New venture capital program seeds MIT commercial AI research

MIT has launched a new program to support research into AI, data science, and machine learning, with a focus on making the new technologies more commercial

The MIT School of Engineering has launched a one-year pilot program to provide seed grants for artificial intelligence, machine learning, and data science projects which will be used to develop prototypes and find new markets for AI-powered products and services. 

The new MIT-Pillar AI Collective is funded by Pillar VC and will support graduate and postdoctoral students with investment and mentorships. Administered by the MIT Deshpande Center for Technological Innovation, the Collective will focus on a market discovery process, building projects with market research, customer discovery, and prototyping. 

Each team will have access to prospective customers across a variety of industries who are actively interested in leveraging new AI-enabled solutions, say organisers. Teams will also conduct customer interviews to identify promising new applications.

“We are grateful for this support from Pillar VC and to join forces to converge the commercialisation of translational research in AI, data science, and machine learning, with an emphasis on identifying and cultivating prospective entrepreneurs,” says Anantha Chandrakasan, Dean of the MIT School of Engineering and Vannevar Bush Professor of Electrical Engineering and Computer Science. “Pillar’s focus on mentorship for our graduate students and postdoctoral researchers, and centring the program within the Deshpande Center, will undoubtedly foster big ideas in AI and create an environment for prospective companies to launch and thrive.” 

Pillar VC founder Jamie Goldstein says his company is committed to growing companies and investing in personal and professional development, coaching, and community. 

“Many of the most promising companies of the future are living at MIT in the form of transformational research in the fields of data science, AI, and machine learning,” says Goldstein. “We’re honoured by the chance to help unlock this potential and catalyse a new generation of founders by surrounding students and postdoctoral researchers with the resources and mentorship they need to move from the lab to industry.”

Finding opportunities in AI, machine learning, and data science

Funding will be provided for up to nine research teams, and the program will launch in the 2022-23 academic year. Grants will be open only to MIT faculty and students, with an emphasis on funding for postdocs as well as graduate students in their final year. 

A selection committee composed of three MIT representatives will include Devavrat Shah, Faculty Director of the Deshpande Center, and a representative from the MIT Schwarzman College of Computing. The committee will also include representation from Pillar VC. 

“The Deshpande Center will serve as the perfect home for the new collective, given its focus on moving innovative technologies from the lab to the marketplace in the form of breakthrough products and new companies,” adds Chandrakasan. 

“The Deshpande Center has a 20-year history of guiding new technologies toward commercialisation, where they can have a greater impact,” says Shah. “This new collective will help the centre expand its own impact by helping more projects realise their market potential and providing more support to researchers in the fast-growing fields of AI, machine learning, and data science.”


Featured Articles

Why are the UK and China Leading in Gen AI Adoption?

China and the UK are leading the adoption of Gen AI, which although sounds surprising to begin with, becomes clearer as you dig into their state strategies

Moody's Gen AI Tool Alerts CRE Investors on Risk-Posing News

Moody's new Early Warning System will use Gen AI to monitor breaking news headlines and alert clients on how it could impact their real estate portfolios

AWS Unveils AI Service That Makes Enterprise Apps in Minutes

Amazon Web Services' new App Studio offers low-code solutions so those not too familiar with code create applications for internal processes in minutes

Jitterbit CEO: Confronting the Challenges of Business AI

AI Strategy

Graphcore: Who is the Nvidia Challenger SoftBank Acquired?


Amazon Takes On AI Hallucinations Across Its AI Portfolio

Machine Learning