•Google's Gemma 4 26B-A4B, a Mixture-of-Experts (MoE) model, offers high performance with a small active parameter footprint (4B), making it ideal for local inference.
•LM Studio's new headless CLI allows developers to easily serve Gemma 4 locally as an API, providing benefits like zero costs, enhanced privacy, and consistent availability.
•Integrating the locally served Gemma 4 with tools like Claude Code (via aliases) empowers developers to leverage powerful AI capabilities directly on their hardware for coding tasks, despite potential...
•Anthropic's Claude Code AI successfully discovered multiple remotely exploitable security vulnerabilities in the Linux kernel.
•One critical bug in the Network File System (NFS) driver remained hidden for an astonishing 23 years, demonstrating the AI's deep understanding.
•The discovery was made with surprisingly little human oversight, using a simple script to 'point' Claude at kernel source files and ask it to find vulnerabilities as if in a CTF.
•This breakthrough highlights the immense potential of large language models (LLMs) in automating complex vulnerability research and enhancing software security.
•Google's Gemma 4 26B-A4B, a Mixture-of-Experts (MoE) model, offers high performance with a small active parameter footprint (4B), making it ideal for local inference.
•LM Studio's new headless CLI allows developers to easily serve Gemma 4 locally as an API, providing benefits like zero costs, enhanced privacy, and consistent availability.
•Integrating the locally served Gemma 4 with tools like Claude Code (via aliases) empowers developers to leverage powerful AI capabilities directly on their hardware for coding tasks, despite potential...
•Anthropic's Claude Code AI successfully discovered multiple remotely exploitable security vulnerabilities in the Linux kernel.
•One critical bug in the Network File System (NFS) driver remained hidden for an astonishing 23 years, demonstrating the AI's deep understanding.
•The discovery was made with surprisingly little human oversight, using a simple script to 'point' Claude at kernel source files and ask it to find vulnerabilities as if in a CTF.
•This breakthrough highlights the immense potential of large language models (LLMs) in automating complex vulnerability research and enhancing software security.
