Willow is a testament to human ingenuity and our relentless pursuit of knowledge. While the hype surrounding quantum computing may sometimes outpace reality, the progress being made is irrefutable.

While many quantum computing techniques for machine learning have been proposed, their performance on real-world datasets remains to be studied. In this paper, we explore how a variational quantum circuit could be integrated into a classical neural network for the problem of detecting pneumonia from chest radiographs. Our work serves as an experimental demonstration of the potential of quantum computing to significantly improve neural network performance for real-world, non-trivial problems relevant to society and industry.

The use of machine learning to develop intelligent software tools for interpretation of radiology images has gained widespread attention in recent years. The development, deployment, and eventual adoption of these models in clinical practice, however, remains fraught with challenges. In this paper, we propose a list of key considerations that machine learning researchers must recognize and address to make their models accurate, robust, and usable in practice.

We are in the middle of what the journal Nature has called the “quantum gold rush”. Governments around the world are ramping up their investments in quantum computing. Venture capitalists are pouring billions of dollars into startups sprouting out of university departments. Established technology companies like IBM, Google, Microsoft, Intel, Amazon and Honeywell have recruited highly qualified teams to build quantum computers.

AI is not only making TB diagnosis accessible to people who were previously deprived of it, but by reducing radiologist effort required in reading X-rays, it is lowering healthcare costs and improving reporting times.

Einstein, Bohr, Schrödinger, Heisenberg and others were deeply troubled by the implications of the quantum theory they had developed. They were faced with a personal dilemma: to believe a preposterous theory that worked or discard it for an intuitive theory that didn’t work. Discovering echoes of their theory in the ancient Upanishads gave them comfort, courage, and spiritual guidance.

Time is not real. There is nothing special about the present moment; in fact, a universal present moment does not even exist. The past and the future are equal in all respects. Our notion that time flows irreversibly from the past into the future is an illusion born out of our ignorance about the world. It exists only in our subjective perceptions and not as part of objective reality. Let me convince you of this using simple mathematics, 15-mins of patience, and an open mind.

Discrimination is as old as humankind; religious preaching, moral education, processes or legislation may mitigate its consequences but can’t eliminate it altogether. But today, as we increasingly cede decision-making to AI algorithms, we have a unique opportunity. For the first time in history, we have a real shot at building a fair society that is free of human prejudices by building machines that are fair by design.