COMPLEXITY
David Wolpert & Farita Tasnim on The Thermodynamics of Communication
Episode guests
Podcast summary created with Snipd AI
Quick takeaways
- Studying communication channels reveals the high energy cost of message transmission within living systems.
- Tuning noise levels in communication channels can minimize heat dissipation and enhance information transfer efficiency.
- Lower speeds in communication channels below capacity can provide thermodynamic advantages and decrease energy consumption.
Deep dives
Exploration of Information Theory and Coding Theory
The podcast delves into the history and ongoing evolution of information theory and coding theory. It discusses the relationship between energy, information, and matter, highlighting the deep scientific insights gained from studying communication channels and nonlinear dynamics.
Thermodynamics of Communication Channels in Living Systems
The study focuses on understanding the energetics of communication channels within living systems like the brain. It explores the high energy cost of communication between components and the limited access to information within these systems. By investigating the thermodynamic implications of information transmission, the research sheds light on the energy efficiency of sending messages through multiple channels.
Channel Capacity and Noise in Communication Channels
The research uncovers a non-monotonic relationship between entropy production and noise in communication channels. By modeling the thermodynamic costs of message transmission through various noise sources, the study reveals that tuning noise levels can lead to minimum heat dissipation and efficient information transfer.
Benefits of Slower Speeds in Traffic Systems and Communication Networks
The study draws parallels between the benefits of lower speeds in traffic systems to increase throughput and the thermodynamic advantages of operating communication channels below maximum capacity. By examining the flow of information through networks and the influence of network configurations on communication costs, the research points towards how hierarchical structures and network properties can impact energy efficiency.
Future Directions and Network Expansion
The future research direction involves exploring the energetic benefits of communication within network structures. By extending the study to multiple connected nodes in a network, the focus will be on how network properties such as modularity, hierarchy, and clustering impact the energetic costs of communication. The study aims to investigate how network configurations influence the efficiency of message transmission across various nodes in a network.
Communication is a physical process. It’s common sense that sending and receiving intelligible messages takes work…but how much work? The question of the relationship between energy, information, and matter is one of the deepest known to science. There appear to be limits to the rate at which communication between two systems can happen…but the search for a fundamental relationship between speed, error, and energy (among other things) promises insights far deeper than merely whether we can keep making faster internet devices. Strap in (and consider slowing down) for a broad and deep discussion on the bounds within which our entire universe must play…
Welcome to COMPLEXITY, the official podcast of the Santa Fe Institute. I’m your host, Michael Garfield, and every other week we’ll bring you with us for far-ranging conversations with our worldwide network of rigorous researchers developing new frameworks to explain the deepest mysteries of the universe.
This week we speak with SFI Professor David Wolpert and MIT Physics PhD student Farita Tasnim, who have worked together over the last year on pioneering research into the nonlinear dynamics of communication channels. In this episode, we explore the history and ongoing evolution of information theory and coding theory, what the field of stochastic thermodynamics has to do with limits to human knowledge, and the role of noise in collective intelligence.
Be sure to check out our extensive show notes with links to all our references at complexity.simplecast.com. If you value our research and communication efforts, please subscribe, rate and review us at Apple Podcasts or Spotify, and consider making a donation — or finding other ways to engage with us, including a handful of open postdoctoral fellowships — at santafe.edu/engage.
Lastly, this weekend — October 22nd & 23rd — is the return of our InterPlanetary Festival! Join our YouTube livestream for two full days of panel discussions, keynotes, and bleeding edge multimedia performances focusing space exploration through the lens of complex systems science. The fun begins at 11 A.M. Mountain Time on Saturday and ends 6 P.M. Mountain Time on Sunday. Everything will be recorded and archived at the stream link in case you can’t tune in for the live event. Learn more at interplanetaryfest.org…
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Referenced in this episode:
Nonlinear thermodynamics of communication channels
by Farita Tasnim and David Wolpert (forthcoming at arXiv.org)
Heterogeneity and Efficiency in the Brain
by Vijay Balasubramanian
Noisy Deductive Reasoning: How Humans Construct Math, and How Math Constructs Universes
by David Wolpert & David Kinney
Stochastic Mathematical Systems
by David Wolpert & David Kinney
Twenty-five years of nanoscale thermodynamics
by Chase P. Broedersz & Pierre Ronceray
Ten Questions about The Hard Limits of Human Intelligence
by David Wolpert
What can we know about that which we cannot even imagine?
by David Wolpert
Communication consumes 35 times more energy than computation in the human cortex, but both costs are needed to predict synapse number
by William Levy & Victoria Calvert
An exchange of letters on the role of noise in collective intelligence
by Daniel Kahneman, David Krakauer, Olivier Sibony, Cass Sunstein, David Wolpert
When Slower Is Faster
by Carlos Gershenson & Dirk Helbing
Additional Resources:
The stochastic thermodynamics of computation
by David Wolpert
Elements of Information Theory, Second Edition (textbook)
by Thomas Cover & Joy Thomas
Computational Complexity: A Modern Approach (textbook)
by Sanjeev Arora & Boaz Barak
An Introduction to Kolmogorov Complexity and Its Applications (textbook)
by Ming Li & Paul Vitányi
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