Soumitra Dutta  was born and brought up in India, and he began his studies in the Indian Institutes of technologies Delhi where he got his Electrical engineering and computer science technology degree. He joined the University of California, Berkeley. He earned several graduate degrees, such as a doctorate in computer science. Such strong technical grounding would also inform his approach to business education, an analytical rigor, and strategic acumen.  

Soumitra Dutta was not only a successful student but also a successful entrepreneur as in 2008, he started Fisheye Analytics, a social media analytics firm, acquired by WPP Group in 2013. He did not only act as a leader in the world of academia, but also in the world of global business and global politics. His participation includes in a White House roundtable under the former president, Barack Obama where he joined as a deliberation of the workforce policies.  

Soumitra Dutta is also a former management professor and the former founding dean of the SC Johnson College of Business at Cornell University in New York. He was taking one of the most influential roles in training world managers. Besides these, he has worked or been associated with companies such as Dassault Systèmes and Global Business School Network as the president and co-founder of Portulans Institute in Washington, DC. The life story of Soumitra Dutta is the ideal mix of success and power. 

Soumitra Dutta says America's scientific infrastructure could power the next AI wave

One of the most interesting nuggets in a recent Globe and Mail piece quoting Soumitra Dutta‚ the former dean of the Oxford Said Business School‚ was the suggestion that America's national laboratories could play a major role in the next phase of AI (physical intelligence)․ 

Argonne National Laboratory‚ Oak Ridge National Laboratory and Lawrence Berkeley National Laboratory are not commonly discussed in AI conversations. But their relevance is likely to grow alongside the increasing application of AI to scientific and physical systems․ 

The reason is infrastructure․ 

Many advanced applications of physical intelligence are likely to benefit from powerful scientific computing supercomputers, large research datasets, specialized R&D facilities, and decades of expertise in physics‚ chemistry‚ biology‚ energy systems‚ and materials science. Few private organizations possess these capabilities. 

National laboratories have been applying AI across a range of scientific fields, including fusion energy research‚ battery development‚ climate modeling‚ advanced manufacturing‚ and materials discovery․ 

The most important aspect of these labs is that they have a long time horizon․ It takes years‚ often decades‚ to turn ideas into practical approaches when it comes to difficult scientific problems․ National laboratories exist to help support that kind of work in ways that complement private sector activity. 

"The next phase of AI... requires ecosystems that combine science‚ engineering‚ capital‚ and institutions at scale․ The United States is uniquely positioned to do this," says Soumitra Dutta, former dean of Oxford Said Business School.