Robohub.org
 

CSAIL launches artificial intelligence initiative with industry

by
12 April 2017



share this:

MIT Professor Daniela Rus, director of CSAIL, said the goal of a new SystemsThatLearn@CSAIL initiative is “to create a new generation of AI tools that are deeply rooted in systems.” Photo: Jason Dorfman/MIT CSAIL

From self-driving cars to the internet of things, artificial intelligence (AI) has reached new levels of sophistication in recent years. With that in mind, this week MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) launched an industry collaboration focused on using machine learning to create functional human-like systems.

Nearly 40 senior researchers will participate in the new “SystemsThatLearn@CSAIL” (STL) initiative alongside a range of organizations that include founding members BT, Microsoft, Nokia Bell Labs, Salesforce, and Schlumberger. Member companies will work with CSAIL scientists to suggest new lines of research and develop real-world applications.

“Developing capabilities in AI and machine learning are key to the future of fields like finance, energy, manufacturing, and health care,” says STL Executive Director Lori Glover. “While the demand for expertise is great, the supply of talent remains small and unevenly distributed. By democratizing the field of AI, SystemsThatLearn@CSAIL is an effort to address that skills gap.”

STL builds on CSAIL’s Big Data Initiative, which developed tools for handling complex datasets. While many machine-learning solutions are trained and deployed in separate phases, STL aims to integrate these processes, focusing on a range of resources to handle distributed data and computing power.

Another goal is to make key aspects of data science less laborious. A 2016 report found that data scientists spend 80 percent of their time collecting and organizing data, and only 20 percent analyzing it.

“By promoting industry interaction with academia, we’re hoping to create new tools and systems that can increase productivity by automating much of the tedious work of data science,” says MIT Professor Samuel Madden, one of STL’s two faculty leads alongside Professor Tommi Jaakkola. “We are already seeing that areas like autonomous vehicles and personalized health care have the potential to transform entire industries.”

In her opening remarks, CSAIL Director Daniela Rus described AI and systems researchers as two communities that would benefit from stronger collaboration.

“Our grand vision is to create a new generation of AI tools that are deeply rooted in systems and that can make those systems better,” Rus said. “My aspiration is to get to a place where machine learning becomes a normal part of what an operating system does.”

One STL project is the data discovery tool “Data Civilizer,” which allows organizations to discover related datasets from thousands of distinct business databases and files. Another is “Model DB,” a machine-learning management system that saves time for data scientists and lets them easily correlate performance on particular training examples with specific model features.

According to STL Technical Director Stephen Buckley, many of the software tools they develop will be released under MIT’s open source license.

“The ultimate aim is to democratize access and use of machine learning tools, without requiring advanced knowledge of the underlying technologies,” says Buckley.



tags: , , , , , , ,


CSAIL MIT The Computer Science and Artificial Intelligence Laboratory – known as CSAIL ­– is the largest research laboratory at MIT and one of the world’s most important centers of information technology research.
CSAIL MIT The Computer Science and Artificial Intelligence Laboratory – known as CSAIL ­– is the largest research laboratory at MIT and one of the world’s most important centers of information technology research.





Related posts :



Robot Talk Episode 35 – Interview with Emily S. Cross

In this week's episode of the Robot Talk podcast, host Claire Asher chatted to Professor Emily S. Cross from the University of Glasgow and Western Sydney University all about neuroscience, social learning, and human-robot interaction.
03 February 2023, by

Sea creatures inspire marine robots which can operate in extra-terrestrial oceans

Scientists at the University of Bristol have drawn on the design and life of a mysterious zooplankton to develop underwater robots.
02 February 2023, by

Our future could be full of undying, self-repairing robots – here’s how

Could it be that future AI systems will need robotic “bodies” to interact with the world? If so, will nightmarish ideas like the self-repairing, shape-shifting T-1000 robot from the Terminator 2 movie come to fruition? And could a robot be created that could “live” forever?
01 February 2023, by

Sensing with purpose

Fadel Adib uses wireless technologies to sense the world in new ways, taking aim at sweeping problems such as food insecurity, climate change, and access to health care.
29 January 2023, by

Robot Talk Episode 34 – Interview with Sabine Hauert

In this week's episode of the Robot Talk podcast, host Claire Asher chatted to Dr Sabine Hauert from the University of Bristol all about swarm robotics, nanorobots, and environmental monitoring.
28 January 2023, by

Special drone collects environmental DNA from trees

Researchers at ETH Zurich and the Swiss Federal research institute WSL have developed a flying device that can land on tree branches to take samples. This opens up a new dimension for scientists previously reserved for biodiversity researchers.
27 January 2023, by





©2021 - ROBOTS Association


 












©2021 - ROBOTS Association