COGNITIONCOGNITION
byby
Horst ForsterHorst Forster
Interfaces, Knowledge and Content Technologies; Interfaces, Knowledge and Content Technologies; Applications, Information MarketApplications, Information Market
DG Information SocietyDG Information Society
Brussels, 29.01.2003Brussels, 29.01.2003
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Subject area:
Digital content
Remit:
Make information accessible to all
Overcome multilingual barriers
Three pillars:
Market Applications
Research
Our missionOur mission
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Scope and instrumentsScope and instruments
Research and Technology DevelopmentResearch and Technology Development
Interfaces and CognitionInterfaces and Cognition
Knowledge management and Content creationKnowledge management and Content creation
ApplicationsApplicationsTechnology Enhanced Technology Enhanced
LearningLearningCultural HeritageCultural Heritage
Information Information MarketMarket
Public Sector Info.Public Sector Info.e-Contente-Content
e-Safee-Safe
Legis
lative
Legis
lative
mea
sure
s
mea
sure
sFinancial
Financial
intervention
interven
tion
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Cognition in SystemsCognition in Systems
Information technologies today
data, information, content - can be processed and transformed, transmitted and distributed, stored and displayed,…
Next step
data, information, content - can be interpreted
(understanding and context)
How? Combine with knowledge!
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Cognition in systems – why?Cognition in systems – why?
speech recognition natural ‘hands-free’ interfaces (eg: for mobile and wearable devices)
understanding semantics of information interactive Web services (eg: for tourism)
recognition and tracking in broadcast video creation of sports event statistics in real-time (eg: for advertisers, for audience)
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technological timescapetechnological timescape
1980s: cheap, small processors ubiquitous computing
1990s: cheap, small lasers ubiquitous communications
2000s: cheap, small sensors ubiquitous perception ??
sensors link world of interconnected computation
with real physical world
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perception and computationperception and computation
systems that:
‘see’, ‘hear’, ‘smell’ …
combined with computation to:
‘recognise’, ‘categorise’,‘understand’, ‘decide’, ‘act’ …
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what more do we need??what more do we need??
Interpretation requires more than ‘data’ computation
knowledge of context / situations
knowledge of tasks / goal
Knowledge-based systems
So where are these systems?
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the elusive real-world…the elusive real-world…
Process lines in factories: visual recognition capabilities empower robots to do intricate tasks … yet they can’t help out in the home
The Voice Web: telephone speech recognition can allow automation of customer services … but in very specific application domains
The issue at hand:
constrained conditions and artificial environments
versus
the endlessly variable ‘real world’
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more and more knowledge…more and more knowledge…
‘Real world’ environments and applications:different contexts and situations requires
knowledge to be adapted broader concerns require more and different kinds
of knowledge
systems fail in situations not envisaged in their design (lack of robustness)
systems function within narrow application domain (limited versatility)
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Systems that ‘know’ what they Systems that ‘know’ what they are doingare doing
Build bigger knowledge-bases?
No! – search becomes computationally intractable!
Cognitive systems?
systems that can extend their knowledge by reasoning and by learning from what they perceive
and use this knowledge for the purpose of achieving their performance goals
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Cognition - Why now? Cognition - Why now?
progress in artificial intelligence
progress in cognitive neuroscience
cheap and plentiful computing power
commoditisation of miniaturised sensors
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a window to the world…a window to the world…
Machines that ‘see’ the user: i. interprets gestures / behaviour adaptive,
natural interfaces
Machines that ‘see’ the environment: ii. performs visual tasks that are difficult, tedious or
impossible for humansiii. moves and navigates itself to perform various
tasks for humans (autonomous mobile robots)i and ii ONLY
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Research agendaResearch agenda
1. multimodal interfacesresearch: recognise speech and gestures; learning and adapting to behaviourtarget: facilitating natural interaction between humans and machines applications:user-friendly PCs(!!),wearable interfaces, smart clothes, intelligent rooms, collaborative work environments
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Research agendaResearch agenda
2. Semantic–based knowledge systemsresearch: annotation of content with ‘formalised’ knowledge; development of machine-processable vocabularies (ontologies) target: automated systems for knowledge handling applications:
knowledge discovery in databases, dynamic information services, automated diagnosis and decision support systems, Semantic Web (in time!)
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Research agendaResearch agenda
3. Cognitive systems research: integrate perception, action, representation, reasoning and learning in systems target: systems that do more than ‘canned’ predefined tasks; systems that handle new task specifications on the fly applications:image interpretation (eg: in medical or aerospace domains), behavioural interpretation (eg: in crowd surveillance or traffic monitoring), specialised interfaces (eg: sign language interpretation)
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progressprogress??
eg: machine vision systems:
10 y ago: maintain a description of the identity of objects or actors in a scene,
5y ago: … identity and the location …,
recently: … identity, location and the role …,
towards systems that are aware
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… … ultimately ultimately ……
The introduction of cognitive capabilities into systems will provide a quantum leap in functionality and flexibility:
systems that ‘know’ what they are doing
This is an evolutionary process!
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implicationsimplications
versatility: cost robustness: reliabilty , availibility
extend: scope functionality
efficiency
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On a final note….On a final note….
Progress in IT is not driven by speed and capacity alone.
As computing and communications become ubiquitous,
cognition will emerge as a key enabling technology
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