What Does Watson 2.0 Tell us About the Philosophy, Theory, & Future of AI?
Selmer Bringsjord(1) • Naveen Sundar G.(2)
Rensselaer AI & Reasoning (RAIR) Lab(1,2)
Department of Cognitive Science(1)
Department of Computer Science(1,2)
Lally School of Management & Technology(1)
Rensselaer Polytechnic Institute (RPI)Troy, New York 12180 USA
Oxford UniversityOxford, UK9/21/2013
Tuesday, October 1, 13
What Does Watson 2.0 Tell us About the Philosophy, Theory, & Future of AI?
Selmer Bringsjord(1) • Naveen Sundar G.(2)
Rensselaer AI & Reasoning (RAIR) Lab(1,2)
Department of Cognitive Science(1)
Department of Computer Science(1,2)
Lally School of Management & Technology(1)
Rensselaer Polytechnic Institute (RPI)Troy, New York 12180 USA
Oxford UniversityOxford, UK9/21/2013
Rensselaer AI & Reasoning (RAIR) Lab(1,2)
Tuesday, October 1, 13
What Does Watson 2.0 Tell us About the Philosophy, Theory, & Future of AI?
Selmer Bringsjord(1) • Naveen Sundar G.(2)
Rensselaer AI & Reasoning (RAIR) Lab(1,2)
Department of Cognitive Science(1)
Department of Computer Science(1,2)
Lally School of Management & Technology(1)
Rensselaer Polytechnic Institute (RPI)Troy, New York 12180 USA
Oxford UniversityOxford, UK9/21/2013
Rensselaer AI & Reasoning (RAIR) Lab(1,2)
Made possible by the generosity of:
IBMRPI’s pursuit of ITS/IILE
NSF
JTF
AFOSR
ONR x 2
DARPA
Tuesday, October 1, 13
What Does Watson 2.0 Tell us About the Philosophy, Theory, & Future of AI?
Selmer Bringsjord(1) • Naveen Sundar G.(2)
Rensselaer AI & Reasoning (RAIR) Lab(1,2)
Department of Cognitive Science(1)
Department of Computer Science(1,2)
Lally School of Management & Technology(1)
Rensselaer Polytechnic Institute (RPI)Troy, New York 12180 USA
Oxford UniversityOxford, UK9/21/2013
Rensselaer AI & Reasoning (RAIR) Lab(1,2)
Made possible by the generosity of:
IBMRPI’s pursuit of ITS/IILE
NSF
JTF
AFOSR
ONR x 2
DARPA
Tuesday, October 1, 13
Simon: “Chess is a lofty target for AI, yes. Go for it!”
Tuesday, October 1, 13
Tuesday, October 1, 13
“Chess is Too Easy”
Tuesday, October 1, 13
“Chess is Too Easy”
I was right :).
Tuesday, October 1, 13
What about this, then?
Tuesday, October 1, 13
What about this, then?
Tuesday, October 1, 13
What about this, then?
Experts to IBM: “Can’t be done!”
Tuesday, October 1, 13
What about this, then?
Experts to IBM: “Can’t be done!”
No one asked me.
Tuesday, October 1, 13
What about this, then?
Experts to IBM: “Can’t be done!”
No one asked me.
Tuesday, October 1, 13
Tuesday, October 1, 13
Tuesday, October 1, 13
Tuesday, October 1, 13
Tuesday, October 1, 13
u 2 ⌃⇤
Tuesday, October 1, 13
u 2 ⌃⇤
Tuesday, October 1, 13
u 2 ⌃⇤U = (S, . . .)
Tuesday, October 1, 13
u 2 ⌃⇤
U : u �! �U = (S, . . .)
Tuesday, October 1, 13
u 2 ⌃⇤
U : u �! �U = (S, . . .)
Tuesday, October 1, 13
u 2 ⌃⇤
U : u �! �U = (S, . . .)
A(v1 @ u,R) ^A(v2 @ u,R)
Tuesday, October 1, 13
u 2 ⌃⇤
U : u �! �U = (S, . . .)
A(v1 @ u,R) ^A(v2 @ u,R)(Ab(u) ^ u 2 MedBase) ! t(u) = ‘skin cancer’
Tuesday, October 1, 13
u 2 ⌃⇤
U : u �! �U = (S, . . .)
A(v1 @ u,R) ^A(v2 @ u,R)(Ab(u) ^ u 2 MedBase) ! t(u) = ‘skin cancer’
$
Tuesday, October 1, 13
Many thanks to A Bringsjord for this pair of slides, and discussion.
Tuesday, October 1, 13
Tuesday, October 1, 13
Tuesday, October 1, 13
Autonomy “Magic”
Tuesday, October 1, 13
Autonomy “Magic”Understanding 100% of InformationThe characteristic that makes human information unstructured is its form — it does not fit neatly into the rows and columns of a database, but exists in various formats including books, email messages, surveillance video, chat streams, and phone calls that occur across networks, the web, the cloud, and numerous mobile devices. Growing at a rate three times that of structured data, the increasing deluge of unstructured information makes up approximately 90 percent of all information. The challenge for the modern enterprise is to understand and extract value from this rich sea of human information.
Today, with Autonomy, organizations can now process and understand in real time, the meaning of 100 percent of information.
Tuesday, October 1, 13
Autonomy “Magic”Understanding 100% of InformationThe characteristic that makes human information unstructured is its form — it does not fit neatly into the rows and columns of a database, but exists in various formats including books, email messages, surveillance video, chat streams, and phone calls that occur across networks, the web, the cloud, and numerous mobile devices. Growing at a rate three times that of structured data, the increasing deluge of unstructured information makes up approximately 90 percent of all information. The challenge for the modern enterprise is to understand and extract value from this rich sea of human information.
Today, with Autonomy, organizations can now process and understand in real time, the meaning of 100 percent of information.
Tuesday, October 1, 13
Autonomy “Magic”Understanding 100% of InformationThe characteristic that makes human information unstructured is its form — it does not fit neatly into the rows and columns of a database, but exists in various formats including books, email messages, surveillance video, chat streams, and phone calls that occur across networks, the web, the cloud, and numerous mobile devices. Growing at a rate three times that of structured data, the increasing deluge of unstructured information makes up approximately 90 percent of all information. The challenge for the modern enterprise is to understand and extract value from this rich sea of human information.
Today, with Autonomy, organizations can now process and understand in real time, the meaning of 100 percent of information.
!?!?
Tuesday, October 1, 13
Autonomy “Magic”Understanding 100% of InformationThe characteristic that makes human information unstructured is its form — it does not fit neatly into the rows and columns of a database, but exists in various formats including books, email messages, surveillance video, chat streams, and phone calls that occur across networks, the web, the cloud, and numerous mobile devices. Growing at a rate three times that of structured data, the increasing deluge of unstructured information makes up approximately 90 percent of all information. The challenge for the modern enterprise is to understand and extract value from this rich sea of human information.
Today, with Autonomy, organizations can now process and understand in real time, the meaning of 100 percent of information.
!?!?(They sure as heck never consulted with Floridi.)
Tuesday, October 1, 13
Autonomy “Magic”Understanding 100% of InformationThe characteristic that makes human information unstructured is its form — it does not fit neatly into the rows and columns of a database, but exists in various formats including books, email messages, surveillance video, chat streams, and phone calls that occur across networks, the web, the cloud, and numerous mobile devices. Growing at a rate three times that of structured data, the increasing deluge of unstructured information makes up approximately 90 percent of all information. The challenge for the modern enterprise is to understand and extract value from this rich sea of human information.
Today, with Autonomy, organizations can now process and understand in real time, the meaning of 100 percent of information.
!?!?(They sure as heck never consulted with Floridi.)
The little OUP book that could’ve saved HP $6 billion:
Tuesday, October 1, 13
Autonomy “Magic”Understanding 100% of InformationThe characteristic that makes human information unstructured is its form — it does not fit neatly into the rows and columns of a database, but exists in various formats including books, email messages, surveillance video, chat streams, and phone calls that occur across networks, the web, the cloud, and numerous mobile devices. Growing at a rate three times that of structured data, the increasing deluge of unstructured information makes up approximately 90 percent of all information. The challenge for the modern enterprise is to understand and extract value from this rich sea of human information.
Today, with Autonomy, organizations can now process and understand in real time, the meaning of 100 percent of information.
!?!?(They sure as heck never consulted with Floridi.)
The little OUP book that could’ve saved HP $6 billion:
Tuesday, October 1, 13
Let’s in fact talk about 100% of semantic information, using Watson 2.0 as a springboard ...
Tuesday, October 1, 13
Tuesday, October 1, 13
Logic
Tuesday, October 1, 13
Logic
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL
UIMA outp
ut
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
UIMA outp
ut
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
UIMA outp
ut
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
Art of Infallibility 1
UIMA outp
ut
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
Art of Infallibility 1
UIMA outp
ut
FOL
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
Art of Infallibility 1
UIMA outp
ut
FOLSOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
Art of Infallibility 1
UIMA outp
utepistemic
FOLSOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
Art of Infallibility 1
UIMA outp
utepistemic
FOLSOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
Art of Infallibility 1
UIMA outp
utepistemic
FOLSOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Art of Infallibility 1
UIMA outp
utepistemic
FOLSOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
FOLSOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOLSOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
SOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
SOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
Vivid
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
DCEC ⇤
Deontic Cognitive Event Calculus
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
DCEC ⇤
Deontic Cognitive Event Calculus
1. natural language semantics (non-Montagovian)2. higher-cognition tests (for Psychometric AI) (false-belief test, deliberative mind-reading mirror test for self-consciousness ...)
4. biz & econ simulation 3. ethically correct robots
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
DCEC ⇤
Deontic Cognitive Event Calculus
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
Gödel’s “God Theorem”
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
ITS (Culture, Language, Math)
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
AI-ified Axiomatic Physics!(Synthese)
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...
temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
Goodstein’s Theorem!
Tuesday, October 1, 13
Licato, J.; Govindarajulu, N.; Bringsjord, S.; Pomeranz, M.; Gittelson, L. 2013. Analogico-Deductive Generation of Godel’s First Incompleteness Theorem from the Liar Paradox. In Proceedings of IJCAI 2013. Pdf
Govindarajulu, N.; Licato, J.; Bringsjord, S. 2013. Small Steps Toward Hypercomputation via Infinitary Machine Proof Verification and Proof Generation. In Proceedings of UCNC 2013. Pdf
Tuesday, October 1, 13
Liar Paradox (L)• Collection of semiformal statements• Syntax not rigorously defined• Represents intuitive understanding of problem
domain
Ending one of AI’s “bad dreams”:
s = “This statement is a lie”There is a statement that is neither
true nor false....
G1• Completely formal statements• Syntax very rigorously defined• Purely mathematical objects: numbers, formal
theories, etc.
s = ?
∃φ∈LA ¬(PA |⎯ φ) ∧ ¬(PA |⎯ ¬φ)...
Tuesday, October 1, 13
Liar Paradox (L)• Collection of semiformal statements• Syntax not rigorously defined• Represents intuitive understanding of problem
domain
Ending one of AI’s “bad dreams”:
s = “This statement is a lie”There is a statement that is neither
true nor false....
G1• Completely formal statements• Syntax very rigorously defined• Purely mathematical objects: numbers, formal
theories, etc.
s = ?
∃φ∈LA ¬(PA |⎯ φ) ∧ ¬(PA |⎯ ¬φ)...
Tuesday, October 1, 13
Liar Paradox (L)• Collection of semiformal statements• Syntax not rigorously defined• Represents intuitive understanding of problem
domain
Ending one of AI’s “bad dreams”:
s = “This statement is a lie”There is a statement that is neither
true nor false....
G1• Completely formal statements• Syntax very rigorously defined• Purely mathematical objects: numbers, formal
theories, etc.
s = ?
∃φ∈LA ¬(PA |⎯ φ) ∧ ¬(PA |⎯ ¬φ)...
S• Semiformal statements (but more formal than L)• Syntax somewhat rigorously defined• Somewhat intuitive; deals with stories of reasoners
and utterances made by inhabitants of an island
s = ¬Bs
∃p ¬Bp ∧ ¬B¬p...
Tuesday, October 1, 13
Liar Paradox (L)• Collection of semiformal statements• Syntax not rigorously defined• Represents intuitive understanding of problem
domain
Ending one of AI’s “bad dreams”:
s = “This statement is a lie”There is a statement that is neither
true nor false....
G1• Completely formal statements• Syntax very rigorously defined• Purely mathematical objects: numbers, formal
theories, etc.
s = ?
∃φ∈LA ¬(PA |⎯ φ) ∧ ¬(PA |⎯ ¬φ)...
S• Semiformal statements (but more formal than L)• Syntax somewhat rigorously defined• Somewhat intuitive; deals with stories of reasoners
and utterances made by inhabitants of an island
s = ¬Bs
∃p ¬Bp ∧ ¬B¬p...
Tuesday, October 1, 13
The Singularity Approaches ...
Tuesday, October 1, 13
The Singularity Approaches ...
Tuesday, October 1, 13
The Singularity Approaches ...
(Good 1965; Chalmers 2010)
Tuesday, October 1, 13
Tuesday, October 1, 13
If AI is only Ray-1 AI ...
Tuesday, October 1, 13
If AI is only Ray-1 AI ...
False!
Tuesday, October 1, 13
Tuesday, October 1, 13
If AI is only Ray-2 AI ...
Tuesday, October 1, 13
If AI is only Ray-2 AI ...
False!
Tuesday, October 1, 13
If AI is only Ray-2 AI ...
False!False!
Tuesday, October 1, 13
If AI is only Ray-2 AI ...
False!
And of course ...
False!
Tuesday, October 1, 13
Tuesday, October 1, 13
... if AI is Ray-3 AI ...
Tuesday, October 1, 13
... if AI is Ray-3 AI ...
False!False!
Tuesday, October 1, 13
“My, that’s rather negative, even violent. Can we talk about positive views, please?”
Tuesday, October 1, 13
SupermindsPeople Harness Hypercomputation,
and More(2003)
Turing Limit
Information Processing
Subjective consciousness, qualia, etc. — phenomena in the incorporeal realm that can’t be expressed in any third-person scheme
persons
animals (chess, go, swimming, flying, locomotion)
Hypercomputation
People Harness Hypercomputation, and More
29
by
SUPERMINDSPeople Harness Hypercomputation, and More
bySelmer Bringsjord and Micael Zenzen
This is the first book-length presentation and defense of a new theory of human andmachine cognition, according to which human persons are superminds. Superminds arecapable of processing information not only at and below the level of Turing machines(standard computers), but above that level (the “Turing Limit”), as information processingdevices that have not yet been (and perhaps can never be) built, but have beenmathematically specified; these devices are known as super-Turing machines orhypercomputers. Superminds, as explained herein, also have properties no machine,whether above or below the Turing Limit, can have. The present book is the third andpivotal volume in Bringsjord’s supermind quartet; the first two books were What RobotsCan and Can’t Be (Kluwer) and AI and Literary Creativity (Lawrence Erlbaum). The finalchapter of this book offers eight prescriptions for the concrete practice of AI and cognitivescience in light of the fact that we are superminds.
SELMER
BR
ING
SJOR
D
AN
D M
ICH
AEL ZEN
ZENSU
PERM
IND
SPeople H
arness Hypercom
putation, and More
KLUWER ACADEMIC PUBLISHERS COGS 29
Bringsjord COGS 29 PB(2)xpr 07-02-2003 16:26 Pagina 1
Tuesday, October 1, 13
SupermindsPeople Harness Hypercomputation,
and More(2003)
Turing Limit
Information Processing
Subjective consciousness, qualia, etc. — phenomena in the incorporeal realm that can’t be expressed in any third-person scheme
persons
animals (chess, go, swimming, flying, locomotion)
Hypercomputation
People Harness Hypercomputation, and More
29
by
SUPERMINDSPeople Harness Hypercomputation, and More
bySelmer Bringsjord and Micael Zenzen
This is the first book-length presentation and defense of a new theory of human andmachine cognition, according to which human persons are superminds. Superminds arecapable of processing information not only at and below the level of Turing machines(standard computers), but above that level (the “Turing Limit”), as information processingdevices that have not yet been (and perhaps can never be) built, but have beenmathematically specified; these devices are known as super-Turing machines orhypercomputers. Superminds, as explained herein, also have properties no machine,whether above or below the Turing Limit, can have. The present book is the third andpivotal volume in Bringsjord’s supermind quartet; the first two books were What RobotsCan and Can’t Be (Kluwer) and AI and Literary Creativity (Lawrence Erlbaum). The finalchapter of this book offers eight prescriptions for the concrete practice of AI and cognitivescience in light of the fact that we are superminds.
SELMER
BR
ING
SJOR
D
AN
D M
ICH
AEL ZEN
ZENSU
PERM
IND
SPeople H
arness Hypercom
putation, and More
KLUWER ACADEMIC PUBLISHERS COGS 29
Bringsjord COGS 29 PB(2)xpr 07-02-2003 16:26 Pagina 1
!u!v["kH(n, k, u, v) # "k!H(m, k!, u, v)](programming)
Tuesday, October 1, 13
SupermindsPeople Harness Hypercomputation,
and More(2003)
Turing Limit
Information Processing
Subjective consciousness, qualia, etc. — phenomena in the incorporeal realm that can’t be expressed in any third-person scheme
persons
animals (chess, go, swimming, flying, locomotion)
Hypercomputation
People Harness Hypercomputation, and More
29
by
SUPERMINDSPeople Harness Hypercomputation, and More
bySelmer Bringsjord and Micael Zenzen
This is the first book-length presentation and defense of a new theory of human andmachine cognition, according to which human persons are superminds. Superminds arecapable of processing information not only at and below the level of Turing machines(standard computers), but above that level (the “Turing Limit”), as information processingdevices that have not yet been (and perhaps can never be) built, but have beenmathematically specified; these devices are known as super-Turing machines orhypercomputers. Superminds, as explained herein, also have properties no machine,whether above or below the Turing Limit, can have. The present book is the third andpivotal volume in Bringsjord’s supermind quartet; the first two books were What RobotsCan and Can’t Be (Kluwer) and AI and Literary Creativity (Lawrence Erlbaum). The finalchapter of this book offers eight prescriptions for the concrete practice of AI and cognitivescience in light of the fact that we are superminds.
SELMER
BR
ING
SJOR
D
AN
D M
ICH
AEL ZEN
ZENSU
PERM
IND
SPeople H
arness Hypercom
putation, and More
KLUWER ACADEMIC PUBLISHERS COGS 29
Bringsjord COGS 29 PB(2)xpr 07-02-2003 16:26 Pagina 1
!u!v["kH(n, k, u, v) # "k!H(m, k!, u, v)](programming)
Tuesday, October 1, 13
SupermindsPeople Harness Hypercomputation,
and More(2003)
Turing Limit
Information Processing
Subjective consciousness, qualia, etc. — phenomena in the incorporeal realm that can’t be expressed in any third-person scheme
persons
animals (chess, go, swimming, flying, locomotion)
Hypercomputation
People Harness Hypercomputation, and More
29
by
SUPERMINDSPeople Harness Hypercomputation, and More
bySelmer Bringsjord and Micael Zenzen
This is the first book-length presentation and defense of a new theory of human andmachine cognition, according to which human persons are superminds. Superminds arecapable of processing information not only at and below the level of Turing machines(standard computers), but above that level (the “Turing Limit”), as information processingdevices that have not yet been (and perhaps can never be) built, but have beenmathematically specified; these devices are known as super-Turing machines orhypercomputers. Superminds, as explained herein, also have properties no machine,whether above or below the Turing Limit, can have. The present book is the third andpivotal volume in Bringsjord’s supermind quartet; the first two books were What RobotsCan and Can’t Be (Kluwer) and AI and Literary Creativity (Lawrence Erlbaum). The finalchapter of this book offers eight prescriptions for the concrete practice of AI and cognitivescience in light of the fact that we are superminds.
SELMER
BR
ING
SJOR
D
AN
D M
ICH
AEL ZEN
ZENSU
PERM
IND
SPeople H
arness Hypercom
putation, and More
KLUWER ACADEMIC PUBLISHERS COGS 29
Bringsjord COGS 29 PB(2)xpr 07-02-2003 16:26 Pagina 1
!u!v["kH(n, k, u, v) # "k!H(m, k!, u, v)](programming)
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
What is AI for you?
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
What is AI for you?
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
Elevated AI only!:
“The ultimate goal of AI is to build a person, or more humbly, an animal.” —C&M
What is AI for you?
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
Darwininan “Canine” AI
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
“Monkey” AI
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
“Full-Watson” AI
Tuesday, October 1, 13
MiniMax
ularit
y
Logic
propo
stional
logic
semant
ic-web
logic
s
descr
iption l
ogics
fragm
ents
of FOL ...temporal
temporal+epistemic
temporal+epistemic+deontic
Lw1,w
Art of Infallibility 1
UIMA outp
ut
+planning+arg semantics
epistemic
...
FOL
heterogeneous/visual
Infinitary (AoI 2)
SOL
...
Person-Aspiring AI
Tuesday, October 1, 13