Gauntlet is a simulation platform for building financial models of blockchain protocols and applications. Their platform uses machine learning methods to simulate different environments with various user behaviors and see how the system holds up in those conditions. They perform analysis on things like core mechanisms to test for liveness, block propagation, and at higher layers like simulating markets. Their offering is complementary to security audits as their analysis goes beyond code functionality and looks at how systems may behave in real-life conditions.
Tarun Chitra, CEO & Founder of Gauntlet, talks about his previous life in chip manufacturing and how he built Gauntlet. He also goes deep into the machine learning and statistical analysis involved with Gauntlet. It is quite a fascinating concept and when applied to blockchain systems, there is huge potential for this to become something that is expected by users, investors, and the community for new protocols.
Topics covered in this episode:
- Tarun’s background and how he got into crypto
- Chip manufacturing in the US and its geopolitical implications
- What sorts of things does Gauntlet model?
- How does historical data play a part in predicting blockchain protocol behavior
- Simulation models used by Gauntlet
- Game design analysis
- The parts of the crypto economic stack that would benefit from this simulation work today
- How does Gauntlet complement a security audit for a new blockchain
- What tools they use for simulation
- What Gauntlet looks like as a business and what is the roadmap going forward
Episode links:
Sponsors:
- Algorand: To learn more about Algorand and how it’s unique design makes it easy for developers to build sophisticated applications, visit algorand.com/epicenter - http://algorand.com/epicenter
This episode is hosted by Sebastien Couture & Sunny Aggarwal. Show notes and listening options: epicenter.tv/356
