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When Things Start to Think
One underlying theme dear to Gershenfeld's heart is the death of traditional academic distinctions between physics and engineering, or between academia and commerce. Applied research is real research.
Another major theme is that older technologies should be treated with respect as we seek to supplement or replace them. For example, a laptop's display is much harder to read in most light than the paper in a book.
The book starts by drawing a contrast between Digital Revolution and Digital Evolution. Digital Revolution is the already-tired metaphor for universal connectivity to infinite information and memory via personal computers, the Internet, etc. Digital Evolution describes a more democratic future, from Gershenfeld's point of view, when computers are so smart, cheap, and ubiquitous that they do many ordinary chores to help ordinary people. When things talk to things, human beings are set free to do work they find more appealing.
"What are things that think?" asks the first section of the book.
Gershenfeld's whizbang examples won't be big news to Slashdot readers. My favorite, the Personal Fabricator, ("a printer that outputs working things instead of static objects")-- whose relationship to a full machine shop analog is like that of the Personal Computer to the old-fashioned mainframe. Gershenfeld actually has one of these in his lab (it outputs plastic doohickeys)--seeing it was one of the high points of my visit there.
"Why should things think?" asks the second section.
My favorite here is the Bill of Rights for machine users. (In true Baby-Boom style, it's of list of wants arbitrarily declared to be rights.) "You have the right to
Have information available when you want it, where you want it, and in the form you want it
Be protected from sending or receiving information that you don't want
Use technology without attending to its needs"
Under the heading "Bad Words," Gershenfeld offers a snide but useful summary of many high-tech pop-sci buzzwords, showing how they get misused by people who don't understand their real content or context.
"How will things that think be developed?"
By making them small and cheap. By getting industry to pay the bills for targeted, practical research, using the Media Lab model TTT ("Things That Think.") By reorganizing education on the model of the Media Lab, where students learn things as they need them for practical projects, not all at once in a huge, abstract lump.
The book concludes with directions to various websites, including the Physics and Media Group (One of their projects these days is "Intrabody Signaling.") Slashdotters might also be interested in Gershenfeld's textbooks The Nature of Mathematical Modeling and The Physics of Information Technology.
You can purchase When Things Start To Think from bn.com, and Amazon has the book paperback discounted to $11.20. Slashdot welcomes readers' book reviews -- to see your own review here, read the book review guidelines, then visit the submission page.
I mean, come'on. We have pattern recognition, and bots that have huge libraries of information. We aren't anywhere near true AI, and won't be for several decades, unless some huge breakthrough occurs in learning algorithms.
I think we are going to look back a hundered years from now and say how silly we were to ever believe computers could think like we do.
How is a computer program ever going to adopt abstract thinking and creativity? Is a computer program ever going to invent mathematics without previous knowledge of it just because it finds it to be a useful utility for solving problems?
Heck, if someone could write a decent language translation program I might think there is a hope.
Humans already have loads of free time now and what do we do? We piss it away watching Jerry Springer and WWF eating cheezy poof's on the sofa turning into fat slobs.
For me, I'd rather spend a little more time outside and with real people instead of wiring myself more than I already am.
Technology has it's place...serving me not usurping me.
"TV, a medium as it is neither rare nor well done." Ernie Kovacs
Sounds like he makes a point or two:
"older technologies should be treated with respect as we seek to supplement or replace them"
This is something that most launches of new and amazing gadgets fail to see. An ebook is not better if it cannot offer more that an ordinary book. An ordinary book is usually the best book there is.
In the why section: "Be protected from sending or receiving information that you don't want "
Like "bug reports" to M$ with so much irrelevant info in 'em that they aught to pay the poor sucker's [who send them in] internet bill.
In the last section it looks like he is trying to get more funding: "By getting industry to pay the bills for targeted, practical research, using the Media Lab model TTT"
My favorite, the Personal Fabricator, ("a printer that outputs working things instead of static objects")
This bears resemblance to "Molecular Compilers" as imagined by Neal Stephneson in everyone's favourite nanotechnology novel, The Diamond Age, a device where you simply insert the program describing the object you want, plus payment, and return in an hour or so to retrieve your newly formed item.
Gives a whole new meaning to Internet Shopping...
sig:- (wit >= sarcasm)
Don't buy into the same hype that he uses
/. readers would love. (If you ever actually
to charm tech companies into donating to the Media
Lab. He's been spouting this stuff for so long he starting to believe it.
I also read several of his books: beware the typos and far-reaching statements. Although, "The Physics
of Information Technology" is something I believe
most
use any of the formulas in that book, look them up elsewhere... they're always slightly wrong.)
10:27am up 46 days, 18:02, 19 users, load average: 0.69, 0.35, 0.23
I must be late.
-JPJ
Feh.
Maybe you need a different PC?
As the header says, it does seem a bit overly optimistic. Esp: "When things talk to things, human beings are set free to do work they find more appealing." It just seems to scream utopia socalism, but more to the point in our history with all the great time saving inventions and methods, many "ordinary people" still spend as much time doing "chores" as they did 50, or even a 100 years ago.
Of course, if one is talking about the work place then there's an entierly differnt issue. That of unemployment. (I'm not saying wheter it's good or bad to introduce technology that can do another's job. I'm only saying it *is* an issue, esp. if you're somone who's job is at risk.)
...when computers are so smart, cheap, and ubiquitous that they do many ordinary chores to help ordinary people. When things talk to things, human beings are set free to do work they find more appealing.
This is the same old nonsense that's been touted ever since the age of the washing machine. Considering the thousands of labor-saving devices we've acquired throughout the 20th century, by this logic we ought to be living lives of perfect leisure now. But this isn't what happens. In industrial societies, "labor-saving" devices don't. Work expands to fill the time available. When things think, I'm sure you and I will be freed from the tedious chores of cooking, driving, cleaning, and living. We can become machines ourselves, consumed with work until we burn out or die.
(More at Talbot's Netfuture, if you're interested.)
He who refuses to do arithmetic is doomed to talk nonsense.
One underlying theme dear to Gershenfeld's heart is the death of traditional academic distinctions between physics and engineering, or between academia and commerce. Applied research is real research.
How would he know? MIT Media Lab, under Nicholas Negroponte, don't do anything that any academic or industry practitioner would consider to be "research". You see, in the words of Negroponte, they live in a world not of "atoms" but of "bits". In the world of atoms, researchers have to produce such things as peer-reviewed papers and working prototypes. In the world of "bits", researchers are measured by the number of column inches they get in Wired magazine. MIT Media lab churns out books and articles by the tonne, but it's little better than scifi, most of it, and very little of it is even original.
You would think that the hard-headed engineers at MIT would have seen that the Emperor has no clothes and would have cut off their funding by now, but mysterious the Media Lab clings to life. They are an embarassment to real futurists everywhere. Contrast them with the work done at IBM's labs, or BT's, or even Nokia, where stuff is made that actually makes an impact on the real world a decade or two later.
How will things that think be developed?"
By making them small and cheap.
The invisible addendum to this sentence is expendable. Small, cheap, and expendable - the mantra of the Japanese economy. Someday we'll be so deep in silicon poisoning that it will be a worldwide crisis, and we'll have to have a resolution like the Kyoto Protocol so that our president can ignore it. But like our automobile industry fifty years ago, we should march relentlessly ahead with abandon until we reach a crisis point, rather than attempt to head it off now.
If machines could truly think they would be screaming at us: "Don't Throw Us Out!!!".
Dr. Joseph Hairston
Superintendent, CCBC
C:\>uptime
'uptime' is not recognized as an internal or external command,
operable program or batch file.
C:\>Windows has found unknown command and is executing command for it.
C:\>Don't try to save your work because I'm rebooting now.
C:\>Warning, could not upload pirated software registry to Microsoft
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My grandfather once gave me a copy of this book. Being interested in what I do learning Artificial Intelligence he also read it. He found it clarifying the possibilities of AI and IT in general a lot. Him not having the slightest experience with computers generally would mean that it's not so interesting for someone deeper into the subject.
But while it's true that the book doesn't get really technical and left me wondering for a lot of the details, the enthusiastic way it's written and the really original projects that are described make it a really nice read. It's really motivating and can help the known problem of having learned a programming language and not having the slightest clue what to program in it.
I think that when you don't see it as a computer book but as reading material for a holiday the book deserves more than a 5. Borrow it from someone and read it, it's not like it'll take a lot of time.
Materialism can never offer a satisfactory explanation of the world.
For every attempt at an explanation must begin with the formation of
thoughts about the phenomena of the world.
Materialism thus begins with the thought of matter or material
processes. But, in doing so, it is already confronted by two different
sets of facts: the material world, and the thoughts about it.
The materialist seeks to make these latter intelligible by regarding
them as purely material processes. He believes that thinking takes
place in the brain, much in the same way that digestion takes place in
the animal organs. Just as he attributes mechanical and organic
effects to matter, so he credits matter in certain circumstances with
the capacity to think.
He overlooks that, in doing so, he is merely shifting the problem from
one place to another. He ascribes the power of thinking to matter
instead of to himself.
And thus he is back again at his starting point. How does matter come
to think about its own nature? Why is it not simply satisfied with
itself and content just to exist?
The materialist has turned his attention away from the definite
subject, his own I, and has arrived at an image of something quite
vague and indefinite. Here the old riddle meets him again. The
materialistic conception cannot solve the problem; it can only shift
it from one place to another.
(Philosophy of Freedom, Chapter 2)
Here is a poem that illustrate the limitations of a computerized brain:
No program can say what another will do.
Now, I won't just assert that, I'll prove it to you:
I will prove that although you might work til you drop,
you can't predict whether a program will stop.
Imagine we have a procedure called P
that will snoop in the source code of programs to see
there aren't infinite loops that go round and around;
and P prints the word "Fine!" if no looping is found.
You feed in your code, and the input it needs,
and then P takes them both and it studies and reads
and computes whether things will all end as the should
(as opposed to going loopy the way that they could).
Well, the truth is that P cannot possibly be,
because if you wrote it and gave it to me,
I could use it to set up a logical bind
that would shatter your reason and scramble your mind.
Here's the trick I would use - and it's simple to do.
I'd define a procedure - we'll name the thing Q -
that would take and program and call P (of course!)
to tell if it looped, by reading the source;
And if so, Q would simply print "Loop!" and then stop;
but if no, Q would go right back to the top,
and start off again, looping endlessly back,
til the universe dies and is frozen and black.
And this program called Q wouldn't stay on the shelf;
I would run it, and (fiendishly) feed it itself.
What behaviour results when I do this with Q?
When it reads its own source, just what will it do?
If P warns of loops, Q will print "Loop!" and quit;
yet P is supposed to speak truly of it.
So if Q's going to quit, then P should say, "Fine!" -
which will make Q go back to its very first line!
No matter what P would have done, Q will scoop it:
Q uses P's output to make P look stupid.
If P gets things right then it lies in its tooth;
and if it speaks falsely, it's telling the truth!
I've created a paradox, neat as can be -
and simply by using your putative P.
When you assumed P you stepped into a snare;
Your assumptions have led you right into my lair.
So, how to escape from this logical mess?
I don't have to tell you; I'm sure you can guess.
By reductio, there cannot possibly be
a procedure that acts like the mythical P.
You can never discover mechanical means
for predicting the acts of computing machines.
It's something that cannot be done. So we users
must find our own bugs; our computers are losers!
by Geoffrey K. Pullum
Stevenson College
University of California
have you been defaced today?
To quote Joe vs. the Volcano: '99% of people go through life asleep; the remaining 1% walk around in a state of constant amazement.'
To add to that I'd say: 99% of people *think* they're awake; the remaining 1% know they've got some waking up to do.
There you have it, your Zen moment of the day.
To be quite honest, if I'm still waiting for a Photoshop render, or a level to load in RTCW, our machines aren't ready to think.
To quote the [bad] movie Runaway:
"Humans aren't perfect so why should machines be perfect?"
Honestly, I see engineers and developers walking down the hall with their shirt half-tucked in and their shoes untied. A sign that either
- they can't think for themselves
- they don't care enough
Now, both of those indicators give me serious pause when I consider that they may be designing machines that "think." If the developers can't think for himself/herself, how is his/her "thinking" machine going to think? If the developer doesn't even care enough to tie his/her shoes, do they care enough to engineer a "thinking" machine to the very high degree it requires and can I trust them to care enough?I dunno. Maybe I'd feel better about all this if every time I turn around I didn't see Yet Another stack-overflow or buffer-overrun bug (yes, the quality of code is getting better but there is still too much of this crap.) Maybe I'm just a pessimistic pisser. Perhaps I enjoy laughing at an engineer when they fall flat on their face after tripping over their untied shoelace.
"Those who would sacrifice liberty for security deserve neither!"
The primary advantage of ebooks is pretty much the ability to search text, and take up little physical space.
But that's only really useful for reference texts. For fiction, only the lack of space is much of a benefit that is overwhelmed by all of the other complications ebooks offer (like needing to have power to read or have to deal with an interface to change pages).
I think the most successful eBook will be when they make a "real" book with pages out of electronic paper, and let books "flow" in and out of the eBook. Then you still have a paperback that doesn't require power to read, but you can carry hundreds or thousands of books with you in the space of one physical book.
"There is more worth loving than we have strength to love." - Brian Jay Stanley
I gave up on futurists when Alvin Toffler predicted that "in the future" we'd wear paper clothing.
I mean, maybe he's right. But who cares?
There are no trails. There are no trees out here.
"Thinking" has been ascribed to mechanical devices for quite some time. Watt's flyball governor for steam engines yielded such comments in its day. Railroad switch and signal interlocking systems were said to "think" early in the 20th century. At that level, we can do "things that think".
But strong AI seems further away than ever. After years in the AI field, and having met most of the big names, I'm now convinced that we don't have a clue. Logic-based AI hit a wall decades ago; mapping the world into the right formalism is the hard part, not crunching on the formalism. Hill-climbing in spaces dominated by local minima (which includes neural nets, genetic algorithms, and simulated annealing) works for a while, but doesn't self-improve indefinitely. Reactive, bottom-up systems without world models (i.e. Brooks) can do insect-level stuff, but don't progress beyond that point.
I personally think that we now know enough to start developing something with a good "lizard brain", with balance, coordination, and a local world model. That may be useful, but it's still a long way from strong AI. And even that's very hard. But we're seeing the beginnings of it from game developers and from a very few good robot groups.
Related to this is that we don't really understand how evolution works, either. We seem to understand how variation and selection result in minor changes, but we don't understand the mechanism that produces major improvements. If we did, genetic algorithm systems would work a lot better. (Koza's been working on systems that evolve "subroutines" for a while now, trying to crack this, but hasn't made a breakthrough.)
It's very frustrating.
www.HearMySoulSpeak.com