Sentences with phrase «done by machine learning»

Of course, most e-discovery is done by machine learning unless lawyers think they can do it better (a false premise if ever there was one).

Not exact matches

Driven by machine - learning systems, even the smallest of businesses can do the work of giant corporations, leveraging reams of untapped data to boost performance.

Powered by machine learning, our top stock analysis software does more than a human analyst ever could, unearthing details previously missed.

By combining our deep insurance knowledge, understanding, and experience with modern technologies like machine learning and artificial intelligence, we have created an entirely new and more effective way do distribute an essential business service to the deeply neglected small business market.

We've done some research on the invention and ownership in the artificial intelligence machine learning space, and more than half of Canadian - developed IP is now owned by foreign companies.

Equally if not more important, scientists are using the classifications made by Zooniverse participants to develop more accurate machine - learning algorithms so that computers will be able to do this kind of work in the future.See for yourself: zooniverse.org

Also, the machine learning software can help experimental physicists by allowing them to perform virtual measurements that would be hard to do in the laboratory, such as measuring the degree of entanglement of a system composed of many interacting qubits.

However, their exhaustive, 14 - month study of each candidate's Twitter followers - enabled by machine learning and other data science tools - offers tantalizing clues as to why the race turned out the way it did.

Proponents say, however, the real beauty of training AI to be creative does not lie in the end product — but rather in the technology's potential to expand on its own machine - learning education, and to solve problems by thinking outside the box far faster and better than humans can.

However, by recording brain activity during a simple task — whether one hears BA or DA — neuroscientists from the University of Geneva (UNIGE), Switzerland, and the Ecole normale supérieure (ENS) in Paris now show that the brain does not necessarily use the regions of the brain identified by machine learning to perform a task.

«To go beyond this we use modern machine - learning methods where you don't necessarily know how a computer has made a decision about a particular sound, but by training it, which means showing it lots of previous examples, we can encourage a computer algorithm to generalise from those.»

«The machine learning developed by industry is great if you want to do high - frequency trading on the stock market,» Brown said.

In this case, seven different characteristics were necessary for predicting how the materials behaved, and our team's grad student Cory Simon's application of machine learning techniques greatly sped up the material discovery process by eliminating those that didn't meet the criteria.»

Another thought that the authors» statement brings to mind is if learning is not needed to help people perform better then perhaps the tasks that they are working on should be done by an intelligent machine using Artificial Intelligence (AI).

Coding, Computer Science, Interdisciplinary, Learning By Doing, Machine Learning, Open Educational Resource, Personalized Learning, Platform, Professional Development, Project Based Learning, Robotics, Self Directed Learning, STEM, Technology

A time came when we learned to make machines and achieved great advances by enjoying the leverage that comes when an internal combustion engine does the pushing rather than our legs.

The Doma Gallery, New York, NY 1990 GROUP SHOW, «THE MEMORY OF LOSS» Universidad Andina Simon Bolivar, Sucre, Bolivia 1990 GROUP SHOW, «VOICES OF LATIN AMERICA» City Without Walls Gallery, Newark, NJ 1989 GROUP SHOW, «PRESENCE AND PERCEPTION» LECTURES, CONFERENCES AND PUBLIC PANELS University of Puerto Rico, San Juan, Puerto Rico 2011 «Education of an Architect 40 Years Later» «Hejduk, Hamlet and the Ghost Promise» 99th ACSA Annual Meeting: WHERE DO YOU STAND, Montreal, Canada 2011 Technology and Desire, co-chaired by Alberto Perez Gomez «Discreet Machines of Desire: from Edward Bernays to Robert Oppenheimer» NSF: Bridging STEM TO STEAM, Providence, RI 2011 Sponsored by the Rhode Island School of Design (RISD) and the National Science Foundation (NSF) A Gathering of leading thinkers from differing fields to inspire new collaborations among the arts / design / sciences in support of interdisciplinary STEAM learning, research and pedagogy.

The audio analysis system is said to employ machine learning so as to «get smarter over time,» and all of the data gathered by the devices will be open source and publicly available for study, with the aim of contributing to the global work being done on colony collapse disorder (CCD), pesticide exposure, and bee colony health.

He was an optical engineer who repaired aircraft instruments in Alaska in WWII, a mountain man who could turn a canoe into a sailboat with a folding machete, bed sheets and a few sticks, who taught me diffraction, color theory and relativity on paper when other kids were learning multiplication tables, who designed a potentiometer that went to the Moon by pointing the world's fastest camera at the world's fastest oscilloscope, who designed those traffic lights which only appear bright when you are in the appropriate lane, who didn't have to help me at all when I built my own Heathkit dual - channel scope in grade school, nor had to help me program my Apple II in machine language, who quit Honeywell to work for 3M when the Space Program turned into the nuclear missile program, who studied mining geology in college after growing up in a mining town in Utah, it was he who taught me, early on: make sure your contraption works!

And while thinking about all of this a colleague * was kind enough to send around a link to a recent post by Brian Sheppard over on the Legal Rebels blog called, «Does machine - learning - powered software make good research decisions?

It doesn't matter if you're using fancy machine learning or a gut feeling, if you're evaluating the efficacy of a model, you're limited by your access to ground truth.

Le Blanc has done some preliminary testing of Employment Foresight, which helps users navigate difficult areas of employment law such as reasonable notice, worker classification, overtime exemptions and work classification by using machine learning to identify hidden patterns in judicial rulings.

As data analytics, machine learning, and artificial intelligence progress, more and more data - oriented and routine tasks will be done by technology.

It isn't true machine learning but it is red - flagging applications and giving an estimated charge by our organization, if person does not revise their drawing to meet a standard.

Nevertheless, I did my best to defend my thesis (expressed in prior talks and posts) that while Legal A.I. is an unstoppable technological force, the impending «machine learning age» will actually be a «human learning age» in disguise, by returning precious time back to attorneys to focus on more meaningful and satisfying work.

They do this by using AI and machine learning to help you make a better assessment of your risk.

The endless streams of data generated by applications lends its name to this paradigm, but also brings some hard to deal with requirements to the table: How do you deal with querying semantics and implementation when your data is not finite, what kind of processing can you do on such data, and how do you combine it with data from other sources or feed it to your machine learning pipelines, and do this at production scale?

Rather, it was a consolidation of many ideas into one cohesive message: «We do these many different things, but they're all underpinned by AI and machine learning.

In fact, with the exception of Google's machine learning magic utilized by the Pixel flagships, that's exactly how the so - called portrait modes are done on every smartphone.

Cloud AutoML does this by offering users a simple graphical interface for training their own machine learning model.

«Neuromation does an amazing job by combining synthetic data machine learning with blockchain technology.

It does this by utilising machine learning and a «dual pixel sensor technology» to detect what the foreground, and what's in the background.

Know Your Worth uses sophisticated data science and machine learning algorithms that leverage millions of salary reports shared by employees on Glassdoor, while analyzing real - time supply and demand trends in local job markets, and typical career transitions of people doing similar work.