XDA Developers on MSN

Google's Gemma 4 isn't the smartest local LLM I've run, but it's the one I reach for most

Google's newest Gemma 4 models are both powerful and useful.

Endee Launches Managed Cloud for its Open-Source Vector Database with Generous Free Tier

The open-source vector database Endee.io, that is well known for its Ultra High performance with 10x lower Infra, is ...
IEEE

Two-Bit Quantization and Its Priority Under Low Sampling Rate

Abstract: In recent years, extreme quantization methods-particularly one-bit quantization-have garnered significant attention in signal processing and data acquisition systems. While one-bit ...

Your developers are already running AI locally: Why on-device inference is the CISO’s new ...

Shadow AI 2.0 isn’t a hypothetical future, it’s a predictable consequence of fast hardware, easy distribution, and developer ...
eWeek

Gemma 4 Arrives: Google Drops Restrictions, Embraces True Open Models

Google unveils Gemma 4 under an Apache 2.0 license, boosting enterprise adoption of efficient, multimodal AI models across ...

谷歌劲爆论文被曝学术不端！华人学者公开指控抄袭、贬低已有理论 ...

谷歌前几天发布的一篇博客文章：“内存减6倍、精度0损失，推理提速8倍！谷歌新技术震撼了AI圈”。 这项被谷歌高调宣传、号称把大模型KV缓存压到原来1/6、推理提速8倍的TurboQuant算法，一夜让内存股蒸发超过900亿美元。 X上关于该技术的消息，发布不到24小时上千万浏览。 就在整个AI圈为之震动时，一位华人博士后，公开指出这篇论文的核心方法与他的团队两年前发表的RaBitQ高度雷同，而且论 ...
腾讯网

血洗内存股900亿刀的谷歌AI论文，竟涉嫌学术造假

编辑｜泽南、杨文没想到这次大面积市场震荡，还引出了学术大瓜。本周五晚，谷歌的学术不端事件成为了 AI 圈的焦点。来自苏黎世联邦理工学院（ETH Zurich）的博士后高健扬在知乎发布文章，表示 Google Research ...
GitHub

Python implementation of the TurboQuant and QJL vector quantization algorithms.

turboquant-py implements the TurboQuant and QJL vector quantization algorithms from Google Research (ICLR 2026 / AISTATS 2026). It compresses high-dimensional floating-point vectors to 1-4 bits per ...
IEEE

Lightweight Adaptive Quantization Algorithms for Federated Learning With Heterogeneous Clients

Abstract: Quantization is a common method to improve communication efficiency in federated learning (FL) by compressing the gradients that clients upload. Currently, most application scenarios involve ...
Semiconductor Engineering

Balancing Training, Quantization, And Hardware Integration In NPUs

Experts At The Table: AI/ML is driving a steep ramp in neural processing unit (NPU) design activity for everything from data centers to edge devices such as PCs and smartphones. Semiconductor ...
Forbes

How Mixed-Precision Quantization Could Break AI’s Power Addiction

It turns out the rapid growth of AI has a massive downside: namely, spiraling power consumption, strained infrastructure and runaway environmental damage. It’s clear the status quo won’t cut it ...
Hacker

A Quick Guide to Quantization for LLMs

Writing about AI, tech, and startups. with a focus on practical insights for builders, founders, and creators. Writing about AI, tech, and startups. with a focus on practical insights for builders, ...