Education, Science, Technology — January 11, 2020 at 4:16 am

Understanding Artificial Intelligence


Understanding Artificial Intelligence

The field of Artificial Intelligence (AI) is so broad that we cannot scratch the surface in this blog. What we can do however is to give you a broad view of what AI is and it’s application today. AI controls the backbone of several websites and robots, the drones you assemble or play with as soon as you have a free time, and anytime you do a search online to find the best price for that favorite thing you’ve being saving money for. Since AI controls all sorts of technologies that affect your daily life in so many ways, it’s a fare play that you will spend some time to learn how companies are leveraging it to provide better user experiences.

If you don’t know much about AI, the absence of an explanation can be confusing. Artificial intelligence was founded as an academic discipline in 1956, and the research in AI back them has been divided into subfields that often fail to communicate with each other like they do today. These sub-fields are based on technical considerations, such as robotics or machine learning, and the use of particular tools such as logic or artificial neural networks, or deep philosophical differences. If you’re inclined towards a fear of a computer-instigated apocalypse, it may even be scary. Artificial Intelligence is complicated, and it’s constantly evolving, but that doesn’t mean that it should be confusing or anxiety inducing — especially not when your personal information is involved.

There is no doubt about it, AI has the strong tendency to disrupt every aspect of life and radiate enthusiasm and skepticism collectively. AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding; and AI techniques have become an essential part of the technology industry, helping to solve many challenging problems in computer science, software engineering and operations research.

There is no doubt, AI and robotics are changing the way we do business. And so many pundits are burying you in information and disinformation about AI, too. Some see AI as cute and fuzzy; others see it as a potential mass murderer of the human race. The problem with being so loaded down with information in so many ways is that you spend so much time separating what’s real from what is simply the product of an overactive imagination. Much of the hype about AI originates from overzealous and unrealistic expectations of people in power like scientists, entrepreneurs, and businesspersons. The fact that you can be in the office or in your house and start your car remotely to warm it up or control the temperature in your house remotely or remotely control the irrigation in your yard while you’re thousands of miles away means you’ve experience the practical application of AI even in your own life.

To bring AI down to earth, it is any technology that is designed to operate in a way that mimics how humans operate. The AI available today are not perfect and they don’t pretend to be either. They have to learn and adapt, and all of that is done just like you and me (humans) learn and adapt: by taking in information, or data, processing it, and storing it for future reference. It’s like when a young kid touches a hot stove. Their brain registers the pain and makes note to not do it again.

Humans develop AI but Neural Networks are the most clear and tangible application of that thinking. A fully functioning human brain is so complex because it is made of lots of things that have simple tasks, but layers them together to make big things happen. The brain has billions of neurons that are linked together by trillions of synapses. The sheer scale of the operation makes it very difficult to replicate by machine, but that’s exactly what scientists, mathematicians, and experts are trying to do through Neural Networks.

At the Consumer Electronics Show (CES) this year, Samsung’s Ballie wants to be just about everything to you. The tiny, ball-shaped robot can act as a home security system, a fitness assistant, and can also use its AI capabilities to react to its human owner’s ever-evolving needs, according to Sebastian Seung. “On-device AI puts you in control of your information and protects your privacy, while still delivering the power of personalization.”

There are a few computer-generated humans at CES this year as well but they all failed to impress the majority of people. I’m impressed though that they can carry on conversation like a regular human being but lacks the mobility of their flesh and blood counterparts. The “artificial humans” are a result of Neon, a project created by Samsung’s STAR Labs.

One takeaway from this blog is that humans will never be replaced by machines and humans will continue to be important till the end of time. What AI will do is help humans excel in ways that you frankly might not be able to imagine. You just need to prepare yourself so you’re not left behind.

Some of the problems that researchers are having is that the cognitive capabilities of current architectures are very limited, using only a simplified version of what intelligence is really capable of. For instance, the human mind has come up with ways to reason beyond measure and logical explanations to different occurrences in life. What would have been otherwise straightforward, an equivalently difficult problem may be challenging to solve computationally as opposed to using the human mind. This gives rise to two classes of models: structuralist and functionalist. The structural models aim to loosely mimic the basic intelligence operations of the mind such as reasoning and logic. The functional model refers to the correlating data to its computed counterpart.

The overall research goal of artificial intelligence is to create technology that allows computers and machines to function in an intelligent manner. The general problem of simulating (or creating) intelligence has been broken down into sub-problems. These consist of particular traits or capabilities that researchers expect an intelligent system to display.

Early researchers developed algorithms that imitated step-by-step reasoning that humans use when they solve puzzles or make logical deductions. AI research develops concepts from probability and economics for dealing with uncertain or incomplete information. These algorithms proved to be insufficient for solving large reasoning problems, because they become exponentially slower as the problems grew larger. In fact, even humans rarely use the step-by-step deduction that early AI research was able to model. They solve most of their problems using fast, intuitive judgments.

Robot designer Hans Moravec, cyberneticist Kevin Warwick and inventor Ray Kurzweil have predicted that humans and machines will merge in the future into cyborgs that are more capable and powerful than either. This idea, called transhumanism, has roots in Aldous Huxley and Robert Ettinger. Edward Fredkin argues that “artificial intelligence is the next stage in evolution”, an idea first proposed by Samuel Butler’s “Darwin among the Machines” as far back as 1863, and expanded upon by George Dyson in his book of the same name in 1998.

Application of Artificial Intelligence in Business Today
Many businesses are developing their own AI or contract it out to other developers to have their own AI based apps. In the business world, it is always crucial to keep track of what your competitors are doing. Competitive analysis tools like Crayon help track competitors with the help of different channels like websites, social media, and apps to provide business owners with a close look into any changes in competitors’ marketing planning like price changes, subtle message modifications, and PR activities. AI also automates regular sales and monitors overall marketing spend so that business owners can reduce the time spent on tracking marketing campaigns and pay attention to other important areas. AI customer service solutions like DigitalGenius or ChattyPeople suggest or automate answers to incoming customer questions, classify help tickets and direct inquiries or messages to the appropriate department. AI business tools like Monkey Learn integrate and analyze data across various channels and achieve timesaving analytics and reporting like sentiment analysis in Google Sheets, CSV, etc.


The Age of A.I.


  • Rowland Adeniyi

    Rowland Adeniyi is a Botanist, Biologist and a security and Infrastructure Architectures Consultant. Consulting to Universities, High Tech firms, and other agencies.

    View all posts

Leave a Comment

Your email address will not be published. Required fields are marked *