When it comes to spycraft — or rather, “tradecraft,” as they say in the biz — what do the movies get right, and what do they get wrong? In this episode of the a16z Podcast, Michael Morell — former Deputy Director and twice-Acting Director of the CIA — talks all things tradecraft and tech with a16z partners Matt Spence and Hanne Tidnam. What it is that the CIA really does? Is it a) James Bond, b) Maxwell Smart, c) Jason Bourne, or d) none of the above? For starters, it’s not at all about predicting what will happen — it’s figuring out what you need to know now to make the right decisions, asking the right questions, and reducing uncertainty. But that’s a tall order when you’re in the Situation Room advising the President — because there’s no such thing as zero uncertainty. So what makes the difference between a good analyst and a great one? How does technology affect tradecraft? And where do human spies come in? This podcast was recorded as part of our (now-annual!) podcast road trip, in conjunction with the a16z Tech Policy Summit, in Washington, D.C.

Moore's Law -- putting more and more transistors on a chip -- accelerated the computing industry by so many orders of magnitude, it has (and continues to) achieve seemingly impossible feats. However, we're now resorting to brute-force hacks to keep pushing it beyond its limits and are getting closer to the point of diminishing returns (especially given costly manufacturing infrastructure). Yet this very dynamic is leading to "a Cambrian explosion" in computing capabilities… just look at what's happening today with GPUs, FPGAs, and neuromorphic chips. Through such continuing performance improvements and parallelization, classic computing continues to reshape the modern world. But we're so focused on making our computers do more that we're not talking enough about what classic computers can't do -- and that's to compute things the way nature does, which operates in quantum mechanics. So our smart machines are really quite dumb, argues Rigetti Computing founder and CEO Chad Rigetti; they're limited to human-made binary code vs. the natural reality of continuous variables. This in turn limits our ability to work on problems that classic computers can't solve, such as key applications in computational chemistry or large-scale optimization for machine learning and artificial intelligence. Which is where quantum computing comes in. But what is quantum computing, really -- beyond the history and the hype? And where are we in reaching the promise of practical quantum computers? (Hint: it will take a hybrid approach to get there.) Who are the players -- companies, countries, types of people/skills -- working on it, and how can a startup compete in this space? Finally, what will it take to get "the flywheel" of application development and discovery going? Part of the answer comes full circle to the same economic engine that drove previous computing advances, argues Chris Dixon; Moore's Law, after all, is more of an economic principle that combined the forces of capitalism, a critical mass of ideas, and people moving things forward by sheer will. Quantum computing is finally getting pulled into the same economic forces as well.