Axial encoding unlocks up to eightfold faster 3D microscopy with less light

A research team from HKU Engineering has pioneered a fundamentally new imaging strategy known as AIMED (Arbitrary illumination microscopy with encoded depth), which utilizes a sub-sampling approach.
Crypto Briefing

MIT’s MeMo framework boosts LLM performance by 26% without retraining

MIT's MeMo framework trains a compact memory model that boosts LLM performance by up to 26.73% without retraining, with major implications for crypto AI agents.

MIT's MeMo lets teams swap in a better LLM without retraining — and performance jumps 26%

MIT's MeMo keeps AI memory separate from reasoning, so teams can upgrade their LLM without retraining and see a 26% performance gain, researchers say.

Researchers automated LLM reasoning strategy design and cut token usage by 69.5%

Researchers from Meta and Google built AutoTTS to automatically discover optimal LLM reasoning strategies, cutting token ...
Crypto Briefing

AutoTTS reduces token usage by 69.5% in LLM reasoning strategies

AutoTTS, a framework from Meta, Google, and university researchers, cuts LLM token usage by 69.5% while maintaining accuracy, with implications for AI-driven crypto tools.
Microsoft

The Gentlemen ransomware: Dissecting a self-propagating Go encryptor

Microsoft Threat Intelligence presents a comprehensive analysis of The Gentlemen, a Go-based ransomware deployed by ...
AndroidPIMP

SpacemiT K3 Pico-ITX Review: 60-TOPS RISC-V Powerhouse for LLMs?

SpacemiT K3 challenges Nvidia Jetson with 60-TOPS AI performance. Explore the new Pico-ITX and CoM260 developer kits for RISC ...
Edhat

Yuheng Bu seeks a better way to ensure the trustworthiness of AI-generated text

UC Santa Barbara’s Robert Mehrabian College of Engineering, Yuheng Bu, assistant professor in the Computer Science Department ...
Ars Technica

Google’s Gemma 4 AI models get 3x speed boost by predicting future tokens

Google launched its Gemma 4 open models this spring, promising a new level of power and performance for local AI. Google’s take on edge AI could be getting even faster already with the release of ...
IEEE

Low Bit-Width LLM Acceleration via Symmetric Lookup Format and Compute-in-Decoding Paradigm

Abstract: Recent large language models (LLMs), driven by the scaling law, have demonstrated remarkable performance in various machine learning tasks by significantly increasing model size. However, ...