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Quantum Tech Pod Episode 68: Peter Chapman, CEO, IonQ

Quantum Tech Pod

NOTE

Exploring IonQ's Quantum Computing Timeline and Applications

In the timeline for IonQ's quantum computing applications, by 2024, quantum machine learning is expected to become a practical application with improved model expressiveness, reduced cycles for model creation, and less data needed for training. By 2026, quantum computing could make advancements in material science, especially in fields like battery technology and solar panel materials. And by 2028, IonQ envisages quantum solutions transforming the field of chemistry, potentially revolutionizing drug discovery through more efficient computational chemistry algorithms. Recent innovations in quantum algorithmic improvements have shown significant reductions in gate requirements, hinting at the possibility of accelerating these timelines with further advancements.

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