Looking up an unknown sign in an ASL dictionary can be difficult. Most ASL dictionaries are organized based on English glosses, despite the fact that (1) there is no convention for assigning English-based glosses to ASL signs; and (2) there is no 1-1 correspondence between ASL signs and English words. Furthermore, what if the user does not know either the meaning of the target sign or its possible English translation(s)? Some ASL dictionaries enable searching through specification of articulatory properties, such as handshapes, locations, movement properties, etc. However, this is a cumbersome process and does not always result in successful lookup. Here we describe a new system, publicly shared on the Web, to enable lookup of a video of an ASL sign (e.g., a webcam recording or a clip from a continuous signing video). The user submits a video for analysis and is presented with the five most likely sign matches, in decreasing order of likelihood, so that the user can confirm the selection and then be taken to our ASLLRP Sign Bank entry for that sign. Furthermore, this video lookup is also integrated into our newest version of SignStream(R) software to facilitate linguistic annotation of ASL video data, enabling the user to directly look up a sign in the video being annotated, and, upon confirmation of the match, to directly enter into the annotation the gloss and features of that sign, greatly increasing the efficiency and consistency of linguistic annotations of ASL video data.

Researchers from MIT and elsewhere have built a wake-up receiver that communicates using terahertz waves, which enabled them to produce a chip more than 10 times smaller than similar devices. Their receiver, which also includes authentication to protect it from a certain type of attack, could help preserve the battery life of tiny sensors or robots. Scientists are striving to develop ever-smaller internet-of-things devices, like sensors tinier than a fingertip that could make nearly any object trackable. These diminutive sensors have miniscule batteries which are often nearly impossible to replace, so engineers incorporate wake-up receivers that keep devices in low-power "sleep" mode when not in use, preserving battery life. Researchers at MIT have developed a new wake-up receiver that is less than one-tenth the size of previous devices and consumes only a few microwatts of power.

We develop a simple framework to learn bio-inspired foraging policies using human data. We conduct an experiment where humans are virtually immersed in an open field foraging environment and are trained to collect the highest amount of rewards. A Markov Decision Process (MDP) framework is introduced to model the human decision dynamics. Then, Imitation Learning (IL) based on maximum likelihood estimation is used to train Neural Networks (NN) that map human decisions to observed states. The results show that passive imitation substantially underperforms humans. We further refine the human-inspired policies via Reinforcement Learning (RL) using the on-policy Proximal Policy Optimization (PPO) algorithm which shows better stability than other algorithms and can steadily improve the policies pretrained with IL. We show that the combination of IL and RL can match human results and that good performance strongly depends on combining the allocentric information with an egocentric representation of the environment.

More young people than old, and more men than women, are open to artificial intelligence-powered machines replacing people in a variety of jobs, according to the latest Media & Technology Survey from Boston University's College of Communication and Ipsos. By more than 30 percentage points, Americans ages 18 to 34 surveyed were more receptive than those 55 or older when considering AI replacing people working as journalists, hiring managers, trial judges, spiritual advisers or leaders of religious congregations. Respondents ages 35 to 54 were in-between. Men were more receptive than women to AI replacing workers in those jobs by almost 10 percentage points. Still, three out of four respondents across all ages, genders, ethnicities and income groups say having AI replace people in these jobs "doesn't seem like a good idea" or is "definitely a bad idea."

A new artificial intelligence language-processing tool could potentially help detect cognitive impairment and mental degenerative diseases like Alzheimer's, researchers at Boston University say. Their findings, which were published in The Journal of the Alzheimer's Association, suggest that a machine-learning computational model could identify cognitive decline through audio recordings of neuropsychological tests. "It can form the basis of an online tool that could reach everyone and could increase the number of people who get screened early," said Ioannis Paschalidis, a professor of engineering and one of the researchers at Boston University, in a news release. The computational model, which does not require in-person assessments, could ultimately help clinicians triage the urgency of patients' symptoms more efficiently, allowing them to allocate resources without replacing follow-up processes for diagnosis, she said. Using automated speech recognition software, the program transcribes interviews and, by encoding them into numbers, detects patterns that assess the likelihood and severity of a patient's cognitive impairment.

Before I started this MS program, I was looking for course curricula of different Masters programs and trying to find reviews of other people to understand which program is suitable for me. Now, as I am almost done with my MS, I thought I should write a review to help other learners who are looking for an MS program in Data Science or Analytics. Before I dive into the MS program, here is my background. I have a Bachelor's in Civil Engineering and a master's in Environmental Engineering. So, I am not from a computer science background.

Accenture's partnership with AI4ALL gives emerging leaders exposure to Responsible AI in practice. The field of AI is changing rapidly, making the need for responsible AI greater than ever. While only 18% of data science students reported learning about ethics in a recent industry survey, examples of AI products with unintended negative consequences continue to grow. Marisa Tricarico, the North America Practice Lead for Responsible AI at Accenture, has a unique perspective on the rapid expansion of this field, as she works with a growing roster of Accenture clients as they develop and deploy AI. Marisa and Accenture's work intersects with AI4ALL's work to train the next generation of responsible AI leaders as well.

Spotting these clues may allow for lifestyle changes that could possibly delay the disease's destruction of the brain. "Improving the diagnostic accuracy of Alzheimer's disease is an important clinical goal. If we are able to increase the diagnostic accuracy of the models in ways that can leverage existing data such as MRI scans, then that can be hugely beneficial," explained corresponding author Vijaya B. Kolachalama, PhD, assistant professor of medicine at Boston University School of Medicine (BUSM). Using an advanced AI (artificial intelligence) framework based on game theory (known as generative adversarial network or GAN), Kolachalama and his team processed brain images (some low and high quality) to generate a model that was able to classify Alzheimer's disease with improved accuracy. Quality of an MRI scan is dependent on the scanner instrument that is used.

This is very common to switch to data science. Most data scientists I know out there do not have a degree in data science. They switched from another area. I also know many people who are trying to switch from another major. I meet many people being confused if it is the right career track for them.

Timothy Gardner is the Founder and the CEO of Riffyn. He was previously Vice President of Research & Development at Amyris, where he led the engineering of yeast strain and processes technology for large-scale bio-manufacturing of renewable chemicals. Earlier, he was an Assistant Professor of Biomedical Engineering at Boston University, the Founder of Cellicon Biotechnologies, and a Programmer at ALK Associates. Tim has been recognized for his pioneering work in Synthetic Biology by Scientific American, the New Scientist, Nature, Technology Review, and the New York Times. He also served as an advisor to the European Union Scientific Committees and the Boston University Engineering Alumni Advisory Board.