Eureka Robotics, an automation company based in Singapore, has developed their products based on research from MIT and Nanyang Technological University, reports Catherine Shu for TechCrunch. “It [Eureka Robotics] focuses on robotic software and systems to automate tasks that require High Accuracy and high Agility (HAHA),” writes Shu. “Its robots are used for precision handling, assembly, inspection, drilling and other tasks.”
Graduate student Anna Waldman-Brown writes for Wired about the future of automation technology and how it can impact labor dynamics in the future. “While some scholars believe that our fates are predetermined by the technologies themselves, emerging evidence indicates that we may have considerable influence over how such machines are employed within our factories and offices – if we can only figure out how to wield this power,” writes Waldman-Brown.
Fast Company reporter Connie Lin spotlights how Algorand, an MIT startup founded by Prof. Silvio Micali, dimmed the lights in Times Square on April 21 to help conserve energy and demonstrate how cryptocurrency could reduce energy consumption. Algorand has developed a carbon-negative blockchain protocol and “utilizes a pure proof-of-stake consensus mechanism to verify authentic transactions.”
Prof. Jessika Trancik speaks with ABC News about the urgent need to transition to renewable energy sources, and how we can build a future powered by alternative energy. “Up until recently there were really significant questions about whether we could transition to another [energy] foundation,” says Trancik. “This question has now been answered in that we now have cost competitive renewable primary energy in the form of solar and wind energy and also in other types of renewable energy.”
Boston Globe reporter Robert Weisman spotlights how researchers at the MIT AgeLab are “designing prototypes of ‘smart homes’ for older residents, equipped with social robots, voice-activated speakers that give medication reminders, motion sensors embedded in carpets to detect falls, and intelligent doorbells that double as security cameras.”
STAT reporter Katie Palmer spotlights Principal Research Scientist Leo Anthony Celi’s research underscoring the importance of improving the diversity of datasets used to design and test clinical AI systems. “The biggest concern now is that the algorithms that we’re building are only going to benefit the population that’s contributing to the dataset,” says Celi. “And none of that will have any value to those who carry the biggest burden of disease in this country, or in the world.”
Prof. Jessika Trancik speaks with Wall Street Journal reporter Nidhi Subbaraman about the dramatic drops in costs to manufacture and sell renewable technologies. Subbaraman notes that Trancik’s research shows that “the steep drop in solar and lithium-ion battery technology was enabled by market expansion policies as well as investment in research and development by governments and the private sector.”
The MIT AI Hardware Program seeks to bring together researchers from academia and industry to “examine each step of designing and manufacturing the hardware behind AI-powered technologies,” reports Emily Bamforth for EdScoop. “This program is about accelerating the development of new hardware to implement AI algorithms so we can do justice to the capabilities that computer scientists are developing,” explains Prof. Jesús del Alamo.
The MIT AI Hardware Program is aimed at bringing together academia and industry to develop energy-optimized machine-learning and quantum-computing systems, reports Katyanna Quach for The Register. “As progress in algorithms and data sets continues at a brisk pace, hardware must keep up or the promise of AI will not be realized,” explains Professor Jesús del Alamo. “That is why it is critically important that research takes place on AI hardware."
TechCrunch reporters Christine Hall, Anita Ramaswamy, Connie Loizos and Mary Ann Azevedo spotlight Sribuu, an AI-powered personal financial advisor in Indonesia, co-founded by Nadia Amalia ’20. The company is aimed at helping “users make better money decisions with our wealth management tools and give personalized saving advice based on their financial habits,” they write.
Prof. Ekene Ijeoma speaks with KUER’s Ivana Martinez about his group’s art project, “A Counting,” which spotlights people counting to 100 in their native languages. “I think [this is] speaking to ideas of what it means to live in this diverse society,” said Ijeoma. “And whether or not we're able to live up to the dream of this society, which is — we're a multicultural place. Can we actually be that?”
Using machine learning techniques, MIT researchers analyzed social media sentiment around the world during the early days of the Covid-19 pandemic and found that the “pandemic precipitated a dramatic drop in happiness,” reports Charlotte Hu for Popular Science. “We wanted to do this global study to compare different countries because they were hit by the pandemic at different times,” explains Prof. Siqi Zheng, “and they have different cultures, different political systems, and different healthcare systems.”
Fortune reporter Jeremy Kahn spotlights a study co-authored by Prof. Marzyeh Ghassemi exploring issues associated with “explainable” AI systems that are being applied in fields such as healthcare, finance and government. The researchers explain that those using such systems “might have misunderstood the capabilities of contemporary explainability techniques—they can produce broad descriptions of how the AI system works in a general sense but, for individual decisions, the explanations are unreliable or, in some instances, only offer superficial levels of explanation.”
Prof. Stuart Madnick writes for The Wall Street Journal about how flaws in a company’s cybersecurity defenses can lead to cyberattacks. “Every decision regarding cybersecurity must weigh the benefits of not doing something (cost savings or the faster growth) against the increased risk to the organization,” writes Madnick.
Gizmodo reporter Andrew Liszewski writes that CSAIL researchers developed a new AI system to teach the MIT mini cheetah how to adapt its gait, allowing it to learn to run. Using AI and simulations, “in just three hours’ time, the robot experienced 100 days worth of virtual adventures over a diverse variety of terrains,” writes Liszewski, “and learned countless new techniques for modifying its gait so that it can still effectively loco-mote from point A to point B no matter what might be underfoot.”