KEYNOTE SPEAKERS
Wednesday, September 26
David Newman
Strategic Planning Manager, Senior VP, Innovation R&D, Wells Fargo Bank, USA
Ontologies, Knowledge Graphs and AI: The Future of Data
Abstract: We are at a critical junction in the evolution of data within the enterprise. Organizations are beginning to realize that the legacy relational model may not be sustainable for the future. There is increasing curiosity about emerging trends in data management based on ontologies, semantic technology and knowledge graphs. This presentation will focus on identifying some of the critical challenges in data management within legacy environments. We will identify how ontologies may provide a new foundation for data and data lakes. We will also focus on how ontologies and machine learning converge together in the form of knowledge graphs A vision for the future of data based on AI will also be presented.
Bio: David provides leadership and expertise for the advancement of knowledge graph and machine intelligence based data strategies, capabilities, and technologies for Wells Fargo. David’s team develops and prototypes innovations that employ various AI technologies for business value, which includes semantic web technology, machine and deep learning, and natural language processing.
David also chairs the Financial Industry Business Ontology (FIBO) initiative, which is a collaborative effort of global banks and vendors, under the auspices of the Enterprise Data Management Council, to semantically define a common language standard for finance using semantic technology. David is engaged in a variety of operational applications of the FIBO ontology. This includes risk management and regulatory compliance; using FIBO as a scaffolding for building enterprise ontologies and data lakes, as well as using FIBO as a means to optimize and better exploit machine learning for finance. David holds an MBA in Information Systems and an MSW in Psychiatric Social Work.
Thursday, September 27
Nestor Rychtyckyj
Sr. Analytics Scientist, Global Data Insight & Analytics, Ford Motor Company, USA
Avoiding the Road to Ruin: Creating Success with AI in Industry
Abstract: We are in the midst of another boom in Artificial Intelligence, which we have not seen for quite a while. History has shown us that expert systems, artificial neural networks, fuzzy logic and evolutionary computation have all been heralded as the dawn of a new era in Artificial Intelligence. This current resurgence in AI is powered primarily through data-driven approaches such as deep learning in conjunction with advances in big data. There has been great progress made, but we are realizing that these approaches also have limitations. AI is a lot more than Machine Learning and future progress will depend on the integration of semantic and cognitive computing approaches along with machine learning and lots of data.
For industry, the enormous investment in AI also brings the responsibility to deliver AI/ML systems that justify these costs. The technology may be changing, but the factors needed for success still include tried and true methods such as clear problem definition, management support, user cooperation and enthusiasm, a skilled development team, project planning, testing and maintenance. The use of technologies such as deep learning, distributed file systems and GPU processing does not negate the need for delivering solutions that solve real business problems.
In this talk I will discuss some of the AI systems that I have been involved in throughout my career at Ford – some successful and others not so much. I want to focus on the critical success factors for building and deploying AI systems that work in industry and demonstrate how they matter even more in our current Machine Learning/Big Data world. Lastly, I want to show how semantics and cognitive computing still have a critical role to play in AI and may lead us into an era where AI finally delivers on its promise.
Bio: Nestor Rychtyckyj is a Senior Analytics Scientist in the Machine Learning & Scalable Computing group as part of Global Data Insight & Analytics at Ford Motor Company. His responsibilities include the application of machine learning, natural language processing, semantic computing and machine translation for manufacturing, quality, customer interaction and cybersecurity. Previously Nestor was responsible for the development and deployment of AI-based systems for vehicle assembly process planning and ergonomic analysis. Nestor has published over 40 papers and has presented at conferences such as IAAI (Innovative Applications of Artificial Intelligence) and the International Conference on Semantic Computing. He received his Ph.D. in Computer Science from Wayne State University in Detroit, Michigan. He also chaired the IAAI conference in 2010 and was co-chair for Cybernetics at the IEEE Systems, Man & Cybernetics conference in 2011. Nestor is a senior member of AAAI and IEEE (SMC) and a member of ACM.
Thursday, September 27
James C. Ram
President, A.I. Solve, UK
AI in a New World Order
Abstract: Technological progress is a main driver of economic growth and improvements in living standards over the long term. It increases overall productivity, thereby boosting per capita income and consumption. While new technologies hold immense promise, they are also seen as a threat, potentially disrupting labor markets and contributing to income inequality. The biggest public fear is that robots and artificial intelligence will replace human jobs on a large scale, resulting in mass unemployment around the world. As machines did with muscle power in the past, AI is challenging to substitute brainpower in revolutionary technological way.
Furthermore, decisions based on data alone are not necessarily free of bias. For instance, machines learn very quickly to exhibit some of the worst traits of humanity, such as being racist or sexist. ProPublica found that a US court program to assess risks of reoffending prisoners was systematically biased against black prisoners – flagging them as almost twice as likely to reoffend as white prisoners. This assessment was based on questions such as parents’ history with correctional services and use of drugs by friends and acquaintances. It did not even include any questions on race and yet the system was biased based on the inputs it had received.
Treating AI as a savior of all is woefully naive. As with any technology, it holds promises and risks and that is why we need to heed the wisdom of Winston Churchill, “The price of greatness is responsibility” as we proceed with the many and wide uses of AI.
Bio: James C. Ram has been brought in as President of A.I Solve, a technology based VR Entertainment and Training company to help them grow in the Americas and beyond. Previously Ram was Founder and President of Indusa Global LLC, an information systems firm located in Atlanta, Georgia with additional offices in Montego Bay, Jamaica, Nassau, Bahamas and Calcutta, India. In 2015, Ram became the co-creator of Avatron Park, an interactive theme park concept that was proposed in Atlanta using cutting edge, user-centered design and technology to provide an immersive experience for its guests. Ram began his career at United Nations when he was appointed as the youngest Director and Senior Fellow at the United Nations Institute for Training & Research (UNITAR) by the UN Under Secretary General, Dr. Michel Doo Kingue. Ram represented Southern Company, Delta Air Lines and Turner Broadcasting Corp. in their bid to establish an off-shore IT presence in India.
Friday, September 28
Ravi Iyer
Intel Fellow, Datacenter Group, Intel Corporation, USA
The Era of AI: Opportunities for Industry Transformation and Research Challenges
Abstract: The emergence of AI capabilities is rapidly helping transform industries and enabling new usage opportunities and research challenges. In this talk, I will start by presenting examples of exciting usages and outline applications of AI in the short-term. I will also outline emerging challenges by describing how the AI research as well as the usage landscape is evolving and outline long-term research challenges that need to be solved. These developments bring forth technical challenges that can be solved jointly by industry and academia. The talk will describe examples of research in algorithms, HW/SW platforms as well as end-to-end AI solutions.
Bio: Ravi Iyer is an Intel Fellow and works in Intel’s datacenter group on AI, visual and cloud/edge platforms. He has published >150 papers in areas such as high performance server and low power SoC architectures, accelerators, cache/memory hierarchies, QoS, workload characterization and performance analysis. He has filed more than 70 patent applications. He participates frequently in conferences and journals. Most recently he was the general chair of the IEEE/ACM PACT 2017 conference. He received his Ph.D in Computer Science from Texas A&M University. He is also an IEEE Fellow.