Computer pioneer Willis Ware saw the future, and it worried him. In 1966, Ware, who worked as an engineer at Rand Corp., foresaw not only the omnipresence of personal computers, but also social networks like Twitter and Facebook. "The computer will touch men everywhere and in every way, almost on a minute-to-minute basis," he wrote in a paper presented at Rand 47 years ago. "Every man will communicate through a computer whatever he does. It will change and reshape his life, modify his career and force him to accept a life of continuous change."

In another Minority Report-like research finding, a UCLA research team has made crucial advances in "brain reading," using fMRI and machine learning methods to predict reactions of smokers experiencing nicotine cravings. The research, presented last week at the Neural Information Processing Systems Machine Learning and Interpretation in Neuroimaging workshop in Spain, was funded by the National Institute on Drug Abuse, which is interested in using these methods to help people control drug cravings. At UCLA's Laboratory of Integrative Neuroimaging Technology, researchers use functional MRI brain scans to observe brain signal changes that take place during mental activity. They then employ computerized machine learning (ML) methods to study these patterns and identify the cognitive state -- or sometimes the thought process -- of human subjects. The technique is called "brain reading" or "brain decoding."

Debrief tool used in the experiment displays a video replay of the operator console (similar to this map display), and a timeline of events suggested by AEMASE for discussion during debrief. The tool also includes visualizations of entity movement over time. Navy pilots and other flight specialists soon will have a new "smart machine" installed in training simulators that learns from expert instructors to more efficiently train their students. Sandia National Laboratories' Automated Expert Modeling & Student Evaluation (AEMASE, pronounced "amaze") is being provided to the Navy as a component of flight simulators. Components are now being used to train Navy personnel to fly H-60 helicopters and a complete system will soon be delivered for training on the E-2C Hawkeye aircraft, said Robert G. Abbott, a Sandia computer scientist and AEMASE's inventor.

Prof. Dr. (Juris) Jon Bing is the Institute leader of the Norwegian Research Center for Computers and Law, the second oldest academic institution in the world working specifically with the interrelationship of law and information / communication technology; Dr. Bing is the recipient of numerous international awards. He is the Editor of the news-letter Lov&data (Norwegian news-letter on computers and law, published by the Lawdata foundation) and is an editorial board member of over 16 international journals.

The development of artificial intelligence (AI) is rapidly advancing thanks to a machine learning process called "deep learning," raising expectations of radical changes and greater convenience in people's lives. The AI boom began early in the 2010s when major information technology companies such as U.S. companies Google Inc. and Facebook Inc. established research institutes, and the development of deep learning has added fuel to the fire. Deep learning is a branch of machine learning in which a computer system mimics human neural circuits and processes information in multiple processing layers. It is a "revolution" in the foundation of AI, said Yutaka Matsuo, an associate professor at the University of Tokyo and expert on information technology and AI. The AI in a computer system teaches itself by processing huge amounts of data. When, for example, AI processes input data and outputs them, it repeatedly learns the features of the data so as to bring out the same data as those entered.

LOS ANGELES – Automakers intending to develop driverless cars need to work as much on software design as mechanical engineering, according to the researcher leading Nissan Motor Co.'s automated-vehicle program. Making cars that are "deliberative" in assessing road conditions, rather than just reactive, requires artificial intelligence, said Maarten Sierhuis, director of Nissan's Silicon Valley research center in Sunnyvale, California. Nissan, which aims to sell vehicles that can drive themselves by 2020 or sooner, is developing software to read and filter sensor data much as a human brain does, he said. "What the auto industry has to come to is a shift from thinking about the car as a physical, mechanical system," Sierhuis said in an interview Tuesday at the Automated Vehicles Symposium in San Francisco. "Autonomy, autonomous systems, is about understanding how humans do that, and then replicating it with software."

Objective: A research prototype Physician Workstation (PWS) incorporating a graphical user interface and a drug ordering module was compared with the existing hospital information system in an academic Veterans Administration General Medical Clinic. Physicians in the intervention group received recommendations for drug substitutions to reduce costs and were alerted to potential drug interactions. The objective was to evaluate the effect of the PWS on user satisfaction, on health-related outcomes, and on costs. Design: A one-year, two-period, randomized controlled trial with 37 subjects. Measurements: Differences in the reliance on noncomputer sources of information, in user satisfaction, in the cost of prescribed medications, and in the rate of clinically relevant drug interactions were assessed.

A Toronto-based content marketing and live publishing SaaS platform is boosting its big data capabilities with the acquisition of a New York City-based influence analytics marketing platform. ScribbleLive announced its acquisition on Wednesday of Appinions Inc., developers of an influence analytics marketing platform that is built on natural language processing and social network analysis technology. The vendor says combining ScribbleLive's data centric content workflow and publishing platform with Appinions' deep data technology will create an even more powerful content marketing platform for data-driven marketers. Toronto-based web platform creators Scribble Technologies Inc. has acquired another well-known live publishing platform in CoveritLive from California-based Demand Media. "By enabling over 500 brands such as Red Bull, PwC and Oracle to serve up the right content at the right time in the right place online, ScribbleLive has been validated as the platform for planning, creating and distributing content," said Vince Mifsud, CEO of ScribbleLive, in a statement.

Soon they will be sophisticated enough to fill certain faculty roles at traditional universities. But to make this revolution work for students, academic leaders at those traditional institutions will need to broker a peace between artificially intelligent teaching programs and their human counterparts, according to a new report written by the former presidents of two prominent traditional universities on behalf of the nonprofit Ithaka S R. Online education has enabled many colleges to transition into the prevailing modern medium while adding new sources of revenue in times of scarcity, according to the Ithaka report. However, these innovative colleges have shown less interest in using the novel medium to curb tuition charges and measure learning outcomes. The report, called "Barriers to Adoption of Online Learning Systems in U.S. Higher Education," was co-written by Lawrence S. Bacow and William G. Bowen, the former presidents of Tufts and Princeton Universities, respectively, along with several Ithaka analysts. It was bankrolled by the Bill & Melinda Gates Foundation.

Robin John Popplestone, one of the early pioneers in Robotics and Computer Programming Languages, died on 14th April 2004 in Glasgow, Scotland, after a 10-year battle with prostate cancer. Robin was born in Bristol in 1938. After the war his family moved to Belfast, where he grew up. He was educated at Queen's University Belfast, receiving an honours degree in mathematics in 1960. He first worked with computing while studying for a PhD initially at Manchester University and then at Leeds University.