What will artificial intelligence lead to? On one hand, optimists believe that hunger and poverty will end, and unlimited wealth will be experienced. On the other hand, pessimists fear waves of unemployment and a growing gap between the rich and poor. Bernard Marr, Steve Wozniak, Ayşegül İldeniz, Faruk Eczacıbaşı, Altan Çakır, Matt Brittin discussed these topics for ntv.com.tr.

Megabytes, gigabytes, terabytes, petabytes, and zettabytes… The numerical values of the vast amount of “big data” gathered, processed, stored, and reaching unbelievable sizes quietly led us into an artificial intelligence revolution. In fact, the question is clear: What will artificial intelligence lead to? Optimists believe in the end of hunger, poverty, and a world of unlimited wealth… Pessimists fear waves of unemployment and a growing gap between the rich and the poor… Which is correct… Will artificial intelligence be constructive or destructive? Finding the answer requires looking back at history. This axe is nearly the same as the one used a million years ago. 99.99% of human history shares the same fate. It hasn’t changed much. Major inventions and the world’s significant changes have piled up in the past few centuries…

Ayşegül İldeniz:

I believe we are entering a brand new era where we leave the jobs that stress our bodies, question more, build more, and emphasize innovation.

Matt Brittin: There is a fantastic project named “Project Relate.” This project helps speech-impaired individuals communicate. You can add subtitles to what you say using your phone, eliminating communication barriers. Thus, creating bridges to make people understand each other and express themselves easier is a massive opportunity, not walls.

Suncem Koçer: We will be living with machines that solve many things for us. Then we will need to redefine our skills.

Faruk Eczacıbaşı: Just like electricity marked the beginning of an era, the printing press, steam engine, and the internet were all the beginning of a new age. Artificial intelligence is also the same. But there will be new era-changing approaches awaiting us. Today, artificial intelligence guides us, recognizes faces, evaluates medical data, creates images, graphics, videos, narratives, scripts, and music. In any field with sufficient data today, artificial intelligence successfully operates. Expectations for the future are even greater: eliminating incurable diseases, eradicating poverty, providing solutions to the climate crisis, and preventing traffic accidents.

Altan Çakır: We are talking about the doubling of processing capacity within Chips containing transistors every two years. This means the processing capacity of a processor doubles. Let’s consider a Gigaflop, a computer that can perform one billion operations per second. In 1960, making such a computer was impossible, even if you wanted to, the money you had to spend equaled the United States’ budget at that time (850 billion dollars). In 1984, the prices dropped, and it became possible to make a computer that can perform one billion operations per second. Yet, the amount you had to spend was enough to buy a jet plane (40 million dollars). In 1997, a computer with the same speed fell to the price of a sports car (400,000 dollars). In 2013, the price of a chip that can perform a billion operations per second dropped to 25 cents. The price of a play station 4, which can perform 1.2 trillion operations per second, was 400 dollars. Today, the price of a chip that can perform one billion operations per second is 2 cents. Yes, you heard right, only 2 cents. Now we are talking about teraflops. Moreover, these computers cost only five hundred dollars. Today, the unchanging fact is technology’s limitlessness. Changing facts are constantly improving, becoming more affordable, never stopping their evolution, and expanding and democratizing.

STEVE WOZNIAK: Every advancement of new technology fosters the gradual progress of this framework. It’s like producing more and more transistors on a chip. There was only one transistor before. Now, you can find 60 billion transistors on a chip for the same price. This is called exponential growth. When you build upon the growth before you, all technology somehow grows exponentially. Today, computers are everywhere. There are 40 billion computers connected to the internet. It is expected that this number will reach 500 billion in the near future. The banking system, land registrations, video editing, cameras, subway transportation plans, cars’ software, airplanes, traffic lights, product stocks, city water supply systems, in short, everything you can think of works with computers. The brain is a fantastic organ. Even the brain of an ordinary person like me can process a trillion operations per second, handling 35 gigabytes of data. Scientists have created a mechanical brain similar to mine nowadays. They call it Artificial intelligence. Between us, this machine is not yet as capable as even my brain.

That’s for sure. Yes, it can perform complex calculations faster than me, but it can’t make jokes like me, can’t dream. It can’t even know the taste of a slice of baklava. The capabilities of artificial intelligence are currently limited, but scientists are working hard to make it capable of doing these and other things. In fact, the question is simple: can science enable this program to operate on its own, think, or even learn? I don’t know about this. I think even scientists don’t know. At least for now.

Bernard Marr: One of the early major successes of artificial intelligence was IBM’s computer Deep Blue defeating Garry Kasparov in a chess game. However, this was a traditional artificial intelligence algorithm, primarily based on calculating more chess moves than a human can think of. The next significant step came with a question: how to train machines in situations where we don’t know the rules. Google developed an artificial intelligence for a strategic game called Go. Go is much more complex than chess, and even grandmasters make their moves intuitively. After training the algorithm with all the past Go games, Google then said, “What if we make two computers play against each other, rewarding the winner?” Through this process, artificial intelligence gradually improved and succeeded in defeating world champion Lee Sedol.

In November 2020, Google’s artificial intelligence company Deep Mind announced a groundbreaking discovery in computational biology. Deep Mind successfully calculated how a molecule of a protein would fold, evaluating an infinite number of folding possibilities, and knowing the final result. This was a revolution. Many scientists had dedicated their whole careers to solving this problem but had not made progress. Deep Mind solved this problem through a genetic code-based prediction. This groundbreaking discovery emerged during the pandemic era, giving hope to the world to be prepared for the next pandemic. This was a very critical development that could shed light on which existing drugs could be effective against an emerging virus. This innovation also had other promises. It could help us better understand incurable diseases like diabetes, Parkinson’s, and Alzheimer’s, and could be used to produce proteins that solve wastes like oil. In the last four years, Deep Mind has never slowed down and turned into a system that can uncover the great secrets of biological life. It is used in various fields, from developing new vaccines and medicines to obtaining seeds resistant to weather conditions. Now, artificial intelligence is transforming the world with increasingly practical applications. Two significant developments are accelerating this progress: the vast amount of data produced at extraordinary speed and the supercomputers enabling us to process this data. The simple question facing humanity is: will artificial intelligence develop further to resemble the human brain? As anyone who has learned a second language knows, the more we use a new language, the faster we learn. The same applies to machines learning. The more data a computer has access to, the quicker it learns and becomes masterful in interpretation. Thanks to the rapid digitalization of the world, we can access more data, making artificial intelligence faster, smarter, and more accurate.