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Google Gemma: Because Google doesn't want to let go of Gemini just yet

Google Gemma: Because Google doesn't want to let go of Gemini just yet


Google has released Gemma 2B and 7B, two open source AI models that give developers more freedom to leverage the research that went into the company's flagship product, Gemini. Gemini is a large closed AI model that directly competes with (and is nearly as powerful as) OpenAI's ChatGPT, while the lightweight Gemma may be better suited for simple chatbots or smaller tasks such as summaries.

However, what these models lack in complexity, they may make up for in speed and cost of use. Google claims that despite its small size, the Gemma model significantly outperforms larger models on key benchmarks and can run directly on a developer's laptop or desktop computer. These will be available via Kaggle, Hugging Face, Nvidias NeMo, and Google Vertex AI.

Releasing Gemmas to the open source ecosystem is completely different from how Gemini is released. Developers can build on Gemini, either through APIs or by working on Google's Vertex AI platform. Gemini is considered a closed AI model. By making Gemma open source, more people can try out Google's AI instead of relying on competitors that offer better access.

Both model sizes are available with commercial licenses, regardless of the size of your organization, number of users, or type of project. However, Google, like other companies, often prohibits the use of its models for certain tasks, such as weapons development programs.

Gemma also ships with a responsible AI toolkit, as open models are harder to put guardrails on than closed systems like Gemini. Tris Warkentin, director of product management at Google DeepMind, said the company conducted a more extensive red team on his Gemma because open models come with inherent risks.

The Responsible AI Toolkit allows developers to create their own guidelines and list of prohibited words when implementing Gemma in their projects. It also includes model debugging tools that allow users to investigate Gemmas behavior and fix problems.

According to Warkentin, the model currently works best for language-related tasks in English. We hope to work with the community to address the needs of the market beyond English work, he told reporters.

Developers can use Gemma for free on Kaggle, and first-time Google Cloud users will receive a $300 credit to use the model. The company says researchers can apply for up to $500,000 in cloud credits.

Other AI companies have also released lighter versions of their flagship underlying models, although it's unclear how much demand there will be for smaller models like Gemma. Last year, Meta released Llama 2 7B, the smallest iteration of Llama 2. Gemini itself comes in several weights, including Gemini Nano, Gemini Pro, Gemini Ultra, and recently Google once again announced the faster Gemini 1.5 for business users and developers. At this point.

By the way, Gemma means jewel.




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