Building Better Systems

Galois, Joey Dodds, Shpat Morina

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TECHNOLOGY

Exploring tools and approaches that make us more effective engineers and make our systems safe and reliable. Join us for discussions on recent developments in topics such as best practices in reliability and security, applied formal methods, encryption, and safe and secure hardware.

09/08/2022

Episode #22: Eric Daimler — Guaranteeing the Integrity of Data Models with Category Theory

In this episode, we're joined by Eric Daimler, CEO & co-founder of Conexus AI, Inc, an MIT spin out. We discuss the Conexus software platform, which is built on top of breakthroughs in the mathematics of Category Theory, and how it guarantees the integrity of universal data models. Eric shares real-world examples of applying this approach to various complex industries, such as transportation and logistics, avionics, and energy. Listen to this episode wherever you listen to podcasts. Eric Daimler: https://www.linkedin.com/in/ericdaimler/ Joey Dodds: https://www.linkedin.com/in/joey-dodds-4b462a41/ Rob Dockins: https://galois.com/team/robert-dockins/ Galois, Inc.: https://galois.com/ Contact us: podcast@galois.com

38 min
10/06/2022

Episode #21: Nikhil Swamy — Fully In Bed With Dependent Types

Today we're joined by Nikhil Swamy, Senior Principal Researcher in the RiSE group at Microsoft Research. We are very excited to hear about what he's been working on. In particular, we're going discuss a language that he's co-created and continually develops called F* (pronounced F star). F* is a dependently typed language that you can both program and prove things about the programs that you write. We'll talk about what makes that language special and unique from other similar languages, as well as some of the applications of F*.

49 min
28/04/2022

Episode #20: Ankush Desai — P: The Modeling Language That Could

Joey and Shpat talk with Ankush Desai, a Senior Applied Scientist at AWS and one of the primary developers behind the P language. They dig into uses for P, bug finding, and what it takes for formal methods researchers to build useful tools for applied engineers.

46 min
14/04/2022

#19: Steve Weis — Security Shouldn't Be the Last Check Box

In this episode, we talk with Steve Weis, a Senior Staff Security Engineer at Databricks with extensive knowledge of security, cryptography, and software engineering. Steve shares his experience working for large companies like Google and Facebook and how their security needs differ from start-ups and companies trying to scale. He talks about why he thinks companies should share more about how they design their infrastructure and how they can develop a “security mindset” so even non-security-related roles can contribute to building secure systems.

42 min
09/03/2022

#18: Jordan Kyriakidis — Helping People Write More Useful Requirements

In episode #18, we chat with Jordan Kyriakidis, co-founder and CEO of QRA Corp. QRA is developing QVScribe, a product that helps engineers write requirements and analyze those requirements to gauge whether they are framed well and capture the writer's intent. We discuss the impact of writing good, early-stage design requirements, how they impact your system, how to write better requirements, the state of natural language processing, and machine learning for this use case. We also talk about applying those in situations where you need explainability and where ambiguity is unacceptable.

47 min
09/02/2022

#17: Iain Whiteside — The Twists and Turns of Validating Neural Networks for Autonomous Driving (Part 2)

In this two-part episode, we speak with Iain Whiteside about the challenges and some of the more novel solutions to make autonomous vehicles safer and easier to program. In part 1, we discuss how Ian and his team formalize and check the different actions and situations that a car finds itself in while on the road. In part 2, we discuss how you might validate the accuracy of neural networks that sense the world, and how to mitigate issues that might arise.

29 min
09/02/2022

#16: Iain Whiteside – Autonomous Driving: Reasoning About the Rules of the Road (Part 1)

In this two-part episode, we speak with Iain Whiteside about the challenges and some of the more novel solutions to make autonomous vehicles safer and easier to program. In part 1, we discuss how Ian and his team formalize and check the different actions and situations that a car finds itself in while on the road. In part 2, we discuss how you might validate the accuracy of neural networks that sense the world, and how to mitigate issues that might arise.

56 min
10/01/2022

#15: Dr. Kathleen Fisher – Sparking the New Age of Formal Verification at DARPA

In this episode, we chat with Dr. Kathleen Fisher, who was chair of the Computer Science department at Tufts University at the time of the interview. We talk about Kathleen’s experience in applying formal methods and PL theory to solve significant practical problems throughout her career. Equally important, we discuss how it came to be that she is practically a pro at golf!

56 min

See All (22)

Creator

Galois, Joey Dodds, Shpat Morina
Years Active

2020 - 2022
Episodes

22
Rating

Clean
Show Website

Building Better Systems

Building Better Systems

Episodes

Episode #22: Eric Daimler — Guaranteeing the Integrity of Data Models with Category Theory

Episode #21: Nikhil Swamy — Fully In Bed With Dependent Types

Episode #20: Ankush Desai — P: The Modeling Language That Could

#19: Steve Weis — Security Shouldn't Be the Last Check Box

#18: Jordan Kyriakidis — Helping People Write More Useful Requirements

#17: Iain Whiteside — The Twists and Turns of Validating Neural Networks for Autonomous Driving (Part 2)

#16: Iain Whiteside – Autonomous Driving: Reasoning About the Rules of the Road (Part 1)

#15: Dr. Kathleen Fisher – Sparking the New Age of Formal Verification at DARPA

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