82 afleveringen
- The internet was built by reading packet headers.
Quantum networks cannot do that.
In this episode, I explore my biggest takeaways from Part 1 of my Beyond the Qubit interview with Vijoy Pandey, head of Outshift at Cisco. The key difference is simple but profound: classical networks scale by inspecting and forwarding information, while quantum networks have to preserve information they cannot directly inspect.
This episode is for investors, founders, and anyone trying to understand what infrastructure quantum computing will need beyond the QPU itself. If quantum systems are going to scale beyond isolated machines, they will need a network layer that can connect processors, sensors, and resources while preserving fragile quantum states.
Cisco’s approach is interesting because the company is not trying to build the quantum computer itself. It is exploring the networking layer around quantum systems, using photonics, telecom frequencies, room-temperature components, and existing fiber infrastructure. The goal is not to recreate the classical internet, but to build the architecture needed for quantum scale.
The strategic question is not only who builds the best qubits.
It is also:
Who builds the network that connects them?
💡 In this episode, we cover:
Why quantum networks cannot simply copy classical internet architecture
Why quantum information cannot be inspected like classical packets
How quantum switches and entanglement sources could enable scaling
Why networking between QPUs may become a major bottleneck
Why Cisco is focusing on the infrastructure layer around quantum computers
How photonics and existing fiber infrastructure could improve deployability
Why quantum networks may also connect sensors and shared resources
What investors should watch in the quantum networking stack
Chapters
00:00 Why Cisco is exploring quantum networking
00:50 Why quantum needs a network layer
03:22 Quantum clusters and the need for connectivity
04:47 What quantum networking actually means
05:23 The quantum switch challenge
08:01 Why classical networking cannot be copied
10:03 Why quantum networks cannot inspect information
12:29 Building networks without destroying quantum states
14:42 Why Cisco focuses on photonics and fiber
17:39 Connecting quantum computers and sensors
27:14 The current state of quantum networking
Share this episode with someone investing in or building in quantum, and subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.
📌 Disclaimer: This is not investment advice. This post is shared on a personal basis and I do not represent any company. - Quantum will not scale by optimizing hardware, software, and testing independently.
The winners will have to make the entire system work.
In this episode, I continue my conversation with Adriaan van Rol from OrangeQS to explore why quantum testing may become one of the most important infrastructure layers in the industry. OrangeQS looks like a hardware company at first. Its OrangeQS MAX platform combines cryogenics, electronics, cabling, control systems, and data acquisition to test quantum chips.
But one of the more interesting parts of the system is the software layer underneath: OrangeQS Juice. What started as the software environment around OrangeQS MAX evolved into a broader platform for multi-user workflows, instrument control, structured data, and scalable test operations.
This episode is for investors, founders, and anyone trying to understand what it takes for quantum to move from research toward manufacturing. At scale, testing is not just about measuring a chip. It is about turning measurements into diagnosis, validated insights, and better manufacturing decisions.
That is where the strategic opportunity becomes interesting. The potential moat is not only the hardware or the software individually. It is the integrated system: hardware + software + data + domain knowledge. Because in quantum manufacturing, the ability to create a faster feedback loop may become just as important as the ability to build the device itself.
💡 In this episode, we cover:
Why quantum testing needs to evolve beyond laboratory workflows
How OrangeQS MAX combines hardware infrastructure for quantum chip testing
Why OrangeQS built Juice instead of relying on simple lab scripts
How software enables repeatable, traceable, multi-user testing
Why testing becomes inseparable from manufacturing at scale
How measurement data can become manufacturing insight
Why integrated systems may create stronger moats than individual products
The importance of data governance in quantum manufacturing
Chapters
00:00 Why quantum testing needs a complete system
01:50 What OrangeQS is building for quantum chip testing
08:10 Why testing and manufacturing need feedback loops
14:40 Turning test data into manufacturing learning
29:33 Why OrangeQS Juice became a hidden gem
30:54 Moving from lab scripts to scalable workflows
35:00 Hardware, software, data and domain knowledge together
42:15 The future of quantum manufacturing infrastructure
Share this episode with someone investing in or building in quantum, and subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.
📌 Disclaimer:This is not investment advice.This post is shared on a personal basis and I do not represent any company. - Why is building a great deep-tech product only half the battle?
In this episode, I explore one of my biggest takeaways from my conversation with Adriaan Rol from OrangeQS. OrangeQS is building test solutions for quantum chips, but the challenge is not only technical. When a product costs millions, the company also has to solve a different problem: how customers actually buy.
This episode is for investors, founders, and anyone interested in deep-tech commercialization. Adriaan shares an honest lesson from OrangeQS’s journey: they underestimated not the physics or engineering, but the complexity of corporate decision-making, CapEx budgets, procurement processes, and internal risk.
A strong technical story is not enough. A great product is not enough. At some point, deep-tech companies need to make the buying decision easier. That means understanding the customer’s internal process, creating the right milestones, reducing risk step by step, and turning technical interest into a purchase order.
The lesson is bigger than quantum. In deep tech, product-market fit is only part of the equation. Companies also need procurement-market fit.
💡 In this episode, we cover:
Why deep-tech companies need more than product-market fit
Why expensive hardware requires a different sales approach
How OrangeQS learned to navigate CapEx decisions and procurement
Why technical validation does not automatically lead to purchases
How partnership programs can reduce customer risk
Why customers need a buying process they can defend internally
How deep-tech founders can turn interest into purchase orders
Why adoption is often as difficult as the technology itself
Chapters
00:00 Why deep tech needs procurement-market fit
08:34 Why million-euro hardware changes the buying process
17:32 Building a partnership program to reduce risk
22:19 The hidden challenge of CapEx decisions
40:29 Why procurement can make or break adoption
Share this episode with someone building or investing in deep tech, and subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.
📌 Disclaimer:This is not investment advice.This post is shared on a personal basis and I do not represent any company. - When quantum computers scale out, the algorithm has to know where the weak links are.
In this episode, I continue my conversation with Enrique Solano from Kipu Quantum to explore why modular quantum computing is not only a hardware challenge. Most people think modularity means more chips, more qubits, and more scale. But Enrique highlights a deeper issue: once quantum computers become distributed systems, the algorithm has to understand the physical reality of the machine.
This episode is for investors, founders, and anyone trying to understand where quantum software value may emerge. When computation moves across multiple chips, not every connection is equal. Some gates may have very high fidelity inside a chip, while connections between chips can introduce weaker operations. Small differences in fidelity can determine whether an algorithm survives long enough to become useful.
That is where Kipu’s hardware-aware approach becomes interesting. The software cannot treat every quantum backend as identical. It needs to understand connectivity, topology, fidelities, and the weak points of the architecture. In quantum, scaling hardware creates a new software problem. The winning software layer may be the one that understands the machine well enough to extract value from its imperfections.
💡 In this episode, we cover:
Why modular quantum computing changes the software challenge
Why more qubits do not automatically mean more useful computation
How inter-chip connections can create new fidelity bottlenecks
Why algorithms need to understand quantum hardware topology
Why hardware-aware software may matter more than hardware-agnostic approaches today
How Kipu thinks about extracting value from imperfect quantum systems
Why scaling quantum hardware creates new algorithmic challenges
What investors should watch in quantum software companies
Chapters
00:00 Why Kipu Quantum focuses on hardware-aware software
01:29 Why algorithms must adapt as hardware changes
03:26 Why architecture matters in quantum systems
06:46 Fidelity limits inside quantum architectures
08:03 Why modularity changes the algorithm
09:01 Building quantum systems beyond single chips
15:04 Why inter-chip connections create new challenges
15:21 Why small fidelity differences matter
16:30 Why algorithms must know the machine
Share this episode with someone investing in or building in quantum, and subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.
📌 Disclaimer:This is not investment advice.This post is shared on a personal basis and I do not represent any company. - Much of quantum software is built around one assumption: better hardware will eventually solve the problem.
Kipu Quantum takes a different view.
In this episode, I explore my biggest takeaways from Part 1 of my Beyond the Qubit interview with Enrique Solano, CEO of Kipu Quantum. The traditional quantum narrative is familiar: today’s machines are too noisy, qubits are not good enough, and real value will only arrive with fault-tolerant quantum computers. Enrique challenges that mindset.
The point is not that today’s hardware is perfect. It clearly is not. The point is different: accept the reality conditions of the machines that exist today and build software that works within those constraints. Instead of waiting for perfect hardware, Kipu studies the architecture, connectivity, fidelities, and limitations of current quantum systems, then designs algorithms that can extract useful performance from them.
This episode is for investors, founders, and anyone trying to understand where quantum value may emerge. Kipu’s bet is that useful quantum computing may arrive before fault tolerance, by finding the corners where today’s imperfect machines can already create value.
The question is not only who builds the best quantum computer.
It is also:
Who can make today’s quantum computers useful?
💡 In this episode, we cover:
Why Kipu Quantum challenges the idea that hardware must come first
Why current quantum limitations should become design constraints
How hardware-aware algorithms can extract more value from existing machines
Why Kipu focuses on industrial problems and customer needs
How algorithm compression can reduce the requirements for quantum hardware
Why hybrid quantum-classical workflows may matter before fault tolerance
Why quantum software companies may create value earlier than expected
What investors should watch in quantum software businesses
Chapters
00:00 Why Kipu Quantum matters for investors
01:10 Building value with today’s quantum hardware
03:33 Why Kipu does not wait for fault tolerance
04:15 Starting from hardware, not use cases
05:59 Finding industrial problems quantum can solve
06:59 Customer applications and commercial validation
08:56 Why current hardware is still worth using
28:57 Why Kipu rejects blaming the hardware
31:27 Accepting reality conditions in quantum
38:05 Hardware-aware algorithms and compression
50:53 Why software must adapt as hardware improves
Share this episode with someone investing in or building in quantum, and subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.
📌 Disclaimers:This is not investment advice.This post is shared on a personal basis and I do not represent any company.
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