Artificial intelligence, blockchain and robotics will continue to gain in importance. For the next growth cycle, however, we will need a lot more computing capacity. Computers with conventional transistor technology are reaching their limits. New
ideas are needed.
100 years ago, the Russian economist Nikolai Kondratieff divided the economy into 40- to 60-year business cycles. Joseph Schumpeter expanded this theory and placed a basic technology at the beginning of the cycles, which triggers innovation spurts, enables
structural change and ultimately leads to an economic boom.
The first Kondratieff cycle began with the steam engine, and the current fifth wave began in the 1970s with transistor technology. Since then, Gordon Moore’s law has applied, according to which the number of transistors on a given surface doubles every two
years. Today we have arrived at a transistor density of over 170 million transistors per square millimeter. Despite this exponential development, Moore’s Law will lose its validity within the next five years, as the limits of what is physically possible have
been reached. Accordingly, more and more institutions and companies are researching new approaches to replace silicon technology.
Supercomputing made in Switzerland
In the ranking of the fastest computers, Switzerland can keep up. The “Piz Daint” of the Swiss National Supercomputing Center, for example, took third place in 2017 behind supercomputers from China and the USA. But even supercomputers are subject to Moor’s
Law. A fundamental innovation is therefore required.
To that end, ETH Zurich and the University of Zurich are continuing the long history in quantum mechanics that began with Albert Einstein by conducting research on quantum computers. Last year, ETH scientists developed the first quantum programming language,
Silq, for simple, reliable and error-free programming, and are improving quantum hardware for higher stability and new architectures. The fundamental innovation in quantum computers is that they are no longer based on transistor technology and thus bound to
binary computational logic with two states 0 and 1. Instead, their so-called “qubits” can assume an infinite number of states between 0 and 1. The list of possible applications is already considerable and can be divided into model-based simulation, optimization,
secure communication and pattern recognition using artificial intelligence.
This involves more energy-efficient batteries for electric cars or the simulation of molecules and their chemical behavior, which enables faster and more precise drug development. In aviation, the potential applications range from aircraft design – currently,
a sufficiently accurate airflow simulation on wings takes several years – to optimizing flight routes, speed and fuel quantities in order to increase the sustainability of aviation. In the automotive industry, we are starting to see concrete results in optimizing
traffic flows and preventing congestion. In addition, encryption and communication are promising application areas, since data encoded in a quantum state cannot be read without changing the quantum state.
Stimulus for the Swiss financial center
In banking, we see potential in fraud detection, pricing of complex structured products, high-frequency trading and risk management. For these areas, large amounts of data need to be linked and processed, because the more data that flows into AI algorithms,
the more accurate analyses, fraud detection and risk simulations will become.
Traditional risk models use Monte Carlo simulations to try to forecast the impact of macroeconomic events, transparency requirements and other regulatory frameworks. Increasingly complex models with many simulation parameters mean that the number of scenarios
to be analyzed grows exponentially. The calculation time can then quickly take several days, which calls into question the economic benefit. In a pilot project, Deutsche Börse has reduced a complete sensitivity analysis with 1000 input parameters, which would
take ten years with conventional computers, to less than 30 minutes of computing time using quantum algorithms.
Unprecedented competitive advantages and market differentiation could also arise in high-speed trading. In this form of stock market trading, algorithms anticipate market changes, calculate price advantages and make trading decisions independently on this
basis. Today, processing market data in real time and sending orders to the stock exchange via optimized data lines takes little more than a second. Theoretically, the quantum computer can handle the calculations within a few nanoseconds. Although there are
only tiny profits per transaction here, large volumes could dominate stock market activity.
Quantum computers complement existing systems
Despite their vast capabilities, quantum computers will not replace traditional computer systems, but rather extend their capacity limits. Thus, quantum computing is not a disruptive innovation as is often assumed: It neither threatens the ICT industry nor
does it make current business models obsolete. Existing high-performance systems will continue to be necessary to prepare and preprocess the data, to bring it into a “qubit format” and to make optimum use of the quantum computer. In addition, high performance
systems will take over the last mile of computation, meaning quantum computers reduce the set of possible results to a level that existing high performance systems can handle.
Securing the future with a hybrid approach
Although IBM does not expect a stable, functioning quantum computer until 2023 at the earliest, companies should start looking at this future technology today. Identify concrete areas of application! Venture into simulators with Qiskit, program with Silq,
use Quantum Learning Machines (QLM) and cloud services to familiarize yourself with the use, programming and behavior of quantum computers!
More importantly, prepare your IT landscape accordingly, as legacy concepts and architectures usually don’t provide the flexibility and connectivity needed to make sense of the quantum computing capabilities delivered “as a service” in a meaningful and efficient
However, SMEs do not have to acquire their own quantum computers, but they should look into application areas for this promising technology at an early stage. This increases their own innovative strength and is an investment for the future.
This is a syndicated post. Read the original post at Source link .