dr. frank rosenblatt, 1928-1971
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Dr. Frank Rosenblatt, 1928-1971. PhD Experimental Psychology, Cornell, 1956 Developed neural networks called perceptrons A probabilistic model for information storage and organization in the brain Key properties Association or learning Generalization to new patterns Distributed memory - PowerPoint PPT PresentationTRANSCRIPT
Frank Rosenblatt
Dr. Frank Rosenblatt, 1928-1971
PhD Experimental Psychology, Cornell, 1956 Developed neural networks called perceptrons
A probabilistic model for informationstorage and organization in the brain Key properties
Association or learning Generalization to new patterns Distributed memory Biologically plausible brain model
Cornell Aeronautical Lab (1957-1959), Cornell (1960-71)
Frank Rosenblatt
Dr. Frank Rosenblatt
Wikipedia portrayal exaggerated“Rosenblatt was a colorful character at Cornellin the early 1960s. A handsome bachelor, he drove a classic MGA sports car and was often seen with his cat named Tobermory.”
Those who knew him would consider him a rather shy genius and more of a Renaissance man Renaissance man because he excelled in a wide variety of subjects, including psychology (his original field), computing, mathematics, neurophysiology, astronomy, and music
Frank Rosenblatt
Agenda
The Mark I Perceptron – Visual System Model The Tobermory Perceptron – Auditory System
Model Perceptron Computer Simulations Rosenblatt's Book Rosenblatt-Minsky Debates and Minsky-Papert
Book Rat Brain Experiments Hobbies – Astronomy, Climbing, Music, Sailing Untimely Death
Frank Rosenblatt
The Mark I Perceptron Visual system model and pattern
classifier
Typical three-layer perceptron: fixed S→A and variable A→R connections
Examining A-unit of Mark I
Frank Rosenblatt
The Mark I PerceptronVisual system model and pattern
classifier
Input (sensory) layer of 400 photosensitive units in a 20x20 grid modeling a small retina
Connections from input to association layer altered through plug-board wiring, but once wired they were fixed for the duration of an experiment
Association layer of 512 units (stepping motors) each of which could take several excitatory and inhibitory inputs
Connections from association to output layer were variable weights (motor-driven potentiometers) adjusted through error-propagating training process
Output (response) layer of 8 units
Frank Rosenblatt
The Tobermory PerceptronAuditory system model and pattern
classifier
Named after talking cat, Tobermory, in story by H.H. Munro (aka Saki) Large machine
S-units: 45 band-pass filters and 80 difference detectors
A-units: 1600 A1-units (20 time samples per detector) & 1000 A2-units
R-units: 12, with 12,000 adaptive weights A2→R-units.
Frank Rosenblatt
Perceptron Computer Simulations
Hardware implementations made good demonstrations but software simulations were far more flexible
In early 1960s these computer simulations required machine language coding for speed and memory usage
Simulation software package – user could specify the number of layers, the number of units per layer, type of connections between layers, etc.
Computer time at Cornell and NYU
Frank Rosenblatt
Rosenblatt's BookPrinciples of Neurodynamics,
1962
Part I: historical review of brain modeling approaches, physiological and psychological considerations, and basic definitions and concepts of the perceptron approach
Part II: three-layer, series-coupled perceptrons –mathematical underpinnings and experimental results
Part III: multi-layer and cross-coupled perceptrons Part VI: back-coupled perceptrons Book used to teach an interdisciplinary course
"Theory of Brain Mechanisms" that drew students from Cornell's Engineering and Liberal Arts colleges
Frank Rosenblatt
Series-Coupled Perceptrons
A perceptron is a network of sensory (S), association (A), and response (R) signal generating units
A series-coupled perceptron is feed-forward S→A→R An elementary perceptron is a series-coupled
perceptron with one R-unit connected to every A-unit and fixed S→A connections
Convergence Theorem: Given elementary perceptron, stimulus world W, and any classification C(W) for which a solution exists, then if all stimuli in W re-occur in finite time, the error correction procedure will always find a solution
Frank Rosenblatt
Series-Coupled PerceptronsMark I was typical S→A→R perceptron
ConnectionsS→A: fixed, usually localA→R: adjustable w training
Frank Rosenblatt
Series-Coupled PerceptronsA-units usually local biologically-plausible
detectors
Frank Rosenblatt
Series-Coupled Perceptrons
Dotted lines are variable connections
Rosenblatt studied three and four-layer series-coupled perceptrons with two sets of variable weights but was unable to find a suitable training procedure like back-propagation
Frank Rosenblatt
Cross-Coupled Perceptrons
A cross-coupled perceptron is a system in which some connections join units of the same type (S, A, and/or R)
Frank Rosenblatt
Back-Coupled Perceptrons A back-coupled perceptron is a system with feedback
paths from units located near the output end of the system to units closer to the sensory end
Frank Rosenblatt
Rosenblatt-Minsky Debates
and Minsky-Papert Book
Rosenblatt and Marvin Minsky (MIT) debated at conferences the value of biologically inspired computation, Rosenblatt arguing that his neural networks could do almost anything and Minsky countering that they could do little
Minsky, wanting to decide the matter once and for all, collaborated with Seymour Papert and published a book in 1969, Perceptrons: An Introduction to Computational Geometry, where they asserted about perceptrons (page 4), "Most of this writing ... is without scientific value...”
Minsky, although well aware that powerful perceptrons have multiple layers and Rosenblatt's basic feed-forward perceptrons have three layers, defined a perceptron as a two-layer machine that can handle only linearly separable problems and, for example, cannot solve the exclusive-OR problem
Frank Rosenblatt
Minsky-Papert BookH.D. Block’s response paper
The authors address three classes of readers1. Computer scientists specializing in pattern recognition, learning
machines, and threshold logic2. Abstract mathematicians interested in the debut of Computational
Geometry3. Those interested in the general theory of computation leading to
decisions based on the weight of partial evidence, e.g. psychologists and biologists
H.D. Block concludes1. Computer scientists “will find the book of little value”2. Abstract mathematicians consulted “were not captivated”3. “For psychologists and biologists, the level of mathematical
maturity demanded will, I believe, make the book somewhat difficult to read.”
Frank Rosenblatt
Rat Brain Experiments Late 1960s – Rosenblatt began experiments
in the Cornell Department of Entomology on the transfer of learned behavior via rat brain extracts
Rats were taught discrimination tasks such as Y-maze and two-lever Skinner box, their brains extracted and injected into untrained rats that were then tested in the discrimination tasks to determine whether or not there was behavior transfer from the trained to the untrained rats
Rosenblatt spent his last several years on this problem and showed convincingly that the initial reports of larger effects were wrong and that any memory transfer was at most very small
Frank Rosenblatt
Astronomy
Rosenblatt built a modest observatory on a hilltop behind his house 6 miles east of Ithaca. Work began summer 1961, Fecker 12" cassegrain telescope.
He had interest in SETI (Search for Extraterrestrial Intelligence), wrote a proposal touting a "Stellar Coherometer” he designed, and was awarded $75K for the project.
The observatory was completed about 1966 – a circular cinderblock structure with dome housing the telescopeCurrent photo – house in
background
Frank Rosenblatt
Music
Rosenblatt was an accomplished pianist and had a grand piano at his house in Brooktondale
He played the well-known classical pieces of Mozart, Beethoven, etc.
He also composed music and had a penchant of improvising endlessly on "Three Blind Mice"
Frank Rosenblatt
Practical Joker As a graduate student
Frank was a psychology major and Prof. James Gibsonwas a well-known faculty member and Frank’s dissertation advisor. As the story goes, Frank and someother graduate students drove to the town of Gibson one night and stole the town's "Gibson" signs, which they then mounted at the door of Professor Gibson's office.When Department Chair saw the signs, he remarked to the department secretary, "Don't you think Gibby's getting a little ostentatious?“
Traveling to a conference Frank remarked“Do you think McCulloch sleeps with his beard under or over the covers?”
Frank Rosenblatt
Rosenblatt – Renaissance man
Excelled in a wide variety of subjects – psychology (his original field), computing, mathematics, neurophysiology, astronomy, and music
He had two research reputations neural networks with his perceptron work neurophysiology with the rat brain experiments
When learning a new subject (to paraphrase Rodman Miller)
In a few weeks he knew a little In a few months he knew a great deal Soon thereafter he was discussing topics with experts in the
field
Frank Rosenblatt
Untimely Death Sailboat accident on his 43rd birthday
He “was a most gifted human being ... had made his entire life a contribution to mankind”
Congressional Record