Making Intelligence

Artiﬁcial Intelligence Joseph Gentle

Ability to make optimising choices Intelligence

Input Output Intelligence Reward

Input Input Input Input Output Output Output Intelligence Output Intelligence Intelligence Intelligence Reward Reward Reward Reward

Observations Actions Intelligence Reward

Observations Actions Intelligence Goal

Input Output Choice Reward

Input Guided Output Choice Reward

Ability to make optimising choices

Ability to make optimising choices een etw eb oos uts Ch utp o

Ability to make optimising choices een etw eb oos uts Ch WRT Reward Function utp o

Input Guided Output Choice R T Maximise R(t) t=0

Input Guided Output Choice R T Maximise R(t) dt 0

Input Guided Output Choice R T Maximise t R(t)γ dt 0 γ ≈ 0.99

Examples

Chess Player Chess board Move Chess Player Victory?

Vacuum Cleaner Sensors Vacuum Motors Cleaner AI Cleanliness of ﬂoor - run out of power?

Clean my Write a Play Chess ﬂoor sonnet

Clean my Write a Play Chess ﬂoor sonnet Chess Vacuum Sonnet Player Cleaner AI writer

Clean my Write a Play Chess ﬂoor sonnet Chess Vacuum Sonnet Player Cleaner AI writer Generalisable Intelligence

Philosophy

Output Intelligence Reward

Input Output Intelligence

Input Random! Intelligence

Input Intelligence Reward

Input Choice?? Reward

Input Intelligence

Intelligence World Input

Understanding Intelligence World Input

Prediction Intelligence World Input

Input Intelligence Output Reward

Input Intelligence Output ∞

Input Intelligence Random! ∞

People

Ability to make optimising choices Input Output Intelligence Reward

Input Output Choice Reward

Brain Output Input Choice Reward

Brain Muscle control Senses Choice Reward

Brain Muscle control Senses Choice Instantaneous long term sum of instantanious reward Happiness

Brain Muscle control Senses Choice Reward

Brain Conscious Muscle control Senses Choice Reward Subconscious

Brain Conscious Muscle control Senses Choice ∞ Subconscious

Ability to make optimising choices Input Output Intelligence Reward

Bias Its a good thing.

1, 2, 3, ? 2, 4, 8, ? 2, 4, 6, ?

1, 2, 3, ?

4 1, 2, 3, ? Increasing numbers

5 Fibonacci sequence 4 1, 2, 3, ? Increasing numbers

5 Fibonacci sequence 4 1, 2, 3, ? Increasing numbers 2 Largest prime dividing N

5 5 Square-free Fibonacci numbers sequence 4 6 1, 2, 3, ? Increasing Central binomial numbers coefﬁcients 10 2 Numbers with no Largest prime carry when squared dividing N

Source: Online Encyclopedia of Integer Sequences

5 5 Square-free Fibonacci numbers sequence 4 6 1, 2, 3, ? Increasing Central binomial numbers coefﬁcients 10 2 Numbers with no Largest prime carry when squared dividing N

5 5 Square-free Fibonacci numbers sequence 4 1, 2, 3, ? Increasing numbers 6 10 2 Central binomial Numbers with no Largest prime coefﬁcients carry when squared dividing N

4 1, 2, 3, ? Increasing numbers

1, 2, 3, 4 is the simplest pattern 4 1, 2, 3, ? Increasing numbers

1, 2, 3, 4 is the simplest pattern 4 1, 2, 3, ? Increasing numbers 1, 2, 3, 4 is a common sequence

1, 2, 3, 4 is the Simplicity simplest pattern 1, 2, 3, 4 is a Induction common sequence

1, 2, 3, 4 is the Simplicity simplest pattern The simplest explanation is usually the best. Ockham’s Razor

Patterns repeat Induction 1, 2, 3, 4 is a Induction common sequence

Things we’ve seen New things before Simplicity Induction

Simplicity 1, 2, 3, ? 5 5 Square-free Fibonacci > 4 numbers sequence 6 Increasing numbers Central binomial coefﬁcients 10 2 Numbers with no Largest prime carry when squared dividing N

Simplicity 1, 2, 3, ? Largest prime dividing the number’s position in 2 the sequence 5 Numbers in the Fibonacci sequence from n = 2 5 Natural numbers which aren’t perfect squares 4 Natural numbers 6 Central binomial coefﬁcients of C(n, f loor(n/2)) 10 Natural numbers with no carry when squared

Simplicity 1, 2, 3, ? 4 Natural numbers 10 Natural numbers with no carry when squared 5 Numbers in the Fibonacci sequence from n = 2 5 Natural numbers which aren’t perfect squares 6 Central binomial coefﬁcients of C(n, f loor(n/2)) Largest prime dividing the number’s position in 2 the sequence

Simplicity Length 15 Natural numbers 43 Natural numbers with no carry when squared 44 Numbers in the Fibonacci sequence from n = 2 46 Natural numbers which aren’t perfect squares 49 Central binomial coefﬁcients of C(n, f loor(n/2)) Largest prime dividing the number’s position in 62 the sequence

The length of the shortest generating program in a given language Kolmogorov Complexity

Simplicity Central binomial coefﬁcients of C(n, f loor(n/2)) 49 Largest prime dividing the number’s position in 62 the sequence

Simplicity 15 Natural numbers Natural numbers with no carry when squared 43 Numbers in the Fibonacci sequence from n = 2 44 Natural numbers which aren’t perfect squares 46 Central binomial coefﬁcients of C(n, f loor(n/2)) 49 Largest prime dividing the number’s position in 62 the sequence

Architecture

Brain Senses Motor Control

Brain Mapping Senses Vision Write Sonnets Hearing Play chess Motor Taste Control Choice Reward function

Born with Learned Vision Write Choice Sonnets Hearing Taste Reward Play chess function Mapping

Senses Motor Control Brain These are NOT the same Take inspiration, not knowledge! Input Output Intelligence Reward

Intelligence Input Output Reward .... and remember you can design this however you want!

Neural Net Intelligence Input Output Reward

Robotics Intelligence Input Vision Output Mapping Choice function Value function Reward

Robotics approach is hard because you have to engineer all the behaviours Born with Learned Nerural nets approach is hard because your neural net needs to be able of learning everything. Robotics Neural Net Vision Mapping Choice Value function function

Born with Learned Robotics Neural Net Vision Mapping Choice Value function function

Clean my Write a Play Chess ﬂoor sonnet Chess Vacuum Sonnet Player Cleaner AI writer Generalisable Intelligence

My Architecture

Intelligence Input Input model World model

Intelligence Input Input model World model Value function Reward

Intelligence Input Input Action model model World model Value function Reward

Intelligence Input Input Action model model World model Value function Output Reward Choice function

Intelligence Input Input model World model

Input Intelligence

Intelligence World Input

Understanding Intelligence World Input

Prediction Intelligence World Input

Prediction Intelligence World model World Input Input model

Prediction Intelligence World model World Input Input model Prediction Accuracy

Input Intelligence Predictions World model Input model Prediction Accuracy

My Bias

Prediction Intelligence World model World Input Input model

World model = World Input model

Prediction Intelligence World model UNKNOWN World Input Input model

World Intelligence World model World Input Input model World

Intelligence World model 1, 2, 3, ? Input

5 Fibonacci sequence Intelligence 4 World model 1, 2, 3, ? Increasing Input numbers 2 Largest prime dividing N

Intelligence World model 1, 2, 3, 4 Input Increasing numbers

Simplicity Intelligence World model 1, 2, 3, 4 Input Increasing numbers Induction

1, 2, 3, 4 is the Simplicity simplest pattern 1, 2, 3, 4 is a Induction common sequence

Simplicity Induction

Small model > Simplicity Big model Induction

Small model > Simplicity Big model Induction Learn patterns

Input Intelligence Predictions World model Input model Prediction Accuracy

Input Intelligence Predictions World model Input model Prediction Accuracy Learn patterns Prefer small models

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Making Intelligence

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