It is that time of the year again and 2017 is over before we knew it. The Year of Intelligence brought us a lot of progress and change; from over-hyped ICO's to algorithms that created secret languages. As every year since 2012, I provide you with seven of the most important technology trends for 2018 to help you, and your business, prepare for the next year. One thing that we can state is that we are on our way to enter the 4th Industrial Revolution. Many of the technologies that have been promised for decades are constantly improving and are now reaching a point of maturity. Once that happens, it will radically change our societies, how we work and how we live. However, we are not there yet.

TROY, MI – The future of mobility will be data driven, says Glen De Vos, chief technical officer of Aptiv, and the former Delphi electronics unit wants to be the engine behind the transformation. "It is a big change for us," De Vos says of Aptiv's new role in the industry as chiefly a software company after decades of supplying automakers with components and parts hardware now considered low-margin commodities. De Vos would be happy to keep selling the hardware, too, and the Gillingham, U.K.-based company likely will for many years to come, but it will take a back seat to the software its customers need to raise the connectivity, improve the safety and reduce the unfavorable environmental impact of the vehicles they make. The supplier officially launched Dec. 5 with Kevin Clark, president and CEO of Aptiv, saying the company has an opportunity to play a large role in an industry transformation underpinned by the promise of autonomous vehicles. "Aptiv is built on a strong foundation of industry firsts and has the knowledge, capability and agility to win with traditional OEM customers and emerging mobility players," Clark says of the former Delphi Automotive.

Do you remember when Siri first spoke to you? It was impressive and a little bit scary. But mostly it was entertaining. We all figured out Siri's limitations within a few minutes of messing around with her artificial intelligence (AI) functionality. But today, an update: We have AI like Alexa, which can deliver flowers to our spouses at work, or tell us how to say "pork belly" in Portuguese.

I often feel Artificial Intelligence (AI) is still directionless although we do see a lot of Work In Progress (WIP). AI in transportation is not just about autonomous aircrafts, cars, trucks and trains. There is much more that can be done with AI. Recently IBM helped to create an app that would use Watson Visual Recognition to inform travelers about congestion on London bus routes. In India, the state transport corporation of Kolkata took a technological leap by deploying artificial intelligence to analyze commuter behavior, sentiment, suggestions and commute pattern.

What we're watching: Look for Walmart to increase pressure on lawmakers to stand up to the increasingly influential protectionist faction in the White House. Here's what else Penner had to say: Walmart is made better by "being paranoid" about the competition. On how the company is managing its expansion into China by partnering with JD.com: Editors note: Penner is an investor in Axios.

A drone that hovers over Japanese employees and blares out music to force them to go home has been created by an office security and cleaning firm. The'T-Frend' buzzes over those trying to work late, blasting out the notes of'Auld Lang Syne', a Scottish tune used in Japan to announce that a store is closing. The bizarre machine is an offshoot of the country's efforts to reduce its notoriously long work hours. But experts have branded the idea'silly', claiming workers will simply take work home with them if they are forced to leave. A drone that hovers over employees and blares music to force them to go home has been created.

My report is timed to the 60th anniversary of the launch of the First artificial Earth satellite. Artificial intelligence is created by scientists and programmers of the world. The main scientific and research centers in the field of artificial intelligence are the Massachusetts Institute of Technology (MIT) (USA), the Machine Intelligence Research Institute (USA), the German Research Center for Artificial Intelligence (Germany), the National Institute of Advanced Industrial Science and Technology (AIST) Japan, Russian Academy of Sciences (Russia). Different technological communities are also interested in the development of artificial intelligence. They create new technologies and platforms, including crypto-currencies.

COMMANDING the plot lines of Hollywood films, covers of magazines and reams of newsprint, the contest between artificial intelligence (AI) and mankind draws much attention. Doomsayers warn that AI could eradicate jobs, break laws and start wars. The competition today is not between humans and machines but among the world's technology giants, which are investing feverishly to get a lead over each other in AI. An exponential increase in the availability of digital data, the force of computing power and the brilliance of algorithms has fuelled excitement about this formerly obscure corner of computer science. The West's largest tech firms, including Alphabet (Google's parent), Amazon, Apple, Facebook, IBM and Microsoft are investing huge sums to develop their AI capabilities, as are their counterparts in China. Although it is difficult to separate tech firms' investments in AI from other kinds, so far in 2017 (see chart 1) companies globally have completed around $21.3bn in mergers and acquisitions related to AI, according to PitchBook, a data provider, or around 26 times more than in 2015.

Discovering, extracting, and analyzing data patterns in textual data from the myriad data sources streaming into modern data-driven organizations is no easy task. Organizations must be equipped with state-of-the art techniques such as Natural Language Processing (NLP) within well-developed Artificial Intelligence (AI) and Machine Learning (ML) platforms, to reliably understand the pulse of their consumers in real time, while also controlling the data deluge that often overwhelms under-prepared organizations. The ability to derive patterns and insights from a plethora of structured and unstructured document types requires the skill to prioritize and understand which pieces of information are most important to act upon first. According to Karthikeyan Sankaran, Director of Data Science and Machine Learning at LatentView Analytics, in a recent DATAVERSITY interview, such an skill requires organizations to have a platform that can "harness the textual data assets so they can then potentially solve interesting and profitable use cases." This is where Natural Language Processing (NLP), as a branch of Artificial Intelligence steps in, extracting interesting patterns in textual data, using its own unique set of techniques.

Sawada speculates that 70 percent of the jobs at Japan's hotels will be automated in the next five years. "It takes about a year to two years to get your money back," he said. "But since you can work them 24 hours a day, and they don't need vacation, eventually it's more cost-efficient to use the robot." This may seem like a vision of the future best suited--perhaps only suited--to Japan. But according to Michael Chui, a partner at the McKinsey Global Institute, many tasks in the food-service and accommodation industry are exactly the kind that are easily automated.