Google is preparing to release Gemini 3.0 Pro, the latest iteration of its large language model (LLM) technology. The model has been spotted in the Gemini CLI GitHub repository, indicating an imminent launch. Alongside this, Google has introduced Gemini CLI GitHub Actions in beta, designed to assist developers by automating tasks, reviewing code, and accelerating software delivery. A notable enhancement is the integration of Gemini CLI with Visual Studio Code (VS Code), enabling native IDE support that allows users to view code diffs and apply changes directly within the editor. This integration was achieved through contributions from over 40 developers and more than 120 pull requests. Industry observers are discussing the potential of Gemini 3.0 to represent a substantial advancement in AI capabilities, although questions remain about whether LLMs alone can achieve human-level intelligence or if further hardware improvements, ecosystem development, or algorithmic breakthroughs are necessary.
Gemini CLI + VS @Code: Native diffing and context-aware workflows - Launch Gemini CLI in VSCode to setup - Manage your VSCode integration with /ide More info 👇🏼 https://t.co/TVDgkdo2gu
First Google Gemini slots into GitHub actions. Now they slot directly into VS @Code. 🍿 https://t.co/LDclY5ledZ
let's suppose Gemini 3.0 is a substantial leap, does that mean LLMs can reach human-level AI? sure, LLMs are a great I/O frontend, but not human-level on their own and if not this path, do we need: - more hardware? - let the ecosystem mature? - new algorithm breakthrough?