Archive · 9 Jun 2025
AI's Ascent: Can It Outpace Quantum Computing?
Quantum computers use special bits to solve hard problems, but they are hard to build and keep working.
Artificial intelligence, using techniques like deep learning, is getting really good at doing similar things, like finding new materials and simulating how things work.
AI can do this using regular computers, which is cheaper and easier.
This means AI might become the first choice for many tasks, even though quantum computing could, in theory, do them better.
It is like a faster, cheaper option that is becoming a popular choice.
Quantum computing uses qubits to solve complex problems, but faces practical challenges like qubit fragility and error correction.
Artificial intelligence, particularly deep learning, is making rapid advances in areas once exclusive to quantum computing.
AI models are demonstrating capabilities in material discovery and quantum simulation, offering good performance at a lower cost.
AI is beginning to assist in inferring effective Hamiltonians from experimental data, a task that has been difficult for experts.
AI may take the lead in many practical problems before quantum hardware matures, potentially shifting investment from quantum error correction to neural modeling.
- Who
- AI and Quantum Computing Researchers
- What
- AI is advancing in areas previously exclusive to quantum computing.
- When
- 2017 (turning point)
- Where
- N/A
- Why
- AI may take the lead in practical problems before quantum hardware matures.
- Quantum Computing Core
- Qubits
- Classical Computing Core
- Binary bits (0s or 1s)
- AI Technique
- Deep learning
- Turning Point for AI
- 2017
- Labs Integrating AI
- Google's DeepMind