One is the home of America's automotive industry, a heavily regulated, ultra-conservative sector focusing on high-volume, low-margin sales. They are also in competition to own what some are calling the next personal computing platform: the car. The recent focus is less the embedded systems that run vehicles – Linux won that battle – and more the data connections to deliver so-called "infotainment" to those inside and beam diagnostic data back to the manufacturer. Gartner reckons on a five-fold increase in such units globally by 2020 to 61 million. With those units come opportunities.
Everyone has seen all of those sci-fi movies where the machines took over the planet while the unwary humans weren't looking, The good news is that we aren't quite there yet Still, there are real examples of machines that are seeping into our world and most of us aren't really paying attention to them. Artificial intelligence has arrived and the applications that are using it are running the gamut from voice powered assistants like Cortana or Siri or Alexa to the more fundamental ones such as search suggestions, to the downright amazing ones such as self driving cars and trucks, we've got AI working all around us. AI as a technology is a newborn technology, barely in its infancy. Real AI is an entity that actually learns on its own. We use the world entity loosely although many companies and even people call AI an entity.
The last decade was dedicated to building a'mobile-first' world where smartphones took control over the advancements in technology and lifestyle. Lately there has been a dramatic change in the course of action. The big shots of technology have set their sail to build an'AI First' world to unlock capabilities that were unthinkable a few years ago and build a future twice as good. Google Assistant, Amazon Echo, Facebook Spaces and Tesla's self-driving cars stands testimony to this technology shake-up. This technology'Renovation' has already begun and will be in its full swing in the next 3-4 years.
Computers may not wear tennis shoes (yet), but thanks to developing artificial intelligence technologies, they're smarter than ever before. Along with those technologies has come a relatively new category of computer science called machine learning, or ML. Similar to statistics, ML involves computer systems that utilize algorithms to automatically learn about data, recognize patterns, and make decisions, all without outside intervention or explicit directions from human beings. In the real world, you can find it being used in smart assistants like Siri and the Amazon Echo, in online fraud detection services, in the facial recognition feature that identifies photos of you on Facebook, and more recently, in Tesla's self-driving car. ML is distinctive in the world of AI in that it can be used to process vast amounts of data quickly, making it a desirable tech skill among job applicants not only in the fields of computer science and engineering, but also marketing, health care, finance, social media, and beyond.
Alphabet and Google began to embrace practicality in 2016 as the two closely related entities changed course on a number of efforts. After many years of teasing its own self-driving car, it chose instead to become a vendor of car technology. But in more pedestrian device pursuits, the company shifted toward going its own way. It took its virtual reality endeavors to the next level with Daydream, took ownership of its vision for Android phones with the Pixel, and threw its weight around the home with its answer to the Amazon Echo and its tripartite router solution Google Wi-Fi. Here are some things Google could do in 2017 to shore up its path.