PaliGemma is an open vision-language model designed for tasks such as image captioning, visual question answering, and object detection. Credit: Anna Martyanova/Shutterstock Google has expanded on its Gemma family of AI models, introducing the PaliGemma vision-language model (VLM) and announcing Gemma 2, the next generation of Gemma models based on a new architecture. The company also released the LLM Comparator in open source, an addition to its Responsible Generative AI Toolkit. Google announced the new products on May 14. The company described PaliGemma as a powerful open VLM inspired by the Pali-3 vision-language models, intended to be smaller, faster, and stronger. Built on components from the SigLIP vision model, PaliGemma is designed for a range of vision-language tasks including image and video captioning, visual question answering, understanding text in images, object detection, and object segmentation. PaliGemma can be found on GitHub, Hugging Face, Kaggle, and Vertex AI. Gemma 2, due to be formally launched in coming weeks, features a new architecture designed for “breakthrough performance and efficiency,” Google said. At 27 billion parameters, Gemma 2 offers performance comparable to Llama 3B at less than half the size, Google said. An efficient design reduces deployment expenses, with Gemma 2 fitting on less than half the compute of comparable models. For fine-tuning, Gemma 2 can work with solutions ranging from Google Cloud to tools such as Axolotl. Google also added to its Responsible Generative AI Toolkit by releasing the LLM Comparator in open source. Designed to assist developers with conducting model evaluations, the LLM Comparator is an interactive data visualization tool that allows users to perform side-by-side evaluations of model responses to assess their quality and safety. Related content analysis Beyond the usual suspects: 5 fresh data science tools to try today The mid-month report includes quick tips for easier Python installation, a new VS Code-like IDE just for Python and R users, and five newer data science tools you won't want to miss. By Serdar Yegulalp Jul 12, 2024 2 mins Python Programming Languages Software Development analysis Generative AI won’t fix cloud migration You’ve probably heard how generative AI will solve all cloud migration problems. It’s not that simple. Generative AI could actually make it harder and more costly. By David Linthicum Jul 12, 2024 5 mins Generative AI Artificial Intelligence Cloud Computing news HR professionals trust AI recommendations HireVue survey finds 73% of HR professionals trust AI to make candidate recommendations, while 75% of workers are opposed to AI making hiring decisions. By Paul Krill Jul 11, 2024 3 mins Technology Industry Careers how-to Safety off: Programming in Rust with `unsafe` What does it mean to write unsafe code in Rust, and what can you do (and not do) with the 'unsafe' keyword? The facts may surprise you. By Serdar Yegulalp Jul 11, 2024 8 mins Rust Programming Languages Software Development Resources Videos