Technology

EPFL Researchers Unveil FG2 at CVPR: A New AI Model That...

AI Observer
Technology

5 strategies that separate AI leaders from the 92% still stuck...

AI Observer
Technology

How The Ottawa Hospital uses AI ambient voice capture to reduce...

AI Observer
Technology

OpenAI, Microsoft tell Senate ā€˜no one country can win AI’

AI Observer
Technology

Zencoder launches Zen Agents, ushering in a new era of team-based...

AI Observer
Technology

OpenAI’s $3B Windsurf move: the real reason behind its enterprise AI...

AI Observer
Technology

What your tools miss at 2:13 AM: How gen AI attack...

AI Observer
Technology

AI giants pressure Capitol Hill

AI Observer
Technology

Pinterest’s new AI tool helps you shop based on visuals and...

AI Observer
Anthropic

I regret buying RGB for my gaming computer

AI Observer
Anthropic

This $1,200 PTZ is a glorified Webcam, but gave my creator...

AI Observer

Featured

AI Hardware

OpenBMB Releases MiniCPM4: Ultra-Efficient Language Models for Edge Devices with Sparse...

AI Observer
News

The concerted effort of maintaining application resilience

AI Observer
News

Ericsson and AWS bet on AI to create self-healing networks

AI Observer
Legal & Compliance

Meta buys stake in Scale AI, raising antitrust concerns

AI Observer
AI Observer

OpenBMB Releases MiniCPM4: Ultra-Efficient Language Models for Edge Devices with Sparse...

The Need for Efficient On-Device Language Models Large language models have become integral to AI systems, enabling tasks like multilingual translation, virtual assistance, and automated reasoning through transformer-based architectures. While highly capable, these models are typically large, requiring powerful cloud infrastructure for training and inference. This reliance leads to latency,...