Coin World News Report:
After releasing a beta version for developers last month, Google has fulfilled its promise to open its most powerful artificial intelligence model, Gemini 1.5 Pro, to the public.
Google’s Gemini 1.5 Pro is capable of handling more complex tasks than previous AI models, such as analyzing entire text libraries, long Hollywood movies, or almost a full day of audio data. This is 20 times the data of OpenAI’s GPT-4o and nearly 10 times the information that Anthropic’s Claude 3.5 Sonnet can handle.
In its announcement, Google stated its goal of delivering faster and more cost-effective tools to AI developers, enabling “new use cases, additional production robustness, and higher reliability.”
Image: Google
Google previously launched the model in May, showcasing a group of selected testers demonstrating its capabilities in a video. For example, machine learning engineer Lukas Atkins provided the entire Python library to the model and posed questions to help him solve problems. He said in the video, “It got it. It can find specific references to comments in the code and specific requests people made.”
Another tester recorded a video of his entire bookshelf, and Gemini created a database of all his books—a task that traditional AI chatbots would find almost impossible to accomplish.
Gemma 2 Dominates the Open Source Space
However, Google has also made waves in the open-source community. According to LLM Arena rankings, the company has released Gemma 2 27B today, an open-source large-scale language model that quickly takes the throne of open-source models with its top-quality and fast-response performance.
Google claims that Gemma 2 offers “first-class performance, runs at astonishing speed on different hardware, and can easily integrate with other AI toolkits.” The company states that it aims to compete with models “twice its size.”
Image: Google
Gemma 2’s license allows free access and redistribution but differs from traditional open-source licenses such as MIT or Apache. The model is designed for more accessible and budget-friendly AI deployment in the 27B and smaller 9B versions.
This is significant for both regular users and enterprise users because, unlike closed models, powerful open models like Gemma are highly customizable. This means users can fine-tune their models to excel in specific tasks and protect their data by running these models locally.
For example, Microsoft’s small-scale language model, Phi-3, has been specifically fine-tuned for mathematical problems and can outperform larger models like Llama-3 and even Gemma 2 in that field.
Image: Microsoft
Gemma 2 is now available in Google’s AI Studio, and model weights can be downloaded from Kaggle and Hugging Face Models, while the powerful Gemini 1.5 Pro is available for developers to test on Vertex AI.
