#edge-ai

#edge-ai

With the introduction of its EmbeddingGemma, Google is providing a multilingual text embedding model designed to run directly on mobile phones, laptops, and other edge devices for mobile-first generative AI. Unveiled September 4, EmbeddingGemma features a 308 million parameter design that enables developers to build applications using techniques such as RAG ( retrieval-augmented generation) and semantic search that will run directly on the targeted hardware, Google explained.

The platform ingests data from multiple sensors, such as air, land, sea, and space-based imagery and signals, to detect battlefield threats like drones, enemy positions, or other targets. FPS does all of that in a no-code, hardware-agnostic environment that lets the average soldier in the field "build, retrain, and deploy custom machine learning models at the edge without coding," according to the company. Most critically, FPS is designed to operate without a connection to the internet or cloud services.

Artificial intelligence (AI) and software-defined vehicle (SDV) supplier Sonatus has launched a platform to help original equipment manufacturers (OEMs) use AI to transform driving and ownership experiences with greater efficiency and lower costs. The firm believes its Sonatus AI Director will be "game-changing", enabling OEMs to deploy AI at the vehicle edge to shrink roll-out cycles from months to days, while lowering costs and enabling smarter, safer driving.

Malaysia has developed its first domestic edge AI processor. Malaysian chip design company SkyeChip announced its MARS1000 processor at an industry event on Monday, Bloomberg reported. While an edge processor isn't as powerful as an advanced Nvidia chip, it still represents a technological milestone for Malaysia, which is looking to play a bigger role in the global AI race. Malaysia already has a foothold in the chip manufacturing sector and has recently increased its efforts and investment around AI.