Samsung unveiled its generative AI model Samsung Gauss

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Samsung on Wednesday publicly unveiled its own generative AI model called Samsung Gauss for the first time.

The South Korean tech giant’s generative AI model is named after the famous mathematician Carl Friedrich Gauss who established the theory of normal distribution, popularly known as bell curve.

The name “reflects Samsung’s ultimate vision for models, which draw from the world’s phenomena and knowledge to harness the power of AI to improve the lives of consumers everywhere,” the company said. Samsung AI Forum, An annual AI forum hosted by Samsung Research and Samsung Advanced Institute of Technology in Seoul since 2017 for experts and academics.

Samsung said the model, which was developed by its research arm Samsung Research, is currently being used on employee productivity within the company but will be expanded to product applications in the future.

Samsung Gauss consists of Samsung Gauss language, Samsung Gauss code and Samsung Gauss images.

According to the tech giant, Language is a generative language model designed to increase work efficiency by helping with tasks such as writing emails, summarizing documents and translating, Samsung said, and can also improve the consumer experience by providing smart device control when applied to products. . The model itself consists of different models to apply to cloud and devices.

Code and the coding assistant called code.i are based on it for in-house software development of companies. It allows developers to code easily and quickly and supports functions such as code description and test case generation through an interactive interface, Samsung said.

Image, meanwhile, can easily create and edit images, allowing for style changes, additions, and converting low-resolution images to high-resolution ones, the tech giant added.

These models can be applied to devices to protect consumers’ personal information while Samsung has been working to use safe AI through its own AI Red team that examines security and privacy issues that may occur during data collection, AI model development, service deployment. and through the results generated.

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