In plain words
Ordinary computers work with bits that are either 0 or 1. Quantum computers use qubits, which can hold a weighted mix of 0 and 1 and can be linked so their results depend on each other. For a few special kinds of problem, that could give answers ordinary computers would take ages to find.
Today's quantum machines are small and error-prone. Google's Willow chip (December 2024) has 105 qubits, and in October 2025 Google reported one physics calculation running 13,000 times faster than on a top supercomputer. But as of November 2026, no quantum computer has shown a practical advantage for AI.
The link runs both ways. Some researchers hope quantum computers will one day speed up parts of machine learning. Meanwhile AI is already helping quantum computing: Google DeepMind's AlphaQubit, a neural network, spots errors in qubits more accurately than earlier methods.
Everyday example
A pressure cooker in the kitchen
A pressure cooker makes dal and rajma far quicker than an open pan. It does nothing for toast, chapatis or a fried egg. Quantum computers look similar: brilliant for a few kinds of job, such as simulating molecules, and no help for most others. Whether training AI is one of the jobs a quantum "cooker" can speed up is exactly what researchers are still testing.
Where the example breaks: A pressure cooker works today. Quantum computers are still too small and noisy for most of the jobs they promise, so even their best uses are mostly ahead of us.
How it actually works
Quantum computing and AI meet in two directions: quantum for AI, which is still mostly theory, and AI for quantum, which already works.
How qubits differ
A qubit's state is described by amplitudes that behave like waves. Qubits can be entangled, so measuring one tells you about others. Quantum algorithms arrange the waves so that wrong answers cancel out and likely ones reinforce. IBM calls this interference "the engine of quantum computing".
Errors are the main obstacle
Qubits are fragile: heat and stray signals scramble them, so chips are kept extremely cold. The fix is error correction, which combines many physical qubits into one reliable logical qubit. In 2024 Willow showed errors halving each time the grid grew, from 3x3 to 5x5 to 7x7. IBM aims to deliver Starling, with 200 logical qubits, by 2029.
Quantum for AI: promising, unproven
Proposed quantum machine-learning algorithms promised huge speed-ups, but Scott Aaronson warned in 2015 that they come with fine print. In 2018, 18-year-old Ewin Tang found an ordinary algorithm that matched a celebrated quantum one for recommendations. Training quantum neural networks also hits "barren plateaus", where the learning signal fades as qubits are added.
AI for quantum: working now
AlphaQubit (Nature, November 2024) is a transformer-based decoder that reads the checks run on qubits and predicts which errors happened. On Google's Sycamore data it made 6% fewer errors than tensor-network methods and 30% fewer than a faster standard method.
India's programme
India's National Quantum Mission, approved in April 2023 with ₹6,003.65 crore to 2030-31, aims to build quantum computers with 50 to 1,000 physical qubits within eight years, with a computing hub at IISc Bengaluru.
- Google Willow
- December 2024, 105 qubits; Google calls it the first system where errors fall as error-corrected qubits are added
- Quantum Echoes
- October 2025: one physics calculation 13,000 times faster than a top supercomputer (Google, published in Nature)
- IBM's target
- Starling: 200 logical qubits running 100 million operations, by 2029
- India
- National Quantum Mission, April 2023, ₹6,003.65 crore to 2030-31
Will quantum computers speed up AI?
One view
Yes, in time
Google, which builds quantum chips, says "advanced AI will significantly benefit from access to quantum computing", and IBM lists possible speed-ups for some machine learning problems. Researchers keep proposing new quantum learning methods.
The other view
Only for narrow jobs
Sceptics point out that several famous quantum speed-ups for machine learning disappeared once ordinary algorithms improved, and that training quantum models runs into basic obstacles such as barren plateaus.
Most likely: If quantum computers become useful, it will first be for jobs like simulating molecules and materials, which Google and IBM name among their targets. There is no sign yet that they will speed up everyday AI such as chatbots.
Questions people ask
Will quantum computers make ChatGPT faster?
Not in any way that is shown today. Chatbots run on GPUs and other AI chips, and no quantum computer has beaten them at AI work. Quantum machines may help with narrow problems first, such as chemistry, long before anything like a chatbot.
What is quantum machine learning?
Research into running machine-learning methods on quantum computers, or designing new ones that use qubits. It is an active field, but so far no quantum method has clearly beaten ordinary computers on a practical learning task.
What is a qubit in simple words?
A qubit is the quantum version of a bit. A bit is 0 or 1. A qubit can hold a weighted mix of both until it is measured, and qubits can be linked so their results depend on each other. That is what quantum algorithms use.
How is AI used in quantum computing?
Mainly to find and fix errors. Google DeepMind's AlphaQubit learned to read signals from Google's quantum chip and predict which errors occurred, more accurately than earlier methods.
When will quantum computers be useful?
Nobody knows for sure. IBM aims to deliver a fault-tolerant machine with 200 logical qubits by 2029, and Google's next goal is a long-lasting logical qubit. Useful, everyday advantages depend on reaching that kind of scale.
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Further reading
- Meet Willow, our state-of-the-art quantum chipGoogle, 2024
- Our Quantum Echoes algorithm is a big step toward real-world applicationsGoogle, 2025
- AlphaQubit tackles one of quantum computing's biggest challengesGoogle DeepMind, 2024
- Teenager Finds Classical Alternative to Quantum Recommendation AlgorithmQuanta Magazine, 2018
- What is quantum computing?IBM, 2026