If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Machine-learning (ML) technology is radically changing how robots work and dramatically extending their capabilities. The latest crop of ML technologies is still in its infancy, but it looks like we're at the end of the beginning with respect to robots. Much more looms on the horizon. ML is just one aspect of improved robotics. Robotics has demanding computational requirements, and that's being helped by improvements in multicore processing power.
In 2018, the world witnessed the continued development of technologies like artificial intelligence and virtual reality. As these tools become more accessible and widely used among both businesses and consumers, many tech industry experts are speculating about what the next "big thing" will be. Looking ahead to 2019, we asked a panel of Forbes Technology Council members for their take on upcoming trends in their field. From blockchain as a service to enterprise content management, here are their predictions about the next wave of breakout technologies. The blockchain is not as revolutionary as artificial intelligence (AI), or as intuitive and user-friendly as voice control, but it will transform the way we handle finance, real estate, internet of things (IoT), the supply chain of most industries and much more.
The world has been through multiple'AI winters' (a time when the perception of artificial intelligence as a solution collapses and funding is withdrawn from major projects) since the tech's early days in the mid-20th century. However, the last such period, in the 1990s, is long since over, and AI is back in vogue once again, with ever-rising numbers of people working to prove that machines can simulate human learning. One of AI′s early movers and shakers was Marvin Minsky, whose work includes the first randomly wired neural network learning machine, which he built in 1951. In 1967 Minsky predicted that "within a generation... the problem of creating'artificial intelligence' will substantially be solved." He was wrong about that.
In a laboratory that overlooks a busy shopping street in Cambridge, Massachusetts, a robot is attempting to create new materials. A robot arm dips a pipette into a dish and transfers a tiny amount of bright liquid into one of many receptacles sitting in front of another machine. When all the samples are ready, the second machine tests their optical properties, and the results are fed to a computer that controls the arm. Software analyzes the results of these experiments, formulates a few hypotheses, and then starts the process over again. The setup, developed by a startup called Kebotix, hints at how machine learning and robotic automation may be poised to revolutionize materials science in coming years.
Microsoft is demonstrating greater commitment to robotics by announcing Windows support for the Robot Operating System (ROS) and joining an industrial consortium. ROS is a flexible framework that enables developers to write software for advanced robotic behaviours. While the collection of tools, libraries, and conventions has historically only had official support on Linux, developers will now be able to utilise the tools in Windows 10. The move will see Microsoft work with Open Robotics and the ROS Industrial Consortium to bring the Robot Operating System to Windows. Microsoft has also joined the Consortium, which works to extend the advanced capabilities of ROS into manufacturing and improve the productivity and return on investment of industrial robots.
NVIDIA Isaac platform with Jetson Xavier, a computer designed specifically for robotics.NVIDIA Robots are a well-established part of manufacturing but have the opportunity to unlock new efficiencies in industries such as retail, food service and healthcare. To date, robots have primarily been enclosed or segmented into specific areas to protect people from possible injuries. Today, companies want to integrate robotics into various types of workplaces, but this requires a new design paradigm for robotics. Allowing a robot to move freely in an unpredictable environment requires fast, reliable, intelligent computing within the robot. The ability to deliver this level of complex computing at within a small component, at a low price point has held the robotics industry back.
It's a time-tested science fiction trope, guaranteed to strike fear into the heart of anyone who ever watched The Terminator and wondered, "Is that really possible?" But, in reality, machine learning and cloud technologies are already being used to develop robots that are better, smarter, faster, and more useful than ever before. And it's happening faster than many people think. In fact, cloud technology is proving to be the tipping point from the basic, single-purpose robotics of years past--think assembly line robots, or the machines that vacuum our floors and wash our dishes--to devices that can think, act, and work alongside humans seamlessly. Big Data, artificial intelligence, machine learning, and more are now being used to develop robots' own neural networks, making use of today's large data sets to train machines on behavior.
We see news about AI everywhere; sometimes, we see the excitement around AI and sometimes we see articles that talk about how AI will replace or destroy our jobs. We also see the occasional article talking about how AI will destroy humanity. In this article, I will not discuss an artificial general intelligence or an evil AI that wants to destroy humanity. I will focus on current AI, which is mostly based on the algorithms that can do predictions, and discuss how the economics of AI works and how it may affect business. I also want to mention that the content of this article is highly affected by (and this author highly recommends for further reading) Prediction Machines: The Simple Economics of Artificial Intelligence and Human Machine: Reimagining Work in the Age of AI.
A world renowned pioneer in social robotics, Cynthia Breazeal splits her time as an Associate Professor at MIT, where she received her PhD and founded the Personal Robots Group, and Founder and Chief Scientist of Jibo, a personal robotics company with over $85 million in funding. While Breazeal's work has won numerous academic awards, industry accolades, and media attention, she had to fight early skepticism in the 1990s from other experts in robotics and AI. At the time, robots were seen as physical and industrial tools, not social or emotional companions. Her first social robot, Kismet, was unfairly called out in popular press as "useless". Breazeal bucked the trend with a very different vision: "I wanted to create robots with social and emotional intelligence that could work in collaborative partnership with people. In 2-5 years, I see social robots helping families with things that really matter, like education, health, eldercare, entertainment, and companionship." She hopes her work and influence will inspire others to create robots "not only with smarts, but with heart, too."
It took me 4 hours and 5 minutes to effectively annihilate the Universe by pretending to be an Artificial Intelligence tasked with making paper-clips. Put another way, it took me 4 hours and 5 minutes to have an existential crisis. This was done by playing the online game "Paperclip", which was released in 2017. Though the clip-making goal of the game is in itself simple, there are so many contemporary lessons to be extracted from the playthrough that a deep dive seems necessary. Indeed, the game explores our past, present and future in the most interesting way, especially when it comes to the technological advances Silicon Valley is currently oh so proud of.