Episodes

  • Quantum Workforce, Sensing, and the Long Game of Operationalization with Isabella Martinez

    Quantum Workforce, Sensing, and the Long Game of Operationalization with Isabella Martinez
    Oct 12 2026
    Isabella Martinez sits at an unusual intersection in the quantum ecosystem: she's not primarily a hardware researcher or an algorithm theorist, but a practitioner who has to make quantum work in operational environments — for customers who have real missions, real constraints, and very little patience for technology that can't be deployed. Her team at Booz Allen spans quantum computing, quantum sensing, and post-quantum cryptography, which means she's watching all three of the field's major near-term vectors simultaneously.This conversation was recorded at Quantum World Congress 2026, and it reflects the mood of that moment: sensing is on the cusp of real deployment, PQC migration is being driven by policy urgency, and quantum computing is still asking the question of when — but the "when" is getting more specific. If you work in quantum and care about how the technology actually crosses the gap from lab to mission, this episode is for you. It's also a genuinely useful listen for anyone thinking about quantum careers, workforce development, or how to build teams that can navigate a technology that doesn't yet have a playbook.What We Get IntoWhy Isabella's biomedical engineering capstone — not a physics class — shaped her entire approach to quantum: The lesson wasn't about building a better device; it was about why a life-saving tool sat unused because no one had time to get trained on it.The four-stage commercialization arc she uses to frame quantum maturity: Solve for physics, then engineering, then business case, then operationalization — and why that last step is the one the field talks about least.What quantum sensing deployment actually looks like right now: Including a vivid example of a quantum PNT sensor that "can't get wet" and what happens when you try to put it in a waterproof box without destroying its precision advantage.Why quantum sensing and quantum computing will diverge in their adoption paths: A drone operator doesn't need to know their navigation data is quantum-derived. A quantum computing user, at least for now, probably does — and that changes everything about how you design for adoption.How Booz Allen's team discovered the wrong part of a drug discovery workflow was being targeted for quantum speedup: A computational biologist and chemist sat down with the physics team and revealed that the step everyone assumed was the bottleneck wasn't the bottleneck at all.Why Isabella actively recruits people with criminology degrees, economics backgrounds, and education startup experience onto a quantum team: And why she's more worried about the rise of pure quantum-only graduate programs than she is about the talent shortage.The AI parallel that's shaping how enterprise customers think about quantum timing: Customers who watched AI capabilities leap unexpectedly are now asking "when" instead of "what" — but they're also more willing to wait for the right moment rather than jump in early.Her honest read on NISQ-era value: Real scientific output is happening on today's devices, but the early 2030s are where she expects the first commercially meaningful fault-tolerant results to appear.What the quantum community risks losing as the field matures: The collaborative, cross-disciplinary spirit that has defined the early era — and why she thinks that spirit is actually a competitive asset worth protecting.Resources & LinksGuest & OrganizationIsabella Bello Martinez — InformationWeek Author Page — Bio and links to her published articles on quantum talent and PQC for enterprise audiences.Booz Allen Quantum Sciences & Technologies Capability Sheet — Overview of Booz Allen's quantum practice, where Isabella leads products and partnerships.Articles by Isabella Martinez"5 Steps for Implementing the New Post-Quantum Cryptography Standards" — InformationWeek — Her practical framework for organizational PQC migration, including the cryptographic inventory problem discussed in this episode."Leading in the Race for Quantum Talent" — InformationWeek — Her argument for building quantum literacy at every organizational level, not just hiring PhDs — a theme central to this conversation."Can Quantum Supercharge AI?" — Velocity by Booz Allen — Co-authored piece on quantum machine learning applications in defense, health, and intelligence missions.Context & Policy"Post-Quantum Cryptography, Explained" — Booz Allen Hamilton — Booz Allen explainer co-authored by Isabella's team; useful background on the PQC migration landscape she references.NIST NCCoE — PQC Migration FAQ — Authoritative federal policy context, including algorithm finalization and binding federal deadlines."Booz Allen Wins Air Force Quantum Research Contract" — ExecutiveBiz — The $25.3M AFRL contract for quantum R&D through 2031 that frames Booz Allen's current federal quantum posture."Booz Allen Backs the Search for Quantum's Next Breakout Company" — The Quantum Insider — Booz Allen as presenting ...
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    38 mins
  • Superconducting Qubits, STAR Architecture, and Diamond-Spin Qubits with Dr. Shintaro Sato

    Superconducting Qubits, STAR Architecture, and Diamond-Spin Qubits with Dr. Shintaro Sato
    Oct 5 2026
    Dr. Shintaro Sato is a Fellow and Head of the Quantum Laboratory at Fujitsu Research, and Deputy Director of the RIKEN RQC-Fujitsu Collaboration Centre. He oversees Fujitsu's entire quantum effort — from device fabrication through error correction architecture, software, and application research — and has been building toward commercial quantum systems since Fujitsu began its serious quantum R&D push around 2020. With over 164 publications spanning graphene nanoelectronics, superconducting qubit design, and fault-tolerant architectures, he brings both deep technical credibility and a rare full-stack perspective.This conversation is timely because two significant developments converged almost simultaneously just before recording: Fujitsu announced a tin-vacancy (SnV) diamond-spin prototype developed with TU Delft and QuTech, and began testing its STAR error-correction architecture on neutral-atom hardware with startup Yaqumo — an explicit signal that Fujitsu is betting on hardware-agnostic software layers even as it races to scale its own superconducting devices. Listeners who follow quantum hardware roadmaps, fault-tolerant computing, or Japan's national quantum strategy will find this episode unusually specific and candid.What We Get IntoHow Fujitsu actually fabricates its superconducting chips — Sato explains how the team adapted Nakamura-sensei's original RIKEN designs, developed their own Josephson junction uniformity techniques, and built a research fab capability from scratch rather than licensing finished devices.Why packaging is the hardest problem at 1,000+ qubits — not the qubits themselves, but the superconducting wiring, chip-to-chip interconnects, interposers, and the sheer number of control lines running from room temperature to millikelvin. Sato is candid that his engineers "don't want to do it anymore."What STAR architecture actually does — it's not a new error-correction code; it operates at the logical gate layer above the surface code, replacing the notoriously expensive T gate with phase-rotation gates and selectively reintroducing T gates only when rotation angles would otherwise accumulate too much error. Version 3 achieves roughly a 10x accuracy improvement over version 2 for the same physical qubit count.Why STAR is hardware-agnostic — because it operates at the logical operation layer rather than the physical error-correction layer, it can in principle run on any hardware modality. Fujitsu has now begun testing it on Yaqumo's neutral-atom platform, and Sato mentions QuEra has also demonstrated STAR independently.What tin-vacancy (SnV) diamond-spin qubits are actually for — not a replacement for superconducting qubits, but a photonic interconnect technology. SnV centers emit photons that can carry quantum information between modules, potentially linking separate dilution refrigerators — a transduction approach that sidesteps one of the hardest problems in scaling superconducting systems.The speed mismatch problem in hybrid architectures — superconducting qubits operate at gigahertz speeds; nuclear spins in diamond-spin systems operate at kilohertz. Sato acknowledges this directly and frames it as an architectural challenge analogous to CPU-memory hierarchies in classical computing.What Fujitsu's open-source strategy looks like in practice — the collaboration with Osaka University on Project Octopus, which produced an open-source full-stack control and software platform, is now being adopted as part of Fujitsu's commercial offering.What 2030 actually looks like — Sato is measured: a 10,000-qubit machine will still be a "very small scale logical quantum computer," most useful for quantum chemistry in hybrid HPC+quantum workflows. Revolutionary applications will come incrementally, not all at once.The long-term vision — Sato's stated dream is a quantum computer small enough to fit in a smartphone, which he acknowledges requires entirely different physics than anything on today's roadmap.Resources & LinksGuest & OrganizationDr. Shintaro Sato — Fujitsu Quantum Day Profile — Fujitsu's own bio page covering Sato's dual role at Fujitsu Research and RIKEN RQC-Fujitsu Collaboration Centre.Shintaro Sato — ResearchGate Profile — Full publication list (164 papers, 3,096 citations); useful for tracing his path from graphene nanoelectronics to quantum architecture.Interview with Shintaro Sato — QuTech — Sato discusses the NV-center and diamond-spin collaboration with QuTech and the vision for quantum-as-a-service.Hardware Roadmap & STAR ArchitectureFujitsu Quantum Day 2026 — Sato Presentation Slides (PDF) — Primary-source slides showing the full hardware roadmap: 64 → 256 → 1,024 → 10,000+ qubits with STAR architecture milestones.Fujitsu Officially Starts 10,000+ Qubit Development — Fujitsu Press Release (Aug 2025) — Official announcement of the early-FTQC 10,000-qubit program targeting FY2030.STAR Architecture Overview — Fujitsu Global —...
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    41 mins
  • Quantum Venture Investing from the Lab to the Market with Marie Lepske

    Quantum Venture Investing from the Lab to the Market with Marie Lepske
    Sep 28 2026
    Marie Lepske brings a combination that's genuinely rare in venture: a background in applied mathematics and physics, early experience covering quantum at Runa Capital before most generalist funds knew the field existed, and now a GP seat at Constructor Capital, which closed a $110M Fund I in February 2026 with more than half its capital directed toward next-generation computing including quantum. She backed Qnami at Runa — a quantum sensing company acquired by Quantum Design in June 2026, one of the few clean sensing exits the field has produced — and Constructor's portfolio includes QuEra, which raised over $230M in a round led by Google Quantum AI and SoftBank.The conversation matters now because the quantum investment landscape is genuinely changing. SPAC activity, mega-rounds from hyperscalers, and rising valuations are pulling in non-specialist capital at the same time that the science is getting harder to evaluate from the outside. Lepske is one of the people who has to navigate that tension every day, and she's willing to name the failure modes.Founders building quantum or deep-tech companies, investors trying to understand where specialist and generalist capital intersect, and technically curious listeners who want to understand how the business side of quantum actually works will all find this episode useful.What We Get IntoWhy technical training matters at the earliest stages — and what it actually buys you when a founding team's only asset is a laboratory and an optical table, before there's even a legal entityHow the specialist-versus-generalist divide is evolving — Lepske's 2022 argument that early-stage quantum would stay specialist territory, and how she reads the arrival of Google, SoftBank, and NVIDIA in QuEra's cap tableThe due diligence framework for pre-product science startups — team provenance, patent landscape, IP legal review, and how Constructor uses its scientific advisory board to validate founders they can't fully assess internallyWhat a "no" looks like — the specific signals that make Constructor wait rather than invest, including teams with strong science but no credible path to market and IP positions that are already crowdedThe Qnami exit and what it reveals about quantum sensing — why sensing applications are currently concentrated in R&D markets, which verticals Lepske thinks will break out first, and why sensing competes with computing for buyer attentionThe SPAC problem — why the wave of quantum public listings concerns her, and why evaluating roadmap credibility requires the kind of deep familiarity that takes years to buildHow Constructor supports portfolio companies beyond capital — executive hiring, software development guidance, co-investor introductions, and the limits of that hands-on modelAI and quantum as parallel tracks — why she doesn't see AI as cannibalizing quantum talent or capital, and where she thinks the two fields will eventually convergeResources & LinksGuest & FundMarie Lepske — LinkedIn — Primary professional profile; includes keynote highlights and 2026 speaking engagementsConstructor Capital — Official Website — Fund homepage with portfolio listings, team bios, and investment thesis across DeepTech, Software Tech, and Knowledge TechConstructor Capital Fund I Close (Tech.eu, Feb 2026) — Coverage of the $110M close, check sizes ($1–10M, select up to $15M), and the university sourcing networkPortfolio Companies ReferencedQuEra — $230M+ Financing Round Announcement — The round led by Google Quantum AI and SoftBank Vision Fund 2, with NVIDIA's NVentures participatingQnami Acquisition by Quantum Design (The Quantum Insider, June 2026) — The sensing exit discussed in the episode; context on what a quantum sensing acquisition looks likeBackground ReadingQuantum Computing Report — "Venture Capital Trends in Quantum Technologies" (Runa Capital, 2022) — Lepske's co-authored market analysis, the source of her "specialist VC" thesis discussed in the episodeConstructor Capital — "Quantum Investing Playbook" (Nov 2025) — Her Paris keynote on making successful quantum investments; source of the valuation figures cited in the conversationEntangled Future — Quantum Computing Funding & Investment Landscape 2026 — Context on the $4.9B private VC figure for 2025 and the broader public commitment landscapeRecent Constructor NewsConstructor Start Demo Day Finalists (The Quantum Insider, Sept 2026) — Quantum startups among the 16 finalists announced one week before this recordingKey Quotes & InsightsOn what early-stage diligence actually looks like: > "They have only laboratory, and they have optical table which they want to show to you and you should understand if they have some interesting and useful patents or they can file them during the next one to two years."On where specialist and generalist capital divide: > "These bigger players, they're coming later. They're coming when we already investigated that this ...
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    41 mins
  • Rational Quantum Mechanics and the Qubit Ceiling with Tim Palmer

    Rational Quantum Mechanics and the Qubit Ceiling with Tim Palmer
    Sep 21 2026
    Tim Palmer is not a quantum computing skeptic from the outside. He is a Fellow of the Royal Society, a CBE, an IPCC lead author, and the inventor of probabilistic ensemble forecasting — techniques now used in every major weather prediction center on Earth. He did his PhD in general relativity under Roger Penrose. When someone with that profile publishes a peer-reviewed paper in PNAS arguing that the entire fault-tolerant quantum computing roadmap may rest on a mathematical assumption that is subtly and profoundly wrong, it is worth paying close attention. The timing matters. The quantum computing industry is spending billions on the assumption that standard quantum mechanics scales indefinitely — that if you can build enough error-corrected qubits, Shor's algorithm will eventually factor RSA-2048. Palmer's RaQM framework, reviewed by leading quantum foundations researchers including Lucien Hardy and Nicolas Gisin, makes a concrete, falsifiable prediction that this assumption will fail somewhere between 200 and 1,000 error-corrected qubits. That falsification window is opening right now. This episode is for anyone who cares about the foundations of quantum mechanics, the long-term viability of fault-tolerant quantum computing, or the rare pleasure of watching a serious scientist put a real stake in the ground. What We Get Into Why Palmer left general relativity and came back to quantum foundations decades later — the conceptual thread connecting chaos theory, climate forecasting, and the geometry of quantum state spaceWhat Rational Quantum Mechanics actually proposes — specifically, why Palmer argues that Hilbert space should be defined over rational numbers rather than the full continuum of complex numbers, and what that means physicallyThe information-theoretic argument for a qubit ceiling — why, in RaQM, the information content of n entangled qubits grows linearly with n rather than exponentially, and why that creates a hard conflict with the quantum Fourier transform above a few hundred qubitsWhy the 2022 Nobel Prize did not prove non-locality — Palmer's careful distinction between "Bell's inequality is violated" (experimentally established) and "the world is non-local" (an interpretation), and why that distinction matters enormouslyHow gravity enters the picture — Palmer's argument, drawing on Penrose-style thinking, that gravity is the physical mechanism responsible for discretizing Hilbert space, and how that determines the numerical qubit ceilingWhy the ceiling is technology-dependent but bounded absolutely — how Palmer estimates ~400 qubits for current photonic technology and argues that no technology, however exotic, can push the limit above ~1,000What happens to Shor's algorithm specifically — why the quantum Fourier transform is the precise point of failure, and what that means for RSA encryption and the post-quantum cryptography transitionThe optimistic read on a potentially negative result — Palmer's argument that a fundamental discovery about quantum mechanics, even one that limits quantum computing, could open doors we cannot yet imagine, in the same way general relativity eventually gave us GPS Resources & Links Guest Tim Palmer — Oxford Department of Physics — Full publication list, including the RaQM paper and prior quantum foundations workRoyal Society Fellow Profile: Professor Tim Palmer CBE FRS — Official Fellow profile covering Palmer's career from ensemble forecasting to quantum foundationsOxford Quantum Institute: Tim Palmer — Confirms Palmer's affiliation with OQI Papers & Articles "Rational Quantum Mechanics: Testing Quantum Theory with Quantum Computers" — PNAS (March 2026) — The primary paper discussed in this episode; the full RaQM proposal with the qubit-ceiling predictionarXiv preprint: "Rational Quantum Mechanics: Testing Quantum Theory with Quantum Computers" (Feb 2026) — Full preprint version with acknowledgements and referencesarXiv preprint: "Solving the Mysteries of Quantum Mechanics: Why Nature Abhors a Continuum" (Feb 2026) — Companion paper laying out the philosophical and mathematical case for RaQM; good starting point for the conceptual argumentOxford Physics News: "Rational Quantum Mechanics — A New Theory of Quantum Physics" (March 17, 2026) — Oxford's official press release; accessible summary of RaQM and its implicationsIAI TV: "New Theory Argues Quantum Physics Must Abandon Irrational Numbers and the Continuum" (May 2026) — Palmer's own popular-audience explanation of RaQM; a good read before or after the episodeIAI TV: "Chaos Theory Eliminates Quantum Uncertainty" — Palmer's accessible argument that quantum uncertainty is epistemic rather than fundamentalThe Quantum Insider: "Is RSA Safe? New Study Argues Quantum Computers Face a Hard Ceiling" (March 2026) — Industry-facing coverage of RaQM's implications for cryptographyPostQuantum.com: "The 1,000-Qubit Ceiling That Probably Isn't" (April 2026) — Skeptical ...
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    47 mins
  • Classical Reversible Computing on Quantum Dots with Daniel Loss

    Classical Reversible Computing on Quantum Dots with Daniel Loss
    Sep 14 2026
    Daniel Loss is RDIA Chair Professor of Quantum Computing and Director of the Quantum Center at King Fahd University of Petroleum and Minerals in Saudi Arabia, where this work was done. He is also one of the most influential theorists in quantum computing. The 1997 Loss-DiVincenzo proposal — that electron spins in quantum dots could serve as qubits — now has more than 9,000 citations and is the conceptual foundation for the semiconductor spin-qubit platforms that Intel, HRL, Diraq, and a wave of European startups are actively building toward. In 2025, Loss was named a Clarivate Citation Laureate in Physics, a designation with a strong historical track record as a Nobel Prize predictor. The reason to listen now is that Loss has turned his attention to a question that predates quantum computing itself: can reversible, energy-efficient classical logic be physically realized? His 2026 paper argues that the spin-qubit hardware the field has spent decades developing is, almost incidentally, the ideal platform to do exactly that — and that the energy advantage over room-temperature CMOS could be so large it would matter enormously for AI inference workloads and data-center power budgets. This episode is for anyone following the spin-qubit roadmap, the energy crisis in classical computing, or the deeper question of what semiconductor quantum hardware is ultimately good for. What We Get Into Why reversible computing is having a moment now: The ideas of Landauer, Bennett, Fredkin, and Toffoli have been around since the early 1980s — Loss explains what changed experimentally that makes the proposal feel like engineering rather than philosophy.The core energy claim, unpacked: Loss walks through why a spin-qubit Toffoli gate operating near 4 Kelvin could cost roughly 10⁵ times less energy than its CMOS equivalent, even after accounting for refrigeration overhead — and where the accounting is still incomplete.What makes the computation classical and the hardware quantum: The gate uses coherent quantum dynamics internally, but inputs and outputs are classical spin states. No superposition is required between gate operations, which dramatically relaxes the error-correction burden.The iToffoli gate and why it works for classical logic: Loss describes how a target spin hopping between quantum dots, controlled by two neighboring spins, implements a universal reversible gate using only DC voltage pulses — no radio-frequency drives required.The Quantum Zeno trick for classical memory: Frequent projective measurement of a spin state can stabilize it against relaxation, turning one of quantum computing's central headaches into a feature for classical storage.Why AI inference is the natural first application: Error tolerance, parallelizability, and the absence of a need for new algorithms make AI inference workloads a compelling early target — and Loss argues this de-risks the spin-qubit enterprise regardless of whether fault-tolerant quantum computing arrives on schedule.The dual-use platform argument: The same germanium/silicon quantum-dot array could, in principle, run quantum algorithms when superposition is useful and classical reversible logic when it is not — a flexibility that changes the economic calculus for building the hardware.What the experimental community needs to do next: Loss describes the first falsifiable tests — a three-spin iToffoli truth table, energy budget measurements, and a five-dot reversible adder — and names the groups best positioned to run them.How the brain comparison reframes the stakes: Loss notes that his energy estimates put spin-qubit classical computing roughly four orders of magnitude below the energy cost of a biological synapse, which has implications for how we think about the physical limits of AI. Resources & Links Guest & Lab Daniel Loss' profile at King Fahd University of Petroleum and MineralsDaniel Loss — University of Basel, Condensed Matter Theory & Quantum Computing Group — Loss's lab page; lists current research areas, group members, and leadership roles including NCCR SPIN.Daniel Loss — Wikipedia — Comprehensive biographical overview, career history, and awards list for listeners who want background before or after listening. Papers & Articles Classical Reversible Computation by Quantum Coherence — arXiv:2607.06219v3 (2026) — The central paper discussed in this episode; v3 adds a reversible-adder blueprint, control-electronics energy analysis, and optimized pulse sequences.Loss-DiVincenzo: Quantum Computation with Quantum Dots — Physical Review A (1998) — The foundational 1997/1998 proposal that started the spin-qubit field; cited more than 9,000 times and the direct ancestor of the hardware Loss now proposes for classical reversible computing.Long-Range Crossed Andreev Reflection in a Topological Insulator Nanowire — Nature Physics (2025) — A 2025 result from the Loss group with implications for topological quantum computing, ...
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    49 mins
  • Quantum-Inspired AI and Tensor Network Compression with Román Orús

    Quantum-Inspired AI and Tensor Network Compression with Román Orús
    Sep 7 2026
    Román Orús is one of the rare physicists who built a foundational mathematical tool — tensor networks — and then watched it become the engine of a unicorn. His 2013 introduction to tensor networks has been cited over 2,000 times; his company, Multiverse Computing, just announced a $570 million Series C at a $1.7 billion pre-money valuation. That arc — from condensed matter theory to Europe's largest quantum software company — is worth understanding on its own terms. But what makes this conversation particularly timely is a May 2026 paper Orús co-authored demonstrating that individual layers of Meta's Llama 3.1 8B language model can be encoded as quantum circuits and executed on IBM's 156-qubit Quantum System Two while the model generates text. It's a proof of concept, not a product — but it's a real result, and Orús is honest about what it does and doesn't prove.This episode is for listeners who want a technically grounded, hype-free account of the quantum-AI intersection: what tensor networks actually are, why they keep getting rediscovered across different fields, where classical simulation of quantum systems genuinely competes with quantum hardware, and what it looks like to build a company at the boundary between those two worlds.Sponsor MessageThe Capital of Quantum is a people story. Built on a top-five quantum PhD program and 35-plus years of quantum research leadership. It's the billion-dollar initiative behind Discovery Center, launching this month with Microsoft, IQM, and Quantum Motion inside. That's why IonQ was born and is headquartered here, and why global companies keep choosing a spot minutes from Washington, D.C. This is where quantum is transforming the world. Come see it at the Quantum World Congress, September 23rd through 25th, College Park, Maryland. CapitalOfQuantum.com.What We Get IntoWhat tensor networks actually are — Orús explains the core idea without equations: tensors as the "DNA" of a quantum state, and how a network of them lets you see and quantify the internal correlations (entanglement) that matter versus the ones you can safely ignore.Why the same math keeps appearing in different fields — from condensed matter simulation to quantum computing simulation to machine learning, and why Orús sees that recurrence as a sign of something deep rather than a coincidence.How ChatGPT changed Multiverse's trajectory — the company was already applying tensor networks to machine learning before 2022; the emergence of large language models gave them a problem where the fit was obvious and the market was enormous.What "90–95% compression with minimal accuracy loss" actually means — Orús explains the overparameterization problem in current AI models and why he believes tensor networks address a genuine structural inefficiency, not just a tuning opportunity.The IBM kicked Ising model episode — Orús describes how his team rapidly produced a classical tensor network simulation of an experiment IBM had presented as evidence of quantum utility, and what that kind of competition between classical and quantum methods actually does for the field.The Cayley Unitary Adapter experiment — how Multiverse sliced individual layers out of Llama 3.1 8B, encoded them as quantum circuits, ran them on a 156-qubit IBM processor, and achieved a 1.4% perplexity improvement — and why Orús argues the improvement-per-parameter ratio is the number that matters, not the headline percentage.Why edge deployment is the real commercial driver — drones, satellites, vehicles, and industrial devices that cannot rely on cloud connectivity are the market pulling Multiverse toward smaller, more efficient models, not just benchmark competition with frontier labs.How Orús thinks about Multiverse's identity — he calls it a "quantum AI company," not a quantum company or an AI company, and explains what that distinction means for how they allocate research effort and where they expect to be when fault-tolerant quantum hardware matures.What he'd tell a PhD student today — a genuinely honest answer about the trade-offs between academic research and deep-tech industry, from someone who has lived both simultaneously.Resources & LinksGuest & CompanyRomán Orús — Personal Site — Lists talks, reviews, affiliations, and awards including the 2024 Physics, Innovation and Technology Prize from the Royal Spanish Society of Physics.Multiverse Computing — Official Website — Home page for CompactifAI, Singularity, and Multiverse's full product portfolio.Papers & Articles Discussed in This EpisodearXiv 2605.05914 — "Quantum-enhanced Large Language Models on Quantum Hardware via Cayley Unitary Adapters" (May 2026) — The paper at the center of the episode: Llama 3.1 8B layers running on IBM's 156-qubit Quantum System Two. Start here if you want the technical details behind the quantum-in-an-LLM result.Multiverse Computing — "Talking to a Quantum Computer" (May 2026) — The accessible ...
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    41 mins
  • Quantum Workforce Intelligence from qubitsok.com with Piotr Lewandowski

    Quantum Workforce Intelligence from qubitsok.com with Piotr Lewandowski
    Aug 31 2026
    Piotr Lewandowski is a software engineer based in Poland who, as a side project, has built something that no well-funded research institute has: a continuously updated, ontology-tagged intelligence platform that ingests the entire quant-ph archive, tracks thousands of open quantum roles across hundreds of companies, parses patents and grants and open-source repositories, and links all of it to individual researcher profiles. He is not a tenured academic or a hardware engineer. He is an independent data practitioner, and that outsider position gives him a vantage point on the quantum workforce that insiders rarely have — or rarely share.This conversation matters now because the quantum industry is simultaneously claiming a generational workforce opportunity and struggling to fill highly specialized roles. Lewandowski's data offers a rare ground-truth check on both claims. If you work in quantum hiring, research, policy, or investment — or if you're a student trying to understand what the field actually looks like from the outside — this episode will give you a more honest picture than almost anything else currently available.What We Get IntoHow qubitsok's 500-tag ontology was built from scratch — why Lewandowski chose a tree-structured, parent-child tag system rather than relying on existing academic metadata infrastructure, and how it steers AI toward the most specific and useful classification rather than broad category labels.What the full quant-ph corpus reveals about researcher mobility — which countries are gaining quantum talent (Germany and China are notable winners) and which are losing it (the US and Australia are among the top brain-drain sources), based on tracking affiliation changes over time in published papers.The rising share of industry authorship in quantum research — industry-affiliated authors have grown from roughly 3.4% of quant-ph papers in 2005 to nearly 14% in 2026, and what that structural shift might mean for what gets published — and what doesn't.Why the platform tracks open-source contributions alongside papers — when researchers join industry and their publication rate drops, their open-source activity becomes a meaningful proxy for continued technical engagement, and qubitsok indexes both.The "qubie" talent-matching tool Lewandowski is building — rather than keyword overlap, qubie dispatches sub-agents to extract specific, claim-level evidence from a researcher's papers, dissertations, and other public writing, then returns a structured profile and interview guide for each candidate.Why sourcing quantum talent is a fundamentally different problem than general tech recruiting — the evidence of what a quantum researcher can actually do is largely public and published, but no one has had the infrastructure to read it systematically at scale until now.The two product directions Lewandowski is weighing — analytics and competitive intelligence for investors and companies versus talent matching for quantum hiring — and why he's currently prioritizing the latter.What it means to build a field-level intelligence platform as an outsider — Lewandowski is neither employed by a quantum company nor affiliated with a university, and that independence shapes both what he can see and what he can say.Resources & LinksGuest Linksqubitsok.com — The platform itself: quantum job board, daily arXiv paper digest with semantic tagging, and researcher collaboration search. All free for researchers and job seekers.qubitsok.com/collaborate — Search for quantum researchers by expertise, ontology tag, and affiliation — useful for finding collaborators or co-authors.Piotr Lewandowski on LinkedIn — The best place to reach him directly, especially if you're a company interested in early access to the qubie talent-matching product.Piotr Lewandowski on YouTube — His channel covering quantum computing job market analysis and platform updates.Papers & ReportsEPJ Quantum Technology — "The quantum technology job market: data-driven analysis of 3,641 job posts" (March 2026) — Lewandowski's peer-reviewed paper on the quantum job market, the most rigorous published treatment of the data underlying qubitsok.2026 Quantum Computing Salary Report — Analysis of 194 salary data points drawn from real job postings; a useful benchmark for researchers and hiring managers alike.Fastest-Growing Quantum Skills 2026 — Lewandowski's analysis of 1,212 quantum jobs and 14,975 papers identifying which technical skills are accelerating and which are declining in the labor market.Tools & Platformsqubitsok.com/jobs — Live quantum job listings, filtered by the platform's 500-tag ontology.qubitsok.com/region/europe — Live European quantum jobs market data, useful context for the EU talent and salary discussion.qubitsok.com/hire — Information for companies looking to use qubitsok's candidate database and, soon, the qubie matching tool.RecognitionDr. Bob Sutor's "Quantum Follow Friday" (...
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    46 mins
  • Quantum Risk, Readiness, and the Enterprise Boardroom with Richard Entrup

    Quantum Risk, Readiness, and the Enterprise Boardroom with Richard Entrup
    Aug 24 2026
    Richard Entrup is unusual in quantum circles: he's not a physicist, and he doesn't pretend to be. He spent decades as a CIO, CTO, CDO, and CISO at organizations including Verizon, Christie's, Tiffany & Company, MoMA, Disney/ABC, and Time Warner before joining KPMG to lead its Emerging Solutions practice. That background — deep operational experience on the client side — shapes everything about how he thinks about quantum. He's not selling a hardware roadmap; he's thinking about what it actually takes to get a large, complex organization to change its cryptographic infrastructure before a threat materializes.The conversation matters now because the signals are accelerating. NIST has finalized its first post-quantum cryptography standards, executive orders in the US are pushing federal agencies toward PQC migration, and the algorithmic efficiency gains that reduce the qubit threshold for breaking RSA-2048 keep coming. Listeners who work in enterprise technology, cybersecurity, or quantum strategy — or who advise organizations that do — will find Entrup's practitioner perspective a useful counterweight to the more hardware-focused conversations that dominate the field.What We Get IntoWhy Q-Day's exact date is the wrong question — and why the more important issue is how long it will take enterprises to even inventory their cryptographic exposure, let alone remediate itThe scale of the cryptographic migration problem, including why a single laptop may contain hundreds of individual cryptographic components and why upstream/downstream API dependencies make this a supply-chain-wide challenge, not just an internal IT projectWhy "harvest now, decrypt later" creates urgency today, regardless of when fault-tolerant quantum computers arrive — and how compliance and regulatory timelines interact with that threat modelWhat crypto agility actually means in practice — moving from a "set it and forget it" cryptographic posture to a dynamic, continuously monitored framework, including the pressure SSL certificate renewal windows are already creatingHow KPMG built its PQC practice, incubated it within the firm, and handed it off to the cybersecurity advisory team as a core service offeringThe "good quantum" side of the ledger — how KPMG's emerging research function is approaching quantum computing as a source of competitive advantage, not just risk, and what sectors are furthest along in exploring itThe AI-quantum convergence, including Entrup's observation that AI is already being used to read and crack code — and what that means for the urgency of cryptographic modernizationWhy the enterprise quantum opportunity still has a long tail, and how the current moment compares to the early infrastructure phase of the internet — when everyone was talking about TCP/IP and DNS, not Uber or NetflixResources & LinksGuest & OrganizationRichard Entrup — Worth Magazine Profile — Career arc from CIO/CISO roles at major global brands to KPMG's Emerging Solutions practiceKPMG Quantum Dawn (2025) — KPMG's enterprise quantum readiness hub, introducing the Q-PREP framework and PQC implementation services, with Entrup as named leadKPMG Quantum homepageReports & ResearchKPMG — "The Quantum Threat Is No Longer Theoretical" (2026) — The threat brief discussed in this episode, charting the rapid decline in qubits needed to crack RSA-2048 and urging immediate PQC migrationKPMG — "From Theory to Impact: Real-World Results in Quantum Machine Learning" (2026) — KPMG's joint report with IBM and Kipu Quantum on measurable quantum ML results on real hardwareKPMG — "Prepare Now for Quantum Cyber Risk" — Board Leadership Article (2026) — C-suite and board-level guidance on integrating quantum risk into enterprise oversightarXiv — "Quantum-enhanced satellite image classification" (2026) — The underlying research paper behind the KPMG/IBM/Kipu Quantum ML resultsEcosystem & EventsChicago Quantum Exchange — KPMG Joins CQE (October 2024) — Announcement of KPMG's formal CQE membership, referenced in the episode as part of the firm's ecosystem-building strategyKPMG 2026 Quantum Consortium — The inaugural KPMG Quantum Consortium event (March 2026, Orlando) discussed in the episodeIndependent CoverageQuantum Computing Report — KPMG joins Chicago Quantum Exchange (2024) — Independent coverage of KPMG's CQE partnership and enterprise quantum strategyQuantum Zeitgeist — Kipu Quantum satellite imagery coverage (Feb 2026) — Independent analysis of the KPMG/IBM/Kipu hybrid QML resultsKey Quotes & Insights> "It's not if but when. And it could be five years, could be three years, could be ten years. The fact is organizations are not gonna be ready. And that's the scary part." — Richard Entrup on Q-Day> "This is not just the CISO. This is gonna be the software engineering app dev guys. This is gonna be all your partners, upstream and downstream, who have to also be compliant — because if you change your crypto...
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    36 mins