A data scientist at India's prestigious Vellore Institute of Technology has outlined a method for how to purportedly predict crypto prices in real-time using a Long Short-Term Memory (LSTM) neural network. In a blog post published on Dec. 2, researcher Abinhav Sagar demonstrated a four-step process for how to use machine learning technology to forecast prices in a sector he purported is "relatively unpredictable" as compared with traditional markets. Sagar prefaced his demonstration by noting that while machine learning has achieved some success in predicting stock market prices, its application in the cryptocurrency field has been restricted. In support of this claim, he argued that cryptocurrency prices fluctuate in accordance with fast-paced technological developments, as well as economic, security and political factors. Sagar's four-step proposed method involves 1) collecting real-time cryptocurrency data; 2) preparing the data for neural network training; 3) testing the prediction using the LSTM neural network; 4) visualizing the results of the prediction.

Transparency Market Research, in its latest market intelligence study, finds that the global Commercial Artificial Intelligence market registered a value of US$ xx Mn/Bn in 2018 and is spectated to grow at CAGR of xx% during the foreseeable period 2019-2029. In terms of product type, segment holds the largest share, while segment 1 and segment 2 hold significant share in terms of end use. The Commercial Artificial Intelligence market study outlines the key regions – Region 1 (Country 1, Country 2), region 2 (Country 1, Country 2), region 3 (Country 1, Country 2) and region 4 (Country 1, Country 2). All the consumption trends and adoption patterns of the Commercial Artificial Intelligence are covered in the report. The report has been compiled through extensive primary research (through interviews, surveys, and observations of seasoned analysts) and secondary research (which entails reputable paid sources, trade journals, and industry body databases).

When the promising British artificial intelligence start-up DeepMind was bought by Google in 2014 for a reported £400m, the deal came with strict conditions meant to ease fears that its world-leading technology would be exploited by the US tech giant. The company would set up an independent ethics board to preside over its development of "artificial general intelligence", a system that mimics the way humans think. None of DeepMind's health data would be associated with Google accounts or services. And its leaders and headquarters would remain in London, where the company was founded. Critics say that those pledges have been eroded since then.

"Whether they're [international relations] students who want to apply machine learning tools to what they're working on or computer science students …

This book provides an excellent pathway for gaining first-class expertise in machine learning. It provides both the technical background that explains why certain approaches, but not others, are best practice in real world problems, and a framework for how to think about and approach new problems. I highly recommend it for people with a signal processing background who are seeking to become an expert in machine learning.

For now, the solution appears to be to retrain the model using datasets in your domain. This is a great primer on classical text summarization. I covered text summarization a couple of months ago during a DeepCrawl webinar. At that time the PreSumm researchers released an earlier version of their work focused only on extractive text summarization.

SpaceX launched a three-ton shipment to the International Space Station on Thursday, including "mighty mice" for a muscle study, a robot sensitive to astronauts' emotions and a miniature version of a brewery's malt house. The Dragon capsule also is delivering holiday goodies for the six station residents. NASA's Kenny Todd isn't giving any hints, but said, "Santa's sleigh, I think, is certified for the vacuum of space." The recycled capsule should arrive Sunday. The Falcon rocket blasted off from Cape Canaveral a day late because of high winds.

There seems to be a noticeable trend on Wall Street: Most financial services professionals share similar demographics. Recruiting startup Suited plans to break the stigma with artificial intelligence technology – targeting the diversification of the industry. Suited co-founder and CEO Matthew Spencer told FOX Business' Maria Bartiromo on Thursday how Suited matches diverse job candidates with appropriate roles. "Suited opens access to early-career job opportunities in the financial professional services sector to a wider range of candidates," Spencer said. "Leveraging technology enables firms to consider those candidates more efficiently, effectively and equitably."

In a bid to enable its enterprise customers gain better insight into business data, Amazon has launched two artificial intelligence services aimed at helping businesses make sense of business data spread across segments and processes. Usage of Machine Learning has been kept on a pedestal while designing these services. The two services - Contact Lens for Amazon Connect and Amazon Kendra are available for its customers using AWS cloud. The services promise to change how enterprise search is done by incorporating new technological capabilities like Natural Language Processing. Amazon Kendra is a plug and play service and does not require expertise in machine learning for the business user.