In 2014, Elon Musk claimed that AI could pose a greater threat than nuclear weapons. The danger of AI is much greater than the danger of nuclear warheads by a lot. It leads to growing concerns among scientists about the need for AI regulation, but there’s an even more unsettling development on the horizon: Quantum computers. Experts anticipate these super-powered machines will soon become accessible to everyone.
The question that arises is What happens when AI and Quantum Computing join forces? Quantum Computer is the wild card. It could be a game changer. It could change the entire landscape of artificial intelligence. Could it be possible that the combination of quantum computers and AI really reach such a potent level? There is a competitive race among industry tech leaders to launch the first viable quantum computer. A device that promises to be significantly more powerful than current classical computers. When the Wright brothers were pioneering the concept of flight, Their initial attempts weren’t immediately faster than a horse. In fact, a horse could have outrun their first powered flights. But what set airplanes apart wasn’t merely the quest for speed, it was about introducing an entirely new mode of travel. An airplane is more than just a faster horse. It’s a completely different type of machine. It takes advantage of the higher dimension right above us, the sky. This gives us access to a resource that was previously untapped. Scientists suggest that the development of quantum computing is just like this leap from horse to plane.
A quantum computer is not merely a faster classical computer. It’s a different type of machine that takes advantage of the quirky, counter-intuitive, and the untapped phenomena of quantum mechanics. This is its higher dimension. Imagine a computer so powerful it can simulate novel materials to sequester carbon from our atmosphere. A machine that can develop affordable fertilizers that save energy and conserve fossil fuels, or one that can tackle problems so complex that traditional supercomputers struggle under their enormity. It’s kind of a crazy sounding idea, but a quantum computer perhaps can harness that by doing some calculations over here, and other calculations over there in parallel. Now, it’s doing sometimes twice as many calculations as a classical computer existing in one world would be able to do. This might seem like a fantasy, like a dream from a Sci-Fi store, but one company has made this vision a reality. This is IBM’s Quantum Centric supercomputer.
This remarkable creation is a striking testament to human ingenuity. It stands ready to revolutionize our comprehension of computing power. This incredible 100.000 cubic supercomputer doesn’t just represent a shift in paradigm. It’s a monumental event. A quantum jolt that shakes the industry. That’s why there are literally tens of thousands of the world’s brightest minds trying to build these machines and understand them. And it seems that the scientific community is split into two passionate factions when it comes to this field. The first group is utterly fascinated by the physics involved. Here’s a quote from David Deutsch, one of the respected scientists in this field: “Quantum computation will be the first technology that allows useful tasks to be performed in collaboration between parallel universes.” Imagine a world where all known laws of physics as we know them apply, but different choices were made. Choices vary from the movements of tiny microscopic particles to what you chose for lunch, or whether you decided to watch this video or not. Quantum mechanics proposes a peculiar prediction that all of these realities are as real as the one we remember.
It’s strange because we don’t see these alternate realities, but we’ve reached a point in science where we can construct machines that leverage these other worlds. Then, there’s the second group mainly from computer science. They would argue a quantum computer could solve problems that even the most advanced conventional computers can’t. No matter how sophisticated,some problems are just beyond them. But it’s not the case for a quantum machine. Now, you might be thinking all this sounds fascinating, but isn’t it just theory and speculation? Isn’t it similar to other futuristic ideas we’ve heard about, things that physics might allow but haven’t been realized yet? Well, quite a number of these machines have already been deployed. They’re present in research centers open to the public, following the model that first introduced supercomputers to the world. Who doesn’t know Google’s Sycamore? This processor is a step forward in quantum computing, achieving the so-called quantum supremacy. A team from Caltech has even put their wormhole teleportation protocol using this computer. After Google announced its Sycamore processor, scientists in China made another surprising news in quantum computing. They’ve built the world’s strongest quantum computer, the jiuzhang computer.
Chinese scientists have announced their development of the most powerful quantum computer in the world. It works 100 trillion times faster than the fastest supercomputers out there. It took less than a second for a task that the fastest classical supercomputer in the world would take nearly five years to solve. The team says the device could be applied to data mining, network analysis, and chemical modeling research. President Xi Jinping has said that research and development in quantum science is an urgent matter of national concern, and the country has invested heavily in this technology, spending billions in recent years. From the outside, quantum computers look like enormous black monoliths, giant metal boxes about 10 feet wide and 12 feet tall. They’re powered internally by a fridge, a refrigerator that chills the chips to nearly absolute zero. It’s literally hundreds of times colder than the vast interstellar space. This is amongst the coldest and extreme conditions that humans have managed to create.
These fridges have a component called a pulse tube. It emits a sound about once per second which sounds eerily similar to a heartbeat. Standing next to one of these machines is truly mesmerizing. And at the heart of this giant box is a tiny chip about the size of your thumbnail. This chip carries all the wonder and magic that makes this machine operate. We won’t delve into the mathematical details of how it all works, but we will offer a roundabout way of understanding this. Imagine that parallel universes do exist, so you have two universes that are exactly identical in every aspect, from the vast horizon to the tiniest atomic detail, but with only one difference. And that difference lies in the value of a tiny element called qubit. A quid is somewhat like a transistor in a classical computer. It has two distinct physical states which we label as zero and one. In a regular computer, these states are mutually exclusive.
That means the device can either be one or the other, and never anything else. But in a quantum computer, this device can be in a strange situation where these two parallel universes have an axis point. As you increase the number of these devices, every added qubit doubles the number of accessible parallel universes. So when you have a chip like this with about 500 of these bits, you have something like 2 to the 500th power of these parallel Universe existing within that chip. We can think of it as the shadows of these parallel worlds overlapping with ours. If we’re smart enough, we can dive into them and bring them back to our world to make an effect. Quantum algorithms take advantage of the entanglement and parallelism of qubits. This gives them a considerable edge over traditional algorithms for specific problem domains. They also get information from qubits at the end of a calculation, but this presents a unique challenge.
When you measure qubits, they collapse into a single state which eliminates their superposition and entanglement. So, quantum algorithms use advanced techniques to draw meaningful results from measurements before this collapse happens, which would then maximize the benefits of computation. And in fact, we have a trend in quantum computing similar to Moore’s Law. The number of qubits on a chip has doubled every year for the last nine years. If you put it on a chart, you can actually see where certain technologies kicked in where people were ahead of the game or behind the eight ball and lost out by simply looking at Moore’s Law. This exponential growth opens up unprecedented capabilities not just in the realm of processing speed, but also in the exploration of fundamental quantum phenomena. Such a strange quantum phenomenon has truly exemplified the potential of this. It’s called quantum teleportation. Back in 1999, Isaac chuang and his team at IBM successfully implemented the quantum teleportation protocol.
It is a technique for transferring quantum information from one place to another remotely using entanglement. But what does that really mean? can we teleport people like we’ve seen in Star Trek? In principle, quantum teleportation needs quantum entanglement to ensure that the state of one particle is instantly transferred to another no matter the distance. So, the particle itself doesn’t travel, only its state or information. This idea was first put forward by six scientists. One of them was Charles Bennett in 1993. Isaac Chuang put this theory into practice just six years later, but you might ask why do we even need this special process? why can’t we just copy things like we do on regular computers? Let’s demonstrate how it might work. Imagine you’re trying to teleport a baseball from California to New York. So first, you entangle two baseball particles in California. This allows for information sharing, but it’s not teleportation yet. Next, you measure one particle producing two bits of data, and make the baseball disappear from California. You send these bits to New York at the speed of light, say via fiber optics. Once there, these bits help recreate the baseball. And that’s it! The baseball’s information has moved from California to New York without being duplicated. Even so, scientists still have a lot to figure out. Two big issues are how to keep quantum information safe when we create entanglement, and secondly how to send quantum bits over long distances without losing any data. We do expect to be able to teleport molecules, maybe water carbon dioxide, maybe even DNA, maybe organic molecules.
Now, to teleport a human raises all the ethical questions because the original, first of all, has to be destroyed in the process of quantum teleportation. With quantum entanglement, your message is linked to another one, and can change the other message instantly no matter how far apart they are. So, when someone tries to intercept this transmission, they would mess up the quantum state of the particles, and we would immediately spot it. It’s a big step forward for keeping information safe in the world of quantum computing. Before we dive into what artificial intelligence and quantum computers can achieve, let’s first explore the Brief history of quantum physics. Quantum computing has deep roots that trace back to the early 20th century. The journey began with the revolutionary work of Max Planck in quantum theory, and continued with many critical milestones. Planck introduced the idea of quantized energy which set the groundwork for quantum theory. His theory suggests that energy isn’t continuous, but comes in discrete packets which is known as quanta. It explained the concept of black body radiation in a way no other theory could. Building on Planck’s theory, Albert Einstein presented a bold idea in 1905. It is known as the photoelectric effect. He proposed that light has a dual nature behaving as both particles and waves. He suggested that light’s energy is also quantized into discrete packets which we now call photons. Niels Bohr took quantum theory a step further in 1913 with his model of the hydrogen atom.
He theorized that electrons exist in specific energy levels or orbits around an atomic nucleus. According to Bohr, these electrons can shift between these levels by either absorbing or emitting energy. In 1925, Wolfgang Polly introduced the concept of quantum superposition. He proposed that particles could exist in multiple states at once with their precise properties only determined when observed. Werner Heisenberg expanded on this idea in 1927 with the uncertainty principle. This principle states that you can’t simultaneously know certain pairs of properties; such as the position and momentum of a quantum particle. In 1935, a game-changing paper by Albert Einstein, Boris Podolski, and Nathan Rosen was published. This paper, known as the EPR paper, introduced the concept of entanglement, and like we mentioned in the previous chapter, it is a strange but fundamental aspect of quantum mechanics where two or more particles are intertwined. Fast forward to 1951, When Alan Turing first proposed the idea of quantum computing. Turing envisioned a machine operating on quantum mechanical principles which could outperform classical computers. But for several decades, this concept remained mostly theoretical due to the challenges of practical implementation. Significant progress was made in the 1970s by physicist Richard Feynman. He recognized that quantum systems could simulate physical systems which are tough to model with classical methods.
Feynman proposed a universal quantum simulator, a machine that can accurately replicate any physical system. In 1982, physicist Paul Benioff put forward the concept of a quantum training machine. This theoretical model operates on quantum principles. The 1980s also saw the birth of quantum algorithms. A physicist by the name of David Deutsch also came up with the concept of a quantum algorithm. He proposed that a quantum computer could tackle certain problems faster than traditional computers. He introduced what’s now called the Deutsche algorithm. In 1994, Peter Shore Made a significant breakthrough with Shore’s algorithm. It was able to show how quantum computers could efficiently solve integer factorization problems. What made this so groundbreaking was its potential threat to the security of public key encryption systems since it could crack classical encryption algorithms. When it comes to experimental progress, various research groups made important strides in creating quantum computers and exploring different uses for qubits. One key development was a collaboration between Google, NASA, and D-Wave Systems. Together, they launched the D-Wave 2 quantum computer in 2013. This was one of the first commercially available quantum computers. what set it apart was its use of a different approach known as adiabatic quantum computing. By using superconducting qubits, it was designed to solve optimization problems In 2016, IBM grabbed the spotlight by introducing the IBM quantum experience.
This was a cloud-based platform where users could experiment with a small quantum computer made up of five superconducting qubits. Their goal was to give more people access to quantum computing and to encourage collaboration within the quantum community. With the IBM quantum experience, researchers and enthusiasts around the world could study quantum algorithms and conduct experiments from anywhere. Then in 2017, we saw a major milestone with the demonstration of qubits that could correct their own errors. Physicists at Yale University came up with a breakthrough design known as the surface code. This allowed them to create logical qubits with the ability to correct errors. It was a key step to reaching the goal of fault-tolerant computing where information can be kept safe from errors and decoherence. Companies like Google are pushing hard to build practical and market-ready quantum computers. This surge is not merely an effort to ramp up computational speed. It’s about paving the way for a future where the boundaries of technology are redefined. Artificial intelligence is already making a place for itself in this quantum-powered future and what’s more, AI can now enhance images without even looking at the original picture. It does this using only the results of brain scans from MRIs. Tristan Harris and Oza Raskin recently brought attention to this. They shared a new video called “The AI Dilemma” following their Netflix documentary, “The Social Dilemma.”
and they taught the AI, “I want you to translate from readings of the fMRI, so how blood is moving around in your brain, to the image.” “can we reconstruct the image then?” You know, the AI then only looks at the brain, does not get to see the original image, and it’s asked to reconstruct what it sees. The research reveals some concerning data. For instance, half of AI researchers think there’s at least a 10% chance that humans could become extinct because we might not be able to control AI. The cause for this concern is the latest data showing that AI’s capabilities continue to double every few months. What is horrifying is the prediction that, by 2045, AI could reach the point of singularity. This means, it will match the combined capabilities of all human brains. Could our rapid advancement in quantum computing be contributing to this? Some people are concerned about this possibility. It is the worry that AI will eventually develop human-like consciousness, and like something out of a movie, turn against us. Even Elon Musk has shared some of these concerns. I’m really quite close to the cutting edge in AI, and the rate of improvement is exponential. It scares the hell out of me. What Elon’s talking about sounds a lot like what happens in the movie Ex Machina. This movie tells the story of a beautiful AI-powered robot that ends up killing its creator. Interestingly, Ex Machina is derived from the phrase ‘deus ex machina’ a Latin expression that means ‘God out of the machine.’ In the movie title, the word Deus is dropped.
It seems to suggest that, in the world of AI, there’s no need for a divine role when humans can create conscious machines. And this brings us to the Turing test aka the imitation game. This is a simple game involving three participants. The aim is to see if a machine can convincingly mimic a human. The game comes from Turing’s paper entitled ‘Computing Machinery and Intelligence.’ This paper laid the groundwork for artificial intelligence. Turing’s fundamental question was “Can machines think?” And by thinking, he didn’t mean simply calculating or executing tasks like modern computers. He meant genuinely thinking like humans do. This question in essence is philosophical rather than technical because there’s one key difference between humans and machines, and that difference is consciousness. Consciousness has sparked endless debates among scientists and philosophers alike. Is it a part of the brain? or does it exist independently? Generally, there are two viewpoints on this, dualism and materialism.
Dualism believes that consciousness is separate from our physical selves which often referred to as the soul or spirit. Materialism, on the other hand, refutes the existence of a soul or spirit. According to materialism, consciousness is purely a mechanism of the brain. Since our brain operates like a complex machine, The natura
