Nvidia continued to see demand for its graphics processors in the emerging world of artificial intelligence in its fourth quarter earnings reported Thursday. In its fourth quarter earnings release, the Santa Clara, Calif.-based company reported revenue of $2.17 billion, up 55% year over year, on earnings per share of $1.13, up 117% a year ago. Wall Street analysts estimated $2.11 billion in revenue on EPS of 83 cents. Traditionally, the company's processors have been mostly used to power the latest gaming graphics, but the chips have become popular to run AI software in the data center and autonomous vehicles. A specific branch of AI, called deep learning, is where Nvidia's processors particularly shine.

I'm going to start this piece with a confession; I am a'trend' skeptic. Over the last few years I've developed something akin to list fatigue; growing weary of the constant stream of'six things you must know' clickbait headlines that pop up in my feed. If I was being kind I would say that as an industry we are sometimes guilty of exaggerating our predictions on the potential impact of emerging technologies (if I wasn't being kind I'd probably say that in truth a lot of our industry habitually over hypes everything'new' so that anything actually meaningful gets buried in the noise). Artificial Intelligence (AI) is one of those topics that you'll regularly have seen on lists throughout 2016. And editorially, it's fair to say that it's been covered across something of a broad spectrum. A quick Google search will either lead you to an article where AI will bring an end to the food going off in your fridge, or where AI will bring an end to humanity.

In the battle for the 21st century workplace, computers are winning. A January 2017 report from the McKinsey Global Institute estimated that roughly half of today's work activities could be automated by 2055, give or take 20 years. Bottom line is robots want our jobs. And no one is going to build a wall around them or tariff them out of existence. In a way this is nothing new.

When technology and human ingenuity gets together, everybody in society profits. If you look at graphs of GDP / capita over long time periods (850 years), the trend is always upwards. The only things that drag this progress down are severe periods of sickness (like the black death) and widespread war (such as WW2). Overall though, technology makes everyone healthier and richer. At this point in our society's history – technology has never been more important to the global economy.

Artificial intelligence is slowly creeping into our daily lives, and soon, it will become necessary to understand how different agents behave in social dilemmas. To see what would happen in such a scenario, Google's DeepMind researchers developed two games known as'Gathering' and'Wolfpack,' which build off the Prisoner's Dilemma from game theory. Over time, the AI agents learned how to behave rationally – and while they showed the researchers that they would sometimes cooperate, the games revealed the AI would turn on others when necessary. In the first game, known as Gathering, the AI agents (Red and Blue) are tasked with collecting apples. They can also'tag' the other player by shooting a beam at them, which would remove temporarily remove the tagged agent from the game.

Most robot arms we've seen in the past few years have been either attached to our favorite rolling dog/mech robots or been innovative prosthetics on our favorite humans. But why not a little worker bee robolimb plopped on your desk and ready to perform menial and/or delicate tasks? UFactory launched an Indiegogo campaign for its newest domestic helper a few weeks ago, the open source uArm Swift, which has leaped past its $10,000 goal to raise $280,000 at the time of this post. The Swift is an upgrade of UFactory's protoype Metal arm, which came out last May, but keeps its articulated desk lamp appearance that looks like its about to help you build the next Iron Man suit. The new version has expanded functionality, with a port for Grove modular electronics and OpenMV cameras.

An emerging trend promises to bring the power of machine learning to mobile devices, opening the door to a plethora of valuable new applications. Machine learning--the process by which computers can get better at performing tasks through exposure to data, rather than through explicit programming--requires massive computational power, the kind usually found in clusters of energy-guzzling, cloud-based computer servers outfitted with specialized processors. But recent developments may enable machine learning to be embedded into mobile devices, thus greatly expanding applications for its use and providing new opportunities for marketers. Neural networks--computer models designed to mimic aspects of the human brain's structure and function, with elements representing neurons and their interconnections--are an increasingly popular way of implementing machine learning. They are particularly well suited for performing perceptual tasks such as computer vision and speech recognition.

The artificial intelligence market is expected to grow to USD $16.06 Billion by 2022. The McKinsey Global Institute says, "Recent advances in machine learning can be used to solve a tremendous variety of problems--and deep learning is pushing the boundaries even further." One such company set to take advantage of this emerging market is ASX-listed BrainChip Holdings (ASX:BRN) which is headquartered in Aliso Viejo, California. They have developed a Spiking Neuron Adaptive Processor (SNAP) that essentially mimics the human brain: autonomous and unsupervised learning, evolves and associates information. According to CEO Louis DiNardo, SNAP has many applications, which includes surveillance, casino operations, and even investing.

Activity on the tech labs front is happening faster than we can get to it these days, so here are a few "in case you missed it" items... The state of Ohio, JobsOhio and the Ohio State University are putting $45 million into an expansion of the Transportation Research Center's (TRC) 540-acre Smart Mobility Advanced Research and Test (SMART) Center in the Columbus area. Research will focus both on connected and driverless vehicles within this section of the 4,500-acre TRC expanse. This first phase of SMART expansion will include the industry's largest high-speed intersection, an urban network of intersections (i.e., roundabouts, or what we in the Northeast call rotaries), a rural network that includes wooded roads and a neighborhood network for slower speeds. TRC provides the largest independent vehicle testing facility in North America, according to TRC CEO Mark-Tami Hotta.