At least, that could be the case if the fashionista is a customer of one of several services that offer fashion delivered on demand, such as San Francisco-based startup Stitch Fix. Using data analysis software and machine learning to match users with personalized clothing choices, Stitch Fix is ushering the fashion industry into the age of Big Data. For customers who don't pry too closely into the startup's inner workings, the service is intended to feel like magic. "All they're seeing is they order a box of clothes, and presto -- it appears," said Eric Colson, Stitch Fix's chief algorithms officer. Companies in a variety of industries are relying more heavily on data to provide personalized recommendations -- think Netflix using algorithms to find movies or TV shows users might like, or Amazon suggesting additional purchases based on what's in someone's cart.

Deep learning is currently one of the best providers of solutions regarding problems in image recognition, speech recognition, object recognition, and natural language with its increasing number of libraries that are available in Python. The aim of deep learning is to develop deep neural networks by increasing and improving the number of training layers for each network, so that a machine learns more about the data until it's as accurate as possible. Developers can avail the techniques provided by deep learning to accomplish complex machine learning tasks, and train AI networks to develop deep levels of perceptual recognition. Deep learning is the next step to machine learning with a more advanced implementation. Currently, it's not established as an industry standard, but is heading in that direction and brings a strong promise of being a game changer when dealing with raw unstructured data.

Artificial Intelligence seems to have replaced space as the final frontier for man in this century. Toyota unveiled'Yui', the AI agent for a car, at the Consumer Electronics Show held in the US this week. Yui will not just understand driving habits and the roads that the car has travelled; it also plays the role of a Jarvis-like assistant (think the Iron Man movies), offering you information and analyses. The Toyota Research Institute, which has built this technology, thinks these platforms can go live in car models by the end of the decade. However, such modules will not come to Indian markets for another decade, as we lack the telecom infrastructure to support these AI agents with information.

Time series forecasting is an important area of machine learning that is often neglected. It is important because there are so many prediction problems that involve a time component. These problems are neglected because it is this time component that makes time series problems more difficult to handle. In this post, you will discover time series forecasting. What is Time Series Forecasting?

Ten years ago, the best cell phone in the world was the Nokia N73. There was no Uber, no WhatsApp, no Instagram and no Paytm. Then came the iPhone, Android and iPad. App stores, selfies, digital assistants and digital payments followed. Now we have 4G networks, which enable us to broadcast anything to the world from anywhere on Facebook Live.

Though we've always assumed certain crafts will forever remain immune to automation, it seems nowadays nobody is safe from the looming artificial intelligence invasion. While a few years back the prospect of robots snatching jobs from humans might have seemed like a hackneyed plot twist from a cheap science fiction flick, this scenario actually turned into reality for the staff of Japanese insurance firm Fukoku Mutual Life. Get the low-down on the latest and most insane tech being showcased in Las Vegas. The BBC reports the company has made an executive decision to lay off more than 30 employees and replace them with an artificial intelligence system that can calculate insurance payouts. With this move, Fukoku Mutual estimates it will increase productivity by an impressive 30 percent.

Clara Lu is the marketing manager at ViSenze, an artificial intelligence company that makes search by images possible without keywords. With so many articles proliferating the media space on how humans are at the cusp of full AI (artificial intelligence), it's no wonder that we believe that the future -- which is full of robots and drones and self-driven vehicles, as well as diminishing human control over these machines -- is right on our doorstep. But are we really approaching the singularity as fast as we think we are? It's not hard to have that impression with the likes of Elon Musk, Stephen Hawking, leading university departments and research centers around the world and more being highly concerned with the potential risks brought about by AI and taking action now to avoid a doomsday scenario in the near future. They predict that by the year 2030 machines will develop consciousness through the application of human intelligence. In fact, Dr. Hawking told the BBC, "The development of full artificial intelligence could spell the end of the human race."

For more on the future of AI and design, check out Mike Haley's session, The future will see you now: Machine learning transforms design, at the O'Reilly Design Conference, March 19-22, 2017, in San Francisco. Artefact's co-founder, Rob Girling, explores the impact of artificial intelligence on design in this three-part series of articles. His first piece, Will machines take your job?, outlines the unprecedented changes AI and automation will bring to jobs in general. In the second installment, What skills do we need to compete against the machines, he outlines criteria that will make some professions more vulnerable to AI automation. For anyone doubting that AI is here, the New York Times recently reported that Carnegie Mellon University plans to create a research center that focuses on the ethics of artificial intelligence.

As human-like machines begin to perform more advanced tasks, we fear that they will replace us, take our jobs even. But the truth is, machines are making our lives easier and allowing us to focus more on what humans do best, such as making subjective decisions and using our emotional intelligence. Robots and machines, in effect, remove the clutter that often causes our productivity to wane and our attention to waver. Rather than fear technology, we should embrace it because it takes care of repetitive--and often mundane--tasks like data collection and processing. In the workplace, machine learning has the capacity to change how managers spot an employee's talent, how employees share their knowledge and how employers decide whom to promote.

We're barely into the new year, which means it's time for the planet (or the developed world, at least) to get its collective geek on and marvel at the latest electronics at CES. If you've been living in a cave for the past decade or so, CES is the Consumer Electronics Show. It's where newfangled gadgets debut, TV manufacturers try to convince us all that we need to upgrade from our hi-def sets, and techno-hucksters attempt to convince us, yet again, that virtual reality and smartwatches have truly, finally arrived, for real this time. Well, only the cutest little robot you ever did see! His name is Kuri, and you can find him on heykuri.com.