Have you ever wished you could simply think a command and your computer would respond? That's the future envisioned by Massachusetts Institute of Technology (MIT) researchers who created AlterEgo, a wearable system that allows you to converse with a computer without using your voice or movement. According to a video on the project from MIT Media Lab, the ultimate goal of AlterEgo is "to combine humans and computers." A computing system and wearable device comprise AlterEgo, a futuristic project led by graduate student Arnav Kapur of the Fluid Interfaces group at MIT. Electrodes, a machine learning system, and bone-conduction headphones help get the job done: the electrodes "pick up neuromuscular signals in the jaw and face that are triggered by internal verbalizations -- saying words'in your head' -- but are undetectable to the human eye," according to a MIT News statement. A machine learning system, trained to correspond certain signals with words, receives the signals. The bone-conduction headphones "transmit vibrations through the bones of the face to the inner ear."

In one season, it rains heavily, cities get flooded with water, and life comes to a halt. In another season, there is a scarcity of water and thousands of lives are affected every year with drought. Can I harvest the rain water and manage water scarcity? This is one student thinking differently, observing a problem, asking questions and challenging situations, developing a solution and creating an impact. As a society, we often discuss problems, share our views and opinions, but how many of us really contribute towards developing innovative solutions to address the problem?

According to Warren Buffet, the CEO of Berkshire Hathaway, any technology that reduces auto accidents is remarkable, but auto insurance companies should not be holding a party, yet. The truth is, 90% of car accidents are a result of human error. Thanks to autonomous vehicle technology, that percentage will soon be lower than 5%. There are so many technological advancements taking place now. The future of car insurance is here and it's amazing.

The Facebook crisis involving Cambridge Analytica's data breach leads many to question how Facebook treats their users' data; Reaction on'Outnumbered.' The man who revealed the Cambridge Analytica data-harvesting scandal said Sunday he believed the political consulting firm snatched information from more than the previously reported 87 million Facebook users. "I think that there is, you know, a genuine -- a genuine risk that this data has been accessed by quite a few people. And that it could be stored in various parts of the world, including Russia, given the fact that, you know, the professor who was managing the data harvesting process was going back and forward between the U.K. and to Russia," Christopher Wylie said on NBC News' "Meet the Press." Wylie was referring to Aleksandr Kogan, whose company, Global Science Research, harvested Facebook's data using a personality app, according to officials.

The best results come down to you, the practitioner, crafting the features. Feature importance and selection can inform you about the objective utility of features, but those features have to come from somewhere. You need to manually create them. This requires spending a lot of time with actual sample data (not aggregates) and thinking about the underlying form of the problem, structures in the data and how best to expose them to predictive modeling algorithms. With tabular data, it often means a mixture of aggregating or combining features to create new features, and decomposing or splitting features to create new features.

Annual salaries for data scientists and machine learning engineers vary significantly across the world. Based on a 2017 Kaggle survey of data professionals, countries with the highest paid data scientists and machine learning engineers (in USD) were: US ($120K), Australia ($111K), Israel ($88K), Canada ($81K) and Germany ($80K). Countries with the lowest annual salaries were: Brazil ($35K), Poland ($29K), Ukraine ($25K), India ($14K) and Russia ($13K). In my last post, I compared at annual salaries of different data professionals in the US. Data scientists and machine learning engineers from the US reported some of the highest salaries among different data professionals.

An autonomous sentry freezes an "intruder" during a 2006 test of the weapons system by the South Korean military. Fifty-seven scientists from 29 countries have called for a boycott of a top South Korean university because of a new center aimed at using artificial intelligence (AI) to bolster national security. The AI scientists claim the university is developing autonomous weapons, or "killer robots," whereas university officials say the goal of the research is to improve existing defense systems. A web page that has since been removed by the university said the center, to be operated jointly with South Korean defense company Hanwha Systems, would work on "AI-based command and decision systems, composite navigation algorithms for mega-scale unmanned undersea vehicles, AI-based smart aircraft training systems, and AI-based smart object tracking and recognition technology." Toby Walsh, a computer scientist at the University of New South Wales in Sydney, Australia, who organized the boycott, fears that the research will be applied to autonomous weapons, which can include unmanned flying drones or submarines, cruise missiles, autonomously operated sentry guns, or battlefield robots.

Geospatial analytics, an industry where satellites are used to track everything from retail footfall to food production. Companies working on the technology have attracted big money. Orbital Insight raised $50 million in funding last year, while Descartes Labs attracted $30 million and SpaceKnow raised $4 million. One of the industry's pioneers is James Crawford, who worked for NASA and Google before founding Orbital Insight in 2013. "We were seeing an explosion in commercial satellites," said Crawford.

With each industrial revolution mankind, has progressed by leaps and bounds. But that progress has also damaged our environment. Today, climate change, loss of biodiversity, water woes, and food sustainability are among the most pressing global issues. However, the advent of the Fourth Industrial Revolution is set to fundamentally change such trends. Characterized by advanced technologies such as Artificial Intelligence (AI), big data, automation, and quantum computing, the Fourth Industrial Revolution has the potential to heal the past and ensure a better future.

Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. We will use libraries such as scikit-learn, e1071, randomForest, c50, xgboost, and so on.We will discuss the application of frequently used algorithms on various domain problems, using both Python and R programming.It focuses on the various tree-based machine learning models used by industry practitioners.We will also discuss k-nearest neighbors, Naive Bayes, Support Vector Machine and recommendation engine.By the end of the course, you will have mastered the required statistics for Machine Learning Algorithm and will be able to apply your new skills to any sort of industry problem. Pratap Dangeti develops machine learning and deep learning solutions for structured, image, and text data at TCS, in its research and innovation lab in Bangalore.