This is the beginning of a new kind of article in our Medium. We are building this company on the values shared by the two communities we serve, sports and crypto. These values need to be present in everything we do, whether they be paying it forward or transparency. Another one of the values that we hold dear, and that we know our community appreciates, is sharing knowledge.
Both crypto and sports are about bringing people from all backgrounds together and teaching them how to handle themselves in our worlds. Well, we have been fortunate enough to acquire some knowledge ourselves while building dotmoovs from the ground up. Now is the time to start sharing that knowledge with you guys.
Let’s talk AI.
We have been dreaming of AI for a long time
Whenever you google “history of artificial intelligence” you will always find the same immediate references. Dartmouth. 1956. Minsky, McCarthy, Shannon, Rochester. These were the people who founded the academic field of artificial intelligence. More than anything else, that means they were the first people to actually use the term artificial intelligence.
But they weren’t the first to consider it, or to create hypotheses about it.
Artificial Intelligence has been part of the way we imagine our world for a very long time indeed. Every civilization, from the ancient Chinese, Egyptian or Greek peoples all had stories and legends about forms of it.
Perhaps the oldest example hails from the Zhou dynasty in 10th Century BC China. King Mu is said to have met an inventor named Yan Shi who showed him an artificial man of his invention who could move and sing.
That’s just an automaton, though, right?
Just a toy, albeit an impressive one?
No. The automaton, according to the story, started flirting with the women that were traveling with the king. We have, thus, been dreaming of artificial men, made of leather, wood, glue and lacquer, for at least 3000 years.
And not just in China.
Fiction inspired science
So when did we stop ascribing magical and mystical roots to these creations and start thinking of them as something we can create by means of science?
Probably in literary fiction.
Over 100 years before the Dartmouth Conference, Mary Shelley wrote Frankenstein. The story, of course, is well known. Dr. Frankenstein is obsessed with creating life. He assembles all the necessary body parts to create a man, and he activates it with the use of electricity, thus creating an entirely new person, capable of thought.
There is an argument to be made that Frankenstein was the very first science fiction novel. Whether we agree with that notion or not, it’s certainly one of the earliest literary depictions of consciousness (or intelligence) created by a scientist in a laboratory.
It would take about one hundred years for the publication of something much closer to what we think of as AI now. In the Czech Republic, R.U.R. came to be. It is a play by Czech writer Karel Čapek and it actually coined the word robot. It’s about a factory that developed artificial humans capable of thinking and working.
The scientific applications are infinite
Let’s go back to that date. 1956.
That is a remarkably young field we are speaking of. It’s a little over 60 years old. You probably know a number of people who were already alive before the words “artificial intelligence” were recorded for the first time.
This should help paint the picture of why AI has had such a rocky tumbly time coming to full prominence. Scientists and academics took a long time to understand exactly what it was and what it could do.
Turing was a scientist. A mathematician, obsessed with early informatics and the possible applications of software and computers if we continued developing them. He was one of the first people to seriously enquire about the parameters of artificial intelligence (before there was even a name for it). He suggested a simple test to understand whether a computer had true intelligence or not. It would work as follows:
Three computer terminals would be set up. Two run by humans, one by the machine. One of the humans would be the questioner, and he would ask specific questions in a specified field to the other two. After the exam, he would be asked to identify which of the other two is the machine. After enough repetitions, if the questioner failed to identify the machine correctly more than half of the time, then we would be in the presence of true intelligence.
(spoiler: no AI has ever passed the Turing test yet.)
The Three Laws of Robotics were developed by writer Isaac Asimov, and they have been taken by many investigators in artificial intelligence as an important reference as far as limits go. They read as follows, and we’re sure you’ll have read them before:
- A robot may not injure a human being or, through inaction, allow a human being to come to harm.
- A robot must obey orders given it by human beings except where such orders would conflict with the First Law.
- A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.
Why do these two examples in particular concern us?
Because they show very clearly what people thought of AI before true work in the field started: intelligence is human, and artificial intelligence means computers and robots will be more like us.
This isn’t necessarily the case.
Tech took over AI
As computers developed, and software started becoming a true part of our lives, the scientific notion of what constituted “intelligence” started deviating a little from this conception. We no longer think of the ultimate measure of “intelligence” as the ability to mimic human behavior.
We have accepted that computers can think some things through much faster and better than humans ever could, even if they don’t yet fully understand English if it’s spoken with an accent.
We will be doing an article a little further down the line about what perception, manipulation, natural language processing, knowledge representation and all the other fields in which AI is growing and flourishing.
Today however, we want to finish this story by telling you about how artificial intelligence is entering a field very dear to us: sports.
Sports is on the bleeding edge of AI
According to EMERJ (a leading AI research and advisory company), there are four major applications for AI in sports as of now.
Here’s a direct quote:
Computer vision specifically, is one of the areas that has the most fascinating possibilities. Computer vision is when we teach a computer to derive information from pictures and video. AIs nowadays have amazing abilities to interpret what they’re seeing and give us accurate information to a point sometimes the naked eye can’t.
Let’s think of a simple example from football: offside.
VAR was first suggested in the context of football matches with a simple human referee. A person watching the match on a screen, and deciding with the benefit of instant replays. But offsides are tricky. What about the camera angles? What if it’s close?
Even with the most advanced technologies, if you have humans placing the deciding lines, there will always be great potential for error and a lot of time wasting.
But the speed at which this technology is evolving is tremendous. If we can teach a computer to understand what it is seeing when it’s looking at sports, what’s to stop us from using that knowledge to help athletes improve?
Better still, what if we teach it how to referee?
It would allow us to compete anywhere, at any time.
dotmoovs is remaking sports
By developing this tech and leveraging it, dotmoovs is leading the world of sports into a brand new future. A future where a foolproof, entirely fair, totally artificial intelligence will judge sporting competitions.
Our AI algorithm is effectively a video-referee. It watches videos of you playing and it scores your performance according to whatever criteria are in place. The first version of our product, our very own MVP, is already in use. We taught our little creation to watch the wonderful athletes in our community as they perform freestyle tricks with a football.
And it knows exactly what it’s seeing.
As we said before: we now understand that AI isn’t necessarily imitating humans. What our product does, judging performances fairly, with exact criteria, time and again, with no mistakes, and no fluctuations in performance, is something a human being could never do.
Playing ball, however…
We will always need people to do that.
If you want to be a part of this journey, and help us continue this history of AI (it’s just beginning, guys, this article will be outdated by the end of the month), then make sure to register and try it out for yourself.
Sports will never be the same again.