The following is the summary of a breakout session that was part of the 2016 Annual Conference.
Data gathering, signal extraction and pattern analytics make up the discipline of Data Science, while natural language processing, image understanding and decision are elements of Artificial Intelligence (AI). The overlap of it results in Machine Learning: methods used to devise complex models and algorithms that assist with predictions. Machine Learning is a subset of AI, and explores the study of algorithms that can learn from and make predictions in data. Various studies, research and examples were cited to introduce the topic, “Why AI Now?”. Examples of sensors and cameras found in smartphones, the number of hosted networks, clouds for storage, and increased data gathering all point to the current relevance of artificial intelligence.
The implication in the arts is a stunning example of artificial intelligence that creates artistic images. The use of neural representations that separate and then recombine content and style of arbitrary images provides a neural algorithm for the creation of artistic images. Moreover, this work offers a path forward to an algorithmic understanding of how humans create and perceive artistic imagery.
A new wave of the information era has arrived, where we now scale human knowledge. New systems, based on AI technology, now reads and understands language, making it possible for systems to learn, reason and interact with humans. Systems like Watson, IBM’s flagship AI platform and solutions, are leading the way. Since 2011, when Watson was introduced on the game show Jeopardy and defeated the best human champions, the healthcare and financial services industries have turned to Watson for advice and assistance for improved services to patients and customers.
In healthcare, Watson Oncology Solutions assists doctors by providing treatment options, clinical trial matchings and genomic sequencing. Watson for Radiology assists and improves the reading of all types of imaging. Watson for Population Health maintains millions of records to create an intersection between medical big data and medical knowledge. In financial services, Watson for Regulatory Compliance understands complex regulations and laws that improve the processes of financial institutions, while keeping all parties aligned with current regulations.
The Internet of Things (IoT) is the internetworking of things such as physical devices, vehicles and buildings that are embedded with electronics, software, sensors, actuators and network connectivity that enable objects to collect and exchange data. More simply, IoT is the world where physical objects are connected to the internet and communicate with each other. Examples include construction machinery, jet engines and self-driving vehicles. Detection and recognition, analysis and decision and action control are areas that are enhanced through artificial intelligence and IoT systems. Challenges in IoT and the AI business include: achieving performance within reasonable costs; cyber security standardization and agreement on the system and technology by various stakeholders; and social consensus on sensitive matters such as privacy of personal data, and who is accountable for outcomes.
The balance between human influence and artificial intelligence, human control versus AI control and decision-making, and the ethics surrounding the utility of AI are areas that are certain to be of great importance in the near future.