Interview


What Is The Future Of Technology In America?

International Business Times

While consumer protection laws clearly outlaw unfair pricing and require equal employment opportunities, the regulations enforcing these laws are increasingly obsolete and impotent. Politicians of all stripes support creating or increasing competition, preventing price-gouging in communities served by monopoly broadband providers and encouraging companies to provide internet service in remote areas. However, scaling up this approach, called distributed microgeneration, requires an electrical system that enables two-way metering – a smart utility system that credits customers for power generated and charges them for power consumed. The United States spends billions of dollars every year on information technology, and tens of billions more on government-funded research and other grants.


Exclusive interview: Democratising data science & making AI more accessible

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Mark Armstrong, vice president and managing director of international operations for APJ and EMEA, for Progress, discusses the company's mission to democratise data science and make technologies such as machine learning, predictive maintenance and Artificial Intelligence more accessible so businesses in Australia and New Zealand can succeed. Progress believes that democratisation of data science is the key to including all organisations, including SMBs, in the machine learning equation. Data RPM and its meta-learning approach to machine learning will enable us to democratise data science by making it scalable, which will allow businesses to build models without the need for an army of data scientists. Making machine learning and artificial intelligence (AI) accessible is exactly why we acquired DataRPM.


Exclusive interview: Democratising data science & making AI more accessible

#artificialintelligence

Mark Armstrong, vice president and managing director of international operations for APJ and EMEA, for Progress, discusses the company's mission to democratise data science and make technologies such as machine learning, predictive maintenance and Artificial Intelligence more accessible so businesses in Australia and New Zealand can succeed. Progress believes that democratisation of data science is the key to including all organisations, including SMBs, in the machine learning equation. Data RPM and its meta-learning approach to machine learning will enable us to democratise data science by making it scalable, which will allow businesses to build models without the need for an army of data scientists. Making machine learning and artificial intelligence (AI) accessible is exactly why we acquired DataRPM.


A Son's Race to Give His Dying Father Artificial Immortality

WIRED

The computer is set up to run a program called Eliza--an early chatbot created by MIT computer scientist Joseph Weizenbaum in the mid-1960s. But where Eliza's script was written by a single dour German computer scientist, Barbie's script has been concocted by a whole team of people from Mattel and PullString, a computer conversation company founded by alums of Pixar. And where Eliza's natural- language processing abilities were crude at best, Barbie's powers rest on vast recent advances in machine learning, voice recognition, and processing power. At one point the company's CEO, Oren Jacob, a former chief technology officer at Pixar, tells me that PullString's ambitions are not limited to entertainment.


Machine learning takes the fast track - Banking Exchange

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The standard transaction monitoring practices using traditional analytic software, backed by human oversight, may no longer be enough to meet anti-fraud work in particular. "We do have some software in our bank that has the ability to learn based on customer patterns and activities and transactions and use of devices and types of credit instruments, to learn about our customers' activities, to anticipate when something looks unusual," says Peter Graves, chief information officer, Independent Bank Co., Grand Rapids, Mich., in an interview with Banking Exchange. Again, the fraud area is particularly suited for machine learning application, says Chris Nichols, chief strategy officer, CenterState Bank, Winter Haven, Fla. "Any time you have a string of transactions, you're looking for anomalies, whether it's credit cards or wires or account balances," says Nichols. When the bank ran its customer data base through a machine learning program, the machine picked out a group that the humans in the bank would never have found: a group of stay-at-home mothers in Florida who had a big social network, frequently posted to it, and were willing to pass along recommendations to their friends.


Speech Synthesis Research Engineer ObEN, Inc.

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The work will have a particular focus on the development of structured acoustic models which take account of factors such as accent and speaking style, and on the development of machine learning techniques for vocoding. You will have the necessary programming ability to conduct research in this area, a background in statistical modeling using Hidden Markov Models, DNN, RNN, speech signal processing, and research experience in speech synthesis. A background in one or more of the following areas is also desirable: statistical parametric text-to-speech synthesis using HMMs and HSMMs; glottal source modeling; speech signal modeling; speaker adaptation using the MLLR or MAP family of techniques; familiarity with software tools including DNN, Deep Learning, RNN, HTK, HTS, Festival; and familiarity with modern machine learning. Develop and extend speech synthesis technologies in Oben's proprietary speech synthesis system, in view of the realization of prosody and voice quality modifications; Develop and apply algorithms to annotate prosody and voice quality in expressive speech synthesis corpora Carry out a listener evaluation study of expressive synthetic speech.


Artificial Intelligence Predicts Death to Help Us Live Longer

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In an email interview with Singularity Hub, lead author Dr. Luke Oakden-Rayner, a radiologist and PhD student, says that one of the obvious benefits of using AI in precision medicine is to identify health risks earlier and potentially intervene. "Currently, most research into chronic disease and longevity requires long periods of follow-up to detect any difference between patients with and without treatment, because the diseases progress so slowly," he explains. "Predicting remaining life span for people is actually one of the easiest applications of machine learning," Dr. Ziad Obermeyer tells STAT News. Obermeyer co-authored a paper last year with Dr. Ezekiel Emanuel in the New England Journal of Medicine called "Predicting the Future--Big Data, Machine Learning, and Clinical Medicine."


Consumer goods giant Unilever has been hiring employees using brain games and artificial intelligence - and it's a huge success

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For the past year, Dutch-British consumer goods giant Unilever has been using artificial intelligence to hire entry-level employees, and the company says that it has dramatically increased diversity and cost efficiency. Instead of sending representatives to elite universities, collecting resumes, and arranging follow-up phone interviews for the students that stuck out, Unilever has partnered with digital HR service providers Pymetrics and HireVue to completely digitize the first steps of the process. The "balloon game" measures a candidate's relationship to risk. Unilever's North American head of HR, Mike Clementi, said that his team is still finding ways to further refine the process, to ensure that candidates have an enjoyable experience that is unique to Unilever, and one that is not overly mechanized.


Salto-1P Is the Most Amazing Jumping Robot We've Ever Seen

IEEE Spectrum Robotics Channel

We brainstormed about 40 different ways to control Salto-1P's orientation including multiple tails, a single multi-degree-of-freedom inertial tail (like the body of the original Raibert hopper and Disney's LEAP robot), and big steerable wings. You mentioned that Salto-1P's duty factor [the amount of time the robot spends touching the ground] is twice as fast as a one-legged cheetah would be. The low duty factor means high accelerations on the ground, and very little time to do any control with the leg. Interestingly, like running animals, Salto gets more efficient the faster it runs until it can't run any faster.


A machine-learning approach to venture capital

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In this interview, Hone Capital managing partner Veronica Wu describes how her team uses a data-analytics model to make better investment decisions in early-stage start-ups. In 2015, she was brought on as a managing partner to lead Hone Capital (formerly CSC Venture Capital), the Silicon Valley–based arm of one of the largest venture-capital and private-equity firms in China, CSC Group. Based on the data, our model generates an investment recommendation for each deal we review, considering factors such as investors' historical conversion rates, total money raised, the founding team's background, and the syndicate lead's area of expertise. By comparison, 40 percent of the companies that our machine-learning model recommended for investment raised a follow-on round of funding--2.5 times the industry average--remarkably similar to the follow-on rate of companies selected by our investment team without using the model.