IBM and MIT recently launched a new collaborative research lab designed to propel breakthroughs in the field of artificial intelligence over the next decade. The deal involves a US$240 million dollar investment over 10 years from IBM, one of the largest ever seen between a university and a private company.
MIT is no stranger to the world of commercial enterprise with its Media Lab producing a number of startup companies over the past few years, but this is a huge scaling up compared to what has come before. The new enterprise will found what is being called the MIT-IBM Watson AI Lab. While the lab will focus on conceptual AI advances, one of the guiding principles behind the project is to encourage commercial and realistic outcomes for the innovations.
The announcement has outlined four pillars of research the lab will be focusing on: AI algorithm development, AI industry development, investigation of AI computer hardware support, and finally, a more general exploration into how AI can offer economic and societal benefits to a range of people around the world.
"In terms of applications, there are some particular targets we have in mind, including being able to detect cancer (e.g., by using AI with imaging in radiology to automatically detect breast cancer) well before we do now," explains Anantha Chandrakasan, dean of MIT's School of Engineering.
The MIT-IBM Watson AI Lab accompanies two other new project arms recently launched by MIT. The Engine is a startup support department designed to connect new organizations with specialized equipment, services and expertise. Meanwhile, MIT.nano, launching in 2018, will be a new 200,000-sq ft (1,858-sq m) faculty building directed solely towards the fields of nanoscience and nanotechnology.
This ambitious collaboration between the MIT and IBM is a giant statement about where future technological innovation will be concentrated. With the rise of autonomous cars and other technologies relying on big AI integration, this significant investment will undoubtedly deliver some exciting, and pragmatic, real-world outcomes over the coming decade.
Source: MIT News