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Hybrid Thinking: When Classical and Quantum Computing Team Up | Henning Dekant Interview

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Republished By Echobase.ai
Republished By Echobase.ai

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Quantum computing, for those unfamiliar, often seems like a concept drawn straight from a sci-fi novel. However, its implications and potential applications are very real and increasingly relevant. Henning’s journey began in the world of physics, but it’s his pivot to combining AI with quantum mechanics that brings us exciting possibilities and new frontiers.

In this episode of Impact Quantum, we sit down with Henning Dekant — physicist, entrepreneur, and co-founder of AQB Net — to explore how classical and quantum computing can work together to solve problems once thought impossible.

Henning shares his journey from early days in physics and AI to the forefront of the quantum industry, why quantum machine learning’s hype has faded (for now), and how hybrid systems are bringing us closer to real-world quantum advantage.

This video is from ImpactQuantum.

The early days of quantum computing were rife with speculation and limited demonstrations by giants like IBM and Google. However, the field has evolved dramatically. Today, we’re seeing the dawn of hybrid systems where classical and quantum computing resources are pooled together to tackle problems that were once considered insurmountable. But what fascinates me, and should probably pique your interest too, is the tale of quantum machine learning—a hype that fizzled out, only to hint at a promising resurgence. Why is that? Simply put, despite the impressive strides made in AI, the technology’s current limitations in complex problem-solving signal that quantum computing might yet have a card to play.

Henning explains this using a metaphor I find particularly vivid: we’re at the stage in quantum computing akin to early automotive history—experimenting with various models and setups to find a viable path forward. Each failure, each hype cycle, is akin to those early vehicles—sometimes ending up as mere footnotes in history and other times revolutionizing the entire industry.

A particularly enlightening moment is Henning’s insight into how quantum computing’s impact stretches beyond the obvious realms of tech—it seeps into material science and finance. He discussed quantum’s potential role in evolving industries that rely heavily on processing power and complex simulations, like pharmaceuticals and environmental science.

And how about those real-world applications that seem just around the corner? The answer lies not in the grandiose, world-altering shifts, but rather in the accumulation of smaller, impactful advancements. Quantum computing isn’t just about solving problems faster; it’s about addressing problems that were previously out of reach.

For those looking to dive into this quantum quandary—you don’t need to be a physicist. Curiosity is your ticket. Platforms and simulations are more accessible than ever, allowing even the layperson to experiment with quantum algorithms. It’s a veritable playground for the intellectually adventurous.

And to those already in the field or looking to make their career out of quantum computing, Henning offers this: the paradigm is shifting from purely theoretical research to practical, hybrid applications and problem-solving. There’s a fine balance between understanding the theory deeply and applying it practically, using the tools and systems that are available today.

So, what can we take away from today’s quantum journey? The field is evolving, not always predictably but excitingly. With every supposed hype ‘failure’ comes a deeper understanding and refinement of the quantum computing landscape. We’re not just spectators at the dawn of a new technological era; we’re participants, each capable in our way of contributing to its shape.

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