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) …
The future of decision-making includes an inventive blend of information, analytics, and artificial intelligence (AI), with the perfect scramble of human judgment. The outcome is augmented intelligence, where the analytical force and speed of AI assumes control over most of data processing, controlling human workers to make progressively agile, more intelligent choices and find new discoveries. The development of analytics has caught the consideration of the heads of significant organizations. However, regardless of progressions throughout the years, few have had the option to stay aware of how to utilize analytics and AI among employees, in processes, and with appropriate oversight. The outcome is a lot of smart thoughts and technologies, however, applications that miss the mark regarding their potential.
For many service providers, 2.7 touch points annually would be too few for them to adequately run their business on. Data is integral to improving processes and is being treated with, with it expected to reach 175 zettabytes by 2025 (Swiss Re, 2020). Any company that therefore does not collect data for their users, or, more importantly, actively collects data and utilises feedback information to better inform their service offerings, will be left behind. The most successful companies in the world are those that solve problems and pain points before the user even knows they exist; Amazon, for example, letting us know what people similar to us have also bought so that we know not to forget our batteries, or Asos, offering views of what clothes look like on a variety of body types. These customer informed solutions are informed by the data these companies collect on a second- by- second basis.
In this section, we will talk about Artificial Intelligence, its history, applications, the different types of AI, and the programming languages that are used for AI. Note that I will not be talking about how to code AI but mainly focus on the various languages which support AI. No, don't close this tab!!! Ok fine, I'll start doing my job of explaining properly. "The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages." In simple words, AI is the science of making machines that can think. It's a technique of getting machines to work and behave like humans which accomplishes this task by creating machines and robots.
There is no denying that artificial intelligence (AI) is one of the biggest technologies of the current generation. It holds tremendous potential in domains like healthcare, education, manufacturing, etc. However, to everyone's surprise, AI has also found an application in the creative arena. For instance, mobile app developers are using AI to design a better mobile app user experience. There is also a wide range of graphic design software that leverage AI for creating complex designs.
How dangerous will artificial general intelligence (aka super intelligence) really be? It depends on who you ask. Elon Musk believes unregulated AI will kill us all, while Steven Pinker asks us not to assume all intelligence is evil and callous, and suggests safeguards can prevent the worst-case scenario. In this video, Elon Musk, Steven Pinker, Michio Kaku, Max Tegmark, Luis Perez-Breva, Joscha Bach and Sophia the Robot herself all weigh in on the debate.
Artificial Intelligence is making a great noise adding weight to the superhuman intelligent machines and long-term goal of human-level intelligence. It could be catastrophic for the human race if that happens to be true. At the current juncture, we are unable to specify the objective, nor can we anticipate or prevent the potential pitfalls that may arise if machines capacitate themselves with superhuman capabilities. Already, an alternate world of deep fakes exists which has caused a great deal of hullabaloo across the world, with disastrous consequences for well know personalities and power figures. Thus, with so much at stake, the great minds of today have already locked horns over a serious debate, seeking solutions, ferreting out loopholes, weighing up the risks and benefits, and so on.
I don't know whether you know it or not… but there are a lot of misconceptions surrounding artificial intelligence. While some assume it means robots coming to life to interact with humans, other ones believe it is a superintelligence that soon will take over the world. Well, I consider this to be very discouraging. Not for me to explain the importance of knowing what AI is and what it can really do (especially if you are thinking about establishing your own AI expertise, or you are already using it). Today, I offer to take care of terminology and don't be so naive anymore. In this article, I'll aim to highlight some of the most necessary concepts in a clear, straightforward way. So, feel free to grab your coffee and a comfortable chair, and just dive in.
Human error is one of the greatest causes of data breaches worldwide, but the seeming inevitability of it makes human error especially dangerous While malicious or criminal attacks can be combatted by state-of-the-art cybersecurity software, and while you can prepare for IT failures with a diligent backup strategy, human error is still in need of a remedy. Humans are naturally prone to making mistakes. Such errors are increasingly impactful in the workplace, but human error in the realm of cybersecurity can have particularly devastating and long-lasting effects. As the digital world becomes more complex, it becomes much tougher to navigate
Artificial intelligence (AI) has traditionally been deployed in the cloud, because AI algorithms crunch massive amounts of data and consume massive computing resources. But AI doesn't only live in the cloud. In many situations, AI-based data crunching and decisions need to be made locally, on devices that are close to the edge of the network. AI at the edge allows mission-critical and time-sensitive decisions to be made faster, more reliably and with greater security. The rush to push AI to the edge is being fueled by the rapid growth of smart devices at the edge of the network--smartphones, smart watches and sensors placed on machines and infrastructure.
It is becoming increasingly clear that there is an infinite number of definitions of intelligence. Machines that are intelligent in different narrow ways have been built since the 50s. We are entering now a golden age for the engineering of intelligence and the development of many different kinds of intelligent machines. At the same time there is a widespread interest among scientists in understanding a specific and well defined form of intelligence, that is human intelligence. For this reason we propose a stronger version of the original Turing test.