Imagine that you are dropped into a vast mountain range, such as the Adirondacks, and are given the task of finding a particular lake.
You are told that the lake is located at the lowest part of the mountain range and that the only tools available to you are a compass and a way to record the paths you have taken. As you can imagine, this task would be next to impossible. You may get lucky and find it right away, or you may spend years searching.
Now imagine that you are in a helicopter over the mountains and you are asked to do the same thing. Looking below, at the entire mountain range at once, you can see all the possible paths and find the lake almost immediately.
I often use this analogy to explain the difference between quantum and classical computing. Classical computers move step by step, evaluating one path at a time. Quantum computers take advantage of the physics of the quantum world to explore many paths simultaneously. They operate in an exponentially expanding solution space – giving them the ability to solve certain classes of problems in seconds that would take classical machines centuries.
Why quantity matters (and why it sounds familiar)
Quantum computing may seem like a futuristic title, but it reflects a pattern we’ve seen before.
I remember watching Steve Jobs and Steve Wozniak on the evening news when I was a kid — two guys in a garage building what the community said were actually larger, more powerful calculators. It is difficult to imagine that Apple will become one of the most influential companies in the world.
However, from an everyday application point of view, the same thing happened with the Internet. In the 1980s, modems were so slow that they would tether your home phone line, and your parents would often yell at you. A final example is the mobile phone, which began as a large bag with a corded telephone attached. In all three cases, no one could have ever predicted that each would have changed the world in the way it did. Finally, we are currently living this again with Amnesty International And we’re about to try it again with quantum computing.
Quantum AI: What it is and why it matters
From theory to traction
Professor Richard Feynman proposed the idea of quantum computing in the 1980s. I first read about it while in graduate school in a biophysics laboratory in the late 1990s. Fast forward to today, and I will compare today’s quantum computers to the classical computers of the 1970s and 1980s. They work; They perform calculations using quantum physics, but they are limited to very specific use cases, largely due to limitations of current hardware.
However, I see the writing on the wall and believe its limitations will be overcome. When they are, who knows? Let your imagination run wild. It could redefine industries, scientific discoveries, and national security, among other impacts.
Key developments and moving timeline
I first started programming quantum computers about six years ago. At the time, quantum computers were estimated to have enough logical qubits – the basic unit of information in a quantum computer – to be useful, about 30 years later. Now, quantum roadmaps aim for 2030, as published by the website IBM Quantum, Ion Q, Quira and Google.
The industry has made tremendous progress in areas such as qubit quality, error mitigation and correction, numbers of logical qubits, and architectural communication between qubits. All of these things combined bring us closer to quantum advantages in the near term. I have no doubt that 2030 will constantly be adjusted to be closer.
What’s next in the quantitative race?
What’s also accelerating quantum computing is similar to what happened in the 1970s and 1980s. At that time, there were about 45 unique computer manufacturers (e.g. Apple, IBM, Commodore, TRS, etc.). Most of them have disappeared through mergers and acquisitions, leading to technology acquisitions.
As in the past, today there are more than 100 quantum computing companies across various quantum approaches (e.g., superconductivity, photons, neutral atoms, trapped ions, etc.). Us too I’m starting to see mergers and acquisitions in the quantum computing sector.
According to MacKenzie, The potential economic value of quantum computing in 2035 will reach about $1.5 trillionResulting in huge investment to be leaders in this field.
I would consider quantum computing to be a kind of arms race that initially broke out when Professor Peter Shor of MIT published his quantum analysis algorithm, which showed that with a sufficiently powerful quantum computer, RSA could be decrypted. All our encryption is based on some form of this and governments have taken notice.
Public investments increased year after year. As of 2023, There was a record $42 billion in government investment. Now, some countries have a version of a quantum initiative that aims to build the most powerful quantum computer while developing methods to prevent quantum RSA attacks. This has also developed into large national defense projects across most of the three-letter agencies. In terms of private financing, Investments decreased between 2022 and 2023 from $2.33 billion to $1.7 billion.This is due to several reasons, including the stability of the quantitative landscape and ROI expectations. When we talk about ROI, it is important to distinguish between the short and long term.
Most companies focus on long-term ROI, adopting a “build now, use later” mentality. Companies publish articles, algorithms, and patents knowing that their usefulness for real-world applications depends on the maturity of quantum hardware. These companies are looking to own IP for long-term ROI.
This doesn’t mean that short-term ROI isn’t important, because it is. Using innovative approaches and hybrid processes, a short-term return on investment has been achieved in areas such as optimization and machine learning. This is not universal and tends to be on a case-by-case basis, usually centered around speed and ability to represent complex aggregate data structures, more expressive models built with less data, and lower power consumption. For short-term ROI, imagination and outside-the-box thinking are important.
Hybrid reality and convergence
Currently, quantum computers are still in the early stages of development. Professor John Preskill coined what the industry refers to as The Noisy Intermediate Quantum Epoch (NISQ). – Meaning systems are powerful, but still noisy and limited. They can only solve small, specialized problems and need help from traditional computers to obtain meaningful results.
Quantum computing will complement the HPC, which serves as another tool in the computational toolbox that can be used as an accelerator, a higher-dimensional feature engineer, or a simulator, among other applications.
There has been extensive research in areas of QML, including quantum Neural networksquantum tanks, quantum Natural language processingand quantum LLMs, with mixed results. This is to be expected with this new and modern technology, which is completely different from anything the world has seen before. This is uncharted territory with no established rules or best practices; These are determined in real time. Creativity and thinking outside the box is essential – and perhaps even thinking more like a physicist than a statistician will make it easier to step outside the box.
Where do we stand?
Quantum computing is now like standing on the event horizon of a black hole.
We have no idea how some aspects of quantum computing work, but we know how to use them. We can look into it, measure its effects, but we don’t have the full picture.
Every week, there are posts about amazing new findings or discoveries. We’re pushing technology to the quantum level, taking advantage of the strange world of quantum physics, where things can exist in two states at once, be entangled across light-years, tunnel through barriers, and be teleported. This makes the field very challenging, but that’s why it’s so fun. In fact, I believe this is the most exciting technological development and will have the greatest impact on humanity.
