Gemma: Google’s Cutting-Edge Open-Source AI Model for Developers
Despite recent Gemini-related developments, Google continues its relentless pace of AI development. The latest endeavor from Google involves an open-source iteration of Gemini named Gemma. Google unveiled the release of a series of lightweight open-source AI models constructed using the same technical and infrastructure foundations as Gemini. This collection of open models is available in two variants: Gemma 2B, boasting 2 billion parameters, and Gemma 7B, featuring 7 billion parameters.
Both variants of Gemma are equipped with pre-trained and instruction-tuned versions and have been fine-tuned to operate efficiently across a range of AI hardware platforms, including NVIDIA GPUs and Google Cloud TPUs. Google asserts that Gemma is sufficiently lightweight to operate on developer laptops and desktops. Despite its lightweight nature, Google claims that Gemma delivers impressive performance. The company asserts that Gemma outperforms other open models, such as Meta’s Llama 2, and even surpasses larger models on crucial benchmarks.
Following a similar approach to its management of Gemini, Google emphasizes that the new AI model prioritizes safety and reliability. To achieve this objective, the company employed automated methods to filter out specific personal information and other sensitive data from training sets. Following a similar approach to its management of Gemini, Google emphasizes that Gemma prioritizes safety and reliability. To achieve this objective, the company employed automated methods to filter out specific personal information and other sensitive data from training sets.
Gemini AI is Making Its Debut on iOS Devices
Additionally, Google utilized fine-tuning and reinforcement learning techniques based on human feedback to ensure the model aligns with responsible behaviors. Furthermore, the company conducted evaluations to mitigate risks and prevent harmful activities. Moreover, Google is launching a responsible Generative AI Toolkit, which includes a debugging tool, safety classification, and guidance, to support the responsible use of AI.
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