Ben Goertzel - Singularity Summit Australia talk in 2011

Artificial General Intelligence: 1950-2050

Dr. Ben GoertzelCEO, Novamente LLC and Biomind LLC

CTO, Genescient CorpCo-Founder, OpenCog Project

Vice Chairman, Humanity+External Research Professor, Xiamen University

Advisor, Singularity Institute and Singularity University

Wednesday, September 7, 2011

1950-1970


1970-1990


1990s


2001



2011


The Robot Revolutionis Accelerating


“Narrow AI”, rather than“Artificial General Intelligence” (AGI)

still dominates the AI field


Artificial General Intelligence (AGI)

Humans are, in a certain sense, general-purpose rather than narrowly specialized intelligences…

General intelligence may be loosely conceived as

“The ability of a system to achieve a variety of complex goals in a variety of complex environments using limited computational resources -- including goals and environments that were not anticipated at the time the system was created.”


General intelligence in regard to the environments & goals for which humans evolved, and in which humans now operate, involves certain key competencies



2009 AGI Roadmap Workshop


Current virtual world platforms have some fairly severe limitations, which fortunately can be remedied with effort

Object-object interactions are oversimplified, making tool use difficult

Agent control relies on animations and other simplified mechanisms, rather than having virtual servomotors associated with each joint of an agent’s skeleton


Partial solution: Integration of a robot simulator with a virtual world engine

Player / Gazebo: 3D robot control + simulation framework

OpenSim: open-source virtual world

It seems feasible to replace OpenSim’s physics engine with appropriate components of Player/Gazebo, and make coordinated OpenSim client modifications

+


Current Virtual Worlds lack fluids, powders, pastes, fabrics … they donʼt completely implement

“naïve physics”


One possible solution: bead physics

Spherical beads with specially designed adhesion properties can emulate fluids, fabrics, pastes, strings, rubber bands, etc.

Bead physics can be added to virtual world physics engines


Possible solution: build robots from “macrocells” -- flexible ball-like units that can stretch into different shapes, sense the environment, and pass power and

information to each other

Current robots are made mainly of inert parts -- very few of their parts are sensors or actuators...

claytronics, etc.??


2020Wednesday, September 7, 2011

2020:Rise of the

Robot Children



animal/childlike

AGI+

useful narrow AI =

useful early-stage AGI,

such as virtual AI scientists

2020:Rise of the

AI Scientists


one path to a powerful global brain: AGI + narrow-AI + humans + communication networks

2020:Emergence of

a more reflective,deliberative global brain

spanning AGIs,narrow AIs and humans



2030:One Big

AI Network


2030:Jacked into

the AI Network



Kurzweil projectstechnological Singularity

around 2045


Text


A Very Hard Problem

Goal Invariance Under Radical Self-Modification

How to architect an AGI system so as

to maximize the odds that, as it radically self-modifies and self-improves, it will not lose track of its originally programmed/taught goal system?

And ... what are the goals/values that we want the AGI system to preserve as it evolves and grows and learns??


Another Very Hard Problem

Making Sure the “Good Guys” Win

Suppose we eventually do understand how to build a safe, powerful AGI, pursuing a positive value system...

How do we guarantee that this is the first kind that gets built and achieves wide influence?


Does Humanity Need an AI Nanny?

Humanity’s Dilemma

The rapid advance of technology seems effectively unstoppable

Advanced tech lets people with less education and resources cause more damage more easily

Solving the problem of engineering relatively safe, beneficial uber-God-minds is difficult and may take a while



What Might an AGI Nanny Be Like?

•General intelligence somewhat above the human level, but not too dramatically so

• Interconnection to powerful worldwide surveillance systems, online and in the physical world

• Control of a massive contingent of robots (e.g. service robots, teacher robots, etc.) and connectivity to the world’s home and building automation systems, robot factories, self-driving cars, and so on and so forth

• A cognitive architecture featuring an explicit set of goals, and an action selection system that causes it to choose those actions that it rationally calculates will best help it achieve those goals



What Might an AGI Nanny’s Goals Include?

•A strong inhibition against modifying its preprogrammed goals•A strong inhibition against rapidly modifying its general

intelligence•A mandate to cede control of the world to a more intelligent

AI within N years (where N could be, say, 10, 100 or 5000)•A mandate to help abolish human disease, involuntary

human death, and the practical scarcity of common humanly-useful resources like food, water, housing, computers, etc.•A mandate to prevent the development of technologies that

would threaten its ability to carry out its other goals•A strong inhibition against carrying out actions with a result

that a strong majority of humans would oppose, if they knew about the action in advance•A mandate to be open-minded toward suggestions by

intelligent, thoughtful humans about the possibility that it may be misinterpreting its initial, preprogrammed goals



Argument for Creating an AI Nanny

1.It’s impracticable to halt the exponential advancement of technology (even if one wanted to)

2. As technology advances, it becomes possible for individuals or groups to wreak greater and greater damage using less and less intelligence and resources

3. As technology advances, humans will more and more acutely lack the capability to monitor global technology development and forestall radically dangerous technology-enabled events

4. Creating an AI Nanny is a significantly less difficult technological problem than creating an AI or other technology with a predictably high probability of launching a full-scale positive Singularity

5.Imposing a permanent or very long term constraint on the development of new technologies is undesirable


OpenCog:An Open Source Software Framework

&A Design & Vision for Advanced AGI

• 2011-2012: A Proto-AGI Virtual Agent in a Videogame type world

• 2013-2014: A Complete, Integrated Proto-AGI Mind ... virtual world + humanoid robot

• 2015-2016: Advanced Learning and Reasoning

• 2017-2018: AGI Experts: biology, finance, service robotics,???

• 2019-2021: Full-On Human Level AGI

• 2021-2023: Advanced Self-Improvement

Extremely tentative schedule,

assuming the design/theory is basically right and funding is adequate


biomedicalinformatics

financial prediction /

analytics

video games / virtual worlds

robot toys

service robots

information retrieval

etc. !!!


memory

prediction

perception

action

goals

a mind uses

and

to do

of what

will achieve its

core operating principle of a general intelligence


Should we implement AGI via...

-- A single core complex cognitive process, supported by others as needed

-- Multiple simple processes interacting together, emergently yielding intelligence... ?

-- A number of complex cognitive processes, interacting together in a specific way? Glued together perhaps

using probabilistic & economic semantics?

The human brain seems involve a number of complex processes (modelable as algorithmic), interacting together in specified ways...


Which is critical?

-- The overall cognitive architecture?

-- The power of the learning algorithms?

-- Both? and they have to synergize well?

\


Which is critical?

-- The particulars of the system’s explicitly implemented processes and representations?

-- The structures and dynamics that emerge via complex self-organization, as the system grows and

learns?

-- Both? and they have to synergize well?

\


a mind is an evolving, autopoietic, self-referring set of patterns, associated with a system that’s interpreted as goal-achieving -- including patterns in the system and the world (and emergent

therebetween), and patterns regarding goal-achievement

2006 2010 2012 (?)


MotorSensory

Declarative Episodic AttentionalIntentional Procedural

OpenPsi

DeSTIN(vision / audition)

RewardHierarchy

Motor Control

Hierarchy

robot proxy

game proxy

memory

PLN (inference)

Pattern mining

conceptblending

dimensional embedding

MOSES Hillclimbing Internal simulation ECAN

(economic attention allocation

Language processing


DeclarativeProbabilistic Logic

Networks,concept blending,

language comprehension &

generation

Episodicinternal world

simulation engine

Attentional/Intentional

economic attention networks, adaptive

goal hierarchy

Sensoryhierarchy of memory/

processing units

ProceduralMOSES

(probabilistic evolutionary

learning),hillclimbing

cognitive synergy in OpenCog

In OpenCog, multiple cognitive processes act concurrently on the

same knowledge store


Psi Architecture Overviewfigure from “Principles of Synthetic Intelligence” by Joscha Bach


Explicit knowledge representation:

Nodes and links (collectively “Atoms”) that explicitly encode individual pieces of knowledge

Implicit knowledge representation:

Knowledge that is encoded in the coordinated structure or activity of a large set of nodes and links

Knowledge Representation in OpenCog


MindAgents are objects that act on the Atomspace: modifying, adding and/or removing Atoms

MindAgents’ activities are scheduled by a Scheduler: the simplest Scheduler would just cycle through all available MindAgents

OpenCog involves a carefully constructed combination of MindAgents, intended to reinforce rather than confuse each other!


Currently the OpenCog “core (AtomSpace, scheduler, comms,

saving to disk, etc.) is C++ for Unix, with an STL-based API

MindAgents are currently

coded in C++ or Python.

Some MindAgents also invoke

external Java processes


Economic Attention Allocation

Each node or link in the AtomSpace is tagged with a probabilistic truth value, and also with an “attention value”, containing Short-Term Importance and Long-Term Importance components.An artificial-economics-based process is used to update these attention values dynamically -- a complex, adaptive nonlinear process.


MOSES Probabilistic Evolutionary Learning

Combines the power of two leading AI paradigms: evolutionary and probabilistic

learning

Extremely broad applicability. Successful track record in bioinformatics, text and data mining,

and virtual agent control.

Moshe Looks 2006 PhD thesis: metacog.org

Probabilistic Logic NetworksA highly general, practical integration of

probability theory and symbolic logic.

Extremely broad applicability. Successful track record in bio text mining, virtual agent control.

Based on mathematics described in Probabilistic Logic Networks, published by Springer in 2008

Two Key Algorithms for Procedural and Declarative Knowledge Creation


adviceinput

below

belowbelow

between

aligned on axis perpendicular to

mouth-nose-eyes axis...

visual patterns (e.g. DeSTIN centroids) corresponding to

the semantic perception node linked to “human

eye”

concept node

phrase node

“human eye”

referencelink

PERCEPTUAL CSDLN

SEMANTIC-PERCEPTUAL CSDLN

COGNITIVESEMANTICNETWORK

referencelink

referencelink

semantic HTM nodes/linksformed by pattern mining

perceptual HTM

semantic HTM provides probabilistic biasing to

perceptual HTM

aligned on axis perpendicular to

eyes axis

CSDLN = “Compositional Spatiotemporal Deep Learning

Network, e.g. HTM, DeSTIN,...


grasp object

The motoric hierarchy node corresponding to a particular set of servomotors, might for instance contain

clusters of paths through configuration space that the servomotors have historically followed.

MOTORIC CSDLN

SEMANTIC- MOTORIC CSDLN

rotate arm toward object

raise or lower arm toward object

raise or lower arm toward default position

after

after

before/after/simultaneous

get object

adviceinput

COGNITIVESEMANTICNETWORK

“get”

phrase nodeconcept node

referencelink

referencelink

referencelink

motor patterns (e.g. centroids) corresponding to the semantic motoric

node “raise or lower arm toward object”




This shows OpenCog oscillating between the robot's "home" and batteries, as a result of its quests to fulfill integrity and energy demands respectively. After a few movements back and forth, it also shows the Psi monitor updating graphs of the Psi variables (note the updates are synchronized between graphs).



Piagetan Stages of Development


Text


Ben Goertzel - Singularity Summit Australia talk in 2011

Technology