GO is arguably the most complex board game in existence. Its goal is simple, surround more territory than your opponent. This game has been played by humans for the past 2500 years and is thought to be the oldest board game – still being played today. However, it’s not only humans that are playing this game nowadays. In 2016, Google’s deep mind’s AlphaGo beat 18-time-world champion Lee Sedol in four out of five games. Now, normally a computer beating a human at a game like chess or checkers wouldn’t be that impressive but GO is different. GO cannot be solved by brute force. GO cannot be predicted.
There are over 10 to the 170 moves possible in GO. To put that into perspective there are only 10 to the 80 atoms in the observable universe. AlphaGo was trained to use data from real human GO games. It ran through millions of games and learned the techniques used and even made up the new ones that no one had ever seen. And this very impressive alone. However, what many people don’t know is that only a year after AlphaGo’s victory over Lee Sedol, a brand-new AI called AlphaGo ZERO beat the original AlphaGo. Not in four out of five games, not in five out of five games, not in ten out of ten games, but beat AlphaGo 100 to zero.
Without human interaction, it can play
There are 100 games in a row, the most impressive part, it learned how to play with zero human interaction. This technique is more powerful than any previous version. Why? It isn’t restricted to human knowledge. No data was given, no historical figures were given, with just the bare-bones rules. AlphaGo Zero surpassed the previous AlphaGo in only 40 days of learning. In only 40 days it surpassed over 2500 years of strategy and knowledge. It only played against itself and is now regarded as the best GO player in the world, even though it isn’t human.
But wait, if this AI has learned without any human interaction, made-up strategies on its own and then beat us with those strategies, then that means there’s more non-human knowledge about GO then there is human.
Continue to develop artificial intelligence
And if we continue to develop artificial intelligence, then that means there’s going to be more and more non-human intelligence. Eventually, there’s going to be a point, where we represent the minority of intelligence, maybe a very minuscule amount. That’s fine though, we can just turn it off. That’s a thought but think! When modern-day humans begin to take over the planet, why didn’t the chimps and the earth turn us off?
If this artificial intelligence becomes super-intelligent and learns through and is connect to the Internet, we can’t just shut down the entire Internet. There’s no off switch! So, what happens if we end up stuck with AI that is constantly and exponentially getting smarter than we are? What if it gets to a point that humans get in the way and the AI hits the off switch on humans?
Robots that defeat people playing chess that we can talk to – science has for many years been trying to artificially replicate the complex human mind. So far, it has not had much success with it.
How intelligent is Artificial Intelligence?
The research field “Artificial Intelligence” (AI) tries to reproduce human perception and human action through machines. What began as a science of computer programming has become more and more the research of human thought. Because after decades of research, one has recognized the impossibility of creating a “thinking” machine without first having researched and understood human thinking itself. Therefore, there are some major overlaps between artificial intelligence research and neurology or psychology.
To this day, it has not even been possible to reconstruct human psychological achievements as a whole with machines. A big obstacle is language processing. Even the execution of simple commands is a highly complex process for a machine. In the meantime, research is increasingly concentrating on individual subareas, with the aim of making work easier there. For this purpose, a constant exchange between scientists of various disciplines (cognitive science, psychology, neurology, philosophy, and linguistics) is necessary.
When does a computer pass the Turing test?
The question of when a machine is considered intelligent drives artificial intelligence research for decades. One measurement tool that is commonly accepted is the so-called Turing test. It was developed in 1950 by the British mathematician Alan Turing: A person communicates for a long time in parallel with another person and a machine without visual or hearing contact – for example via a chat program.
Man and machines try to convince the tester that they are thinking people. If, after the conversation, the tester can not say with certainty which of the interlocutors is a human and which is a machine, the machine has passed the test and may be considered intelligent.
The US sociologist Hugh G. Loebner praised in 1991 a price of $ 100,000 for the computer program that passes the Turing test. So far, no one has received the award, and the bulk of the Artificial Intelligence researchers believe that will not happen in the foreseeable future.
Tamagotchis, Robots & Co
The fields of application of Artificial Intelligence are extremely diversified. Often we are not even aware of them. Their use is most successful in small areas such as medicine: robots perform certain surgical procedures – in the thousandths of a millimeter range – much more precisely than a surgeon.
In production lines, especially in the automotive industry, robots replace a myriad of human handholds. Especially in health-damaging, accident-prone tasks, such as when painting or welding, robotic arms, as they were used in the 1960s at General Motors, have become indispensable.
Classic applications for Artificial Intelligence are games, especially board games like chess. Programmable and adaptable toys, mini robots and computer programs long ago conquered the nursery.
Robot dog AIBO is already a reality!
The legendary Tamagotchi is already the past, but other artificial companions such as the robot dog AIBO are entering the market. It can record videos, keeps its own diary and plays CDs on request if you hold the respective cover to its mouth.
GO is arguably the most complex board game in existence. Its goal is simple, surround more territory than your opponent. Humans have played the game for the past 2500 years and is thought to be the oldest board game – still being played today. However, it’s not only humans that are playing this game nowadays. In 2016, Google’s deep mind’s AlphaGo beat 18-time-world champion Lee Sedol in four out of five games. Now, normally a computer beating a human at a game like chess or checkers wouldn’t be that impressive but GO is different. Brute force cannot solve GO. It can not predict GO.
There are over 10 to the 170 moves possible in GO. To put that into perspective there are only 10 to the 80 atoms in the observable universe. AlphaGo’s trained to use data from real human GO games. It ran through millions of games and learned the techniques used and even made up the new ones that no one had ever seen. And this very impressive alone. However, what many people don’t know is that only a year after AlphaGo’s victory over Lee Sedol, a brand-new AI called AlphaGo ZERO beat the original AlphaGo. Not in four out of five games, not in five out of five games, not in ten out of ten games, but beat AlphaGo 100 to zero.
AlphaGo
There are 100 games in a row, the most impressive part, it learned how to play with zero human interaction. This technique is more powerful than any previous version. Why? It isn’t restricted to human knowledge. No data was given, no historical figures were given, with just the bare-bones rules. AlphaGo Zero surpassed the previous AlphaGo in only 40 days of learning. In only 40 days it surpassed over 2500 years of strategy and knowledge. It only played against itself and is now regarded as the best GO player in the world, even though it isn’t human.
But wait, if this AI has learned without any human interaction, made-up strategies on its own and then beat us with those strategies, then that means there’s more non-human knowledge about GO then there is human. And if we continue to develop artificial intelligence, then that means there’s going to be more and more non- human intelligence.
We represent the minority of intelligence
Eventually, there’s going to be a point, where we represent the minority of intelligence, maybe a very minuscule amount. That’s fine though, we can just turn it off. That’s a thought but think! When modern-day humans begin to take over the planet, why didn’t the chimps and the earth turn us off? If this artificial intelligence becomes super-intelligent and learns through and is connect to the Internet, we can’t just shut down the entire Internet. There’s no off switch! So, what happens if we end up stuck with AI that is constantly and exponentially getting smarter than we are? What if it gets to a point that humans get in the way and the AI hits the off switch on humans?
Artificial Intelligence
When we compare the human brain to a computer processor, the most important difference is that a robot “thinks” but does not think about its consciousness. It program Computers and robots and therefore can only be as smart as the developer. In the meantime, there are already robots who learn from their own mistakes, that is to say, control their own actions in a certain way and do not make certain mistakes again without this having to be programmed.
Building blocks of the human brain
The seat of human intelligence is the brain. The most important building blocks of the brain are neurons. Everybody has about 20 billion of them. These interconnect in a variety of so-called synapses and form a complex network. This results in a barely conceivable number of possible combinations, which makes our brain so powerful.
Difference between human and computer
However, compared to a computer, the human brain is very slow. However, our brain can still function smoothly even if there is any injury in individual nerve cells. The computer crashed most of the time.
This is because the brain and the computer process the information differently. While the computer simply stores information, the brain processes that information according to what it is currently experiencing or what the human being feels at the moment. There are now components that can partially mimic this property of the brain.
Robot as a work relief for humans
Presumably, it will never be completely possible to artificially recreate human thinking. Speech processing in particular still poses a major challenge for robots. Science is now less concerned with building one intelligent super robot than with different helpers trained in special fields.
How has research on artificial intelligence developed?
In 1950, the English mathematician Alan M. Turing dealt with the question of how intelligent human behavior can really compare with that of a machine. In his so-called Turing test received, one checks how a conversation partner reacts to questions addressed to him. On the one hand a human, on the other hand, a machine. The communication takes place without eye contact via a computer terminal. The subject who interrogates both must find out which partner is the machine and which person is. If the computer manages to deceive, he is intelligent.
To date, the Turing test for the machines has been unsuccessful and is controversial. Nonetheless, research has continued to evolve. What began as a science of computer science has, over time, become an exploration of human thought. To this day, researchers have not been able to follow the workings of the human brain in detail, and then reproduce them one-to-one on the machines.
Processing the language is a Main challenge
The hardest thing is processing the language. Highly complicated machine operation requires in order to be able to carry out even the smallest instructions. Meanwhile, the focus is rather on smaller sub-areas, in order to achieve greater success. However, this is only possible with the constant exchange of different disciplines.
Where was artificial intelligence already applied?
Artificial intelligence has already succeeded in many different areas. Especially in smaller sub-areas, the application offers good results. In everyday life, we often do not notice it.
Artificial intelligence can make very effective results in the field of medicine. When it comes to operations that require action to do millimeter-level work, robots are the better sidekicks. Her work is far more precise than that of a surgeon. In logistics as well as in the automotive industry, robots are now successfully taking over a large number of work steps. Especially when tasks are on the agenda that could endanger people, it is very useful. For example, the machines do certain work during painting or welding.
What comes to mind immediately?
Of course, is artificial intelligence in games. Instead of dolls and wooden blocks, cute miniature-style robots, computer programs, and toys for programming and learning can now be found in many children’s rooms. The Tamagotchi should probably still be a household name, but now there are even robot dogs like AIBO. With this, the children can record videos and play CDs, you just have to show him the cover.
Apart from the already existing robots in everyday life, there have been great successes of artificial intelligence in other areas as well, for example in mathematical symbol processing, in the proof of mathematical and logical sentences and beyond that also in expert systems. They can explain their problem solving by naming the user knowledge.
MYCN
They are and are highly efficient in their field of application because they have comfortable user interfaces. MYCN is one of the best-known expert systems and supports the diagnosis and therapy decisions in meningitis and blood infectious diseases. Afterward, a researcher has found that the robot’s decisions were equivalent to those of the expert. However, after many predictions could not be met, the field of artificial intelligence fought for attention.
Areas of application of artificial intelligence so far. Latest Research Topics in Artificial Intelligence:
– Medicine, e.g. precise millimeter work during operations – logistics
– The automotive industry, dangerous tasks e.g. in welding
– Toys for children, e.g. Tamagotchi
-Mathematical symbol processing
– Proving logical and mathematical sentences – Expert systems, still upgradeable
What chances of success exist for the future use of Artificial Intelligence?
In the meantime, however, the dampers have removed and several other disciplines have emerged, such as special languages and concepts for the presentation and application of knowledge, machine learning techniques, and models for revisit ability, uncertainty and inaccuracy as differentiated aspects of knowledge. So far success has been the use in the areas of natural-language interfaces, fuzzy logic, robotics, and artificial neural networks.
Precisely through the fuzzy logic and the artificial neural networks one could notice a change of the schema in the field of artificial intelligence. We believe that in the future also in the financial industry-relevant changes will take place. Because artificial intelligence could be a lucrative investment option for those planning for a long time. Protection and safety are the number one priority. Other news in the field of artificial intelligence is the progress of Apple. The company has taken over other sub-companies that deal with this, such as the smart voice recognition service VocalIQ. It should also be possible to ensure that it is not necessary to send user data to the cloud for investigation.
Future chances of success, AI:
– Improvements in expert systems
– Development of a new, high-performance chip by Intel
– Artificial intelligence will introduce to the capital markets
– More use of robots in professional life
With all the intoxicating technical innovations, one should ask oneself, however, how far one wants to go. What place should robots occupy in society in the future? Are you stealing us the jobs when they can perform predecessors more precisely and efficiently? Experts say vending machines will soon displace human resources from their jobs and that would eventually lead to social problems. At the moment, however, the state of the art does not seem to be enough to really cause serious social consequences. Development for the future cannot be set in stone, because progress is there and that every day.