While we mostly hear about Artificial Intelligence systems like IBM's Watson, which won Jeopardy! Over the last five years or so, Machine Learning, a type of AI, has been a quickly rising tide that's now starting to permeate nearly every corner of technology. From self-driving cars to online advertising, cybersecurity, and video surveillance, companies are training computers to do many of the things human workers have been doing but better, or at least cheaper. Neural networks, computer systems that aim to simulate the way neurons are interconnected in the human brain, are trained to do these tasks the same way babies learn about the world – by observation, repetition, trial, and error, assisted instead of parents by computer scientists – although babies are still much, much better at it. A neural net learns to understand spoken language, for example, by listening to a lot of recorded speech, such as movie dialogue; it learns to identify objects by looking at tons of images.

Utrip, a Seattle startup that uses machine learning to help travelers plan their trips, just closed a $4 million funding round. Investors in the Series A round include Plug and Play, Tiempo Capital, Acorn Ventures, and executives from companies such as Apple and Costco, participating as angel investors. The cash will go toward Utrip's machine learning and data science operations, which fuel the platform's recommendation engine. "One of the things that our travelers love about Utrip is the depth with which we curate destinations and go beyond those top 10 lists that are available everywhere to offer experiences that are really unique and local and authentic for that destination," said Utrip CEO Gilad Berenstein. "That's one big priority, continuing to build out our machine learning capabilities as well as our human expert network, our chefs, artists, historians, etcetera."

A vast majority of recorded video data is never viewed. Adding more cameras increases the amount of video data collected, but if it's not viewed, the useful information is missed. There is an imbalance between the amount of video data collected and the human attention available to effectively mine that data. As security technology continues to evolve, exciting developments are taking place, with the inclusion of artificial intelligence (AI). Powerful tools are being created that will allow us to modify our approach to video search.

Opinions expressed by Forbes Contributors are their own. The author is a Forbes contributor. The opinions expressed are those of the writer. The Tsubame3.0 is currently being built in Japan. The Tokyo Institute of Technology Global Scientific Information (Tokyo Tech) and Computing Center (GSIC) have begun the development and construction of a supercomputer that's expected to meet the demands of artificial intelligence (AI) and big data applications and process in the petaFLOPS range, which is a quadrillion floating point operations per second (FLOPS).

Did you ever consider all of the examples of machine learning in your personal life? Google's page ranking system, photo tagging on Facebook, and customized product recommendations from Amazon are all driven by machine learning under the hood. How do these same techniques improve productivity for your business? Search is the new data and content curation. Download the Five-Minute Guide to Machine Learning to find out how self-learning technologies drive increasingly relevant answers and better context for cognitive search.

Step counting apps might be not only a waste of time but a dangerous one, according to one expert. The fitness apps might be doing more harm than good because they don't work but force people to focus on ambitious goals that they will never reach, according to a leading computer scientist. "Very few" of the roughly 165,000 healthcare apps are actually based on any scientific evidence, said Dr Greg Hager, from Johns Hopkins University in the US. But they have been downloaded more than a billion times by people looking to improve their health. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar.

A new tool shows just how much of people's personal information is made public on Facebook for anyone to see. The utility, which calls itself Stalkscan, claims to offer all the "'public' info Facebook doesn't let you see". It combs through everything that has been made public by a person – which will probably have happened involuntarily – and collects all of it in one place. It does that using only the unique identifier that each profile has. That means that it's possible to do it for yourself, and see what parts of your online life you may have left exposed, but also that anyone in the world can do it to you, too.

In the immortal words of Steve Jobs: "A lot of times, people don't know what they want until you show it to them." You might believe that customers will love your movie, your product, your job opening- but they may not even know it exists. The job of a Recommendation Engine is to open the customer/user up to a whole new world of products and possibilities, which they would not even think of directly searching for themselves. A Recommendation Engine plays a vital role in increasing the chances of a user buying a product. In today's world, with tons of data from searched products available (thanks to the digital data explosion), it is very easy to find what people are likely to buy – just by looking at their'intent' data. Needless to say, right analysis of such BIG data is absolutely necessary.

How many people could self-driving cars kill before we would no longer tolerate them? This once-hypothetical question is now taking on greater urgency, particularly among policymakers in Washington. The promise of autonomous vehicles is that they will make our roads safer and more efficient, but no technology is without its shortcomings and unintended consequences -- in this instance, potentially fatal consequences. "What if we can build a car that's 10 times as safe, which means 3,500 people die on the roads each year. Would we accept that?" asks John Hanson, a spokesman for the Toyota Research Institute, which is developing the automaker's self-driving technology.

The digital revolution is faster and more comprehensive than the Industrial Revolution at the beginning of the last century. It requires less capital, and focuses on intellectual and digital innovation, which is affordable to many. The innovations produced have therefore had a much more immediate impact on the market. A wide variety of services are now offered by the leaders of this digital revolution, including Google, Amazon, Facebook and Apple. This has resulted in a rush to set up data-oriented cultures and predictive algorithms, to increase company knowledge and automate more business processes.