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Prototype [Shared]

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by

Ali Alatas

on 22 August 2015

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Transcript of Prototype [Shared]

Bug model structure

Bot with integrated 'central nervous system'
The human cognitive and speech model applied to an autonomous agent
Model shows perception, thought and speech acting together
Bots might be able to use speech to communicate complex ideas
Prototype architecture

Language description of environment
Perception + mapping + quantification + schemata + language production
Bots would use real language for information trading and collaboration
Prototype as created

Hunger drives bots to move around mapping their environmental
Language enables bots to share mapped information
Shared information enables shared decision-making towards a common goal
Octopus-like body control (brain makes decisions, limbs carry them out semi-independently)
GOAP-based decision making
CONCERT OF EXPERTS
Concert of Experts

Multi-disciplinary group:
Arts (linguists, anthropologists, neuroscientists...); technical (engineers, mathematicians, designers...)
The development of a unified theory
'soft' (informal) theory
'hard' (formal) theory
Standardized Platform

Combined in one
Theory ('hard' and 'soft')
Application
Software AI
Hardware AI

Participation

Variegated access
Core group
Licensees
Academic affiliates
On-line community and open-source
Choice of participation increases circle of activity which increases unique perspectives
PLAN FOR A STANDARD PLATFORM
START-UP NEEDS
Startup needs

Resource injection needed at beginning
Guidance form those with industry experience
Development of wide 'exchange network'
BUSINESS OPPORTUNITIES
FUTURE PLANS AND PROJECTS
Future plans

New prototype requires new research direction
Simulation, autonomous agents, games, robotics, alien cognition...
The creation of a larger AI 'eco-system'
Extension of A.I. application to multiple fields
PROTOTYPE ARCHITECTURE
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APPLICATIONS
Applications

A testable model will aid digital cognition development and neuroscience
A unified theory will benefit hardware application such as robots and cognitive chips
Software models will allow for the exploration of unique non-human thought spaces
This stimulation will push fields from neuroscience to nanotech forward as they both feed off of and contribute to cognitive tech
Investment Choices
DIGITAL LIFE
Digital Life

Simple rules, emergent behavior (cellular automata)
Complex systems that achieve a balance between chaos and rigidity
Autonomous agents that can simulate thought and so intentional action
Differing forms of life, in differing contexts, even culture can now be simulated
COMPUTER GAMES
AI in real games

Realistic and unscripted action is now possible
Agents are now autonomous so must make decisions free from a common 'blackboard'
Natural dynamic speech both bot-bot and bot/user is now achievable
Richer environments free to change with or without user interaction
Game Support of Development

Millions of players become testers, deepening feedback
Provides a practical proof of the validity of the theory
Enables an independent income stream
CHAT BOTS
Digital Discourse bots

Eliza – elicited human-like qualities ina machine
Façade - used dynamic scripting as part of an interactive story
Siri and Cortana - possible realistic avatars
THE IRISH & MINORITY
LANGUAGES

Maintenance of indigenous languages
and environmental integrity
Anthropology affording understanding of culture/language dynamics
Minority languages across Europe empowering of speaker rights
Origins

The keeping of indigenous culture helps maintain environmental integrity
Better language teaching would help minorities use both local and national languages
The study of Anthropology enriched my personal understanding of history, culture, politics, medicine and technology

RESEARCH WORK CARRIED OUT
Research work in Korea

Creating a model of spoken language
Working with students
Uncovering psycho-linguistic structures
Experiencing another culture – opens new objectivity as an outsider looking on
THE MODEL OF LANGUAGE
DEVELOPED
Developing The Language Model

In university, there were early cognitive models
Teaching grammar and pragmatics uncovered more features
Topicality and speech management appeared to be broadly cross-linguistic
The only way to test the psycho-linguistic and pragmatic models was to apply them to bots
The Descriptive Model

In order for a computer to use language, it must be able to describe what it sees or 'thinks'
In order to make descriptions there must be a way to quantify perception
The re-purposing of an earlier 'ASER' model plus new additions made this possible
Once I had a way to 'capture' the complexity of perception in speech, I knew I could build a bot
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