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Simon Benjamin

05/26/18

@ Y Combinator

Quantum-enabled discovery could revolutionize fields like drug discovery by allowing quantum computers to predict molecular behaviors, significantly speeding up the process of synthesizing complex molecules without relying on trial and error.

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Simon Benjamin on Architectures for Quantum Computing

@ Y Combinator

Simon Benjamin on Architectures for Quantum Computing

05/26/18

Related Takeaways

John Preskill

05/16/18

@ Y Combinator

Quantum computers will likely excel in understanding and inventing new materials and chemical compounds, which are fundamentally quantum physics problems.

Simon Benjamin

05/26/18

@ Y Combinator

The potential for quantum computers to simulate chemistry and material systems could lead to breakthroughs in various scientific fields, although the exact number of qubits required for these tasks remains uncertain.

Leonard Susskind

12/07/18

@ Y Combinator

Quantum mechanics has already shaped technology significantly, and the exploration of massive entanglement in quantum systems will lead to advancements that classical computers cannot achieve.

Patrick Hsu

04/15/25

@ Sequoia Capital

The promise of AI in drug discovery lies not just in predictive power but in the ability to simulate experiments in a parallelized fashion, which could significantly reduce the time and cost involved in traditional methods.

Chad Rigetti

09/30/16

@ Y Combinator

The problems that quantum computers will solve are incredibly impactful, falling into two broad categories: quantum chemistry and machine learning.

Chad Rigetti

09/30/16

@ Y Combinator

Quantum computing offers a faster and cheaper path to achieving high levels of computing power compared to traditional methods.

John Preskill

05/16/18

@ Y Combinator

Quantum systems can be used for improved sensing, potentially achieving higher sensitivity and spatial resolution than existing technologies, with applications in biology and medicine.

Simon Benjamin

05/26/18

@ Y Combinator

Quantum computing has gained significant attention recently because it's starting to work in labs, reaching a point where it can perform tasks that classical computers cannot.

Patrick Hsu

04/15/25

@ Sequoia Capital

By 2050, we envision a fully automated lab capable of simulating drug interactions with high accuracy, significantly speeding up drug discovery processes.