Faculty
Rama Ramakrishnan is a Professor of the Practice at the MIT Sloan School of Management.
His teaching, research, and advisory interests center on the practical application of Predictive and Generative AI techniques to problems and opportunities in industry and in the creation of intelligent products and services.
Prior to joining MIT Sloan, Rama was a tech entrepreneur and executive for over 20 years. He has founded or has been a senior executive in four software companies that have exited to technology titans: Oracle, Salesforce, and Demandware. He is active in the startup ecosystem as an advisor, angel investor, and board member.
Most recently, Rama was senior vice president at Salesforce (NYSE: CRM) and chief data scientist for Salesforce Commerce Cloud. In this role, he led Salesforce Einstein for Commerce—the analytics/machine-learning platform that powers Salesforce Commerce Cloud—and was responsible for product management, engineering, data science, and cloud production operations. The Einstein platform uses analytics techniques to predict and influence the shopping behavior of hundreds of millions of unique shoppers monthly.
The path that led Rama to Salesforce started in July 2010 when he founded a startup, CQuotient, to build a data-science-based personalization platform for retail and e-commerce. Backed by funding from Bain Capital Ventures, Rama built and grew the company to a successful exit to Demandware (NYSE: DWRE) in October 2014. As a member of the Demandware executive team, Rama was involved in the successful sale of Demandware to Salesforce in July 2016 for $2.8 billion. CQuotient technology, now known as Salesforce Einstein for Commerce, is one of the top B2C recommendation engines in the world and influences the shopping behavior of billions of consumers annually.
Prior to founding CQuotient, Rama taught analytics at MIT Sloan, was chief scientist and vp of R&D at ProfitLogic, was chief analytics officer and vp of R&D for the retail business of Oracle, founded two analytics companies, and was a consultant at McKinsey & Company.
Rama has a BTech degree from the Indian Institute of Technology, Chennai and MS and PhD degrees from MIT.
Recent Writing
Extract just what you need from long LLM responses (August 2024) Using LLMs in business: A few guidelines (May 2024) How to use LLMs as "helpers" to build and customize other LLMs (January 2024) Get better answers from ChatGPT by using custom instructions (December 2023)How ChatGPT can answer complex questions and execute actions on your behalf using external tools - A non-technical explainer, June 14, 2023
The Road To ChatGPT - An Informal Explainer On How ChatGPT Was Built, March 5, 2023
How Big Should Your Sample Size Be? A Handy Little Formula Every Data Scientist Should Know, December 14, 2022
How to Build Good AI Solutions When Data Is Scarce, MIT Sloan Management Review, November 23, 2022
From Prediction to Action — How to Learn Optimal Policies From Data (4/4), August 12, 2021
From Prediction to Action — How to Learn Optimal Policies From Data (3/4), August 7, 2021
From Prediction to Action — How to Learn Optimal Policies From Data (2/4), July 21, 2021
From Prediction to Action — How to Learn Optimal Policies From Data (1/4), June 10, 2021
... more
Recent Press
Meet Khan Academy’s chatbot tutor, CNN, August 21, 2023A technophobe's guide to chatbots, The Boston Globe, July 10, 2023
Ideas about how to best deploy generative artificial intelligence, how it will affect the workforce, and how it should be regulated.
Artificial intelligence is everywhere. But it’s humble leadership that leads our list.
"A rigorous evaluation process is a key driver of success for LLM application development projects."
"By following a systematic approach, businesses can leverage the powerful capabilities of modern AI systems while mitigating their risks."
"The number of searches going through an LLM is going to go up, and therefore, probably, the energy costs are going to go up."
“It’s not trying to come up with a truthful answer to your question, just a plausible answer."
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