Abstract: We are increasingly surrounded by artificially intelligent technology that takes decisions and executes actions on our behalf. This creates a pressing need for general means to communicate with, instruct and guide artificial agents, with human language the most compelling means for such communication. Here we present an agent that learns to interpret language in a simulated 3D environment where it is rewarded for the successful execution of written instructions. Trained via a combination of reinforcement and unsupervised learning, and beginning with minimal prior knowledge, the agent learns to relate linguistic symbols to emergent perceptual representations of its physical surroundings and to pertinent sequences of actions.
Campus Technology reports that a team of educators developed a writing-to-learn tool called M-Write, which uses automated text analysis (ATA) to identify the strengths of a writing submission. A report from the EDUCAUSE Center for Analysis and Research explores how the University of Central Florida piloted adaptive learning in large, introductory courses like General Psychology. General Psychology is a general education course with many sections that can often be taught by adjuncts. "As with any new tool, adaptive learning provides a new set of capabilities and insights -- and a lot of very useful data -- that can be used to explore ways to increase students learning and success," ECAR reports.
By prefecture, Aichi tops the list with 7,277 non-Japanese children with poor Japanese skills, followed by Kanagawa at 3,947, Tokyo at 2,932, Shizuoka at 2,673 and Osaka at 2,275. The survey also found 9,612 children who hold Japanese citizenship but have poor Japanese skills, needing remedial language instruction. Such children often have no choice but to learn basic Japanese at language schools or in classes provided by nonprofit groups like the center before entering a public school, Hazeki said. "There are a lot of language schools in Japan for international students, but Japan does not have a well-established system to train people who can teach Japanese to those elementary and junior high school children," Hazeki said.
Machine translation systems that convert sign language into text and back again are helping people who are deaf or have difficulty hearing to communicate with those who cannot sign. A sign language user can approach a bank teller and sign to the KinTrans camera that they'd like assistance, for example. KinTrans's machine learning algorithm translates each sign as it is made and then a separate algorithm turns those signs into a sentence that makes grammatical sense. KinTrans founder Mohamed Elwazer says his system can already recognise thousands of signs in both American and Arabic sign language with 98 per cent accuracy.
With both machine learning and data analytics skill set, one can easily fetch an average pay of Rs 13.94 lakh per annum (LPA). Although knowledge of machine learning algorithms do add to the highest package, the skill set alone can fetch a handsome Rs 10.43 LPA on average. If the latest Analytics India Industry Report 2017 – Salaries & Trends report is anything to go by, one could make an average of Rs 10.40 LPA with exceptional R language skills. One of the most popular programming languages, professionals with Python skill set can make around Rs 10.12 LPA on average.
We recommend addressing this through the explicit characterization of acceptable behavior. One such approach is seen in the nascent field of fairness in machine learning, which specifies and enforces mathematical formulations of nondiscrimination in decision-making. Another approach can be found in modular AI architectures, such as cognitive systems, in which implicit learning of statistical regularities can be compartmentalized and augmented with explicit instruction of rules of appropriate conduct . Certainly, caution must be used in incorporating modules constructed via unsupervised machine learning into decision-making systems.
All it takes is a few taps of her tablet, and with a specialized app stringing letters into words, and words into phrases, her thoughts are played out loud. The music mode helps amplify low notes Rakowski can't hear otherwise, while the standard mode helps her to instruct her students. Rakowski, whose musical passion and profession rely on the ability to hear, started using hearing aids a little over a year ago. While Rakowski relies on visuals to control the volume of sounds coming through her hearing aids, Vasquez relies completely on his voice to navigate his Apple devices.
This evening event at Westminster Law School, University of Westminster, brings together three prominent experts in the fields of artificial intelligence, robotics and law for a conversation around current developments in these areas, followed by an opportunity for the audience to engage and ask questions. Chrissie Lightfoot is a prominent international legal figure, an entrepreneur, a legal futurist, legaltech investor, writer, international keynote speaker, legal and business commentator (quoted periodically in The Times and FT), solicitor (non-practising), Honorary Visiting Fellow at the University of Westminster School of Law, and author of best-seller The Naked Lawyer and Tomorrow s Naked Lawyer. Chair: Dr Paresh Kathrani is a Senior Lecturer in Law at Westminster Law School and a member of the Centre on the Legal Profession. He has written on the challenges that AI will bring for the legal profession and chaired a panel on artificial intelligence at Westminster Law School in 2015, as well as an AI film and debate series for the Centre for Law, Society and Popular Culture, of which he is also a member, in 2016.
Manser's employer, IBM, and an independent carmaker called Local Motors are developing a self-driving, electric shuttle bus that combines artificial intelligence, augmented reality, and smartphone apps to serve people with vision, hearing, physical, and cognitive disabilities. Future Ollis, for example, might direct visually impaired passengers to empty seats using machine vision to identify open spots, and audio cues and a mobile app to direct the passenger. For deaf people, the buses could employ machine vision and augmented reality to read and speak sign language via onboard screens or passengers' smartphones. Another potential Olli technology combines machine vision and sensors to detect when passengers leave items under their seats and issues alerts so the possessions can be retrieved, a feature meant to benefit people with age-related dementia and other cognitive disabilities.