Quantum computing has the potential to revolutionize AI, even in its early stages. Companies like Microsoft, IBM, Google and Honeywell have already invested in technology to create many innovations and breakthroughs.
But, before we get our hands dirty, let’s understand first:
Well, quantum computing is very similar to traditional computers as it relies on bits to encode information. But what makes quantum computing unique is the version of bits, also known as a qubit.
Make Qubit quantum calculation revolutionary as it can have information in several states at the same time. This leads to the effects of quantum mechanics, such as entanglement and superposition.
And, if you’re wondering, yes, this is the ghostly world of Schrodinger’s cat, alive and dead.
According to dr. Jay Gambetta, Vice President of IBM Quantum, “Quantum computing is a new kind of computer that uses the same physical rules that atoms follow to manipulate information.”
“At this fundamental level, quantum computers run quantum circuits – like a computer’s logic circuits, but now use the physical phenomena of superposition, entanglement and interference to implement mathematical calculations beyond the reach of even our most advanced supercomputers.”
Quantum computers are not mainstream yet; their arrival will require algorithms. Google recently unveiled a new version of TensorFlow Quantum (TFQ), the TensorFlow framework. TFQ is an open source library for prototyping learning models to enable developers to create hybrid AI algorithms.
TFQ, a clever fusion of TensorFlow and Cinq, makes it possible to build deep learning models that combine both traditional and quantum computing techniques to run Python with minimal lines.
Google AI, in a blog post, said TFQ was designed to provide the necessary tools to bring together the techniques of quantum computer and machine learning research communities to build and control artificial quantum systems. e.g. Noisy Intermediate Scale Quantum (NISQ) processors with ~ 50 – 100 qubits.
Quantum computing aims to expand the capabilities of traditional computers by performing tasks accurately and efficiently like conventional computers. Experts believe that instead of replacing their traditional counterparts, quantum computers will use classical computers to support their specialized capabilities.
To run increasingly complex programs, scientists have been trying to improve software for decades; however, software optimization has its limitations.
With increasingly complex machines, businesses will sooner or later need more powerful machines. Therefore, experts are working to find a way to extract value by speeding up this process from the unmanageable pieces of data. This has given rise to a new discipline known as Quantum Machine Learning.
It is reported that quantum computers will grow from USD 93 million in 2019 to USD 283 million by 2024, at a CAGR of 24.9%.
Well, we know that quantum machine learning is more efficient than classic machine learning. However, there is still no known extent to what extent these models occur in practical applications.
So, let’s look at the ways in which quantum computing can change the future of artificial intelligence:
1. Data set
Every day we are dealing with newer technologies, for example AI and machine learning. These technologies tend to eat up a lot of data, making it difficult for traditional computers to evaluate massive data sets.
On the other hand, quantum computers are designed to manage large data sets, along with detecting anomalies and exposing patterns quickly. Developers can manage the potential of qubits with the newly launched iteration of new designs and enhancements made on the quantum error correction code.
Another way quantum computers can facilitate revolution, apart from sampling large datasets, is to be the same for solving all kinds of business problems. Quantum computers will give great power to businesses for better decision making.
2. Complex problem solving
Today, businesses manage the growth of data sets that are faster than our computer resources. Quantum computers can complete these calculations in seconds, which today’s computers can take years to calculate.
Traditional computers work on a principle called superposition that represents a combination of both zero and one, unlike traditional computers. As a result, quantum computers are exponentially faster and can perform multiple calculations with multiple inputs simultaneously.
Google’s quantum computer can compute 100 million times faster than today’s computer systems. Such a system is critical in processing the monumental amount of data generated by businesses on a daily basis. The fast calculation can be used to solve very complex real problems by converting them into quantum language.
3. Build better models
With the increasing amount of data, businesses are losing ties with classic computer rope. They need complex models with the potential to handle the most complex situations in order to have a better data framework.
Here, quantum computers play a major role in creating better models with quantum technology. They lead to a decrease in a financial collapse in the banking sector, better treatments for diseases in the healthcare sector, and improve the logistics chain in the manufacturing industry.
4. Integration of multiple data sets
Organizations face the problem of different amounts of data being provided, whether it be too much or too little. Many times the data is placed in a variety of datasets to manage and integrate multiple numbers of datasets
Quantum computers can be used to speed up the process and make analysis easier. This means that businesses will allow rapid analysis and integration of large datasets to improve and transform machine learning and artificial intelligence abilities.
Quantum computers’ ability to handle many interests makes them an adequate choice to solve business problems.
5. Combat Fraud Detection
Quantum Computer Applications with integration of AIin the banking and financial sector, will improve and combat the detection of fraud.
A fraud detection model trained using quantum computers is capable of detecting difficult patterns using conventional equipment. However, improvement in algorithms helps to manage the volume of information.
Also, for the companies that aim to provide customers in the BFSI sector with custom products, the best way to achieve this is by using advanced recommendation systems. Various quantum models can also be used to improve the performance of these systems.
One begins to understand the reservations that are buried and understand the existing challenges of quantum computers as you dig deeper into the details.