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IMPROVING ARTIFICIAL INTELLIGENCE BY STUDYING

THE BRAINGUNNAR NEWQUIST, PHD

WHAT IS THE MOST COMPLICATED OBJECT IN THE KNOWN UNIVERSE?

Question

Human brain(1.3kg)

Sperm whale brain(7.8kg)

5x the size!!

ALL ARTIFICIAL INTELLIGENCE IS LOOSELY BASED UPON THE BRAIN

ARTIFICIAL INTELLIGENCE (AI)

• KDD = knowledge discovery in databases

-- the capacity of a computer to perform operations analogous to learning and decision making in humans

HOW ARE WE DOING AT MIMICKING THE BRAIN WITH AI?

WHAT AI IS GOOD AT:• Repetitive tasks• Identification (objects, faces, words)• Narrow tasks• Finding patterns in big data

Novembre et al., 2008, Nature

WHAT THE BRAIN IS GOOD AT:

• Non-repetitive behavior (variability)• Instant recognition & response• Flexibility• Open-ended tasks

ARTIFICIAL VS NATURAL INTELLIGENCE:MIRROR IMAGES

AI: mimic what humans do• Great at repetition• Great at data processing• Great at narrow tasks

NI: what humans do• Great at flexibility• Great at instant decisions• Great at open-ended tasks

THE INTELLIGENCE WE REALLY WANT

Artificial General Intelligence

AGI: The ability of a machine to machine to learn, plan, and acquire new skills in complex environments

HOW DO WE BRIDGE THE AI INTELLIGENCE GAP?

1) Big Data with Deep Learning

2) Neuroscience: Figure out what brains do

DEEP LEARNING WITH BIG DATA

• Record everything you can about the world, and sort into patterns

• Knowledge-based -> Data Oligarchy

• Problems?

Example: Ex Machina

NEUROSCIENCE: USING NEOCORTEX TO GET AI

Example: Vicarious

• Model neocortex for data flow• Big data and machine learning

techniques for learning• Neurocomputing approach• Problems?

NEUROSCIENCE: SIMULATE BRAIN

• Thalamocortical model: 100 billion neurons with 1 quadrillion connections

• Biologically accurate neural types and numbers of neurons

• Neurocomputing approach

• Problems?

Example: Brain Corp

NEUROSCIENCE: BOTTOM UP APPROACH

• Behavior-based robotics

• No thinking. Just do something.

• Problems?

Example: iRobot

Genghis (mid-1980s)

BUT THAT’S NOT ENOUGH!!

• Big data doesn’t give anything new. Power ≠ intelligence.

• We don’t know all the details about human intelligence.

• Animals without a neocortex are smart.

NEUROSCIENCE: BOTTOM UP WITH LEARNING

Example: Brain2Bot

• Figure out the principles of intelligence starting at simple organisms and working up

WHERE WE ARE ATTACKING THE PROBLEM

Artificial General Intelligence

My interests: the fringe of AGI

HOW TO BUILD AGI PRINCIPLES• Every aspect of human intelligence is found in some form in other animals.

• Compare brains!

tools

conversation

Optimal navigation

Action planning

WHY WORK FROM THE BOTTOM UP?

• Ability to understand much more about simple animals than complex ones.

• Genetics

• Brain cell identity

• Control

MOLECULAR PRINCIPLE OF LEARNING

• No biological principle of learning for AI!• Need to build a biological principle if we want AGI

PRIORITIZATION• Animals have different states

• Robots need to have different behaviors based upon a particular situation

playingalert

CONTEXT SPECIFIC LEARNING

• Flies can tell the difference between the same stimulus at different times of day!

• Self-driving car needs to operate differently under different conditions.

• (Do you want a data-geek from SF to teach your autonomous car to drive in the snow?)

morning night

odor

mmm… food

odor

Run Away!!

SMALL DATASET IDENTIFICATION

• Wasps recognize faces!

• Computer facial recognition without big data.• http://www.sciencemag.org/news/2015/02/wasps-employ-facial-recognition-defend-nests

VARIABILITY

• Each bird has a unique signature to its song.

• How to build creativity

NON-STEREOTYPED MOVEMENT

• Master musicians are more flexible, not more stereotyped

• Give flexibility to robots in uncertain environments

NAVIGATION WITHOUT GPS OR MAPS

• Bees find the optimum path without GPS or mapping their whole environment.

• Safe-guard internet/satellite connectivity in autonomous vehicles

HUMANS AREN’T ALWAYS THE SMARTEST!

• Squirrels can remember more nut locations over winter than we can.

MANY WAYS TO BUILD A COMPLEX BRAIN

• Why do these animals need such brain complexity?

Elephant-nosed fish(same brain/body ratio as humans)

Long-finned pilot whale(more neurons in cortex than humans)

WANT SAFETY?

• Smart machines are safer than dumb machines.

Moral judgment Emotional connection Cost-effective/efficient

WHY GETTING AGI RIGHT IS IMPORTANT

• Technology could solve many of our problems, but we have to be able to trust it and listen to it.

• We want AI that relates well to us, not terminators and stupid machines

• Self-driving cars need to be safe.

• AI needs to work for everyone, not just some.

NEUROSCIENCE IS OUR BEST AGI STRATEGY

• By principle, deep learning and traditional AI is not developing AGI

• Deep learning optimizes a specific response

• Animals do flexible, variable, and creative responses

To get AGI, we might have to understand the most complex thing in the known universe

But not without understanding this: