Neil Jacobstein

Teknowledge Chairman & CEO

Innovative Applications of Early Stage AI
22 minutes, 10.5mb, recorded 2007-09-08
Neil Jacobstein

Through his consulting work with some of the largest companies and organizations on the planet, Neil Jacobstein has worked with AI in the real world in many capacities. While human level artificial general intelligence hasn't happened yet, early stage AI systems have created billions of dollars of value, working in dozens of diverse fields. He gives the results of a survey of hundreds of AI applications in fields ranging from computer software to paleontology to treaty verification. AI systems routinely do specialized tasks faster and more accurately than skilled human workers, and expand the range of what's possible.

Early AI systems were built from the ground up, on high-end hardware and poorly integrated into existing programs, enterprises, organizations. This was tolerated because of the huge value they created, but modern systems are much better integrated into their client companies. Now they are delivered as part of integrated systems, incorporating mainstream languages (not just Lisp), with web and other public interfaces. They have moved from domain specific tools to useful customer applications.

Jacobstein closes with a list of 10 rules when developing a real world AI system, as well as several predictions of how early stage AI will develop over the next few years.


Neil Jacobstein is chairman and CEO of Teknowledge Corporation. He has served as a technical consultant on software research and development projects for NSF, DARPA, NASA, NIH, EPA, DOE, the U.S. Army and Air Force, GM, Ford, Boeing, Applied Materials, and other agencies. In 1999, he co-chaired the American Association for Artificial Intelligence's 16th Innovative Applications of Artificial Intelligence Conference, and chaired the 17th IAAI Conference in 2005. In 1999, he was selected as an Aspen Institute Henry Crown Fellow. Since 1992, he has served as chairman of the Institute for Molecular Manufacturing, a not-for-profit research group focused on the long-term feasibility, embedded safeguards, and applications of molecular manufacturing. He was the leading co-author of the Foresight Guidelines for Responsible Nanotechnology Development. In 2006, he became a senior research fellow in the Digital Visions Program at Stanford University.

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