Editor’s note: Zavain Dar is an early-stage VC at Lux Capital and Lecturer at Stanford University. He invests and supports deep technology companies leveraging advancements in Artificial Intelligence, Infrastructure, and emerging data and has taught courses on cryptocurrency and the intersections of AI, philosophy and venture.
Like many in Silicon Valley, I recently saw Morten Tyldum’s The Imitation Game. I have a soft spot for underdog academic narratives and actually teared up. However, I couldn’t shake the feeling the film pigeonholed the breadth and depth of Turing’s work to early cryptography and its mechanized instantiation during WWII.Cryptography aside, Turing’s work, theory and models still underline undergraduate curriculums in computer science, mathematics and philosophy. His models for computation form the basis for how mathematicians and computer scientists structure both what is solvable and the efficiency with which we can algorithmically solve answerable questions. His Church-Turing Thesis coupled with Godel’s Incompleteness Theorems still has philosophers debating the existence of universal constraints around human knowledge.Finally, and perhaps most pressing given the ongoing renaissance in machine learning, the Turing Test remains the de facto yardstick against which we measure progress and traction in artificial intelligence.Whereas The Imitation Game focuses on cryptography and wartime technology, there is no doubt that Turing’s work also includes AI, theoretical computer science, mathematics and even epistemology.The realization that Turing’s work still has high relevance in both academia and industry got me thinking about how and why this is the case. What lessons can today’s technology entrepreneurs and investors pull from Turing’s intellectual longevity?I start with a few very basic and generalized broad-stroke assumptions. (The focus on high level
Like many in Silicon Valley, I recently saw Morten Tyldum’s The Imitation Game. I have a soft spot for underdog academic narratives and actually teared up. However, I couldn’t shake the feeling the film pigeonholed the breadth and depth of Turing’s work to early cryptography and its mechanized instantiation during WWII.Cryptography aside, Turing’s work, theory and models still underline undergraduate curriculums in computer science, mathematics and philosophy. His models for computation form the basis for how mathematicians and computer scientists structure both what is solvable and the efficiency with which we can algorithmically solve answerable questions. His Church-Turing Thesis coupled with Godel’s Incompleteness Theorems still has philosophers debating the existence of universal constraints around human knowledge.Finally, and perhaps most pressing given the ongoing renaissance in machine learning, the Turing Test remains the de facto yardstick against which we measure progress and traction in artificial intelligence.Whereas The Imitation Game focuses on cryptography and wartime technology, there is no doubt that Turing’s work also includes AI, theoretical computer science, mathematics and even epistemology.The realization that Turing’s work still has high relevance in both academia and industry got me thinking about how and why this is the case. What lessons can today’s technology entrepreneurs and investors pull from Turing’s intellectual longevity?I start with a few very basic and generalized broad-stroke assumptions. (The focus on high level
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