Ben Vigoda

Ben Vigoda

Early life

After winning his local science fair in sixth grade with a laser, Vigoda became interested in artificial neural networks in seventh grade, and at the age of 15 interned in David Rumelhart's lab at Stanford University studying the effects of adding momentum terms to the back-propagation algorithm.[1]

Vigoda went on to graduate from Swarthmore Physics '97, and to complete his Master's and Phd in Neil Gershenfeld's Lab at MIT, MS ’99, PhD ’03, Post-Doctoral Fellow '04, MIT Visiting Scientist '05-'06.[2] He was an Intel Student Fellow at MIT,[3] and a Kavli Foundation/National Academy of Sciences Fellow,[4] won second place in the MIT $50k Entrepreneurship Competition,[5] and first place in the Harvard Business School New Ventures Competition.[6]

While at MIT, Vigoda also co-founded Design That Matters (DtM)[7] in 2001,[2] a student led seminar that engaged MIT students with problems in under-served communities and developing countries. Design That Matters projects have won several young innovator’s awards, generated significant licensing revenue, seeded a startup company, and led to the establishment of a not-for-profit organization to support these activities. He also built an interactive virtual juggling system for the Flying Karamazov Brothers that they used onstage for nearly a decade,[8] and co-founded the Experimental Musical Instrument Workshop at MIT that built novel instruments, hosted and recorded with composer John Zorn, and developed video documentary for Public Television.[9]

Career

In 2007, growing out of Vigoda's PhD at MIT and subsequent work as a Research Scientist at Mitsubishi Electric Research Labs (MERL), Vigoda co-founded and was CEO of Lyric Semiconductor,[10] which developed the first microprocessor and circuit architectures dedicated to statistical machine learning.[11][10]

At Lyric Vigoda helped author over 70 patents and scientific publications, and Lyric was named one of the 50 most innovative companies by MIT Technology Review.[12] Lyric was successfully acquired in 2011 by Analog Devices, and Lyric’s technology is deployed in leading smartphones and consumer electronics, medical devices, wireless base stations, and automobiles.[13]

Vigoda is currently the CEO and Founder of Gamalon. Funded by DARPA[14] and leading Venture Capital firms[15] to help develop a next generation of machine learning and AI technology,[16] Vigoda is leading the development at Gamalon of Idea Learning[17] and Bayesian Program Synthesis,[18] with first applications to structuring unstructured data.

Gamalon was recently identified by MIT as one of the twenty-five MIT STEX25 technology startups in 2017 "particularly well-suited for industry collaboration. These young, vibrant companies have proved themselves with early use cases, clients, demos, or partnerships, and may be on the cusp of significant growth."[18] Gamalon's work has been covered in Bloomberg BusinessWeek,[19] Forbes,[20] MIT Technology Review,[21] Wired,[22] The Christian Science Monitor,[23] TechCrunch,[24] and EE Times.[25]

From 2013 to 2016, Vigoda served on the DARPA Information Science and Technology (ISAT) study group.[7] He also co-authored a paper relating string theory and Markov chain Monte Carlo.[26]

Patents

References

  1. ↑ "Open Source Releases and The End of Season One". Talking Machines. Retrieved 2017-03-31.
  2. 1 2 "High probability of success". MIT News. Retrieved 2017-03-31.
  3. ↑ "events and talks abstract". www.cs.swarthmore.edu. Retrieved 2017-04-23.
  4. ↑ http://www.nasonline.org, National Academy of Sciences -. "Public Directory". www.nasonline.org. Retrieved 2017-05-13.
  5. ↑ "MITs Winning Entrepreneurs". www.bizjournals.com. Retrieved 2017-05-13.
  6. ↑ "Winners - New Venture Competition - Harvard Business School". www.hbs.edu. Retrieved 2017-05-12.
  7. 1 2 "MIT Technology Review Events Videos - When Machines Have Ideas". MIT Technology Review Events. Retrieved 2017-04-20.
  8. ↑ Benjamin Vigoda (2012-09-02), Ben_Vigoda_FKB_Virtual_Juggling.mov, retrieved 2017-05-13
  9. ↑ David Merrill (2006-12-29), the Experimental Musical Instrument Workshop at MIT, retrieved 2017-05-13
  10. 1 2 "High probability of success". MIT News. Retrieved 2017-04-23.
  11. ↑ Vance, Ashlee (2010-08-17). "Lyric Semiconductor Develops a Probability Chip". The New York Times. ISSN 0362-4331. Retrieved 2017-04-23.
  12. ↑ Review, MIT Technology. "Lyric Semiconductor - MIT Technology Review". MIT Technology Review. Retrieved 2017-05-13.
  13. ↑ "ADI buys Lyric - probability processing specialist | EE Times". EETimes. Retrieved 2017-04-23.
  14. ↑ "Probabilistic Programming for Advancing Machine Learning (PPAML)".
  15. ↑ "Gamalon, Inc. | crunchbase". www.crunchbase.com. Retrieved 2017-05-13.
  16. ↑ DARPAtv (2017-02-15), A DARPA Perspective on Artificial Intelligence, retrieved 2017-05-13
  17. ↑ "MIT Technology Review Events Videos - When Machines Have Ideas". MIT Technology Review Events. Retrieved 2017-05-13.
  18. 1 2 "New Startup, Gamalon, Invents And Commercializes Revolutionary Machine Learning Technology". Mit ILP. Retrieved 2017-04-20.
  19. ↑ "Here’s Why This Cat-Spotting AI Is Different". Bloomberg.com. 2017-02-14. Retrieved 2017-03-31.
  20. ↑ Tilley, Aaron. "This Startup Has Developed A New Artificial Intelligence That Can (Sometimes) Beat Google". Forbes. Retrieved 2017-05-13.
  21. ↑ Knight, Will. "AI software writes, and rewrites, its own code, getting smarter as it does". MIT Technology Review. Retrieved 2017-05-13.
  22. ↑ Metz, Cade. "AI’s Factions Get Feisty. But Really, They’re All on the Same Team". WIRED. Retrieved 2017-05-13.
  23. ↑ Wood, Charlie (2017-02-16). "Startup pairs man with machine to crack the 'black box' of neural networks". Christian Science Monitor. ISSN 0882-7729. Retrieved 2017-05-13.
  24. ↑ Mannes, John. "Gamalon leverages the work of an 18th century reverend to organize unstructured enterprise data". TechCrunch. Retrieved 2017-05-13.
  25. ↑ "Startup Schools Machine Learning | EE Times". EETimes. Retrieved 2017-05-13.
  26. ↑ Heckman, Jonathan J.; Bernstein, Jeffrey G.; Vigoda, Ben (2016-05-17). "MCMC with Strings and Branes: The Suburban Algorithm (Extended Version)". arXiv:1605.05334 Freely accessible [physics.comp-ph].
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