Samsung Electronics is committed to leading advancements in the field of artificial intelligence. To discuss what the future may hold for AI technology, and to address and overcome the technological challenges that researchers are currently facing, the company recently hosted its third annual Samsung AI Forum in Seoul. The event featured renowned AI experts from around the world, who offered its ideas for addressing some of the most pressing challenges facing AI research today. Modern AI technology is not only capable of analyzing data with algorithms, it’s also making strides toward achieving human-like cognition. With increases in computing power and advances in deep learning, AI technology is attempting to analyze data on its own, and learning to identify the most appropriate response for a given situation or context. The application of big data in deep learning is accelerating this trend. While recent advancements have proven promising, the speakers at the AI forum agreed that certain technological challenges remain unaddressed. Prof. Kyunghyun Cho of New York University put the technology’s current status in simple terms. “Imagine a hypothetical AI agent equipped with the current technology – he said -. It has barely opened its eyes so that it can see and detect objects; it has barely opened its ears to listen to people and hear what they are saying; it has barely opened its mouth to speak short utterances; it is barely learning to move its limbs. In other words, we have just taken a tiny step toward building a truly intelligent machine – or a set of algorithms to drive such an intelligent agent”. Prof. Noah Smith of the University of Washington expanded on this point, noting that “we’ve seen a lot of progress through the use of increasingly ‘deep’ neural networks trained on ever-larger datasets”. Prof. Smith also identified preparing efficient algorithms, reducing system construction costs and improving data learning methods as points that will need to be addressed in order to take AI technology to the next level. The speakers also offered their opinions on where AI advancements should focus next, spotlighting things like wireless network controls, increasing AI’s autonomy, expanding AI’s applications in chemical and biological research, and streamlining interactions between humans and AI. As Prof. Abhinav Gupta of Carnegie Mellon University explained, “in the past few years, we have made significant advancements in AI, but most of these advancements have been in solving specific tasks where lots of data and supervision are available. On the other hand, humans can perform hundreds of thousands of tasks, often with little to no supervision or data for them. This is the next frontier in AI: developing general purpose smart and intelligent agents without access to lots of data and supervision”.