30 years ago, having a home phone line was a sign of being up-to-date and keeping up with the technology of the day. Today, home phones have given way to smartphones and personal computers that have the ability to process commands in natural language and run artificial ielligence models. But in the next 30 years, these devices will give way to newer devices, some of which we may have only seen in science-fiction movies, such as flying cars, spaceships, service robots and many others.
The next decades are the years of computer developme, but probably the next 3 decades will not be as easily predictable as the previous decades.
Currely, companies are trying to go beyond Moore’s law and start producing powerful classical systems. On the other hand, we are moving to new paradigms of computing. It is clear that at some poi, we will go beyond the traditional form of cloud computing. But how these developmes will be in 3 decades, 50 years or a ceury is another question.
With this in mind, we envision a world in which four major computer systems (classical, photonic, hybrid, and quaum) have reached a level of maturity where they can be used. Experts are optimistic that this will happen in the next 30 years.
Classic computers
For those people who think that classical computers will soon be replaced by quaum computers, we have bad news. You should know that classic computers will be with us even after 2050.
Comparing binary systems with quaum computers is like comparing pen and paper with hadron colliders. The average person doesn’t need direct access to a quaum computer or a hadron collider in their lifetime, but we all benefit from their existence.
Think of your smartphone. In the next 30 years, there will be a similar device. Smartphones may have existed then in the form of glass gadgets or brain implas, but the concept and function is the same. We still need on-board processors to run certain algorithms and applications, which is what smartphones already do.
Like today’s phones, future models must be powerful enough to connect to cloud services. Binary computers of the future will perform most of the tasks of today’s binary computers. But for tasks that require more power (than we expect from future computers), classic computers can act as an ierface to more powerful systems.
Photonic computers
These types of computers would be fascinating systems that don’t exist yet, but the big idea behind them is to use photons for processing instead of electricity. Electrons can travel at high speeds, but photons can travel at the speed of light because, as you know, they are light itself.
This means (theoretically) it is possible to build a computer system that can handle information at the speed of light. Researchers from IBM and the Skolkovo Institute of Science and Technology have recely developed a type of photonic switch, which is actually a device that can be used instead of silicon transistors.
Photonic computers can be thousands of times faster than today’s most powerful binary supercomputers, and because of the way they work, require less energy. It is predicted that this technology will be perfected by the next 3 decades, and its biggest benefit that will be visible to all is the emergence of the fifth level of autonomous vehicles. But what does level 5 autonomous vehicles mean? Autonomous vehicles at their highest level can move completely independely without the need for human supervision.
Also, thanks to photonic computers, it is possible to fit a gia supercomputer io a small car. Of course, in this case, the “gia supercomputer” will be replaced by a “photonic microcomputer” that can produce 100 to 1000 times the power of its classical fathers with one hundredth of the energy.
Hybrid computers
In this section, we specifically refer to hybrid quaum-classical systems. It is possible for photonic computers to cooperate with quaum systems, but the explanation of this requires another article. We meioned before that quaum systems sometimes need classical systems to act as their portal, ierface or coroller. But there is another paradigm where the system switches between classical and quaum computing or iegrates the results of both to run a particular algorithm.
The ieresting thing is that these systems could be the first quaum computers that can be bought in stores. Remember that we won’t be able to get quaum computing to the poi where we can build a time machine in our baseme and travel through time for the next 30 years.
In fact, quaum systems are considered solutions to specific problems. You cannot edit video faster by installing an API on an IBM Q system and choosing to enable Quaum Mode.
But it is theoretically possible to build a system that can run airport flight scheduling software with the help of classical multitasking (for infrastructure manageme) and quaum algorithms (for mathematical calculations that are too complex for traditional processors).
Consider similar systems that currely exist at the grassroots level; Within the next 30 years, large businesses (those worth more than a billion dollars) will purchase and install the next generation of these quaum-hybrid systems as their IT infrastructure.
Quaum computers
Here is the ieresting part of the story! Quaum computers are about 20 years away from us, and depending on who the user is and what is the purpose of using the computer, he may never need quaum computers.
Today, quaum computers are built in the experimeal phase and in laboratories, which of course cost a lot and are used to solve one or two mathematical problems. It is impossible to guess when practical quaum processing will become available.
But it can be said that these systems will revolutionize the next 30 years. Truly practical quaum computers could help us develop cold fusion, warp machines, and artificial ielligence. We do not iend to exaggerate the capabilities of quaum computers, but their application in the fields of chemistry, drug discovery, and pathology cannot be calculated. Millions of people can be saved and thousands of diseases can be eliminated thanks to science.
But if we are talking about strange tasks at long distances or processing at the speed of light, we cannot comme with certaiy about the future. It may take 10 years, 30 years or even 100 years for these technologies to mature.
Source: The Next Web
