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Wednesday, April 24 2024

Google Unveils Gemma: Open-Source AI Models for Developers

Photo Credit : Google

Google released a new lightweight open-source family of artificial intelligence (AI) models called Gemma on Wednesday, February 21. Two variants of Gemma, Gemma 2B and Gemma 7B, have been made available to developers and researchers. The tech giant said it used the same technology and research for Gemma that it used to create Gemini AI models. Interestingly, Gemini 1.5 model was unveiled last week. These smaller language models can be used to make task-specific AI tools, and the company allows responsible commercial usage and distribution.

The announcement was made by Google CEO Sundar Pichai in a post on X (formerly known as Twitter). He said, “Demonstrating strong performance across benchmarks for language understanding and reasoning, 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.” The company has also created a developer-focused landing page for the AI model, where people can find quickstart links and code examples on its Kaggle Models page, quickly deploy AI tools via Vertex AI (Google’s platform for developers to build AI/ML tools), or play around with the model and attach it to a separate domain using Collab (it will require Keras 3.0).

Google stated that both versions of the Gemma AI models are instruction-tuned and pre-trained, highlighting some of their 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 responsible AI tools, the tech giant has also released a new Responsible Generative AI Toolkit.

As per reports shared by Google, Gemma has outperformed Meta’s Llama-2 language model in multiple major benchmarks such as Massive Multitask Language Understanding (MMLU), HumanEval, HellaSwag, and BIG-Bench Hard (BBH). Notably, Meta has already begun working on Llama-3, as per various reports.

In the field of artificial intelligence, it has become popular to release smaller language models as open-source tools for researchers and developers. There are already open-source solutions for stability, Meta, MosaicML, and even Google with its Flan-T5 models. On the one hand, it fosters the development of an ecosystem by enabling developers and data scientists outside of AI firms to experiment with the technology and produce original tools. However, it also helps the business because, in most cases, companies provide deployment platforms that require a subscription fee. Additionally, the adoption process by developers frequently draws attention to algorithmic or training data flaws that might have gone unnoticed before release, enabling the businesses to enhance their models.

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