chat UI and guide the code generation myself.
Cognitive offloading is real. When the agent just does it, I stop holding the problem in my head.
Thinking of going back to the old-school copy-paste loop for a while and seeing if the sharpness comes back.
Do you think ai is degrading your cognitive ability?
⚡ Fine-tune and quantize AI models directly on NVIDIA Jetson.
Our new Jetson AI Lab tutorial shows how to use Unsloth and memory-efficient QLoRA to customize models, export quantized GGUF files, and run them locally with llama.cpp.
Follow hands-on examples for:
🔹 NVIDIA Nemotron 3.5 Lightning on Jetson AGX Thor
🔹 Qwen3.5-4B on Jetson Orin Nano
Start optimizing: https://t.co/hDUCiNnQcW
Movies have a funny way of showing us what we already know but refuse to admit.
Sometimes the character we’re judging is carrying the same flaw we’re trying to hide