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

Source: Zeping Macro

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

What is so powerful about Willow chips? How far is it from mass production?

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

For a benchmark task called "Random Circuit Sampling," the fastest current supercomputers would take 10 25 years to solve, a time well beyond the age of the universe (26.7 billion years);< /strong>AndWillow completed this task in less than 5 minutes.

Quantum computing has the potential to significantly increase computing speed and surpass classical computers on specific tasks, which is called "quantum superiority." As early as 2019, Google has verified this fact and published it in Nature, indicating that it used a 54-qubit quantum computer Sycamore to achieve a task that traditional architecture computers cannot complete: becoming the first in the world. In an experiment that required a supercomputer to calculate 10,000 years, Sycamore only took 3 minutes and 20 seconds. At that time, Google CEO Sundar Pichai said that this was the "Hello World" that researchers had been waiting for for a long time. 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 the most noteworthy thing about Willow breakthrough.

Willow’s biggest highlight is its super error correction ability.

In the past, during the data processing process of quantum chips, due to the fragility of the quantum state, it was easily affected by environmental interference and decoherence occurred, resulting in errors in the state of the qubits. Therefore, despite their "quantum superiority", quantum computers are susceptible to environmental influences and are very error-prone. Generally, the more qubits there are, the more errors can occur.

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

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

When the number of qubits increases,when expanding from a 3×3 array to a 5×5 to a 7×7 array, each expansion in Google’s Willow chip experiment can lead to coding errors. The rate is reduced by 2.14 times, and the error rate is decreasing faster and faster.

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

In 1935, the Austrian physicist Schrödinger proposed a great thought experiment: If you put a cat in a box with radioactive material, there is a 50% probability that the radioactive material will Decaying and releasing poisonous gas kills the cat, but there is a 50% chance 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. It can only be described as "in a superposition state of life and death."

The quantum world is like "Schrödinger's cat" "The same, in a pending superposition state;The corresponding new computing theory is "quantum computing", and the hardware layer is represented by quantum chips and quantum computers.

Quantum computing shows two advantages:

First, powerful data storage ability. 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 determined, either 0 or 1; while a qubit 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 pieces of data at the same time; while a chip with n qubits can store 2^n pieces of data at the same time.

Second, demonstrate powerful parallel computing capabilities for specific problems.

Traditional electronic computers are serial calculations. Each operation can only convert a single value into another value, which means that it must be calculated in sequence. A quantum computer 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 various applications have developed rapidly in recent years, and the demand for computing power has also increased exponentially.

Theoretically, the parallel processing capabilities of quantum computing give it a natural advantage in processing complex artificial intelligence algorithms, and can greatly improve the training speed and accuracy of the model. The emergence of Willow chips may provide 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. For example, 3D scene rendering in games, modeling and special effects processing in animation production, video visual effects in film and television production, etc. However, due to its powerful computing power, GPU was later widely used in the fields of scientific computing and artificial intelligence, especially in the neural network training and inference stages of deep learning. It performs well in processing large-scale data sets and high-parallel computing tasks. outstanding.

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

The growth in quantum chip computing power is mainly related to the increase in the number and quality of qubits. In the future, as the number of qubits increases, the computing power of quantum computers will increase exponentially. Each additional qubit doubles the number of possible state combinations. For example, 2 qubits have 4 state combinations, 3 qubits have 8 state combinations, and so on. At the same time, the quality of qubits (such as coherence time, fidelity, etc.) also has an important impact on computing power. High-quality qubits 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 status of GPUs. Quantum chips have stronger computing power than GPUs and can theoretically be replaced. But the moat of GPU is only one aspect: computing power. More importantly: programmable architecture and developer ecological advantages, manufacturing technology and industry maturity.

GPU’s programmable architecture and developer ecosystem are core barriers. The “AI computing power revolution” launched by NVIDIA with GPU has been paving the way 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,< /strong>Algorithm engineers can explore the capabilities of the GPU according to their own needs, which also expands the application field of the GPU from graphics rendering to general fields.

If you develop new software based on new hardware (such as quantum chips), you need to achieve forward compatibility. However, existing major AI software basically relies on CUDA platform development, soit breaks away from the CUDA architecture There is a high costto be paid. Coupled with the moat effect of the development community, many high-performance computing developers have accumulated development experience in the CUDA ecosystem. CUDA has up to five million downloads per year. It will beto push the developer community to switch to other programming models. A project measured in ten years.

GPU chip manufacturing process and industry The chain is maturewith a broad consumer market anda positive industry cycle.

It has been 25 years since the birth of GPU, and downstream commercial application scenarios such as personal PCs, customized development, and AI data centers have been formed for 10 to 30 years. Currently, GPU takes one year from chip project establishment to tape-out, and one year from 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 will be difficult to break in a positive cycle of more than ten years.

It is difficult for quantum chip manufacturing and GPU industry chains to overlap. The design and manufacturing process of quantum chips are extremely complex and require a highly pure experimental environment, precise quantum control technology and stable qubits. Therefore, for a long time, a few top technology companies have been "working alone" and have not yet matured. industrial supply chain. Therefore, it is a big problem 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 (Proof of Work) that relies on hash functions. The higher the hash rate, the greater the possibility of successful mining. big. The second is transaction signature, which is based on the Elliptic Curve Digital Signature Algorithm (ECDSA) and is equivalent to the user's "identity wallet". The design of these two mechanisms makesBitcoin almost impossible to crack in traditional computing, and quantum chips will pose a direct threat to Bitcoin.

The first is quantum computing’s violent cracking of the “mining” mechanism. Quantum computing algorithms can accelerate the calculation of hash functions, that is, the mining speed is accelerated, and the extent is greater than that of all previous traditional equipment. As a result, the mining success rate increases, the supply of cryptocurrency increases sharply, causing its market price to rise. Big swings. On December 10, Bitcoin fell from US$100,000 to US$94,000. Coinglass data shows that a total of 237,000 people liquidated their positions from December 10 to 12.

The second is the direct threat of quantum computing to transaction signatures. There are two types of credentials for cryptocurrency transactions: "public key" and "private key". The former is equivalent to a bank card number, and the latter is equivalent to a wallet password. Normally, the disclosure of public key addresses does not affect the security of users' funds, but quantum computing can use public keys to crack signatures and forge transactions. For example, the Shor algorithm in quantum computing is specially 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 the moment, it is very likely that cryptocurrencies will be broken through by quantum computing in the future. Theoretically, to launch an attack on Bitcoin's signature and mining mechanism, approximately several million physical qubits are needed. Compared with the 105 physical qubits Willow currently possesses, the gap is still very large. But if Willow iterates like a general-purpose GPU and achieves mass production and computing power leaps, then it is not impossible for Bitcoin to be "compromised" in the next ten years.

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

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

High performance computing (HPC) refers to Using powerful computer capabilities to solve science, engineering and technology implementation problems is similar to today's large AI models to a certain extent, but the direction and focus are different.

HPC focuses on "Complex problem solving". For example, the application of supercomputers in meteorology, physics, astronomy and other fields has brought about major scientific research 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 field of HPC. Solving complex problems no longer requires the long-term "violent calculation" of traditional HPC, but can develop in a new direction—— Combine with AI for more complex general trainings.

First, traditional AI training cannot process qubit data, while quantum computing can optimize specific learning models that cannot be processed by traditional computing and buildquantum Phenomenon-Sensitive System Models. That is, future AI models will have the ability to reason and predict complex worlds, reducing or even eliminating the phenomenon of "AI hallucination" compared to current large models.

The second is Quantum error correction technology Advantages Willow chip has overcome the key challenges of quantum error correction and achieved Significant reduction in error rate. 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 ofcomplexdata >, reducing calculation errors caused by the fragility of qubits, thereby improving the effectiveness and credibility of AI training.

Although current AI training does not yet have the conditions to apply quantum chips, it is very likely that quantum chips will be needed as the core support of computing power in the future. Because qubits 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 certain 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 the quantum system still need to be further improved.

Google released Willow, a new generation of quantum computing chip, which 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 cutting-edge of global technology.

There are still thorns in the road to the development of quantum computing technology in the future, and there are still many problems to be solved before large-scale application in AI training.

Technological progress has never been a smooth road, just as GPU has gone from obscurity to brilliance.