Waterloo's PAW compiles task specs into 23MB LoRA adapters a 600M-parameter model runs entirely offline.

Local AI inference at 32B-parameter quality, no cloud API required: University of Waterloo researchers released PAW on July 2 ...

Liquid AI's smallest model yet LFM2.5-230M beats models 4X its size at data extraction, can run 'anywhere'

LFM2.5-230M proves that while 3-billion-parameter models like VibeThinker are solving advanced calculus, a ...
Tech Times

Compile Once, Run Offline: New AI Method Matches 32B Models With a 23MB File

Local AI inference at 32B-parameter quality, no cloud API required: University of Waterloo researchers released PAW on July 2 ...
Chosunbiz

Lambda256 launches Nodit Datashare beta to deliver normalized on-chain data

Lambda256, an on-chain (Blockchain network) finance platform supporting financial institutions' virtual asset conversion and ...
WeLiveSecurity

ESET takes part in Operation Endgame to disrupt Amadey and Stealc

ESET researchers assisted in the global disruption of the Amadey botnet and Stealc infostealer, providing technical analysis, ...
note

How to use Claude Code | Identify JSON parsing errors in 10 minutes | How to find broken parts

json.decoder.JSONDecodeError: Expecting value: line 4 column 22 (char 61). The moment I load the configuration file, it stops with this single line. Even though it tells me the location as "line 4 ...
XDA Developers on MSN

I tested Google's new Gemma 4 12B on my 8GB GPU, and now I don't want to go back to smaller models

Not bad for limited hardware ...
MUO on MSN

5 things to build with the $4 chip that's outselling the Raspberry Pi

The ESP32 keeps finding new jobs in my house.
GitHub

Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads

[2024/1] Medusa technical report is now available on arXiv. We've added multiple new features, including Medusa-2 recipe for full-model training, self-distillation for adding Medusa to any fine-tuned ...