Samsung Exynos 2600 Chip Reduces AI Models by 90% to Promote Mobile Intelligence

South Korean media ETNews reported that Samsung Electronics will integrate Nota's AI model optimization solution into its latest Exynos2600 chip. This technological breakthrough allows the size of AI models to be compressed by more than 90% while maintaining high accuracy. This means that in the future, users will be able to run complex AI tasks more efficiently on mobile devices.

Nota is a South Korean company specializing in AI optimization technology, and their collaboration with Samsung is not the first time. In this cooperation, Nota will provide technical support for the Exynos2600 using its self-developed "NetsPresso" platform. NetsPresso can efficiently optimize and deploy AI models in different hardware environments, allowing large generative AI models to run smoothly on mobile devices without relying on internet connections.

The core goal of this collaboration is to promote the application of generative AI on Samsung's Exynos2600. With Nota's optimization technology, future mobile devices will be able to handle complex AI tasks, such as image generation and text creation, more easily. In addition, Nota will also participate in developing the next version of Samsung's AI model optimization toolchain "Exynos AI Studio," which will significantly improve the efficiency of developers deploying AI models on the Exynos platform, reduce development difficulty, and shorten product launch time.

This development marks Samsung's continuous efforts in the field of AI and brings more convenient and efficient intelligent experiences to users. As the technology continues to mature, we look forward to seeing more innovative applications based on Exynos2600.

Key points:

- 🤖 The Samsung Exynos2600 chip will integrate Nota's AI model optimization solution, compressing the model size by 90%.

- 📱 Nota's NetsPresso platform enables complex AI tasks to run smoothly on mobile devices without an internet connection.

- ⚙️ Nota will participate in the development of Exynos AI Studio, helping developers deploy AI models more efficiently.