Generative AI and Its Business Impact

March 14, 2024
10:00 AM - 12:00 PM EDT (UTC-4)
Generative AI and Its Business Impact
Leading Edge

Location

Zoom Webinar

 

 


Overview

Uncover the power of Generative AI in shaping the future of industries. Our expert speakers from MIT and industry will delve into its technology, applications, potential, and real-world impact on businesses. With its potential to disrupt virtually every industry, from healthcare to finance and from entertainment to manufacturing, generative AI stands at the forefront of the next technological revolution. Whether you're a corporate executive, tech enthusiast, entrepreneur, or industry professional, this Leading Edge webinar is tailored for you.

Key Highlights:

  • Deep insights into Generative AI technology
  • Real-world use cases and success stories
  • Opportunities and challenges in implementing Generative AI
  • Q&A session with MIT experts

Don't miss out on this opportunity to stay ahead in the dynamic world of AI!

  • Overview

    Uncover the power of Generative AI in shaping the future of industries. Our expert speakers from MIT and industry will delve into its technology, applications, potential, and real-world impact on businesses. With its potential to disrupt virtually every industry, from healthcare to finance and from entertainment to manufacturing, generative AI stands at the forefront of the next technological revolution. Whether you're a corporate executive, tech enthusiast, entrepreneur, or industry professional, this Leading Edge webinar is tailored for you.

    Key Highlights:

    • Deep insights into Generative AI technology
    • Real-world use cases and success stories
    • Opportunities and challenges in implementing Generative AI
    • Q&A session with MIT experts

    Don't miss out on this opportunity to stay ahead in the dynamic world of AI!

Register

Agenda

10:00 AM

Welcome & Introduction
Graham Rong
Director

Dr. Rong is Director of Corporate Relations at MIT. He currently supervises a group of ILP officers who promote and manage the interactions and relationships between the research at MIT and companies worldwide, particularly in greater China and extended Asian countries, to help them stay abreast of the latest developments in technology and business practices.

Previously, Dr. Rong founded IKA, LLC. He has led corporate development and product innovation, and provided strategic advices to companies in corporate strategy, IT leadership, digital transformation, AI, enterprise content management, and customer relationship. He held senior roles in Harte-Hanks and Vignette Corporation. He held an EU postdoctoral research fellowship in the University of Edinburgh in Scotland where he started global collaborative research.

Dr. Rong is on the board of multiple organizations, including 128CUTE since 2005 and MIT Sloan Alumni Association of Boston from 2009 to 2012. He chaired MIT Sloan CIO Symposium from 2009-2011. He is a senior expert invited by international organizations.

Dr. Rong holds a M.B.A. in global and innovation leadership from the MIT Sloan School of Management and Ph.D in numerical computing from University of Guelph in Canada.

10:05 AM

Applied Generative AI for Digital Transformation
Professor of Information Engineering, MIT Department of Civil and Environmental Engineering
John Williams
Professor of Information Engineering

John Williams holds a BA in Physics from Oxford University, a MS in Physics from UCLA, and a Ph.D. in Numerical Methods from University of Wales, Swansea. His research focuses on the application of large-scale computation to problems in cyber-physical security and energy. He is director of MIT’s Geospatial Data Center and from 2006-2012, was Director of the MIT Auto-ID Laboratory, where the Internet of Things was invented. He is author or co-author of over 250 journal and conference papers, as well as the books on Rock Mechanics and RFID Technology. He contributed to the 2013 report for the UK Office for Science Foresight Project- The Future of Manufacturing. Alongside Bill Gates and Larry Ellison, he was named as one of the 50 most powerful people in Computer Networks. He consults to companies including Accenture, Schlumberger, Shell, Total, Exxon, SAP Research, Microsoft Research, Kajima Corp, US Lincoln Laboratory, Sandia National Laboratories, US Intelligence Advanced Research Projects Activity, Motorola, Phillip-Morris Inc., Ford Motor Company, Exxon-Mobil, Shell, Total, and ARAMCO. His international collaborations include Oxford and Cambridge Universities, HKUST, KACST, Alfaisal University, PolyU Hong Kong, Imperial College of Science and Technology UK, Malaysia University of Science and Technology (MUST), and Masdar Institute of Science and Technology Abu Dhabi. He organized the first Cyber-Physical Security Conference in the UK (2011), and along with Dr. Sanchez, he runs the MIT Applied Cyber Security Professional Education summer course. At MIT, he teaches courses Architecting Software Systems (MIT 1.125) and Engineering Computation and Data Science (MIT 1.00/1.001). .

In data engineering and data science, early work included simulation of Ford's global network, and analysis of SAP smart grid billing system. For Altria, he analyzed the performance of item level tagging and also their implementation of an anti-counterfeiting system using the Electronic Product Code (EPC)

In password security, Dr. Williams was a PI that developed the algorithms for a negative password authentication system for the Intelligence Advanced Research Projects Activity (IARPA) agency.

Dr. Williams advises companies in the Americas, Europe, the Middle East, and Asia.

 

Dr. Williams affiliations include:

  • MIT Department of Civil and Environmental Engineering
  • MIT Center for Computational Science and Engineering (CCSE)
  • MIT Geospatial Data Center (GDC)
  • MIT Auto-ID Laboratory
  • MIT Center for Complex Engineering Systems (CCES)
  • MIT Consortium for Improving Critical Infrastructure Cybersecurity (IC3)

Generative AI is transforming how businesses approach problem-solving by automating creative processes, such as strategy development, software coding and generating creative images and videos. As we look to the future, the application of generative AI is expected to streamline data operations, automate white-collar workflows, foster innovation, and personalize customer experiences at an unprecedented scale. We will examine some of the issues and innovative solutions of present LLMs, particularly with respect to their handling of large data, such as document libraries, images, and videos and document retrieval using RAGs.  Furthermore, while generative AI may displace certain tasks, it also creates opportunities for new job categories, emphasizing the need for human-AI collaboration, and the necessity for rethinking and how work is done.

10:40 AM

Generative AI for Modeling and Designing New Materials: Connecting Disciplines, Scales, and Modalities
Jerry McAfee Professor of Engineering
MIT Department of Civil and Environmental Engineering,
MIT Department of Mechanical Engineering
Markus J. Buehler
Jerry McAfee Professor of Engineering
MIT Department of Civil and Environmental Engineering,
MIT Department of Mechanical Engineering

Dr. Markus J. Buehler, Jerry McAfee Professor of Engineering at MIT, is a leading researcher in materials science and the mechanics of natural and biological protein materials. Markus' expertise spans large-scale atomistic modeling, the interaction of chemistry and mechanics, and the development of multiscale simulation tools. He recently co-developed a method that uses artificial intelligence to generate new protein designs with specific strengths, mimicking natural materials like silk. This approach, which uses computer simulations for testing, allows the creation of proteins with desired mechanical properties, such as strength and flexibility, beyond what is naturally available. Markus earned a Ph.D. at the Max Planck Institute for Metals Research at the University of Stuttgart and held post-doctoral appointments at both Caltech and MIT.

In this talk, Prof. Buehler will explore the cutting-edge intersection of materials science, biology, and artificial intelligence. Generative AI models have the potential to revolutionize the way we understand, analyze, and design new materials. However, many AI models struggle to understand physical concepts, causing the models to "hallucinate," producing unreliable or even erroneous results. This talk discusses research that addresses these challenges by blurring the boundary between physics-based and data-driven modeling through a series of physics-inspired multimodal graph-based generative AI models set in a hierarchical multi-agent mixture-of-experts framework. We apply this new generation of models in the analysis and design of materials to mimic and improve upon biological materials. Focusing specifically on protein engineering, this talk discusses case studies covering distinct scales, from silk to collagen to biomineralized materials, as well as applications for medicine, food, and agriculture where materials design is critical to achieving performance targets. By harnessing AI's creative power for designing novel proteins, Prof. Buehler's research has opened new avenues in biomedicine, construction, and sustainability. This talk will journey into the future of materials science, demonstrating how generative AI's potential to solve complex challenges is just beginning to be unlocked.

11:15 AM

Industry Panel
Moderator:
Program Director, MIT Industrial Liaison Program
Jim Flynn
Jim Flynn
Program Director

Before MIT, Jim was the assistant dean of research business development at the UMass Amherst College of Information and Computer Sciences. Jim founded, built, and sold multiple technology companies in fintech and online media. He has bootstrapped startups and closed venture capital, angel, and private equity funding rounds. Jim also served as the Chief Operating Officer of a public company and a subsidiary of Pitney Bowes. He began his career at AT&T as a software developer, hardware engineer, and national account manager. Jim has authored patents and wrote one of the first books on Java programming. Out of all the roles he's held, Jim's favorite job title by far is dedicated dad of four. He earned a BS from Manhattan College and an MBA with concentrations in finance and international business from New York University.

Panelists:
d'Arbeloff Career Development Assistant Professor, MIT Department of Mechanical Engineering
Faez Ahmed
Faez Ahmed
d'Arbeloff Career Development Assistant Professor

Prof. Faez Ahmed is the d'Arbeloff Career Development Assistant Professor in the Department of Mechanical Engineering at the Massachusetts Institute of Technology (MIT). He leads the Design Computation and Digital Engineering (DeCoDE) lab, with a research focus on the synergy of machine learning and engineering design. His recent work addresses the synthesis of designs tailored to real-world constraints and promotes the collaborative potential between human designers and machines. Prior to his appointment at MIT, Prof. Ahmed was a postdoctoral fellow at Northwestern University and earned his Ph.D. in Mechanical Engineering from the University of Maryland. He has industrial experience in Australia's railway and mining sectors, where he championed data-driven predictive maintenance initiatives. Prof. Ahmed's vision is to create a world where humans and AI design together to solve our biggest challenges.

Innovation & Research Engineer, IT Innovation & Research, BMW Group
Noel Crawford
Innovation & Research Engineer, IT Innovation & Research

Noel Crawford is a Research Engineer with a focus on AI-centric applications. She has led development of applications and strategy for rapid adoption of Generative AI within BMW. Her interests include leveraging Generative AI for promoting DE&I within the workplace.

Vice President Technology Business, IBM
Nick Holda
Vice President Technology Business

Nick leads global strategic business development for IBM Software, focusing on generative AI for business. During his career, he also held positions at PreVeil, leading sales, marketing, and ecosystem for the cybersecurity startup, and as a project leader at Boston Consulting Group. Nick earned an an MBA from the MIT Sloan School of Management, where he was a Martin Trust Community Fellow.

CEO, Zapata.AI
Christopher Savoie
Christopher Savoie
CEO

Christopher Savoie is a published scholar in medicine, biochemistry, and computer science, and his research and business interests over the years have focused on the intersection of machine learning, biology, and chemistry. Christopher is the co-inventor of AAOSA, the A.I.-based natural language interface technology used to develop Apple’s Siri. He has led big data analytics efforts at Nissan and has previously founded and served as CEO of technology companies that have been acquired or exited via IPO. He a founding member the steering committee of the US Quantum Economic Development Consortium (QED-C). Christopher is also a licensed attorney and has served as the Vice-Chairman of the Big Data Committee of the American Bar Association and is founding and current Chair of thee QED-C Quantum Law technical advisory committee. He is a published legal scholar on liability issues surrounding Artificial Intelligence, Big Data, Information Security and Data Privacy and has lectured and taught continuing legal education courses on these subjects.

12:00 PM

Closing Remarks and Adjournment
  • Agenda
    10:00 AM

    Welcome & Introduction
    Graham Rong
    Director

    Dr. Rong is Director of Corporate Relations at MIT. He currently supervises a group of ILP officers who promote and manage the interactions and relationships between the research at MIT and companies worldwide, particularly in greater China and extended Asian countries, to help them stay abreast of the latest developments in technology and business practices.

    Previously, Dr. Rong founded IKA, LLC. He has led corporate development and product innovation, and provided strategic advices to companies in corporate strategy, IT leadership, digital transformation, AI, enterprise content management, and customer relationship. He held senior roles in Harte-Hanks and Vignette Corporation. He held an EU postdoctoral research fellowship in the University of Edinburgh in Scotland where he started global collaborative research.

    Dr. Rong is on the board of multiple organizations, including 128CUTE since 2005 and MIT Sloan Alumni Association of Boston from 2009 to 2012. He chaired MIT Sloan CIO Symposium from 2009-2011. He is a senior expert invited by international organizations.

    Dr. Rong holds a M.B.A. in global and innovation leadership from the MIT Sloan School of Management and Ph.D in numerical computing from University of Guelph in Canada.

    10:05 AM

    Applied Generative AI for Digital Transformation
    Professor of Information Engineering, MIT Department of Civil and Environmental Engineering
    John Williams
    Professor of Information Engineering

    John Williams holds a BA in Physics from Oxford University, a MS in Physics from UCLA, and a Ph.D. in Numerical Methods from University of Wales, Swansea. His research focuses on the application of large-scale computation to problems in cyber-physical security and energy. He is director of MIT’s Geospatial Data Center and from 2006-2012, was Director of the MIT Auto-ID Laboratory, where the Internet of Things was invented. He is author or co-author of over 250 journal and conference papers, as well as the books on Rock Mechanics and RFID Technology. He contributed to the 2013 report for the UK Office for Science Foresight Project- The Future of Manufacturing. Alongside Bill Gates and Larry Ellison, he was named as one of the 50 most powerful people in Computer Networks. He consults to companies including Accenture, Schlumberger, Shell, Total, Exxon, SAP Research, Microsoft Research, Kajima Corp, US Lincoln Laboratory, Sandia National Laboratories, US Intelligence Advanced Research Projects Activity, Motorola, Phillip-Morris Inc., Ford Motor Company, Exxon-Mobil, Shell, Total, and ARAMCO. His international collaborations include Oxford and Cambridge Universities, HKUST, KACST, Alfaisal University, PolyU Hong Kong, Imperial College of Science and Technology UK, Malaysia University of Science and Technology (MUST), and Masdar Institute of Science and Technology Abu Dhabi. He organized the first Cyber-Physical Security Conference in the UK (2011), and along with Dr. Sanchez, he runs the MIT Applied Cyber Security Professional Education summer course. At MIT, he teaches courses Architecting Software Systems (MIT 1.125) and Engineering Computation and Data Science (MIT 1.00/1.001). .

    In data engineering and data science, early work included simulation of Ford's global network, and analysis of SAP smart grid billing system. For Altria, he analyzed the performance of item level tagging and also their implementation of an anti-counterfeiting system using the Electronic Product Code (EPC)

    In password security, Dr. Williams was a PI that developed the algorithms for a negative password authentication system for the Intelligence Advanced Research Projects Activity (IARPA) agency.

    Dr. Williams advises companies in the Americas, Europe, the Middle East, and Asia.

     

    Dr. Williams affiliations include:

    • MIT Department of Civil and Environmental Engineering
    • MIT Center for Computational Science and Engineering (CCSE)
    • MIT Geospatial Data Center (GDC)
    • MIT Auto-ID Laboratory
    • MIT Center for Complex Engineering Systems (CCES)
    • MIT Consortium for Improving Critical Infrastructure Cybersecurity (IC3)

    Generative AI is transforming how businesses approach problem-solving by automating creative processes, such as strategy development, software coding and generating creative images and videos. As we look to the future, the application of generative AI is expected to streamline data operations, automate white-collar workflows, foster innovation, and personalize customer experiences at an unprecedented scale. We will examine some of the issues and innovative solutions of present LLMs, particularly with respect to their handling of large data, such as document libraries, images, and videos and document retrieval using RAGs.  Furthermore, while generative AI may displace certain tasks, it also creates opportunities for new job categories, emphasizing the need for human-AI collaboration, and the necessity for rethinking and how work is done.

    10:40 AM

    Generative AI for Modeling and Designing New Materials: Connecting Disciplines, Scales, and Modalities
    Jerry McAfee Professor of Engineering
    MIT Department of Civil and Environmental Engineering,
    MIT Department of Mechanical Engineering
    Markus J. Buehler
    Jerry McAfee Professor of Engineering
    MIT Department of Civil and Environmental Engineering,
    MIT Department of Mechanical Engineering

    Dr. Markus J. Buehler, Jerry McAfee Professor of Engineering at MIT, is a leading researcher in materials science and the mechanics of natural and biological protein materials. Markus' expertise spans large-scale atomistic modeling, the interaction of chemistry and mechanics, and the development of multiscale simulation tools. He recently co-developed a method that uses artificial intelligence to generate new protein designs with specific strengths, mimicking natural materials like silk. This approach, which uses computer simulations for testing, allows the creation of proteins with desired mechanical properties, such as strength and flexibility, beyond what is naturally available. Markus earned a Ph.D. at the Max Planck Institute for Metals Research at the University of Stuttgart and held post-doctoral appointments at both Caltech and MIT.

    In this talk, Prof. Buehler will explore the cutting-edge intersection of materials science, biology, and artificial intelligence. Generative AI models have the potential to revolutionize the way we understand, analyze, and design new materials. However, many AI models struggle to understand physical concepts, causing the models to "hallucinate," producing unreliable or even erroneous results. This talk discusses research that addresses these challenges by blurring the boundary between physics-based and data-driven modeling through a series of physics-inspired multimodal graph-based generative AI models set in a hierarchical multi-agent mixture-of-experts framework. We apply this new generation of models in the analysis and design of materials to mimic and improve upon biological materials. Focusing specifically on protein engineering, this talk discusses case studies covering distinct scales, from silk to collagen to biomineralized materials, as well as applications for medicine, food, and agriculture where materials design is critical to achieving performance targets. By harnessing AI's creative power for designing novel proteins, Prof. Buehler's research has opened new avenues in biomedicine, construction, and sustainability. This talk will journey into the future of materials science, demonstrating how generative AI's potential to solve complex challenges is just beginning to be unlocked.

    11:15 AM

    Industry Panel
    Moderator:
    Program Director, MIT Industrial Liaison Program
    Jim Flynn
    Jim Flynn
    Program Director

    Before MIT, Jim was the assistant dean of research business development at the UMass Amherst College of Information and Computer Sciences. Jim founded, built, and sold multiple technology companies in fintech and online media. He has bootstrapped startups and closed venture capital, angel, and private equity funding rounds. Jim also served as the Chief Operating Officer of a public company and a subsidiary of Pitney Bowes. He began his career at AT&T as a software developer, hardware engineer, and national account manager. Jim has authored patents and wrote one of the first books on Java programming. Out of all the roles he's held, Jim's favorite job title by far is dedicated dad of four. He earned a BS from Manhattan College and an MBA with concentrations in finance and international business from New York University.

    Panelists:
    d'Arbeloff Career Development Assistant Professor, MIT Department of Mechanical Engineering
    Faez Ahmed
    Faez Ahmed
    d'Arbeloff Career Development Assistant Professor

    Prof. Faez Ahmed is the d'Arbeloff Career Development Assistant Professor in the Department of Mechanical Engineering at the Massachusetts Institute of Technology (MIT). He leads the Design Computation and Digital Engineering (DeCoDE) lab, with a research focus on the synergy of machine learning and engineering design. His recent work addresses the synthesis of designs tailored to real-world constraints and promotes the collaborative potential between human designers and machines. Prior to his appointment at MIT, Prof. Ahmed was a postdoctoral fellow at Northwestern University and earned his Ph.D. in Mechanical Engineering from the University of Maryland. He has industrial experience in Australia's railway and mining sectors, where he championed data-driven predictive maintenance initiatives. Prof. Ahmed's vision is to create a world where humans and AI design together to solve our biggest challenges.

    Innovation & Research Engineer, IT Innovation & Research, BMW Group
    Noel Crawford
    Innovation & Research Engineer, IT Innovation & Research

    Noel Crawford is a Research Engineer with a focus on AI-centric applications. She has led development of applications and strategy for rapid adoption of Generative AI within BMW. Her interests include leveraging Generative AI for promoting DE&I within the workplace.

    Vice President Technology Business, IBM
    Nick Holda
    Vice President Technology Business

    Nick leads global strategic business development for IBM Software, focusing on generative AI for business. During his career, he also held positions at PreVeil, leading sales, marketing, and ecosystem for the cybersecurity startup, and as a project leader at Boston Consulting Group. Nick earned an an MBA from the MIT Sloan School of Management, where he was a Martin Trust Community Fellow.

    CEO, Zapata.AI
    Christopher Savoie
    Christopher Savoie
    CEO

    Christopher Savoie is a published scholar in medicine, biochemistry, and computer science, and his research and business interests over the years have focused on the intersection of machine learning, biology, and chemistry. Christopher is the co-inventor of AAOSA, the A.I.-based natural language interface technology used to develop Apple’s Siri. He has led big data analytics efforts at Nissan and has previously founded and served as CEO of technology companies that have been acquired or exited via IPO. He a founding member the steering committee of the US Quantum Economic Development Consortium (QED-C). Christopher is also a licensed attorney and has served as the Vice-Chairman of the Big Data Committee of the American Bar Association and is founding and current Chair of thee QED-C Quantum Law technical advisory committee. He is a published legal scholar on liability issues surrounding Artificial Intelligence, Big Data, Information Security and Data Privacy and has lectured and taught continuing legal education courses on these subjects.

    12:00 PM

    Closing Remarks and Adjournment