Re: AI works best when humans are there to hold its hand.

David

just seen this - tried to join your CG a couple of times but its not
happening
Pinged the sysadmin today, So swamped-

Now, to that diagram, how fun!! where did you get the
https://www.w3.org/Data/demos/chunks/robot/sound from????

its the sound effect that does the trick


However, I dont see the cognitive level, I must admit, Perhaps you could
tell more about the cognitive aspect of this robot?
where is the cognitive modelling?

To me, this is pure mechanical automation, I do not see any bit of
intelligence or any creativity in such a process
Mechanical automation has become very sophisticated these days, and very
fast!!!

https://www.youtube.com/watch?v=4DKrcpa8Z_E

Your simulation is fun, but it is nowhere near the state of the art in the
real world afaik but maybe you can say a bit more..

I am intersted in automating higher cognitive functions, for example, one
of the challenges would be to create
new designs and no, I dont think ANNs can do that they only spit out a
probabilist remodelling of some input

Tell us more about the cognitive model behind your wine filling robotic arm

Feature request: a robot that can fold origami following the algo

p

On Tue, Jun 16, 2020 at 4:22 AM Dave Raggett <dsr@w3.org> wrote:

> See also:
>
> *An understanding of AI’s limitations is starting to sink in*
> After years of hype, many people feel AI has failed to deliver, says Tim
> Cross
>
>
>
> https://www.economist.com/technology-quarterly/2020/06/11/an-understanding-of-ais-limitations-is-starting-to-sink-in
>
> Including:
>
> Real managers in real companies are finding AI hard to implement and that
> enthusiasm is cooling
>
>
> and this:
>
> They are powerful pattern-recognition tools, but lack many cognitive
> abilities that biological brains take for granted. They struggle with
> reasoning, generalising from the rules they discover, and with the
> general-purpose savoir faire that researchers, for want of a more precise
> description, dumb “common sense”. The result is an artificial idiot savant
> that can excel at well-bounded tasks, but can get things very wrong if
> faced with unexpected input.
>
>
> That’s why the W3C Cognitive AI CG is focusing on mimicking the human
> brain at a functional level, and benefiting from hundreds of millions of
> years of evolution. This has involved a shift in mindset from logic and
> formal semantics to a more cognitive approach.
>
> Manual development of symbolic AI doesn’t scale either, but a combination
> of symbolic and statistical approaches paves the way to cognitive agents
> can that can learn from experience guided by human collaborators.
>
> The immediate challenge is to open up the use of natural language through
> incremental concurrent processing of syntax and semantics as a basis for
> addressing the abundant ambiguity in natural language and paving the way
> for teaching cognitive agents everyday skills.
>
> This is a lot easier to arrange in a cognitive architecture as it is
> trivial to launch cognitive processes by setting goals that trigger
> reasoning. You can get a first glimpse of a very simple demo at
>
> https://www.w3.org/Data/demos/chunks/nlp/toh/
>
> On Chrome it also supports speech recognition - click the microphone then
> hit enter if the text that appears after a second or two looks okay. This
> demo invokes cognition after generating the word dependency graph. The next
> demo will use fully concurrent processing of syntax and semantics.
>
> Whilst Google’s speech recognition is pretty good, today’s neural network
> based speech recognition lacks context, and real-time integration with
> semantics that would make it much more effective. In the longer term,
> integration with emotional processing will allow further for natural human
> machine interaction.
>
> Here is a demo that shows how modelling the cortico basal ganglia circuit
> can support real-time control of factory machinery:
>
> https://www.w3.org/Data/demos/chunks/robot/
>
> The log shows a trace of goals and rule execution.
>
> This is just a few tiny steps along the road to strong AI, and I am hoping
> to complete a number of demos on NLP and various forms machine learning
> over the rest of this year.
>
> A formal spec is in preparation.
>
> Dave Raggett <dsr@w3.org> http://www.w3.org/People/Raggett
> W3C Data Activity Lead & W3C champion for the Web of things
>
>
>
>
>