Entangled Things

In Episode 153, Daniela Herrmann, CEO and Founder of Dynex, joins Patrick and Ciprian to talk about making quantum accessible to businesses that have no interest in understanding how it works. Dynex takes a problem driven approach — customers describe their computational challenge, Dynex identifies whether it’s a quantum problem, builds the solution, and delivers a working MVP in six to eight weeks, running on Dynex’s own proprietary soft and hardware platform. The conversation covers the breadth of use cases Dynex is pursuing across logistics, trade optimization, materials science, and healthcare, and why Daniela believes the market is ready even if the industry has been communicating badly. The team also discuss Dynex’s Zeus chip prototype, currently in benchmarking with ten thousand logical qubits, the coming pressure on cryptographic infrastructure, and why Daniela expects the quantum timeline to surprise the market again.

In Episode 152, Emma Rosenfeld, Research Scientist at Google Quantum AI, joins Patrick and Ciprian for Google’s first appearance on the show. Emma traces her path from mechanically exploring quantum systems at Harvard to quantum sensing at Google X and quantum computing at Amazon before arriving at Google. The conversation digs into quantum error correction — what it is, why it was the field’s saving grace, and where the experimental evidence now stands across multiple hardware platforms. Emma explains T gates and why they present a unique challenge inside most error correction encodings, before walking through Magic State cultivation, a technique developed by her colleague Craig Gidney that significantly reduces the resource cost of creating T states, and its recent experimental validation on Google’s Willow processor. The episode closes on the honest assessment of where quantum algorithms stand, what quantum computers will realistically be a surgical tool for, and why overpromising is one of the field’s biggest risks.

In Episode 151, Abhi Chopra, Founder and CEO of BQP, joins Patrick and Ciprian to make the case for a different way of thinking about quantum. Rather than chasing quantum advantage as a blanket claim, BQP takes a problem driven approach — identifying which parts of a workflow benefit from quantum inspired or quantum native computation, and meeting engineers where they already work. The team dig into BQP's OneCore Engine, its native integration with MATLAB, and why circuit depth rather than qubit count is the real bottleneck for complex simulations. Abhi shares two concrete examples: a propeller design project with drone company Modobolo that produced a patent pending 3D printed design, and a Space Force SBIR award where quantum assisted machine learning reduced a model from 6.9 gigabytes to 3 megabytes for deployment at the tactical edge. The episode closes on IBM Ventures' investment in BQP and why the quantum and AI convergence is starting to look like it did on the wall.

 In Episode 150, Colton Dillion and Rick Carback of Postquant Labs join Patrick and Ciprian to introduce Quip Network, a decentralized, open source protocol designed to commoditize quantum compute the way CUDA democratized GPU access. The team dig into the four core problems facing quantum today: unclear benchmarks, high education costs, closed ecosystems, and fragmented talent. Quip Network addresses these by creating a bid based marketplace where quantum operators can monetize unused capacity, and consumers can access compute without needing a quantum PhD. The conversation covers proof of useful work, where solving optimization problems and random circuit sampling both benchmarks hardware and earns compute credits, as well as how hybrid quantum classical computation fits into the architecture. Rick weighs in on the cryptographic timeline, estimating a 10% probability of a cryptographically relevant quantum computer by March 2028, and what that means for securing Bitcoin and Ethereum wallets today. Quip Network hub: links.quip.networkQuantum Doomsday Clock: quantumdoomclock.com

In Episode 149, Patrick and Ciprian take stock of where the money in quantum is flowing. The conversation covers IBM's plan to invest more than $10 billion over five years, the US Department of Commerce's nine letters of intent totaling over two billion dollars under the CHIPS Act, and QEra's $230 million raise with Nvidia involvement. The team dig into which modalities are getting the spotlight, why neutral atoms are drawing attention, and what Microsoft's Majorana 2 bet could mean if it holds water. The episode closes on the bigger picture — whether we're nearing a defining moment for quantum like ChatGPT was for AI, the geopolitical dimensions of the race, and the importance of getting to the quantum-born generation.

In Episode 148, Gustavo Cancelo, Senior Scientist at Fermilab near Chicago, joins Patrick and Ciprian to talk about QICK, the Quantum Instrumentation Control Kit, an open source platform developed at Fermilab that has become a widely adopted tool for quantum control and readout across four continents. Gustavo walks through what quantum control actually involves, why calibration and characterization are as important as the qubits themselves, and how QICK's MIT license and affordability have lowered the barrier to entry for universities and startups worldwide. The conversation covers QICK's reach into quantum sensing and networking, including dark matter detection experiments, before closing on QICK 2 — a next-generation version with onboard AI engines and low-latency inter-box communication designed with quantum error correction at scale in mind. Large industry partners including Microsoft and HRL have recently adopted QICK, and QBlocks has acquired commercial distribution rights ahead of the IEEE QSC conference in Toronto in September (https://ieeecsc.org/event/conference/2026-ieee-quantum-week)

In Episode 147, Steve Girvin returns for his third appearance to take stock of where quantum stands across research, hardware, and the commercial landscape. The team cover the ongoing challenge of discovering new quantum algorithms — and why better hardware may be what unlocks them — before moving into the state of the three leading modalities: superconducting qubits, trapped ions, and neutral atoms. Steve walks through the wiring problem facing superconducting systems at scale, why cold atoms are on a steeply rising learning curve, and what photonic approaches like Xanadu and PsiQuantum are betting on. The conversation closes on dynamic circuits — a hybrid model where quantum and classical computation are deeply interwoven mid-algorithm — and why that may be one of the most powerful and least understood frontiers in the field.

In Episode 146, Bob Coecke, Founder and CEO of Relational Intelligence returns alongside Alessandro Cheli, Categorical Machine Learning Operations at Relational Intelligence, to introduce two brand new companies. The bulk of the conversation covers Relational Intelligence, built on the idea that intelligence — human, mechanical, or otherwise — is better understood through relationships than through the reductive, static frameworks that dominate western scientific thinking. The team dig into relational modeling, the DisCoPy Python library for working with string diagrams and category theory, and why this approach produces AI that is interpretable and formally verifiable in a way neural networks are not. The conversation also touches on how the architecture is quantum-native from the ground up, meaning it won't need to be retrofitted when scalable quantum hardware arrives. Bob closes with a brief look at Quantum Entertainment Berlin, including a quantum guitar performance at Wacken Open Air and a VR game designed to teach quantum mechanics by being genuinely fun to play.

In Episode 145, Fred Chong returns to discuss what's new at Infleqtion, now a public company, and the work that's keeping him busy across both academia and industry. The team dig into Quantum for Bio, a multimodal cancer biomarker discovery project developed with Welcome Leap and now continuing with IBM, where hybrid quantum-classical algorithms are uncovering relationships between genes, RNA, and tumor imaging that classical methods haven't been able to tackle. Fred shares Peter Shor's perspective that the shortage of quantum algorithms reflects a shortage of good machines, not a shortage of ideas, and why that's an optimistic take. The conversation also covers neutral atoms as a maturing modality, Infleqtion's dual-species machine and how it reduces the need for physical qubit movement, and the concept of interleaving error-corrected qubit tiles to reduce long-range communication costs.

In Episode 144, Todd Brun, Professor of Electrical Engineering, Computer Science, and Physics at the University of Southern California, returns to break down where quantum error correction stands today. The team cover the transition from theoretical thresholds to real experimental demonstrations, why decoding latency matters as much as code quality, and the counterintuitive insight at the heart of quantum error correction — that you can measure what went wrong without measuring the data itself. Todd also weighs in on the trade-offs between modalities when it comes to implementing error correction in hardware, and closes with a look at how far the field has come since the early nineties when quantum computing was just an idea.