Quantum computing has the potential to significantly transform artificial intelligence due to its exponentially faster ...

Concerns about AI's energy use have a lot of people looking into ways to cut down on its power requirements. Many of these ...

Nvidia invests in accelerating the transition from experimental to practical quantum computing via AI-driven quantum error ...

In this case, a quantum simulator running on a classical computer was used to run quantum algorithms for machine learning. “These simulators allow us to execute simple QML programmes, even though they ...

Quantum annealing shows real advantage for hard problems needing near-perfect answers, beating classical methods.

The quantum simulation of driven ... It is currently unclear whether machine learning model could efficiently learn the dynamics of many-qubit bounded-gate quantum circuits.

Quantum computing startups are learning from the mistakes of the AI boom and funding training programs to develop the talent ...

As quantum-inspired methods enter the AI arena, companies like Dynex are developing alternatives to mainstream LLMs. What does quantum computing mean for the future of AI?

New hybrid quantum applications show quantum computing’s ability to optimize materials science properties using Quantum-Enhanced Generative Adversarial Networks (QGANs) and fine-tune LLM models ...

The modern world would look very different without quantum science. But we’ve only scratched the surface of what’s possible.