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The Future of Artificial Intelligence



Where Things Are & Where They're Headed

What do a Tesla car, Siri, and Rumba vacuum have in common? We'd give you a hint but that would give it away! They all leverage forms of AI, also known as artificial intelligence.

It may or may not surprise you depending on your knowledge of innovative tech, but AI is increasingly involved in our everyday lives. As computers are engineered to be smarter, stronger, and faster, innovators are coming up with ways to use them to make our lives simpler.

Not only do we use software to automate simple tasks daily, such as playing a song or finding out the weather, but AI is integrated now more than ever into the labor market. This may have piqued your interest which is why we're going to be running down some of the most important points when considering where AI is today and where it's going.


What is AI

When you think of artificial intelligence, odds are one of the first things you might think of is robots, right?

Due to the media and cinema depictions of AI over the past couple of decades, humanoid robots and world-ending systems are poster portrayals most people think of when they hear AI. But, artificial intelligence is much more intricate and complex.

In RSnake's interview with Russ Bodnyk, Bodnyk touches on this. He says that AI is such an intricate tool that is always evolving. Bodnyk says that creating a cemented definition can be difficult, especially when considering the idea of consciousness. However, given the developments in artificial intelligence over the past decades, some definitions do exist.

The replication of human intelligence functions by machines, particularly computer systems, is known as artificial intelligence. AI is programming machines to think and act like humans to automate a process or achieve a goal. There are two important subsets of AI that are important to consider, machine learning and deep learning.

Machine learning is the idea that without human involvement, a computer program can pick up new information and adjust. It is the ability of a computer, to recognize data and generate predictions based on that data enabled by a sophisticated algorithm or source code.

Deep learning on the other hand, is a type of machine learning technology, which helps computers to learn by doing what comes easily to people. Machine learning, which is simply a neural network with three or more layers, is a subset of deep learning. This type of AI is different from machine learning because of programming.


A key difference surrounds deep learning being used as a technique for automating predictive analytics. These algorithms are piled in a system of complexity and abstraction, as opposed to conventional machine learning algorithms, which are linear. Digital assistants, voice-activated TV remotes, and credit card fraud prevention are examples of deep learning at work.

With the volume of data and information that is produced online, machine learning is instrumental in ensuring that information is readily available by computed decision-making. Since tech is the leading-edge industry today, machine learning can be applied to a wide array of businesses.

An Overview of AI Today

Artificial Intelligence has come a long way and works within society on so many levels within different spaces and industries. AI is a large focus nowadays with tech companies inventing new ways that it can be used to help businesses and people.


By using artificial intelligence, processes involving decision-making, immediate response, and repetitive actions are streamlined. This means elevated performance and better efficiencies across the board.

Where is AI Being Used?

AI has been integrated into a wide array of industries. Many tasks that would otherwise previously been conducted by humans now rely heavily on AI and machine learning.

Every year billions upon billions of dollars are invested in the development of AI technologies. Some might argue that AI isn't mainstream, yet Amazon Alexa is sitting in millions of living rooms across the world.

Artificial intelligence and machine learning are now being used in finance, healthcare, telecommunications, IT, transportation, marketing, and e-commerce, just to name a few. These industries are just a drop in the bucket for opportunities where AI can be used to streamline efficiency.

Transportation, for instance, is one of the areas which has seen immense growth and opportunity. Since the global market for AI in the transportation market is expected to reach $3,870,000,000 by 2026, many in the transportation industry have already recognized AI's incredible potential.


Russ Bodnyk talks about the furthering development of AI-driven vehicles. On a wider scale, collision rates could dissipate and texting while driving could become redundant. It would be at this point where AI becoming integrated into society at a level to governing how people navigate society.

The History of AI


Artificial intelligence has always been an idea that humans have contemplated, from early theorists and philosophers to modern-day authors and researchers. However, Artificial Intelligence has evolved significantly since its inception in the mid-20th century.

The 1950s were the decade where AI developed and gave way to many findings within the field. One pivotal moment in AI history would be Alan Turing's publication of "Computing Machinery and Intelligence". Remember the 2014, film The Imitation Game? That was based on Turing's idea, renamed the Turing Test, which seeks to examine whether a computer can think like a human, or not, or at least convince a human that it does.

This test became a turning point in AI. Following this, American computer scientist John McCarthy held the first AI conference and coined the term in 1956.

Almost a decade later developments were thriving and looming the 1970s the first mobile robot was built. Fast-forward to the late 1990s and the supercomputer Deep Blue was created. In a game of chess, the computer defeated the world champion. The development of this big computer by IBM was a significant accomplishment.

In the 2000s, the world saw the first robotic vacuum cleaner created. Over the past two decades, developments in AI and ML took off. We've seen many forms of speech recognition, like Apple's Siri and Amazon's Alexa, besides smart home features and self-driving cars.

With such innovation prominent in artificial intelligence, there is much more to come. But many wonder, at what cost will further development come?

Artificial Intelligence: Opportunities vs Obstacles

With almost any invention, with opportunity comes obstacles. In the realm of artificial intelligence, this can mean many things, from funding to development. Russ Bodynk shared his thoughts on where AI is headed in the future. He says at this time we're playing by the benchmarks and that more creativity will be needed.

Pros of AI

Though it is still a developing field of study, artificial intelligence (AI) is already having a significant impact on data analysis, engineering, research, and even medicine. It's no secret that as the scope of AI continues to expand, so do the benefits which will continue to revolutionize industries and sectors alike.

One significant benefit of using artificial intelligence is the reduced the frequency of errors that are made by humans. We've all heard the phrase everyone makes mistakes, but if a computer is programmed correctly, common human errors can be avoided.

Artificial intelligence uses a specific set of algorithms to make conclusions based on information that has already been obtained. This advantage is highly impactful, resulting in minimized errors, and a likelihood of attaining consistency with a greater level of certainty. When you think about it on a grand scale, fewer mistakes leads to cost and time savings, so really you can't go wrong.

Since AIs are programmed to and state machines operate quickly, they make faster decisions more decisively based on their written program. Not to mention AI works with other technologies to make decisions faster, which is advantageous over human decision-making since bias and emotions are often involved. The morality of their decisions is entirely determined by the programmers and inputs the AI operates on, not the machine’s own ethics.

A unique characteristic of artificial intelligence is its capability to continue learning based on previously input information. So really, decisions are made faster, with up-to-date knowledge at any time of the day since AIs don't sleep.

Machine learning and artificial intelligence