Quantum London has partnered with the Lloyd’s Lab from Lloyd’s of London and put together a great event looking at how will quantum computing impact the insurance industry.

In this short video, Anahita Zardoshti presents her “Impacts of #Quantum #Computing on Insurance” report, providing a concise but complete overview of Quantum Computing and the impacts on the #Insurance industry.

In this talk, Phillip Ball explains why quantum mechanics is not weird.

Quantum computers rely on concepts such as superposition and entanglement that defy our intuitions about how things can behave. It’s often said that the world is quantum-mechanical and weird at small scales, and classical and familiar at human scales.

I will challenge that idea, arguing that the classical world isn’t distinct from the quantum but emerges from it. While we don’t yet have a full understanding of how that happens, the outlines are becoming clear – and in one view, the concept of quantum information lies at the heart of that account. In this talk – which is not-technical and requires no specialist scientific knowledge – I will show address some popular misconceptions about what quantum mechanics means, and explain what we can currently say about what it does mean.

Jason Cong talks about
Compilation for Quantum Computing: Gap Analysis and Optimal Solution

Papers in this session.

From the abstract:

As quantum computing devices continues to scale up, we would like to access the quality of the existing quantum compilation (or design automation) tools. As the first step, we focus on the layout synthesis step. We develop a novel method to construct a family of quantum circuits with known optimal, QUEKO, which have known optimal depths and gate counts on a given quantum device coupling graph. With QUEKO, we evaluated several leading industry and academic LSQC tools, including Cirq from Google, Qiskit from IBM, and t|ket from CQC.

We found rather surprisingly large optimality gaps, up to 45x on even near-term feasible circuits. Then, we went on to develop a tool for optimal layout synthesis for quantum computing, named OLSQ, which formulates LSQC as a mathematical optimization problem. OLSQ more compactly represents the solution space than previous optimal solutions and achieved exponential reduction in computational complexity. 

Microsoft places Azure Quantum into public preview.

Does this mean that enterprises are going to start embracing Quantum Computing?

What can you do now to prepare for a quantum career?

Links

Siraj Raval explains Quantum Machine Learning in the fun and approachable way he’s know for.

Quantum Machine Learning may sounds daunting to most people, but it’s way more fun to learn about than Classical Machine Learning. Creative algorithms that leverage concepts like quantum entanglement and superposition are already being studied by various teams to enable new solutions in fields like Chemistry, Finance, Supply Chain, and Energy. 

Before you email or comment regarding controversies around Siraj, I said my piece in a Data Driven data point.

Listen to that before you send angry comments my way. Winking smile

The latest episode of Impact Quantum is out!

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It was recorded on a livestream this morning and is rated one Schroedinger.

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