From their early days at MIT, and even before, Emma Liu '22, MNG '22, Yo-whan "John" Kim '22, MNG '22, and Clemente Ocejo '21, MNG '22 knew they wanted to perform computational research and explore artificial intelligence and machine learning. "Since high school, I've been into deep learning and was involved in projects," says Kim, who participated in a Research Science Institute (RSI) summer program at MIT and Harvard University and went on to work on action recognition in videos using Microsoft's Kinect. As students in the Department of Electrical Engineering and Computer Science who recently graduated from the Master of Engineering (MEng) Thesis Program, Liu, Kim, and Ocejo have developed the skills to help guide application-focused projects. Working with the MIT-IBM Watson AI Lab, they have improved text classification with limited labeled data and designed machine-learning models for better long-term forecasting for product purchases. For Kim, "it was a very smooth transition and … a great opportunity for me to continue working in the field of deep learning and computer vision in the MIT-IBM Watson AI Lab." Collaborating with researchers from academia and industry, Kim designed, trained, and tested a deep learning model for recognizing actions across domains -- in this case, video.

From our attitude towards work to our grasp of what two metres look like, the coronavirus pandemic has made us rethink how we see the world. But while we've found it hard to adjust to the new reality, it's been even harder for the narrowly-designed artificial intelligence models that have been created to help organisation make decisions. Based on data that described the world before the crisis, these won't be making correct predictions anymore, pointing to a fundamental problem in they way AI is being designed. David Cox, IBM director of the MIT-IBM Watson AI Lab, explains that faulty AI is particularly problematic in the case of so-called black box predictive models: those algorithms which work in ways that are not visible, or understandable, to the user. "It's very dangerous," Cox says, "if you don't understand what's going on internally within a model in which you shovel data on one end to get a result on the other end. The model is supposed to embody the structure of the world, but there is no guarantee that it will keep working if the world changes."

Created in 1995 by the Engineering Faculty of the University of Mons, the research innovation center of Multitel has adopted IBM Watson Machine Learning Accelerator to harness the power of deep learning (DL) and tackle some of the biggest challenges of our time. Jean-Yves Parfait, AI Team Leader at Multitel and Franz Bourlet, Power Systems Expert at IBM, explain why ML is an added-value for industrial players. F. Bourlet, IBM: Arthur Samuel is one of the pioneers of machine learning. While working at IBM, Arthur Samuel wrote a Checker's playing program on IBM's first commercial computer 701. IBM Research has been exploring artificial intelligence and machine learning technologies and techniques for decades.

IBM and the Massachusetts Institute of Technology (MIT) have joined forces to establish an MIT-IBM Watson AI Lab in Cambridge that will pursue research in artificial intelligence (AI) with a focus on healthcare and cybersecurity, as well as on commercialising AI technologies born out of the lab. Touted as one of the largest university-industry AI collaborations and investments, the 10-year, $240 million initiative is expected to hire and bring together over 100 AI-focused scientists, professors, and students. In addition to IBM's plan to commercialise technologies developed within the lab, the pair will encourage MIT faculty and students to launch new companies that will focus on commercialising inventions and technologies that are developed at the lab. "The field of artificial intelligence has experienced incredible growth and progress over the past decade. Yet, today's AI systems, as remarkable as they are, will require new innovations to tackle increasingly difficult real-world problems to improve our work and lives," said Dr John Kelly III, IBM senior vice president, Cognitive Solutions and Research.

Algorithms modeled loosely on the brain have helped artificial intelligence take a giant leap forward in recent years. Those algorithms, in turn, have advanced our understanding of human intelligence while fueling discoveries in a range of other fields. MIT founded the Quest for Intelligence to apply new breakthroughs in human intelligence to AI, and use advances in AI to push human intelligence research even further. This fall, nearly 50 undergraduates joined MIT's human-machine intelligence quest under the Undergraduate Research Opportunities Program (UROP). Students worked on a mix of projects focused on the brain, computing, and connecting computing to disciplines across MIT.

Artificial intelligence (AI) has been the domain of researchers for years. The largest commercial companies such as IBM and Microsoft, have the financial ability to build labs and hire AI talent. However, even these organizations need to expand their access to AI researchers. One way to increase AI talent is to develop labs and fund research with a major university. Last September, IBM announced a partnership with MIT.

Want to watch this again later? Sign in to add this video to a playlist. Report Need to report the video? Sign in to report inappropriate content. Report Need to report the video?

The renowned Massachusetts Institute of Technology and the company IBM are setting up a joint laboratory for artificial intelligence: the MIT-IBM Watson AI Lab is to carry out basic research and develop concrete technologies with the help of physicists, economists, and computer developers. IBM will contribute 240 million dollars to the cooperation between the company and the university for the next ten years, reports VentureBeat. Both institutions will hire researchers for the new laboratory, which will jointly carry out research in four areas that have been identified as relevant for the future with AI. The research areas of MIT-IBM Watson AI Lab include, in practical application, the development of new AI algorithms and the use of physical research for new hardware in this area, especially in quantum computing. In more theoretical future studies, the application possibilities of AI in specific industrial areas as well as the possible effects of this technology on society are to be investigated.

On Thursday, MIT and IBM unveiled plans to invest $240 million over the next 10 years to build a new MIT-IBM Watson AI Lab. The lab, announced in an MIT press release, will carry out artificial intelligence (AI) research in an effort to propel forward the hardware, software, and algorithms that power AI itself. According to the release, more than 100 AI scientists, professors, and students will work on the research in Cambridge, MA, nearby the MIT campus and other IBM properties. Their work will seek to boost the impact of AI on cybersecurity and healthcare, while also examining AI's impact on society as a whole. "The field of artificial intelligence has experienced incredible growth and progress over the past decade. Yet today's AI systems, as remarkable as they are, will require new innovations to tackle increasingly difficult real-world problems to improve our work and lives," John Kelly III, IBM senior vice president of Cognitive Solutions and Research, said in the release.