What’s Next for CPUs, GPUs, & Quantum | Alessandro Curioni & Sarah Sheldon

Listen to full episode:

Summary: This year-end episode brings together Anant, Ed, Alessandro Curioni, and Sarah Sheldon to unpack two big shifts: whether scaling laws are hitting a wall and why coding assistants look like the first true killer app for agentic AI. The conversation then moves into quantum computing, focusing on how quantum, AI, CPU, and GPU systems may work together rather than compete.

The guests make the case that quantum is not just a distant accelerator, but a new computing paradigm already influencing software design, algorithm discovery, and hybrid workflows. They also show where quantum could matter sooner than expected, from chemistry and materials science to optimization, trading, and differential equations.

Chapters:

00:00 — Welcome & why AI-quantum crossover matters

02:48 — Scaling laws, GPU brute force, coding as first killer app

12:03 — Why AI, CPUs, GPUs, and quantum belong in one conversation

14:03 — Quantum explained: new math, new way to represent information

20:35 — CPU-centric to GPU-centric to quantum-centric system design

23:49 — Hybrid workflows, compute routing, quantum in chemistry/materials

29:29 — AI for quantum: circuit mapping, transpilers, tuning parameters

33:22 — The developer journey: learning quantum, Qiskit, why domain experts matter

42:51 — Optimization: logistics, scheduling, portfolio management

44:02 — HSBC trading, quantum ML, differential equations

46:32 — The algorithm layer's real payoff: 30% fill-probability gain

48:25 — Closing thoughts + next episode preview

Sound Bites:

"Coding assistants is the first killer app."

"Looking at quantum only as the next accelerator is a mistake."

"The revolution is happening now while we are speaking."