Google's DiffusionGemma generates 256 tokens in parallel and self-corrects as it goes

Google's open-source diffusion language model generates 256 tokens in parallel and self-corrects, hitting 4x speed on one GPU at a cost to quality.
XDA Developers on MSN

I switched my local LLM setup to Ollama's new MLX engine, and my Mac suddenly feels twice as fast

I finally stopped babying my MacBook.
XDA Developers on MSN

6 settings I always change before running a local LLM

You might not need a different model, but better settings ...
IEEE

Dynamic Predictive Sampling Analog to Digital Converter for Sparse Signal Sensing

Abstract: This brief presents a dynamic predictive sampling (DPS) based analog-to-digital converter (ADC) that provides a non-uniform sampling of input analog continuous-time signals. The processing ...
IEEE

Self-Triggered and Event-Triggered Control for Linear Systems With Quantization

Abstract: This paper considers the observer-based event-triggered output control problem with quantization. Both plant-to-controller (measured output) channel and controller-to-plant (control input) ...
note

Model Conversion Simplified with Megatron-Bridge — Discovery of Quantization Token Inflation and Optimal Model Sizes for Edge Inference

Megatron-Bridge (v0.5.0), released by NVIDIA, is a library that converts Megatron-format models to Hugging Face, lowering the barrier to model migration by supporting over 15 models. At the same time, ...
GitHub

AlphaQ: Calibration-Free Bit Allocation for Mixture-of-Experts Quantization

AlphaQ is a novel calibration-free bit-allocation method for Mixture-of-Experts (MoE) model quantization. Unlike traditional data-driven methods that rely on calibration data to estimate expert ...
GitHub

Quantization and Synthesis (Device Specific Code Generation) for ADI's MAX78000 and MAX78002 Edge AI Devices

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