Crystal Grazing: Future of Computing

Future of Computing 

We already expect our smartphones and computers to know where our car is parked and to provide us with personalized offers based on our habits. In the future, computers will also ensure that our cars get from A to B autonomously, control production within entire factories and will likely discover treatments for rare diseases. Innovations such as these are based primarily on AI and therefore require continuously increasing amounts of computing power.

Today, nearly all computers are based on the von Neumann architecture, which is particularly suitable for very precise calculations of complex models. The architecture has proved itself over decades and has been continually optimized. To support the increasing demand for more data, technology has to push the limits of what is physically possible, one example is 3D NAND. This technology enabled further miniaturization by expanding the microchip architecture into three-dimensional space.

The von Neumann architecture is still indispensable and will continue to be further developed in the future. But it is reaching its limits in some aspects, especially when it comes to Artificial Intelligence (AI). Computers increasingly have to perform tasks that include pattern recognition and instinctive and situational processing of information, for example. These kinds of AI applications require a huge number of calculations, using very large sets of data, to be performed simultaneously. The von Neumann architecture is not particularly suitable for this, especially as regards efficient energy consumption. Completely new computing technologies are needed to resolve this issue, which is known as the “von Neumann bottleneck”.

Neurons instead of transistors

For this reason, researchers around the world are looking into the future of computing beyond the von Neumann architecture. These so-called neuromorphic computers are among the most promising new technologies. Neuromorphic chips are modeled on how the human brain works, with deeply connected artificial neurons and synapses.

Just like the human brain, neural networks based on neuromorphic chips need to be extremely flexible and adapt intuitively to unpredictable environments. They learn from experience by using networks, trained on stored data to solve problems which they have not previously seen. This requires tremendous computational intensity and is possible because neuromorphic chips can simultaneously store and process information, just like the neurons and synapses in the human brain. By contrast, ordinary computers run commands sequentially, constantly moving data packets back and forth from the memory to the processor. Neuromorphic chips are therefore not only faster but are also extremely energy efficient. The steady data movements in conventional logic chips consume a lot of energy.

Enabling computers of the future

However, it will be for a while until neuromorphic computers are as smart as humans. With almost 90 billion neurons that are connected by trillions of synapses, a human brain has a computing power of about 4 to 5 petabytes. Current neuromorphic computers have about 100 million artificial neurons – only one thousandth the number of a brain. Nevertheless, the technology has the potential to take artificial intelligence and machine learning to the next level in the coming years.

Future is Quantum Computing !

A comparably disruptive potential is also ascribed to quantum computers. Unlike a von Neumann computer, which performs calculations using classic binary bits with a value of 0 or 1, a quantum computer calculates using so-called qubits, which can process considerably more information. These qubits can become entangled, allowing quantum computers to perform mathematical operations and calculations for highly complex models at an unprecedented speed. However, there are still many challenges to overcome since current qubits are very fragile and the slightest interaction with their surroundings can distort them.

Experts believe that the von Neumann architecture will not be replaced but will instead continue to coexist alongside quantum and neuromorphic computers as all three technologies have distinct advantages in certain areas.

Recently, a  Chinese team of researchers has unveiled the world’s most powerful quantum computer – capable of manipulating 66 qubits of data. At the same time, a team at Cambridge University in the UK has created a quantum computing desktop operating system – which could be as significant a step at bringing quantum capabilities into the mainstream as Microsoft’s development of MS-DOS and Windows was for classical desktop computing.

With this in mind, it might be a good idea to take a look at the current state of play with quantum computing – a technological leap that’s expected to bring us computers capable of operating many thousands of times more quickly than the fastest classical processors available today.

 What is quantum computing, why are so many people excited about it, and how is it expected to affect our lives? Let us find out!

First – what is quantum computing? Well, explaining it in simple terms is quite difficult because it's quite a complicated concept! “Quantum” means “sub-atomic” and, in computing as in physics, is used to describe properties demonstrated by matter when we study it at a sub-atomic level. Often these properties don’t seem to fit with the basic rules of physics that are observable when studying matter of atom-sized or larger. At a sub-atomic level, properties such as entanglement (a connection between particles that means they share the same state, no matter how far apart they are and superposition (where particles can behave as if they simultaneously exist in two different states) can be observed.

One concept that is worth getting your head around is the difference between bits and qubits (pronounced "Q-bits"). Regular computers (referred to as "classical" computers, in the context of quantum computing) store and read data in the form of binary "bits" that can either have a state of one (1) or zero (0). Quantum computers use qubits, which take advantage of quantum phenomena like superposition and entanglement, meaning they can be used to perform certain complex forms of calculation far more quickly than could ever be possible using classical computation algorithms. 

 It isn't necessary to fully understand the mechanics of quantum computers in order to use them or to understand how they are likely to affect our lives in the future! From a procedural point of view, though, it involves cooling super-conductive material 99% of the way to absolute zero (-273 degrees C/ 459 degrees F). Electrons are then passed through this material, which are targeted by photons (electromagnetic particles with no mass). This interaction means the quantum effects acting occurring in the particles can be controlled and measured– becoming the qubits that can be used to store or process information.