A Family of Open-Source Lightweight AI Models for Developers Called Gemma is Released by Google
On Wednesday, February 21, Google unveiled Gemma, a new lightweight open-source family of artificial intelligence (AI) models. Developers and researchers now have access to two Gemma variants: Gemma 2B and Gemma 7B. The tech behemoth claimed to have developed Gemma using the same tools and research as its Gemini AI models. Remarkably, the Gemini 1.5 model was shown just last week. These reduced language models can be used to create AI solutions tailored to specific tasks, and the company permits distribution and responsible commercial use.
Google CEO Sundar Pichai made the announcement in a post on X, formerly known as Twitter. “Gemma is available worldwide starting today in two sizes (2B and 7B), supports a wide range of tools and systems, and runs on a developer laptop, workstation, or @GoogleCloud,” he stated. “Demonstrating strong performance across benchmarks for language understanding and reasoning.” A developer-focused landing page for the AI model has also been created by the company. On this page, users can access code samples and quick start links for Kaggle Models, quickly deploy AI tools using Vertex AI (Google’s platform for developers to build AI/ML tools), or experiment with the model and connect it to a different domain using Collab (Keras 3.0).
Google stated that both versions of the Gemma AI models are instruction-tuned and pre-trained, highlighting some of its features. Popular data repositories like Hugging Face, MaxText, NVIDIA NeMo, and TensorRT-LLM are integrated with it. The language models can be used with Vertex AI and Google Kubernetes Engine (GKE) on laptops, workstations, or Google Clouds. In order to assist developers in creating safe and ethical AI tools, the tech giant has also published a new ethical Generative AI Toolkit.
According to findings made public by Google, Gemma has surpassed Meta’s Llama-2 language model on several significant benchmarks, including BIG-Bench Hard (BBH), HumanEval, HellaSwag, and Massive Multitask Language Understanding (MMLU). Notably, according to a number of rumours, Meta has already started working on Llama-3.
Releasing open-source smaller language models for developers and researchers is something that has become a trend in the AI space. Stability, Meta, MosaicML, and even Google with its Flan-T5 models already exist in open-source. On one hand, it helps build an ecosystem as all developers and data scientists who are not working with the AI firms can try their hands at the technology, and create unique tools. On the other hand, it also benefits the company as most often firms themselves offer deployment platforms that come with a subscription fee. Further, adoption by developers often highlights flaws in the training data or the algorithm that might have escaped detection before release, allowing the enterprises to improve their models.