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Google launched a new family of lightweight, open-source artificial intelligence (AI) models called Gemma on Wednesday, February 21st. 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 the Gemini AI model. Interestingly, the Gemini 1.5 model was revealed last week. These small language models can be used to create task-specific AI tools, and the company allows responsible commercial use and deployment.

The announcement was made by Google CEO Sundar Pichai in a post on X (formerly known as Twitter). He said, “Gemma, which has demonstrated strong performance in benchmarks for language understanding and inference, is available globally today in two sizes (2B and 7B), supports a wide range of tools and systems, and can be deployed on developer laptops, workstations, or @GoogleCloud. It runs. .” The company also created a developer-centric landing page for its AI models. Here, people can find quickstart links and code examples on the Kaggle model page to quickly deploy AI tools with Vertex AI (Google’s platform for developers to build AI/ML tools). , or play around with the model and connect it to a separate domain using Collab (requires Keras 3.0).

Highlighting some of the features of the Gemma AI model, Google said that both variants are pre-trained and directed tuning. Integrates with popular data stores such as Hugging Face, MaxText, NVIDIA NeMo, and TensorRT-LLM. Language models can run on laptops, workstations, or Google Cloud with Vertex AI and Google Kubernetes Engine (GKE). Additionally, the tech giant launched a new Responsible Generative AI Toolkit to help developers build safe and responsible AI tools.

According to a report shared by Google, Gemma outperformed Meta’s Llama-2 language model on several key benchmarks such as Massive Multitask Language Understanding (MMLU), HumanEval, HellaSwag, and BIG-Bench Hard (BBH). In particular, according to various reports, Meta has already started work on Llama-3.

Releasing open-source, small-scale language models for developers and researchers has become a trend in the AI ​​space. Google with Stability, Meta, mosaicML, and Flan-T5 models already exist in open source. On the one hand, it helps build an ecosystem because all developers and data scientists who don’t work with AI companies can try out the technology themselves and create their own tools. On the other hand, most companies provide their own distribution platforms with subscription fees included, which also benefits the company. Additionally, adoption by developers often highlights flaws in training data or algorithms that may not have been detected prior to release, allowing companies to improve their models.

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