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Artificial Intelligence and Machine Learning in the News, February 12, 2018

IApple HomePod vs. Amazon Echo vs. Google Home: Smart Speaker War

… is notable that the three mega-corporations have all released speaker systems, but how do they stack up against one another?

The Apple HomePod vs. Amazon Echo vs. Google Home battle begins with the artificial intelligence capabilities of the three speakers. Amazon essentially created this whole new category of products with the Amazon Echo released back into 2014, and thus the system from the world’s largest retailer has had a a few years head start over its competitors, and certainly the Apple HomePod.

Amazon Echo essentially houses Alexa, the personal assistant developed by the huge company. Google’s Assistant …
2018-02-10 09:18:26-05:00 http://www.valuewalk.com/2018/02/apple-homepod-vs-amazon-echo-vs-google-home/

CloudQuant Thoughts : Amazon are definitely leading the pack with their AI but don’t be mistaken, this is a major play for data.. Whoever wins this battle will be able to gather an enormous amount of incredibly valuable data.

 

Wearables can now Detect Early Signs of Diabetes (using Machine Learning, of course)

… potentially millions of data points required to train the neural network (it’s extremely time consuming and expensive). Instead, Cardiogram and the University of California turned to semi-supervised machine learning. Using 33,628 person weeks worth of sensor health data, they trained their deep neural network (called DeepHeart). Once trained, they tested the neural network on another data set, this one consisting of 12,790 person weeks. The result was a super impressive 85% accuracy rate.

As of today, the researchers are working on increasing this accuracy rate. Apart from diabetes, the neural network can a…
2018-02-09 18:25:43+05:30 https://www.analyticsvidhya.com/blog/2018/02/wearables-can-now-detect-early-signs-of-diabetes-using-machine-learning-of-course/

CloudQuant Thoughts : The more data we gather, the more problems we can solve. Get ahead in Machine Learning in the markets using CloudQuant… See the recent Webinar by one of our ML Traders Trevor Trinkino.

 

Machine learning explained: Understanding supervised, unsupervised, and reinforcement learning

…Once we start delving into the concepts behind Artificial Intelligence (AI) and Machine Learning (ML), we come across copious amounts of jargon related to this field of study. Understanding this jargon and how it can have an impact on the study related to ML goes a long way in comprehending the study that has been conducted by researchers and data scientists to get AI to the state it now is.

In this article, I will be providing you with a comprehensive definition o…
2018-02-05 11:51:34+00:00 http://bigdata-madesimple.com/machine-learning-explained-understanding-supervised-unsupervised-and-reinforcement-learning/

CloudQuant Thoughts : It’s great to apply Machine Learning to the Markets with CloudQuant but with Supervised, Unsupervised and Reinforced Machine Learning and AI there are even more opportunities out there. The markets change rapidly and self-adapting systems are ideal for those situations.

 

Stock Market Volatility & Your Retirement, Who You Gonna Call? Robo Or Human Advisor

…et change mean for me?”

Spooked investors looking for reassurance beyond the panic in the headlines have two options to turn to. They can call up a financial advisor, or they can go on the Internet. Artificial intelligence, or fintech’s application of AI, robo advisors, are viewed by many as the future of affordable and effective retirement and investment advice. These algorithms are seen as the technology that will disrupt, if not replace, human advice.

The February correction is a natural occasion to explore how advice by algorithm compares with human-provided financial advice in times of high anxiety. The Ghost…
2018-02-11 00:00:00 https://www.forbes.com/sites/josephcoughlin/2018/02/11/stock-market-volatility-your-retirement-who-you-gonna-call-robo-or-human-advisor/ 

CloudQuant Thoughts : Curate your backtest data carefully. If you give ML data from the last few years it will assume that the market always goes up. Cleaning can also include carefully selecting a group of negative periods to help develop a backstop for your models that can reduce this myopic view.

 

Robot Rings NYSE Opening Bell

On a day computerized trading was being blamed in part for the market turmoil, a lifelike robot helped ring the opening bell at the NYSE on Tuesday.

The bell ringing followed two days of roiled trading on Wall Street. Treasury Secretary Steven Mnuchin told a Capitol Hill hearing on Tuesday that computerized trading helped drive the big market plungeson Friday and Monday.

Bina48, developed by the company behind the more outspoken bot Sophia, opened the trading day at the New York Stock Exchange alongside UBS executives. “She” was scarily tough to pick from the others on the podium.
2018-02-06 14:17:12-05:00 https://www.cnbc.com/2018/02/06/robot-bina48-rang-the-opening-bell-at-the-nyse-tuesday.html

CloudQuant Thoughts : Want to join in? We are looking for data scientists who want to turn their skills to the world of algorhythmic trading. The volatility over the last week has given us a lot more data to help predict and prevent loses. Use your Machine Learning skills to win an allocation of millions for your own model from CloudQuant.

 

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