embedded devices

Several security vulnerabilities have been discovered in the Linux kernel, according to an article on LWN. The findings are drawing significant attention from the developer and security communities, who are tracking the flaws and the patches that will follow. Kernel vulnerabilities are closely watched because Linux runs across servers, cloud infrastructure, Android devices and embedded systems worldwide.

Google has announced EmbeddingGemma 2, an open, lightweight multimodal embedding model, publishing the details in a company blog post. The release is drawing attention among developers and AI practitioners, who are discussing the model's small size, its multimodal capabilities, and how it might be used for search, retrieval, and on-device applications.

Google has announced EmbeddingGemma 2, the latest version of its open embedding model aimed at lightweight, on-device AI applications. The announcement, shared via the Gemma team, has drawn attention among developers on Hacker News, who are discussing its capabilities and performance relative to other embedding models. Details on benchmarks and availability remain limited in the initial announcement.

Google has released EmbeddingGemma 2, a new embedding model the company says can run directly on devices and handle multimodal inputs. The launch is being discussed among developers and AI watchers as part of the push to bring capable AI models to phones and other consumer hardware without relying on cloud servers. Reaction online has focused on what the model means for privacy, latency and on-device applications.

The NBA is testing smart basketballs with embedded sensors and wearable devices for referees during the preseason. The technology is designed to track ball movement and shot data while helping officials make more accurate calls in real time. Sports media outlets including Yahoo Sports have picked up the story, with fans and analysts debating how such gadgets could change officiating and game analytics if rolled out league-wide.

Google has introduced EmbeddingGemma 2, the latest version of its compact embedding model aimed at developers building search, retrieval and AI applications. The announcement was published on Google's blog and picked up on developer forums, where the release drew modest attention with readers weighing in on its usefulness for building on-device and low-cost AI tools.

A vulnerability in the Linux kernel has been resolved, tracked as EUVD-2026-93289 and affecting the bcmgenet network driver used with Broadcom hardware. The fix restores hardware filters when the interface is opened, correcting an initialization issue in the driver's filter handling. The advisory covers multiple Linux kernel products and was updated on October 6, 2026, though no severity score has been assigned yet.

Meta is releasing the code for its Muse technology for free, aiming to get the AI assistant embedded in a wide range of consumer devices, from televisions to household appliances. The move positions Muse as a building block for third-party gadget makers rather than a feature locked to Meta's own hardware. Tech commentators are weighing what open-sourcing the software means for competition in the AI device market.

Google has announced EmbeddingGemma 2, a model designed to bring multimodal semantic search to edge devices. The release lets developers run embedding-based search across text, images and other media locally, without sending data to the cloud. It signals Google's continued push to move AI capabilities onto phones and other resource-constrained hardware.

wolfSSL has introduced wolfCert, a new tool for certificate enrollment on embedded devices. The announcement outlines how the component supports enrolling and managing certificates in constrained, resource-limited environments, complementing the company's existing TLS and cryptography offerings. The release is being circulated among security and embedded systems developers tracking certificate management options for IoT and embedded deployments.