Samsung Electronics hosted the second day of the Samsung AI Forum 2023, which was led by Samsung Research and focused on generative AI. The rapid progress of generative AI technology is a paradigm shift that is expected to reshape both daily life and work. As such, the forum engaged AI experts from the industry and academia to discuss and share the development and the latest technological trends of AI, and introduced Samsung Gauss, the generative AI model developed by Samsung Research.
“We will continue to support and collaborate with the industry and academia on generative AI research.” said Daehyun Kim, Executive Vice President of the Samsung Research Global AI Centre, in his welcoming speech.
During the first morning session, Dr. Hyung Won Chung from OpenAI — an AI research and deployment company — explained the operation of large language models (LLMs) during his speech, titled, “Large Language Models (in 2023)” and addressed the challenges they face at each stage, as well as their future trajectory.
Then Jason Wei, a researcher at OpenAI and author of the “Chain-of-Thoughts” paper, discussed how LLMs will drive a paradigm shift in AI through his presentation, “New Paradigms in the Large Language Model Renaissance.”
In addition, Korea University Professor Hongsuck Seo presented some of the trends in multimodal AI technology capable of processing various data types simultaneously — including text and images — during his session, “Towards multimodal conversational AI.”
In the afternoon, graduate students from prominent domestic universities that are active in AI research presented their papers, which have been published in leading international AI journals. They also outlined their future research directions.
The team led by Seoul National University Professor Seung-won Hwang showcased an efficient code generation and search technology using generative AI, while Professor Gunhee Kim’s team demonstrated spatial reasoning technology using multimodal approaches.
Professor Minjoon Seo’s team from the Korea Advanced Institute of Science and Technology (KAIST) introduced fine-grained evaluation capability in language models. Additionally, the team led by Yonsei University Professor Jonghyun Choi presented on text-to-image generation technology capable of creating images by comprehending lengthy contexts across multiple sentences.
In the final session, the participants delved into Samsung Gauss and the On-Device AI technologies using this model. The model consists of Samsung Gauss Language, Samsung Gauss Code, and Samsung Gauss Image, and is named after Carl Friedrich Gauss, the legendary mathematician who established normal distribution theory, the backbone of machine learning and AI. Furthermore, the name reflects Samsung’s ultimate vision for the models, which is to draw from all the phenomena and knowledge in the world in order to harness the power of AI to improve the lives of consumers everywhere.
Samsung Gauss Language, a generative language model, enhances work efficiency by facilitating tasks such as composing emails, summarising documents and translating content. It can also enhance the consumer experience by enabling smarter device control when integrated into products.
Samsung Gauss Code and a coding assistant (code.i) — which operates based on it — are optimised for in-house software development, allowing developers to code easily and quickly. It also supports functions such as code description and test case generation through an interactive interface.
In addition, Samsung Gauss Image is a generative image model that can easily generate and edit creative images, including style changes and additions, while also converting low-resolution images to high-resolution.
Samsung Gauss is currently used on employee productivity but will be expanded to a variety of Samsung product applications to provide new user experience in the near future.
Samsung is not only developing AI technologies, but also moving forward with various activities that ensure safe AI usage. Through the AI Red Team, Samsung continues to strengthen the ability to proactively eliminate and monitor security and privacy issues that may arise in the entire process — ranging from data collection to AI model development, service deployment and AI-generated results — all with the principles of AI ethics in mind.
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