Dr. Mitchell Pryor earned is BSME at Southern Methodist University in 1993. After graduating, he taught math and science courses at St. James School in St. James Maryland before returning to Texas. He completed is Masters (1999) and PhD (2002) at UT Austin with an emphasis on the modeling, simulation, and operation of redundant manipulators. Since earning his PhD, Dr. Pryor has taught graduate and undergraduate courses in the mechanical and electrical engineering departments as well as led and conducted research in the area of robotics and automation in Mechanical Engineering, Petroleum Engineering and the Nuclear Engineering Teaching Laboratory. He has worked for numerous research sponsors including, NASA, DARPA, DOE, INL, LANL, ORNL, Y-12, and many industrial partners.

According to McKinsey, AI will create an estimated $13 trillion of GDP growth between now and 2030. As a comparison, the GDP of the entire United States of America was around 19 trillion in 2017. Leading AI scientists, like Andrew Ng, describe AI as the fourth industrial revolution or „the new electricity". AI is undoubtedly a centerpiece of digital transformation and its application throughout the industry will dramatically change our world and how we do business. The problem is that many people want to participate in this AI-revolution but they are overwhelmed by its technological sophistication. They don't know what AI is capable of, let alone how they could use it for their company.

The AI in Finance Summit is returning to New York due to popular demand, this time accompanied by the AI in Insurance Summit. Across 2 days, 400 attendees will come together to learn from over 60 speakers about the most cutting edge advancements in the application of AI in the financial and insurance industries. Topics covered will include investment, fintech, financial compliance, financial forecasting, fraud detection, responsibility, deep learning and more. As the discussions around regulation, cybersecurity and ethics increase, these topics will take centre stage across both tracks at the summit. Sessions will focus on the explainability of algorithms used within the financial industry, and there will be presentations for business leaders and decision makers specifically as well to compliment the technical sessions.

The RE•WORK AI in Finance summit is back in New York. Save 40% on your summit pass with code'BM20' https://bit.ly/2Ywz4ee

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Eric Topol is an American cardiologist and geneticist – among his many roles he is founder and director of the Scripps Research Translational Institute in California. He has previously published two books on the potential for big data and tech to transform medicine, with his third, Deep Medicine, looking at the role that artificial intelligence might play. He has served on the advisory boards of many healthcare companies, and last year published a report into how the NHS needs to change if it is to embrace digital advances. Your field is cardiology – what makes you tick as a doctor? I was in clinic all day yesterday – I love seeing patients – but I also try to use whatever resources I can, to think about how can we do things better, how can we have much better bonding, accuracy and precision in our care.

For most of us, caring for wounds is a matter of applying a bit of antiseptic to a cut finger and slapping on a bandage. But for Jerence Go, an Executive MBA participant at Cambridge Judge Business School (EMBA 2017), a traumatic event in his personal life led to a quest to improve wound care through artificial intelligence. In late 2015, Jerence recounts, his father was involved as a pedestrian in a serious road accident in the New York metropolitan area, causing lasting brain and bodily injuries. After his father had multiple surgeries, including neck and spinal titanium fusion, facial procedures and a tracheostomy, he spent the following years in hospitals, and acute and sub-acute facilities, before entering home care near New York City. At that time, Jerence was an executive responsible for EMEA sales and operations management for high-tech lasers and sensors automation company Keyence Corporation in Belgium.

NEW YORK, July 08, 2019 (GLOBE NEWSWIRE) -- Cowen Inc. (COWN) ("Cowen" or the "Company") and MassRobotics today announced a collaboration to bring together their extensive market knowledge to advance research into the emerging robotics and artificial intelligence industry. Based in the Boston area, MassRobotics is a global hub for robotics, and the collective work of a group of engineers, rocket scientists, and entrepreneurs focused on the needs of the robotics community. "The robotics and artificial intelligence industry is a rapidly expanding market, and one that will define the advancement of manufacturing and services on a global basis. We are thrilled to be partnering with such an innovative collective in MassRobotics, which was established through a shared vision of advancing the robotics industry," said Jeffrey M. Solomon, Chief Executive Officer of Cowen. "Cowen has dedicated substantial time into the research of robotics and AI and we look forward to sharing our knowledge and capital markets expertise to support the emerging growth companies associated with MassRobotics."

Employers are using artificial intelligence (AI) in recruiting chatbots, in video interviews to assess job candidates' body language or word choices, or to extract themes from engagement survey responses. But how companies are using AI to benefit the employee experience, support compliance efforts and ease administrative workloads is not as well-known. "So much of the buzz about AI has been for its'sexy' uses around sourcing and screening in recruiting, but there are a growing number of other applications of value to HR to be aware of," said Jeanne Meister, founding partner of Future Workplace, an HR advisory and research firm in New York City. One example of AI's expanding utility: using it to audit employees' expense reports, to ensure they comply with company policy and avoid wasteful spending. AppZen in Sunnyvale, Calif., uses AI to read and extract information from receipts to catch duplicates, out-of-policy spending, incorrect amounts or suspicious merchants.