Why People Confuse AI with Quantum Computing and Why You Should Care - Investopedia

Table of Contents Expand Table of Contents What AI Actually Is What Quantum Computing Actually Is Where the Two Meet The quantum acceleration of AI tasks could lead to possible breakthroughs in medicine and biotech, materials science, weather modeling, finance, and logistics. gorodenkoff / Getty Images Close Key Takeaways AI is generative software that “learns” patterns from data to make predictions or decisions. Quantum computing is a new kind of hardware that uses quantum bits (qubits) to process many possibilities simultaneously, potentially solving problems too complex for today’s computers. AI and quantum may converge in the future: quantum could supercharge certain AI tasks, while AI is already being used to stabilize quantum systems. Most people think AI and quantum computing are essentially the same thing, which is futuristic technology that's hyped in headlines and driving significant stock market gains. It's certainly doing the last part, but you'd be wrong to confuse these technologies otherwise. AI is a software capability that learns from data to automate or assist decisions, while quantum computing is hardware built on principles of quantum physics, designed to crunch calculations that would take traditional computers millennia to solve.12 What AI Actually Is AI refers to algorithms, including machine learning, neural networks, and large language models (LLMs), that find patterns in big data to make predictions, classify information, or make recommendations based on those patterns.2 This includes popular applications like ChatGPT, product recommendations, fraud alerts, and self-driving features already widely available today. These systems run on traditional computers, using common hardware like CPUs and GPUs.

What Quantum Computing Actually Is Instead of the 0s and 1s used in binary code, quantum computing is based on qubits (short for “quantum bits”), which can represent many possible states at once. This theoretically allows quantum machines to process vast numbers of potential solutions in parallel.1 If this were to occur, these computers would be orders of magnitude more powerful for specific tasks than even the most advanced supercomputers, such as simulating complex molecules or searching through massive search spaces. Meanwhile, as powerful quantum computers threaten to break current encryption, computer scientists are already working on post-quantum cryptography to ensure data security in the long term.3 Quantum devices are still limited and prone to errors today. But the long-term potential is enormous. Indeed, quantum computers are making progress, with qubit processors now able to vastly outperform classical systems—but still on very narrow, benchmark tasks. The promise is that quantum machines would eventually replace traditional computers, ushering in a new post-digital age. AI vs. Quantum Computing AI Novel software architecture Already mainstream Focus on thinking, learning, prediction Runs on classic hardware (binary code) Quantum Computing Novel hardware architecture Still experimental Focus on raw data analysis and simulation Runs on qubits (multistate code) Where the Two Meet The intersection of quantum and AI is likely to take two parallel paths:4 The first is the eventual use of quantum hardware to speed up or augment certain AI tasks, allowing models to consider far more options at once, search solution spaces faster, and tune themselves more quickly.The second would see current AI methods deployed to help build and control quantum systems—keeping these delicate machines stable, automatically adjusting settings, spotting glitches early, and generally helping the hardware function for longer stretches. The quantum acceleration of AI tasks could lead to possible breakthroughs in medicine and biotech, materials science, weather modeling, finance, and logistics. These possibilities may be speculative, but early proofs of concept have been promising.5 Quantum Computing Explained: Definition, Uses, and Leading Examples AI is already everywhere. You can chat with it in plain language, businesses use it automate some everyday tasks, and consumers allow it to personalize their experiences for many things online. Quantum computing is less visible—but could be at least as transformative. It could one day power breakthroughs in medicine, materials, green energy, and ultra-secure encryption. Trade on the Go. Anywhere, Anytime One of the world's largest crypto-asset exchanges is ready for you. Enjoy competitive fees and dedicated customer support while trading securely. You'll also have access to Binance tools that make it easier than ever to view your trade history, manage auto-investments, view price charts, and make conversions with zero fees. Make an account for free and join millions of traders and investors on the global crypto market.

Article Sources Investopedia requires writers to use primary sources to support their work. These include white papers, government data, original reporting, and interviews with industry experts. We also reference original research from other reputable publishers where appropriate. You can learn more about the standards we follow in producing accurate, unbiased content in our editorial policy. IBM. "What Is Quantum Computing?" Stanford University. "Brief Definitions of Key Terms in AI." NIST. "NIST Releases First 3 Finalized Post-Quantum Encryption Standards." Tychola, K. A., Kalampokas, T., & Papakostas, G. A. (2023). Quantum machine learning—an overview. Electronics, 12(11), 2379. Wang, Y., & Liu, J. "A Comprehensive Review of Quantum Machine Learning: From NISQ to Fault Tolerance." Reports on Progress in Physics (2024).

Compare Accounts Advertiser Disclosure × The offers that appear in this table are from partnerships from which Investopedia receives compensation. This compensation may impact how and where listings appear. Investopedia does not include all offers available in the marketplace.