Why did the quantum chip Willow cause a sensation in the global technology community?

On December 10, Google announced its latest generation of quantum chip - Willow, which caused a sensation in the global technology community. Even Musk exclaimed "Wow"!

What is the power of the Willow chip? How far is it from mass production?

1. Google's latest generation of quantum chip Willow was launched, and its biggest breakthrough lies in its super computing power and error correction capabilities

For a benchmark task called "random circuit sampling," the fastest current supercomputer would take 10 to the 25th power years to solve , which is far longer than the age of the universe (26.7 billion years); Willow completed the task in less than 5 minutes.

Quantum computing has the potential to significantly increase computing speed and surpass classical computers in specific tasks, which is called "quantum supremacy." As early as 2019, Google had verified this fact, and published in Nature that it used a 54-qubit quantum computer Sycamore to achieve a task that traditional architecture computers could not complete: in an experiment that the world's first supercomputer needed to calculate for 10,000 years, Sycamore took only 3 minutes and 20 seconds. At that time, Google CEO Sundar Pichai said that this was the "Hello World" that researchers had been looking forward to for a long time, and it was the most meaningful milestone in the practical application of quantum computing up to that time.

The release of Willow is undoubtedly another landmark event in the field of quantum computing.

However, "fast" is not Willow's most noteworthy breakthrough.

The biggest highlight of Willow is its super error correction capability.

In the past, quantum chips were prone to decoherence during data processing due to the fragility of the quantum state, which was easily disturbed by the environment and caused errors in the state of the quantum bits. Therefore, despite having "quantum supremacy", quantum computers are easily affected by the environment and are very prone to errors. Generally, the more quantum bits there are, the more errors will occur.

Therefore, "quantum error correction" has become a key technology. Quantum chips require special quantum error correction technology, which is also an important challenge in this field and has seriously restricted the practical application and development of quantum computing.

The Willow chip successfully solved the quantum error correction problem that has plagued researchers for nearly 30 years, achieving an exponential reduction in the error rate. Google's research shows that the more quantum bits used in Willow, the lower the system's error rate.

As the number of quantum bits increases, from a 3×3 array to a 5×5 and then a 7×7 array, Google's Willow chip experiment reduces the coding error rate by 2.14 times with each expansion, and the error rate drops faster and faster.

2. What is quantum computing? Why is it so powerful?

In 1935, Austrian physicist Erwin Schrödinger proposed a great thought experiment: put a cat in a box with radioactive material. There is a 50% probability that the radioactive material will decay and release poison gas to kill the cat, and there is a 50% probability that the radioactive material will not decay and the cat will survive. Before opening the box, no one knows whether the cat is alive or dead, and it can only be described as "in a superposition state of life and death."

The quantum world, like "Schrödinger's cat", is in an unresolved superposition state; the corresponding new computing theory is "quantum computing", and the hardware layer is manifested as quantum chips and quantum computers.

Quantum computing exhibits two advantages:

First, powerful data storage capacity. Classical computing uses bits as the basic unit, while quantum computing uses qubits as the basic unit.

In classical computing, the state of a bit is fixed, either 0 or 1; but a quantum bit is in a superposition state of 0 and 1, in other words, it can store 0 and 1 at the same time.

A traditional chip with n bits can store n data at the same time; while a chip with n quantum bits can store 2^n data at the same time.

Second, it demonstrates powerful parallel computing capabilities for specific problems.

Traditional electronic computers perform serial calculations, and each operation can only convert a single value into another value, which means that it must be calculated in sequence. However, quantum computers can simultaneously convert 2^n data into new 2^n data in one operation.

3. Can future quantum chips replace GPUs and promote the development of AI?

Artificial intelligence technology and its various applications have developed rapidly in recent years, and the demand for computing power has also grown exponentially.

Theoretically, the parallel processing capability of quantum computing gives it a natural advantage in processing complex artificial intelligence algorithms, which can greatly improve the training speed and accuracy of the model. The emergence of the Willow chip may provide a powerful computing power for the further development of artificial intelligence.

In fact, GPUs, which are now widely used in AI, were originally designed to accelerate graphics processing, such as 3D scene rendering in games, modeling and special effects processing in animation production, and video visual effects in film and television production. However, due to its powerful computing power, GPUs were later widely used in scientific computing and artificial intelligence, especially in the neural network training and reasoning stages of deep learning, and performed well in processing large-scale data sets and highly parallel computing tasks.

From this perspective, quantum chips will also gradually break through development in the future, break computing limitations, and accelerate the training process of various AI machine learning algorithms. Quantum chips are currently mainly used in some specific fields that require extremely high computing complexity, such as encryption algorithm cracking in cryptography (for example, it poses a potential threat to traditional encryption methods based on the RSA algorithm), quantum system simulation (simulating the physical and chemical properties of molecules and materials at the quantum level), and solving complex optimization problems (such as logistics planning, resource allocation, and other complex combinatorial optimization problems). In these fields, the advantages of quantum computing can be fully utilized, and it is possible to solve tasks that traditional computers cannot complete within an acceptable time.

The growth of quantum chip computing power is mainly related to the increase in the number of quantum bits and the improvement in quality. In the future, as the number of quantum bits increases, the computing power of quantum computers will grow exponentially. With each additional quantum bit, the number of possible state combinations will double. For example, 2 quantum bits have 4 state combinations, 3 quantum bits have 8 state combinations, and so on. At the same time, the quality of quantum bits (such as coherence time, fidelity, etc.) also has an important impact on computing power. High-quality quantum bits can maintain quantum states more effectively, thereby achieving more accurate and complex calculations.

However, in the short term, it is difficult for quantum chips to shake the position of GPUs . Quantum chips have stronger computing power than GPUs and can theoretically replace them. But computing power is only one aspect of GPUs’ moat. More important are: programmable architecture and developer ecosystem advantages, manufacturing processes, and industry maturity.

The programmable architecture and developer ecosystem of GPU are the core barriers. Nvidia has been paving the way for the "AI computing revolution" initiated by GPU for more than ten years.

CUDA (Compute Unified Device Architecture) is the first GPU programming architecture platform developed by NVIDIA in 2006. Its value lies in building a GPU developer ecosystem where algorithm engineers can explore the capabilities of the GPU according to their own needs. This also expands the application areas of GPUs from graphics rendering to general fields.

If new software is developed based on new hardware (such as quantum chips), it needs to be forward compatible, but the existing major AI software basically relies on the CUDA platform for development, so it is costly to leave the CUDA architecture . In addition, the moat effect of the development community, many high-performance computing developers have accumulated development experience in the CUDA ecosystem, and CUDA has up to 5 million downloads per year. It will take a decade to push the developer community to turn to other programming models .

The GPU chip manufacturing process and industrial chain are mature , with a broad consumer market and a positive industrial cycle.

It has been 25 years since the GPU was born, and the downstream commercial application scenarios such as personal PCs, custom development, and AI data centers have been formed for 10 to 30 years. At present, it takes one year for GPU to go from chip project establishment to tape-out, and one year for tape-out to mass production. With GPU development as the main tone, a corresponding linkage cycle has been formed, such as lithography equipment development and wafer foundry process iteration. Such a solid industrial chain is difficult to break under the positive cycle of more than ten years.

However, it is difficult for quantum chip manufacturing and GPU industry chains to overlap . The design and manufacturing of quantum chips are extremely complex, requiring a highly pure experimental environment, precise quantum control technology, and stable quantum bits. Therefore, for a long time, a few top technology companies have been "fighting alone", and a mature industrial supply chain has not yet been formed. Therefore, it is a major challenge to achieve mass production and commercial application of quantum chips in the short term.

4. The areas where quantum chips have the greatest impact: cryptocurrency and "HPC+AI"

4.1 Quantum chips may be the "nemesis" of cryptocurrency

Take Bitcoin as an example. Its security is based on two key mechanisms. The first is the "mining" mechanism . Bitcoin output is based on proof of work that relies on hash functions. The higher the hash rate, the greater the possibility of successful mining. The second is transaction signature , which is based on the elliptic curve digital signature algorithm (ECDSA), which is equivalent to the user's "identity wallet". The design of these two mechanisms makes Bitcoin almost impossible to crack in traditional computing, and quantum chips will pose a direct threat to Bitcoin .

One is the brute force cracking of the "mining" mechanism by quantum computing. The algorithm of quantum computing can accelerate the calculation of hash functions, that is, speed up mining, and the magnitude exceeds all previous traditional equipment. As a result, the success rate of mining has increased, the supply of cryptocurrency has increased sharply, and its market price has fluctuated greatly. On December 10, Bitcoin fell from $100,000 to $94,000. According to Coinglass data, a total of 237,000 people had their positions liquidated from December 10 to 12.

The second is the direct threat of quantum computing to transaction signatures. Cryptocurrency transactions have two types of credentials: "public key" and "private key". The former is equivalent to the bank card number, and the latter is equivalent to the wallet password. Usually, the disclosure of the public key address does not affect the user's financial security, but quantum computing can crack the signature through the public key and forge transactions. For example, the Shor algorithm in quantum computing is specifically used to crack the prime factorization and discrete logarithm problems of large integers, which will pose a serious threat to transaction signatures.

Although Willow poses little threat to Bitcoin at present, it is very likely that cryptocurrencies will be broken through by quantum computing in the future . In theory, to launch an attack on Bitcoin's signature and mining mechanism, about several million physical quantum bits are needed, which is still a huge gap compared to the 105 physical quantum bits that Willow currently has. However, if Willow is iterated like a general-purpose GPU, achieving mass production and computing power leap, then it is not impossible for Bitcoin to be "conquered" in the next ten years.

4.2 Quantum chips will promote "HPC+AI" and promote the development of high-level artificial intelligence

According to OpenAI's classification of AI, from L1 (Chatbot) to L5 (AGI), the current AI large model development is only in the transition stage from L1 to L2. L5 AGI is defined as "having organizational-level capabilities" and can judge, reason, predict, and plan actions in dynamic and complex real environments. The industry believes that "HPC+AI" will be a key step in achieving AGI .

High-performance computing (HPC) refers to the use of powerful computer capabilities to solve scientific, engineering, and technological problems. It is to some extent similar to today's large AI models, but has different directions and focuses.

HPC focuses on " complex problem solving ". For example, the application of supercomputers in meteorology, physics, astronomy and other fields has brought about major scientific breakthroughs.

The AI ​​model focuses on " reasoning and generation ". Although it is not good at solving complex models, it has good versatility.

The implementation of quantum chips is a revolutionary breakthrough in the HPC field. Solving complex problems no longer requires the long-term "brute force computing" of traditional HPC, but can develop in a new direction - combining with AI for more complex general training .

First, traditional AI training cannot process quantum bit data , while quantum computing can optimize certain learning models that traditional computing cannot process, and build system models that are sensitive to quantum phenomena . In other words, future AI models will have the ability to reason and predict the complex world, reducing or even eliminating the "AI illusion" phenomenon compared to current large models.

The second is the advantage of quantum error correction technology . The Willow chip overcomes the key challenges of quantum error correction and achieves a significant reduction in error rates. In high-level AI training, the application of quantum error correction technology can ensure the accuracy and reliability of the model when training and processing large amounts of complex data, reduce calculation errors caused by the fragility of quantum bits, and thus improve the effectiveness and credibility of AI training.

Although current AI training does not yet meet the conditions for applying quantum chips, it is very likely that quantum chips will be needed as the core support for computing power in the future . Because quantum bits are extremely sensitive and easily affected by external environmental factors, including temperature and electromagnetic fields, these factors may cause decoherence of quantum states, thereby affecting the accuracy of calculation results. Although Willow has made some progress in quantum error correction technology, in actual artificial intelligence training applications, in order to achieve long-term stable operation, the stability and anti-interference performance of quantum systems still need to be further improved.

Google's release of the new generation quantum computing chip Willow has caused a huge sensation in the global technology community. This is not only a major breakthrough in the field of quantum computing, but also the next global technological frontier.

The future development of quantum computing technology is still full of thorns, and there are still many problems to be solved before it can be used on a large scale in AI training.

The advancement of technology has never been a smooth road, just like the GPU's rise from obscurity to great success.