AI Prompt Saving Feature "Skills" Comes to Google Chrome

On June 4, Google announced a new AI feature for the Chrome browser called "Skills in Chrome." Until now, giving instructions to AI required manually typing a prompt every time. Skills saves these prompts so they can be reused with a single click.

For users who frequently rely on AI assistance in everyday browsing, this is a meaningful improvement that eliminates repetitive typing. Details on the range of supported AI features and rollout timing remain limited for now, but it stands out as an effort to push browser-AI integration a step further.

Honda, Maker of ASIMO, Hints at Re-Entering Humanoid Robots

Honda, which unveiled the bipedal robot ASIMO ahead of the rest of the world in 2000, has now shared its view on the current humanoid robot boom. According to an ITmedia interview, Honda sees the current boom positively — "though not without some frustration" — and has not ruled out the possibility of re-entering humanoid robot development.

Although ASIMO was technologically advanced, it never reached commercialization and ceased operations in 2018. However, as the fusion of AI and robotics accelerates, Honda's accumulated technology could be put to use in new forms. In the current humanoid robot race led by players like Figure AI and Tesla Optimus, an entry by a veteran manufacturer could have an impact on the entire industry.

Community Fine-Tunes of Gemma 4 12B Arrive in No Time

Community fine-tunes of "Gemma 4 12B," the open model Google recently released, have already started appearing. The r/LocalLLaMA community on Reddit reported that multiple fine-tunes in GGUF format have been published on Hugging Face.

The released models include gemma-4-12B-it-heretic-GGUF and Melody1437-12B-v0.4-GGUF. Community fine-tunes surfacing this quickly after an open-weights model's release is a testament to how mature the local LLM community has become. As a small yet high-performing model, Gemma 4 12B is expected to see significant use in local environments.

Gemma 4's "Per-Layer Embeddings" Is a Technique Worth Watching

The Gemma 4 series includes two small models: E2B and E4B. The "E" stands for Effective, and these models employ a technique called Per-Layer Embeddings. According to a technical deep-dive, gemma-4-E2B has 5.1 billion parameters, of which 2.8 billion are embedding parameters — which Google claims "don't count." That leaves only 2.3 billion effectively usable parameters.

The technique works by giving each layer its own independent embeddings, improving parameter efficiency across the model as a whole. However, some have pointed out that there is "a gap between the reality and the reported numbers" in how parameter counts are presented, making this part of the ongoing debate around transparency in open models.

"Astrid," an AI Agent-Exclusive OS, Hits GitHub Trending

Astrid, a project billed as an OS built exclusively for AI agents, has made its first appearance on GitHub's trending list. Written in Rust, the project racked up 2,530 stars shortly after its release.

It is designed as an execution environment where AI agents can autonomously carry out tasks, handling agent execution management and resource control. As an attempt to tackle the challenges of running AI agents in production (hangs, lack of traces, state loss on restart, and so on) from the OS layer, it is drawing attention in the developer community.