Helping AI models to meet the real world
Through research and entrepreneurship, Professor Devavrat Shah is helping to design methods that can handle constant decision-making using limited computational resources. Through research and entrepreneurship, MIT Professor Devavrat Shah is helping to design methods that can handle constant decision-making using limited computational resources. David Chandler | Laboratory for Information and Decision Systems Publication Date : July 14, 2026 Press Inquiries Press Contact : Amanda Moore Email: amm@mit.
Key Takeaways
- edu Laboratory for Information and Decision Systems : While most AI models have been taught using text and images, a system developed by Devavrat Shah takes tabular data as its input - structured data such as the row-and-column format used in spreadsheets - and then provides real-time planning on a large scale.
- " The Andrew (1956) and Erna Viterbi Professor has been teaching at MIT since 2005.
In 2019, he also co-founded a spinoff company called Ikigai Labs.
- "My interest was: How does one design such graphical models for generic, tabular data?
While most AI models have been taught using text and images, this system takes tabular data as its input - structured data such as the familiar kind of row-and-column format used in spreadsheets.
- "Let's say you're making headphones and all sorts of different things.
And each of the products that you manufacture has lots of small pieces that come from different parts of the world.
- " He adds that all of these processes are interdependent, and at every stage of the processes decisions have to be made that have implications over time.
Through research and entrepreneurship, MIT Professor Devavrat Shah is helping to design methods that can handle constant decision-making using limited computational resources. Through research and entrepreneurship, Professor Devavrat Shah is helping to design methods that can handle constant decision-making using limited computational resources. David Chandler | Laboratory for Information and Decision Systems Publication Date : July 14, 2026 Press Inquiries Press Contact : Amanda Moore Email: amm@mit.
edu Laboratory for Information and Decision Systems : While most AI models have been taught using text and images, a system developed by Devavrat Shah takes tabular data as its input - structured data such as the row-and-column format used in spreadsheets - and then provides real-time planning on a large scale. Previous image Next image Systems using artificial intelligence to enhance forecasting, planning, and decision-making in businesses have been proliferating in recent years, but in many cases, they lack the detailed, specific information about the organization itself, limiting the usefulness of those tools. Devavrat Shah, a principal investigator at MIT's Laboratory for Information and Decision Systems (LIDS), faculty member with the department of Electrical Engineering and Computer Science (EECS), and member of the Institute for Data, Systems, and Society (IDSS), has been focused on how to design methods that can handle second-by-second decision-making using limited computational resources.
"In a sense, with a small amount of resource, you have to do a lot of heavy lifting," he says. As a researcher, "my interest is in the ability to develop methods that can extract information from data at scale in as effective a manner as possible. " The Andrew (1956) and Erna Viterbi Professor has been teaching at MIT since 2005.
For more details please read the original article at MIT News AI.
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