Of 10 Uncertainty in Communication1 Communication amid Uncertainty Madhu Sudan Microsoft, Cambridge, USA Based on: Universal Semantic.

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Presentation transcript:

of 10 Uncertainty in Communication1 Communication amid Uncertainty Madhu Sudan Microsoft, Cambridge, USA Based on: Universal Semantic Communication – Juba & S. (STOC 2008) Universal Semantic Communication – Juba & S. (STOC 2008) Goal-Oriented Communication – Goldreich, Juba & S. (JACM 2012) Goal-Oriented Communication – Goldreich, Juba & S. (JACM 2012) Compression without a common prior … – Compression without a common prior … – Kalai, Khanna, Juba & S. (ICS 2011) Kalai, Khanna, Juba & S. (ICS 2011) Efficient Semantic Communication with Compatible Beliefs – Efficient Semantic Communication with Compatible Beliefs – Juba & S. (ICS 2011)

of 10 Uncertainty in Communication? Always has been a central problem: Always has been a central problem: But usually focusses on uncertainty introduced by the channel But usually focusses on uncertainty introduced by the channel Standard Solution: Standard Solution: Use error-correcting codes Use error-correcting codes Significantly: Significantly: Design Encoder/Decoder jointly Design Encoder/Decoder jointly Deploy Encoder at Sender, Decoder at Receiver Deploy Encoder at Sender, Decoder at Receiver Uncertainty in Communication2

of 10 New Era, New Challenges: Interacting entities not jointly designed. Interacting entities not jointly designed. Can’t design encoder+decoder jointly. Can’t design encoder+decoder jointly. Can they be build independently? Can they be build independently? Can we have a theory about such? Can we have a theory about such? Where we prove that they will work? Where we prove that they will work? Hopefully: Hopefully: YES YES And the world of practice will adopt principles. And the world of practice will adopt principles. Uncertainty in Communication3

of 10 Example 1 Uncertainty in Communication4

of 10 Example 2 Heterogenous data? Heterogenous data? Amazon-marketplace spends N programmer hours converting data from mom-n-pop store catalogs to uniform searchable format. Amazon-marketplace spends N programmer hours converting data from mom-n-pop store catalogs to uniform searchable format. Healthcare analysts spend enormous #hours unifying data from multiple sources. Healthcare analysts spend enormous #hours unifying data from multiple sources. Problem: Interface of software with data: Problem: Interface of software with data: Challenge: Challenge: Software designer uncertain of data format. Software designer uncertain of data format. Data designer uncertain of software. Data designer uncertain of software. Uncertainty in Communication5

of 10 Example 3 Archiving data Archiving data Physical libraries have survived for 100s of years. Physical libraries have survived for 100s of years. Digital books have survived for five years. Digital books have survived for five years. Can we be sure they will survive for the next five hundred? Can we be sure they will survive for the next five hundred? Problem: Uncertainty of the future. Problem: Uncertainty of the future. What systems will prevail? What systems will prevail? Why aren’t software systems ever constant? Why aren’t software systems ever constant? Problem: Problem: When designing one system, it is uncertain what the other’s design is (or will be in the future)! When designing one system, it is uncertain what the other’s design is (or will be in the future)! Uncertainty in Communication6

of 10 Modelling uncertainty Classical Shannon Model Uncertainty in Communication7 A B Channel B2B2B2B2 AkAkAkAk A3A3A3A3 A2A2A2A2 A1A1A1A1 B1B1B1B1 B3B3B3B3 BjBjBjBj Semantic Communication Model New Class of Problems New challenges Needs more attention!

of 10 Nature of uncertainty Uncertainty in Communication8

of 10 Future? Understand human communication? Understand human communication? How does it evolve How does it evolve What are influencing factors? What are influencing factors? (My guesses): Compression, Computation, Survival of fittest. (My guesses): Compression, Computation, Survival of fittest. Extend to other “distributed design” settings. Extend to other “distributed design” settings. Architecture/Program for preserving Data? Architecture/Program for preserving Data? Blend safe assumptions, with “likely-to-be- fast” performance. Blend safe assumptions, with “likely-to-be- fast” performance. Uncertainty in Communication9

of 10 Uncertainty in Communication10 Thank You!