Entangled Things

In Episode 154, Jonny Olson, Vice President of Strategy and Operations at Zapata Quantum, joins Patrick and Ciprian. Jonny is a physicist and a quantum algorithm IP attorney, and he opens with the story of Zapata’s early sales calls, where the first questions were always what quantum is, what it can do for you, and when it will matter. The team look at why the first wave of near term quantum solutions fell short against fast improving classical computing, and what DARPA’s Quantum Benchmarking program found when it tried to prove economic value. Ten use cases made it to full resource estimates, and none showed a clear economic win. From there the conversation covers how qubit count, runtime, and scaling shape which modalities fit which problems, why optimization claims are so hard to prove, and how enterprises are following fast while they wait. Jonny explains Zapata’s goal of cutting the cost of validating a quantum use case by a factor of a hundred, and how AI agents and formal verification could close the gaps between tools and experts.

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.network
Quantum Doomsday Clock: quantumdoomclock.com