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Archive for February, 2011

Last night my wife and I ended up seeing The King’s Speech.   We set out to watch Black Swan, but it was sold out.

I was disappointed at the time and still am a little bit.   The King’s Speech was a fine movie, but when you have a rare baby sitter night you want what you want…

Alas, one facet of The King’s Speech intrigued me quit a bit.   How does someone in a position of fame behave when they realize the reality of the facade.   Colin Firth brilliantly played a fascinating character without anchors.   The scene with Geoffrey Rush sitting in Edward’s throne in Westminster Abbey was the clearest example of this.

“People have carved there names in this chair!   I don’t care how many royal assholes…”

A throne with graffiti still used in a coronation ceremony!   What could be more anchorless!

Even at the end of the movie, Firth still had this look when he was waiving at the throngs of people “What is all this for?!”

Not sure there is a resolution to this quandary for any of us and certainly not for a monarch in name.   Oh, sure, we can all find a justification if we don’t question too hard and profess it out to the world enough….

Other thoughts to follow up on:

Impact of radio/mass broadcasting to politics, power, public policy

Current obsession with Monarchy and America’s own “monarchs in name”

 

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UPDATE: I missed SWs blog post.  Brilliant!

Early versions of this approach go back nearly 50 years, to the first phase of artificial intelligence research. And incremental progress has been made—notably as tracked for the past 20 years in the annual TREC (Text Retrieval Conference) question answering competition. IBM’s Jeopardy system is very much in this tradition—though with more sophisticated systems engineering, and with special features aimed at the particular (complex) task of competing on Jeopardy.

Wolfram|Alpha is a completely different kind of thing—something much more radical, based on a quite different paradigm. The key point is that Wolfram|Alpha is not dealing with documents, or anything derived from them. Instead, it is dealing directly with raw, precise, computable knowledge. And what’s inside it is not statistical representations of text, but actual representations of knowledge.

 

Maybe you’ve seen the latest NOVA episode about Watson, the AI machine that played Jeopardy against former champions.

The first blush answer would be: NO.

The linguistics are simply not there yet.

However, if Jeopardy questions were more “computational” vs. linguistic and fact retrivial the answer might be: YES.

Wolfram|Alpha has the raw power to do it, but it lacks the data and linguistic system to do it.

IBM was clever to combine the history of Jeopardy questions with tons of documents.    It’s similar, but not the same as, common sense engine from Cyc.    It’s not fully computational knowledge.  It’s semantic.   It’s cleverness comes from the depth of the question training set and the document training set.

It would breakdown quickly if it were seeing questions about facts that had never been printed in a document before.   An example would be “How far away will the moon be tomorrow?”

Wolfram|Alpha can answer that!   Now, what’s challenging is that there is a much bigger universe of questions that have never been asked than those that have!   So Wolfram|Alpha already has far more knowledge.   However, its linguistics are not strong enough to clearly demonstrate that AND it will probably never catch up!   Because Wolfram|Alpha can answer questions that have never been asked so people will always ask it questions that will trip it up… they will always push the linguistics.

In the end, a combination of Watson, Wolfram|Alpha and Cyc could be very fun indeed!

Perhaps we should hack that up?

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Here’s another article about how the machines will take over and make everything better.

It could draw on huge amounts of data effortlessly. It wouldn’t even take breaks to play Farmville.

Funny, but seriously…
Who’s to say the evolution of “intelligence” doesn’t involve the evolution of play… in fact in might be necessary.
not quite sure why every contemplation of a super smart singularity future simply involves bigger problems being solved.   history doesn’t suggest that’s how it works.

it’s plausible that other systems in the universe have already passed a singularity.   and perhaps we’re their little toy.  and what they did with their super intelligence was set up an experiment to see how things develop.   their own farmville.

it’s also plausible that ever increasing intelligence in the human sense doesn’t amount to squat in the multi verse.   Maybe the multi verse just does what it does and intelligence is a side effect that burns out like a super nova…  maybe it’s common, maybe it’s rare…

the problem with chasing the singularity is we probably don’t have much control over how things evolve.   Can’t say I want the machines to take over or not.  I’m pretty sure I won’t know the difference when and if they do, just like I didn’t notice how The Internet changed us and I couldn’t really prepare for it.    Other generations could say that about birth control, electricity, the printing press, telescope, the wheel, whatever.   Again, things happen.  we behave.  then occasionally we notice, “Gee, looks like something changed”.

 

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This morning is quite amusing in Austin.

Snow fell.   and exposed a severe shortage of knowledge about the world.

I watch a guy pour a small cup of coffee in front of his wheels to help him spin the tires.   Severe misunderstanding of the Heat Equation and Phase Transitions.  The coffee froze.  The car did not escape.

Just now I watched 5 cars spin out on our neighborhood iced over hilly streets.   Probably missed the class on the Coefficient of Friction.

Let’s see how many more physics lessons come up today here in Texas!

 

 

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I think the fundamental explanation of everything is going to come down to that.

No more.

and certainly no less.

networks of networks.   just the relation of nodes to other nodes to other nodes.

Uncomputable.  Never ending.  Always changing.

Spacetime = network.

mass ~ energy ~ network

humans ~ network

here’s some stuff to consider:

Networks of the brain

Space as a network

Graph Theory Background

A History Chart

network of tennis pros research paper

 

 

 

 

 

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