Early History of AI: Reflections on 1960s Innovations and Projects

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Raj Reddy
Carnegie Mellon University
March 21, 2006
Panel at CS40 celebrations
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Robotics
Computer Vision
Knowledge Engineering
Speech
Language Understanding
Computer Music
Chess, Symbolic Mathematics, Correctness of Programs, Theorem
Proving, Logical AI, Common Sense
Time Sharing
LISP
DEC Clones: Foonly, Graphical Editors, Pieces of Glass, Theory of
Computation
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Interaction with the Physical World
Early work by
Karl Pingle, Bill Wichman, Don Pieper
Main Project Team
Jerry Feldman, R. Lou Paul, Marty Tenenbaum,
Gerry Agin, Irwin Sobel, etc.
Robotic Hands
Bernie Roth and  Vic Scheinman
Started in 1965
Using the PDP1 and later the PDP6
Led Machine Vision and Robotics Industry
Via SRI and Vic Scheinman
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Image Analysis
Manfred Hueckel, Ruzena Bajcsy, and Tom Binford
 Led to Vision and Robotics at UPenn
Image Understanding
Natural Scenes and Face Recognition
Mike Kelly and Raj Reddy
Led to Vision and Robotics at CMU
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Mars Rover and Stanford Cart
Marvin Minsky (visiting)
Mars Explorer project 1964
Les Earnest
Bruce Baumgart
Lynn Quam
Hans Moravec
Rod Brooks (later in the seventies)
Influenced direction of programs at SRI and MIT
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Heuristic Dendral: Representation, acquisition and use
of knowledge in chemical inference
Project Team
Ed Feigenbaum, Josh Lederberg, Bruce Buchanan,
Georgia Sutherland et al.
 
Started in 1965
Led to
Expert Systems, Knowledge Engineering
Knowledge Based Systems Industry
Early Applications of AI
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Speech Input to Computers
Started in 1964 as a class project
Using a PDP1 with drum memory and a display
By the end of 1964 we had a vowel recognizer running
Project team in the sixties
Raj Reddy, Pierre Vicens, Lee Erman, Gary
Goodman, Richard Neely
Led to the DARPA Speech Understanding Project
during the years 1971-76
Most influential branch of Speech Recognition
Industry: Dragon Systems, Apple, Microsoft
Indirectly IBM and Bell Labs
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Parsing and Understanding of Natural Language: Question Asking
and Dialog Modeling
Computer Simulation of Belief systems
Ken Colby, Lawrence Tesler, Horace Enea et al
Parsing of Non-Grammatical Sentences
Colby, Enea et al
Conceptual Parsing
Roger Shank
Led to Language Processing Industry
via Shank and associates
Led to other Language Processing groups at Yale and UCLA
CMU, UMass, Berkeley, etc.
Influential strand of Language research
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Computer Synthesis of Music
Started in 1964 on PDP1
John Chowning
Leland Smith
Andy Moorer
Impact
Led to Yamaha adopting digital synthesis for consumer products
Establishment of a Center in Computer Music in Paris
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Chess and other game playing programs
Kalah: R. Russell
Chess: McCarthy, Barbara Huberman (Liskov)
Checkers: Art Samuels
Symbolic Mathematics
Algebraic Simplification: Wooldridge and Enea
Reduce: Tony Hearn
Proving Correctness of Programs
Correctness of Programs: McCarthy and Painter
Equivalence of Programs: Kaplan and Ito
Properties of Programs: Zohar Manna
Theorem Proving
David Luckham and John Allen
Use of Predicate Calculus as a Representation for AI
McCarthy, Cordell Green et al
AI and Philosophy
McCarthy and Pat Hayes
Programs with Common Sense
McCarthy, later  by Doug Lenat
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Programming Languages
LISP
Symbolic Computation
Dynamic Storage Allocation and Garbage Collection
Forerunner of Functional Programming
SAIL
LEAP Associative Data Structure
Feldman and Rovner
Time Sharing and Real Time Systems
Graphics
 scan line graphics!
User Interfaces
Graphics text editors and Graphical debugging
Systems: Foonly and other clones
Team: Earnest, Russell, Weiher, Poole, Panofsky, Sauter, Baumgart, Quam, Swinehart et
al
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Theory of Computation (SAIL Memo No 28, 1965)
Semantics of Programming Languages
What do strings of symbols representing programs … denote!
Data Spaces (aka Data Structures)
Representation of Time Dependent and Simultaneous
Processes
Speed of Computation (aka Computational Complexity)
Storage of Information (aka Databases)
Syntax directed computation such as computations
described by productions and rule based systems
Equivalence of programs
Halting problem for practical cases
O
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I
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Film Reports
Ellis D. Kropotechev and Zeus, his Marvelous TSS,
Gary Feldman
Butterfinger, Gary Feldman
Hear Here, Raj Reddy, Dave Espar, and Art
Eisenson
Avoid, Gary Feldman and Don Peiper
#?+@, Anon
Use of displays and video terminals
Early use of Laser Printing
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Personal Computers!
Alan Kay’s dynabook vs Apple and PCs
Internet and the WWW
ARPAnet in 1968 with Stanford as one of the initial nodes
Moore’s Law and VLSI
Graphics
Human Computer Interaction
UI design
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Speech
Vision
Robotics
Natural Language
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Learning Systems
Learn from examples
Learn from experience
Dynamic Learning
Learning from Sparse data
Architecture of Intelligence
Integrated Intelligence
Learn from Experience
Use Knowledge
Communicate using Speech and Language
Operate in real time
etc
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Lisp 
   
→ Functional Languages
Timesharing 
  
→ Thin Clients
Algorithm Design
 
→ Scalable Dependable
Systems
   
→ beyond OS
Graphics
   
→ 2D to 3D
UI
    
→ Illiterate users?
Hardware
  
→ Low power mobile
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Arthur Clarke’s The Songs of the Distant Earth
Ray Kurzweil’s Immortality
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Computers are for Entertainment and Communication
Not for Computing
“People are the Killer App” from Parc
Software as Service
Death of Software Product Market
Net 2.0 and Web Services
Cell Phone as the Dominant Computing Platform
Embedded Body Computers
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Much of what transpired in AI and CS in
the last 40 years can be seen to have
roots in the Stanford AI Labs activities of
the 60s!
We now have a million times more
computing power!
May be we do need 1.7 Einsteins, 3
Maxwells and 0.7 Manhattan project
(McCarthy, 1980s) to get there
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Techniques and Systems of AI in 1970s
Human Encoding of Knowledge
Expert Systems
Knowledge Based Systems
Rule Based Systems
Systems That Do Tasks that Require Intelligence
Play Chess
Prove Theorems
Discover Molecular Structure
Systems That Do Tasks That Humans Do Effortlessly
Speak and Hear: Speech Understanding and Dialog
See: Computer Vision and Image Understanding
Use Language: Ambiguous and Non-grammatical Language
Advances in AI in 1970s
Enabled by Brute-force, Heuristics, Human Coding
of Rules and Knowledge, and Simple Machine
Learning (Pattern Recognition)
Speech Recognition Systems
1000-word vocabulary Continuous Speech Recognition
Expert Systems
Rule Based Systems
Knowledge Based Systems
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RI, NREC, and the Future of Robotics
Raj Reddy
Carnegie Mellon University
Sep 8, 2016
Talk at 25
th
 Anniversary of NREC
30
Robotics Institute 1979-80
Manufacturing Robotics
Automated Forging Cell
Paul Wright, David Bourne
3D Printing
Fritz Prinz
Autonomous Vehicles
Land, Sea and Air vehicles
RED: Terragator Series
Hans Moravec: Stanford Cart
Kanade: Autonomous Helicopter
Field Robotics Center
RI Video: Manufacturing
 
RI Video: Autonomous Vehicles
 
NREC 1996-2016
Applied Robotics
Agricultural Robotics
Mining Robotics
Nuclear Robotics
Defense Robotics
Video: Applied Robotics
Future Directions in Robotics
Missing Science of Robotics
90% Self Reproducing Factories
Autonomic Systems
Sustainable Systems
9 Sigma Systems
Secure Systems
New Manufacturing Directions
The Virtual Factory
Reconfigurable Programmable Factory
The Networked Factory
Micro-Factory
Future Directions in Applied Robotics
Missing Technology of Applied Robotics
Agricultural Robotics
Mining Robotics
Defense Robotics
Disaster Supply and Rescue Robots
Smart Cities
IT Enabled Manufacturing
Personal Assistants
Robo-Gofer
Robo-Chef
Robo-Chauffeur
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Explore the early history of AI through reflections on the advancements and projects from the 1960s. Delve into key developments in robotics, computer vision, knowledge engineering, speech and language understanding, and more. Learn about pioneering initiatives like The Hand Eye Project, Image Analysis and Understanding, Mobile Robotics, and Expertise Heuristic Dendral that laid the foundation for the AI landscape we see today.

  • AI history
  • 1960s innovations
  • Robotics
  • Computer vision
  • Knowledge engineering

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  1. Personal Early History of AI Raj Reddy Oct 27, 2021 Talk given at CMU Course historical advances in machine learning (and AI) taught by Aditya Ramdas,

  2. Personal History of AI: 1960s

  3. Reflections on Reflections on Early AI and CS at Stanford Early AI and CS at Stanford 1963 1963 1969 and Beyond 1969 and Beyond Raj Reddy Carnegie Mellon University March 21, 2006 Panel at CS40 celebrations

  4. 1960s: The Golden Age of SAIL Robotics Computer Vision Knowledge Engineering Speech Language Understanding Computer Music Chess, Symbolic Mathematics, Correctness of Programs, Theorem Proving, Logical AI, Common Sense Time Sharing LISP DEC Clones: Foonly, Graphical Editors, Pieces of Glass, Theory of Computation

  5. The Hand Eye Project Interaction with the Physical World Early work by Karl Pingle, Bill Wichman, Don Pieper Main Project Team Jerry Feldman, R. Lou Paul, Marty Tenenbaum, Gerry Agin, Irwin Sobel, etc. Robotic Hands Bernie Roth and Vic Scheinman Started in 1965 Using the PDP1 and later the PDP6 Led Machine Vision and Robotics Industry Via SRI and Vic Scheinman

  6. Image Analysis and Understanding Image Analysis Manfred Hueckel, Ruzena Bajcsy, and Tom Binford Led to Vision and Robotics at UPenn Image Understanding Natural Scenes and Face Recognition Mike Kelly and Raj Reddy Led to Vision and Robotics at CMU

  7. Mobile Robotics Mars Rover and Stanford Cart Marvin Minsky (visiting) Mars Explorer project 1964 Les Earnest Bruce Baumgart Lynn Quam Hans Moravec Rod Brooks (later in the seventies) Influenced direction of programs at SRI and MIT

  8. Capturing Expertise Heuristic Dendral: Representation, acquisition and use of knowledge in chemical inference Project Team Ed Feigenbaum, Josh Lederberg, Bruce Buchanan, Georgia Sutherland et al. Started in 1965 Led to Expert Systems, Knowledge Engineering Knowledge Based Systems Industry Early Applications of AI

  9. Speech Speech Input to Computers Started in 1964 as a class project Using a PDP1 with drum memory and a display By the end of 1964 we had a vowel recognizer running Project team in the sixties Raj Reddy, Pierre Vicens, Lee Erman, Gary Goodman, Richard Neely Led to the DARPA Speech Understanding Project during the years 1971-76 Most influential branch of Speech Recognition Industry: Dragon Systems, Apple, Microsoft Indirectly IBM and Bell Labs

  10. Language Understanding Parsing and Understanding of Natural Language: Question Asking and Dialog Modeling Computer Simulation of Belief systems Ken Colby, Lawrence Tesler, Horace Enea et al Parsing of Non-Grammatical Sentences Colby, Enea et al Conceptual Parsing Roger Shank Led to Language Processing Industry via Shank and associates Led to other Language Processing groups at Yale and UCLA CMU, UMass, Berkeley, etc. Influential strand of Language research

  11. Computer Music Computer Synthesis of Music Started in 1964 on PDP1 John Chowning Leland Smith Andy Moorer Impact Led to Yamaha adopting digital synthesis for consumer products Establishment of a Center in Computer Music in Paris

  12. Other AI Projects Chess and other game playing programs Kalah: R. Russell Chess: McCarthy, Barbara Huberman (Liskov) Checkers: Art Samuels Symbolic Mathematics Algebraic Simplification: Wooldridge and Enea Reduce: Tony Hearn Proving Correctness of Programs Correctness of Programs: McCarthy and Painter Equivalence of Programs: Kaplan and Ito Properties of Programs: Zohar Manna Theorem Proving David Luckham and John Allen Use of Predicate Calculus as a Representation for AI McCarthy, Cordell Green et al AI and Philosophy McCarthy and Pat Hayes Programs with Common Sense McCarthy, later by Doug Lenat

  13. Non-AI Research at SAIL Programming Languages LISP Symbolic Computation Dynamic Storage Allocation and Garbage Collection Forerunner of Functional Programming SAIL LEAP Associative Data Structure Feldman and Rovner Time Sharing and Real Time Systems Graphics scan line graphics! User Interfaces Graphics text editors and Graphical debugging Systems: Foonly and other clones Team: Earnest, Russell, Weiher, Poole, Panofsky, Sauter, Baumgart, Quam, Swinehart et al

  14. Non-AI Research at SAIL (Cont) Theory of Computation (SAIL Memo No 28, 1965) Semantics of Programming Languages What do strings of symbols representing programs denote! Data Spaces (aka Data Structures) Representation of Time Dependent and Simultaneous Processes Speed of Computation (aka Computational Complexity) Storage of Information (aka Databases) Syntax directed computation such as computations described by productions and rule based systems Equivalence of programs Halting problem for practical cases

  15. Other Innovations Film Reports Ellis D. Kropotechev and Zeus, his Marvelous TSS, Gary Feldman Butterfinger, Gary Feldman Hear Here, Raj Reddy, Dave Espar, and Art Eisenson Avoid, Gary Feldman and Don Peiper #?+@, Anon Use of displays and video terminals Early use of Laser Printing

  16. Looking back: What we missed! Personal Computers! Alan Kay s dynabook vs Apple and PCs Internet and the WWW ARPAnet in 1968 with Stanford as one of the initial nodes Moore s Law and VLSI Graphics Human Computer Interaction UI design

  17. Looking back: off in timing! Speech Vision Robotics Natural Language

  18. Recent Trends in AI Learning Systems Learn from examples Learn from experience Dynamic Learning Learning from Sparse data Architecture of Intelligence Integrated Intelligence Learn from Experience Use Knowledge Communicate using Speech and Language Operate in real time etc

  19. Recent Trends in CS Lisp Timesharing Algorithm Design Systems Graphics UI Hardware Functional Languages Thin Clients Scalable Dependable beyond OS 2D to 3D Illiterate users? Low power mobile

  20. Whither AI? Arthur Clarke s The Songs of the Distant Earth Ray Kurzweil s Immortality

  21. Whither CS? Computers are for Entertainment and Communication Not for Computing People are the Killer App from Parc Software as Service Death of Software Product Market Net 2.0 and Web Services Cell Phone as the Dominant Computing Platform Embedded Body Computers

  22. In Conclusion Much of what transpired in AI and CS in the last 40 years can be seen to have roots in the Stanford AI Labs activities of the 60s! We now have a million times more computing power! May be we do need 1.7 Einsteins, 3 Maxwells and 0.7 Manhattan project (McCarthy, 1980s) to get there

  23. Hear! Here! Video 1968 (Stanford) https://www.youtube.com/watch?v=JJ_zlj4pFV0&t=117s

  24. Personal History of AI: 1970s

  25. Techniques and Systems of AI in 1970s Human Encoding of Knowledge Expert Systems Knowledge Based Systems Rule Based Systems Systems That Do Tasks that Require Intelligence Play Chess Prove Theorems Discover Molecular Structure Systems That Do Tasks That Humans Do Effortlessly Speak and Hear: Speech Understanding and Dialog See: Computer Vision and Image Understanding Use Language: Ambiguous and Non-grammatical Language

  26. Advances in AI in 1970s Enabled by Brute-force, Heuristics, Human Coding of Rules and Knowledge, and Simple Machine Learning (Pattern Recognition) Speech Recognition Systems 1000-word vocabulary Continuous Speech Recognition Expert Systems Rule Based Systems Knowledge Based Systems

  27. Hearsay Video 1973 (CMU) https://www.youtube.com/watch?v=kJ9WekPYaXQ

  28. Harpy Video 1975 (CMU) https://www.youtube.com/watch?v=NiiDe2n-GeQ

  29. Personal History of AI: 1980s Raj Reddy

  30. RI, NREC, and the Future of Robotics Raj Reddy Carnegie Mellon University Sep 8, 2016 Talk at 25thAnniversary of NREC 30

  31. Robotics Institute 1979-80 Manufacturing Robotics Automated Forging Cell Paul Wright, David Bourne 3D Printing Fritz Prinz Autonomous Vehicles Land, Sea and Air vehicles RED: Terragator Series Hans Moravec: Stanford Cart Kanade: Autonomous Helicopter Field Robotics Center

  32. RI Video: Manufacturing

  33. RI Video: Autonomous Vehicles

  34. NREC 1996-2016 Applied Robotics Agricultural Robotics Mining Robotics Nuclear Robotics Defense Robotics Video: Applied Robotics

  35. Future Directions in Robotics Missing Science of Robotics 90% Self Reproducing Factories Autonomic Systems Sustainable Systems 9 Sigma Systems Secure Systems New Manufacturing Directions The Virtual Factory Reconfigurable Programmable Factory The Networked Factory Micro-Factory

  36. Future Directions in Applied Robotics Missing Technology of Applied Robotics Agricultural Robotics Mining Robotics Defense Robotics Disaster Supply and Rescue Robots Smart Cities IT Enabled Manufacturing Personal Assistants Robo-Gofer Robo-Chef Robo-Chauffeur

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