Researchers at MIT have created an algorithm-based architecture called SpAtten that reduces attention computation and memory access in natural language processing (NLP) systems. If we think it’s hard to learn a new language, imagine the challenges hardware and software engineers face when using CPUs and GPUs to process extensive language data. Natural language processing (NLP) attempts to bridge this gap between language and computing.
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An intro to the fast-paced world of artificial intelligence
The field of artificial intelligence is moving at a staggering clip, with breakthroughs emerging in labs across MIT. Through the Undergraduate Research Opportunities Program (UROP), undergraduates get to join in. In two years, the MIT Quest for Intelligence has placed 329 students in research projects aimed at pushing the frontiers of computing and artificial intelligence, and using these tools to revolutionize how we study the brain, diagnose and treat disease, and search for new materials with mind-boggling properties.
Read MoreAI research survey finds machine learning needs a culture change
The machine learning community, particularly in the fields of computer vision and language processing, has a data culture problem. That’s according to a survey of research into the community’s dataset collection and use practices published earlier this month.
What’s needed is a shift away from reliance on the large, poorly curated datasets used to train machine learning models. Instead, the study recommends a culture that cares for the people who are represented in datasets and respects their privacy and property rights.
New IBM-MIT system brings AI to microcontrollers – paving the way to ‘smarter’ IoT
Smart homes are now all the rage, with smart speakers controlling your lights, your door lock, your fridge. But what if you didn’t want to use a smart speaker or any sophisticated computer to operate your devices? What if instead, a device like a lock had a cheap, tiny but powerful embedded AI that could recognize your face to open the door – and run on batteries for a year, no WIFi or smart speaker needed?
Read MoreAI research finds a ‘compute divide’ concentrates power and accelerates inequality in the era of deep learning
AI researchers from Virginia Tech and Western University have concluded that an unequal distribution of compute power in academia is furthering inequality in the era of deep learning. They also point to the impact on academia of people leaving prestigious universities for high-paying industry jobs.
Read MoreMIT: Building the algorithm commons: Who discovered the algorithms that underpin computing in the modern enterprise?
Analyzing this “Algorithm Commons” reveals that the United States has been the largest contributor to algorithm progress, with universities and large private labs (e.g., IBM) leading the way, but that U.S. leadership has faded in recent decades.
Read MoreCOVID-19 AI model detects the virus through digital cough recordings
Alongside the whole craziness happening in the world right now, phenomenal inventions are being created. For instance, MIT researchers have been working on an AI model that can detect people infected with COVID-19 through a digitally recorded cough.
Read MoreMIT CSAIL researchers claim their algorithm helps doctors pick the right antibiotics
Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) say they’ve developed a recommendation algorithm that predicts the probability a patient’s urinary tract infection (UTI) can be treated by first- or second-line antibiotics.
Read MoreMIT: Artificial intelligence model detects asymptomatic Covid-19 infections through cellphone-recorded coughs
MIT researchers have found that people who are asymptomatic for Covid-19 may differ from healthy individuals in the way that they cough. These differences are not decipherable to the human ear. But it turns out that they can be picked up by artificial intelligence.
Read MoreMIT: AI Cures: data-driven clinical solutions for Covid-19
MIT conference illustrates technologies developed in response to the pandemic and new opportunities for AI solutions for clinical management.
Read MoreMIT: What to expect when you’re expecting Robots
As Covid-19 has made it necessary for people to keep their distance from each other, robots are stepping in to fill essential roles, such as sanitizing warehouses and hospitals, ferrying test samples to laboratories, and serving as telemedicine avatars.
Read MoreMIT CSAIL’s AI revives dead languages it hasn’t seen before
Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) claim to have developed a system that can decipher a lost language without knowing its relation to other languages. The team says this is a step toward a system that’s able to decipher lost languages using just a few thousand words.
Read MoreAI researchers devise failure detection method for safety-critical machine learning
Researchers from MIT, Stanford University, and the University of Pennsylvania have devised a method for predicting failure rates of safety-critical machine learning systems and efficiently determining their rate of occurrence.
Read MoreMIT task force predicts fully autonomous vehicles won’t arrive for ‘at least’ 10 years
Driverless systems will take at least a decade to deploy over large areas and that expansion will happen region-by-region in specific transportation categories, resulting in variations in availability across the country.
Read MoreMIT researchers warn that deep learning is approaching computational limits
“We show deep learning is not computationally expensive by accident, but by design. The same flexibility that makes it excellent at modeling diverse phenomena and outperforming expert models also makes it dramatically more computationally expensive,”
Read MoreMIT researchers find ‘systematic’ shortcomings in ImageNet data set
MIT researchers have concluded that the well-known ImageNet data set has “systematic annotation issues” and is misaligned with ground truth or direct observation when used as a benchmark data set.
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