AI Summary
5 min readIn December 2024, Google published a paper showing that the resource estimates for breaking standard encryption on a quantum computer had dropped dramatically—from millions of qubits to roughly 10,000. That number is small enough that enterprise customers can already order such a system for under $100 million. For the national security community, this qualifies as a "technical surprise": a credible threat that arrived years ahead of schedule.
Prineha Narang, a UCLA professor, government advisor, and venture capitalist, explains that this shift came from simultaneous advances on multiple fronts. New quantum error-correcting codes called QLDPC (quantum low-density parity check) proved far more efficient than the older surface codes. Hardware teams working with neutral atoms, trapped ions, and silicon spin qubits all improved qubit quality and reconfigurability. When the Defense Advanced Research Projects Agency (DARPA) tracked all these vectors through its Quantum Benchmarking Initiative, the combined picture moved from yellow to green. The implication is not immediate panic, Narang says, but a clear signal that migration to post-quantum cryptography (PQC) should move up the to-do list. The National Institute of Standards and Technology (NIST) is already validating a suite of replacement algorithms, though the process remains a cat-and-mouse game: someone proposes a candidate, a
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What you'll learn
- 1 (00:00) **Introduction and Guest Background** - Host Ashley Vance introduces Prineha Narang, a UCLA professor, quantum policy advisor, and venture capitalist, and sets up the episode's scope.
- 2 (03:21) **Prineha's Dual Passions: Physics and Athletics** - Prineha describes her competitive drive in both physics and running, and how her early desire to be a professional athlete intersected with her academic path.
- 3 (08:16) **Current Athletic Ambitions** - Prineha discusses her current marathon training, her goal to qualify for the Olympic trials, and her recent mountaineering adventure in Ecuador.
- 4 (13:45) **The Path to Quantum: From Internship to Grad School** - Prineha traces her journey from an undergraduate internship at IBM to realizing she needed quantum mechanics to model materials, which led her to Caltech.
- 5 (21:19) **Developing Non-Equilibrium Frameworks and Scalable Code** - Prineha explains her focus on simulating "non-equilibrium" quantum matter and the challenge of turning equations into efficient code that runs on supercomputers.
- 6 (25:59) **The Drive: Understanding Matter vs. Quantum's Promise** - Prineha clarifies that her motivation has always been to leverage new devices (like GPUs and quantum computers) to solve physics problems, rather than being driven by the grand promise of quantum computing.
- 7 (31:35) **The Shift: AI, GPUs, and Quantum's New Role** - The conversation turns to how the rise of AI and GPUs has changed the perception of quantum, moving it from a competitor to a complementary part of "next-gen compute."
+ Full timestamped outline available in the app
Show Notes
Prineha Narang is one of the rising stars of science and the field of quantum technology.
She earned her PhD in applied physics at Caltech, taught materials science at Harvard and now has her own lab at UCLA. The lab focuses on quantum materials, non-equilibrium dynamics, photonics, quantum information science and other easily digestible areas. Beyond her academic career, Narang is a science advisor to the government and a venture capitalist at DCVC.
As you might imagine, we get into quantum computing and quantum technology in this episode. Quantum vs. AI, the US vs. China, when quantum tech will break encryption, quantum sensing and whether or not quantum technology actually has a bright future. The quantum sensing portion of the chat was all new to me and rather astonishing.
Since Narang is also a competitive runner and mountaineer, we provide some top tips on gear because that is just the kind of all-purpose podcast that we deliver.
And, if you can’t get enough quantum computing, come check out our video episode on PsiQuantum building the largest quantum machine in history.
Enjoy!
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Narang Lab at UCLA:
https://naranglab.ucla.edu
DCVC:
https://www.dcvc.com
Oratomic (the Caltech neutral atom spinout):
https://www.oratomic.com
Atom Computing:
https://atom-computing.com
Mesa Quantum:
https://mesaquantum.com
Google's work on the cost of quantum factoring: More from this podcast