[Samsung AI Forum 2020] Day 1: How AI Can Make a Meaningful Impact on Real World Issues

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The Samsung AI Forum is an annual event that brings together globally renowned experts in the industry as well as across academia to serve as a platform with which to disseminate the very latest in AI trends, technologies and research.


This year’s AI Forum, the fourth of its kind, is being held over two days this November 2 and 3. The first day of the event, hosted by the Samsung Advanced Institute of Technology (SAIT), Samsung’s R&D hub dedicated to cutting-edge future technologies, is enabling participants to facilitate discussions around how to make the best use of AI technologies in a way that can benefit our daily lives in a rapidly changing world, particularly within the context of the unprecedented situations that have arisen recently due to the global pandemic.




AI Forum Day 1: The Past, Present and Future of AI

On November 2, Dr. Kinam Kim, Vice Chairman & CEO of Device Solutions at Samsung Electronics, commemorated the start of the first day of the AI Forum 2020 by delivering an opening speech that highlighted how AI technologies have shown remarkable progress over the years. He went on to note that, given these changes, many are expecting AI to address the issues brought on by the recent pandemic, but highlighted that since AI bases its models on massive amounts of real-life data and simulations, the task of modeling the current pandemic and other natural disasters with AI was a daunting one.


Dr. Kim went on to provide his own views on the ways in which AI technologies can move forward and be harnessed to have meaningful impact on real world problems, and also highlighted that Samsung Electronics, as a major provider of core technologies in the AI ecosystem, is proactively co-operating with global researchers to seek solutions to such real world problems. Dr. Kim ended his opening speech with the expectation that meaningful discussions on the present and future of AI technologies and their benefit for humanity were set to take place during this year’s Forum.



Recognizing Leading Talent in the Field

At this year’s AI Forum, Samsung introduced their inaugural Samsung AI Researcher of the Year awards with the view to identify prominent emerging researchers in the field from around the world and to support their research activities.


This year’s Samsung AI Research of the Year awards went to Professor Kyunghyun Cho of New York University, Professor Chelsea Finn of Stanford University, Professor Seth Flaxman of Imperial College London, Professor Jiajun Wu of Stanford University and Professor Cho-Jui Hsieh of UCLA.


Professor Kyunghyun Cho, a globally recognized researcher in natural language processing, has been publishing a consistent stream of acclaimed papers across the medicine, biology and optimization disciplines. “I am honored to have received a Samsung AI Researcher of the Year award and am committed to developing AI-focused research further down the road,” said Professor Cho of the recognition.



Expert Highlights: Keynote Speeches

Professor Yoshua Bengio, who served as this year’s co-chair and was selected as Samsung AI Professor of the Year, gave a presentation titled Towards Discovering Casual Representations. In his lecture, Professor Bengio explained that, up until now, conventional deep learning technologies have been relying on inference to recognize sensual information and learn from it, but AI technologies that are instead capable of learning the causality between hidden variables before drawing conclusions could be capable of making inferences just as humans do, and hence would be able to respond to unprogrammed situations. With visions of such a type of AI in mind, Professor Bengio shared the initial outcomes of his research and suggested how, based on this, AI technologies can make steps forward.


Professor Yann LeCun of New York University, a researcher who pioneered the Convolutional Neural Network widely applied to video recognition technologies, presented his latest model related to Self-Supervised Learning. Unlike supervised learning which returns a given answer to each given data set, self-supervised learning adopts a learning model consisting of autonomously creating questions within data and subsequently finding answers. Such a method has been applied to a massive linguistic model capable of generating sentences just as people do. Professor LeCun highlighted how self-supervised learning is similar to the way children experience and learn the world, and presented an energy-based model based on such a comparison.


Professor Chelsea Finn of Stanford University, a young researcher in the spotlight within the field of meta learning, gave a lecture titled From Few-Shot Adaptation to Uncovering Symmetries. In her lecture, Professor Finn introduced meta learning technologies in which AI, in spite of changes in data, can adapt swiftly to untrained data, and proceeded to share success stories of the application of these technologies in the areas of robotics and new drug candidate material design.


Professor Donhee Ham, Fellow at the Samsung Advanced Institute of Technology and Professor at Harvard University, delivered a presentation titled Reconstruction of the Brain. In his presentation, he highlighted that the current level of AI is based on the human brain but in fact works in a way different from how the brain functions, causing limitations to its capability. Professor Ham introduced cutting-edge neural science technologies that could mimic the structure and functionalities of the human brain circuit and create computer integrated circuits on their own.


Industry experts also took part in giving presentations. Dr. Tara Sainath of Google Research released the latest research outcomes of end-to-end models developed for speech recognition capable of enhancing the accuracy, efficiency and multi-lingual capability of voice assistant services widely available across smart devices.


Dr. Jennifer Wortman Vaughan of Microsoft Research gave a lecture titled Intelligibility Throughout the Machine Learning Life Cycle. She shared a human-centric machine learning concept, highlighting that, in order to develop a fair machine learning system capable of garnering the trust of people, people’s clear understanding of the system is required. Dr. Wortman Vaughan then introduced research outcomes that can objectively verify such a mechanism.


Since the Samsung AI Forum 2020 was held virtually this year, students and researchers alike in the AI research field from all over the world were able to engage in online discussions and exchanges. When tuning in to the Forum’s lectures on Samsung Electronics’ YouTube channel, attendees could ask questions to and receive answers from the distinguished speakers thanks to a real-time chat functionality.


Stay tuned to Samsung Newsroom for more information on the Samsung AI Forum 2020.

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