Before Blockchains, There Was State Machine Replication
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DARPA had recognized that this was a serious problem, the problem of malicious attacks, and was looking for research in that area. I had a student, Miguel Castro. He came to me and he said, why don't we see whether we can figure out a way to do replication that handles these malicious attacks? And that seemed like a great idea. The problem, if the primary failed, the primary that was running the protocol, the whole thing came to a crashing halt. We came up with a protocol that if the primary seemed to not be doing its job, the backups then carried out another protocol in which a different repl
Someone who loves computer science, loves research, wants to do important work, wants to have an impact, What would you suggest as kind of a mindset, as an approach?
Computer science is in a very strange place right now with the advent of AI. I think that as far as research is concerned
As part of our summer feed drop series, we're sharing another episode from the A16z Crypto Show. Every blockchain today relies on replication techniques first developed in the 1980s, years before anyone imagined cryptocurrencies. In this episode, Tim Ruffgarten and Itay Abraham speak with Turing Award winner Barbara Liskov, whose pioneering work on distributed systems, state machine replication, and practical Byzantine fault tolerance laid the foundation for many of today's blockchain protocols. Whether you're new to crypto or already building in the space, this conversation offers a deeper un
Hi, everyone, and welcome to First Principles, a series by the team at a sixteen z crypto. I'm Tim Ruffgarden. I'm the head of research at a sixteen z crypto. And today, we're exploring a core challenge in distributed computing. How can a system remain reliable when some of its parts fail or behave maliciously? In this episode, we're going to speak with the Turing Award winning computer scientist whose work helped answer this question: Doctor. Barbara Liscoff. She's famous for many things, but today we're going focus on her work that laid the foundations for modern blockchain systems. For exam
So, what happened was I had finished working on Clue, which was the programming language that, I developed with my group to provide access to data abstraction as a way of building programs. And I had thought a little bit about maybe starting a company to market the language, but I realized that, I was much more interested in research. And I also thought that I had sort of, done as much programming language research as I had anything interesting to do at that point. And I started looking around, and I read, a paper by Bob Kahn in which he talked about the dream of distributed computing and how
Wow. Fantastic.
And it was a great, yeah, great move.
Wow. It was great for computer science that that happened. No doubt about it. I'm curious, did it feel like a pivot at the time, like you were really changing your research field? And maybe a related question would be, you know, how much did sort of the the mindset and the approach to abstraction that you developed during your career, how much did that port over versus how how much did you need to really have a new sort of toolbox for working on those problems?
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