Samsung Electronics on Nov. 21 hosted the Samsung Developer Conference Korea 2024 (SDC24 Korea), a virtual event that showcased the company’s latest software innovations and vision for the future.
Since 2014, Samsung Electronics has held the annual event to engage and collaborate with software developers, making SDC24 Korea the 11th iteration.
This year’s conference highlighted research related to software embedded in products, such as generative AI, software platforms, IoT, healthcare, communications and data. It also delved into the culture of open-source development.
During the keynote address, the company unveiled Samsung Gauss2, the second generation of its proprietary AI model, and highlighted its improved performance, efficiency and various application possibilities.
“Samsung Electronics is committed to developing cutting-edge software, including AI and data analytics, to enhance user experiences,” said Paul Kyungwhoon Cheun, President, CTO of the Device eXperience (DX) Division and Head of Samsung Research.
“With three distinct models, Samsung Gauss2 is already boosting our internal productivity, and we plan to integrate it into products to deliver higher levels of convenience and personalization.”
Samsung Gauss2: A Multimodal Language Model Catering to Diverse Needs
Samsung Gauss2 is the follow-up to the company’s internal generative AI model unveiled last year, and it offers improved performance and efficiency by simultaneously handling various data types as a multimodal model integrating language, code and images.
It is available in three distinct models catered to different purposes: Compact, Balanced and Supreme.
The Compact model is a small-sized model specifically designed to work efficiently, even in limited computing environments.
It delivers optimized performance for on-device usage by maximizing the utilization of the device’s computing resources.
On the other hand, the Balanced model focuses on achieving balance between performance, speed and efficiency, providing consistent performance across diverse tasks.
Finally, the Supreme model aims for a top-notch performance by leveraging the Mixture of Experts technology atop the Balanced model, allowing significant reductions in computational costs during training and inference processes while maintaining high levels of both performance and efficiency.
Samsung Gauss2 supports nine to 14 languages, as well as various programming languages, depending on the model. Samsung has developed and incorporated its own stabilization techniques for training large language models (LLMs) and designed a custom tokenizer2 to ensure maximum efficiency for these supported languages.
The Balanced and Supreme models offer equal or superior performance in key metrics such as generating responses in various languages including English and Korean, and coding capabilities compared to leading open-source generative AI models currently available.
Additionally, their processing speed per hour is 1.5 to three times faster, enabling quicker AI response generation, reduced user wait-times and more efficient task handling.
Customizable for Various Productivity Tasks and Product Development
Having an internal generative AI model allows easier customization so that optimal performance can be achieved for specific goals and applications. Samsung Gauss is already being used in various tasks for Samsung’s employees, leveraging its customizable development capabilities.
Samsung Electronics and Nvidia
Samsung Electronics shares were on the rise on Nov. 25 as Nvidia CEO Jensen Huang reportedly said the company was moving fast to approve Samsung’s delivery of AI memory chips.
Samsung Electronics shares shot up 2.24 percent compared to the previous trading session, trading at 57,200 won as of 9:20 a.m.
In an interview with Bloomberg TV at an awards ceremony to honor Huang with an honorary doctorate at the Hong Kong University of Science and Technology on Nov. 23, CEO Huang said Nvidia was considering receiving both the eight-layer and 12-layer products of the 5th generation of Samsung’s high-bandwidth memory (HBM), known as HBM3E.
