Palm Founders Form AI Company

Mentifex writes "As reported in the New York Times, Kansas City Star and other news media, Jeff Hawkins (co-author of On Intelligence) and Donna Dubinsky, co-founders of Palm Computing and Handspring, along with Dileep George as the principal engineer, are starting an AI company named Numenta as a follow-up to Hawkins' recent work on visual processing."

Comments

Palm-Like "AI"?

[Spencerian]

You had to reset Palm PDAs in interesting ways, like poking a tiny button hidden ina hole with a paper clip. Imagine what you'd have to do a bot with Palm-like AI...

"Sir, to reset the machine, you'll need to sharply press its reset button, located at the back of the machine, just before its legs. just quickly pop your foot against it to press it."

"Uh, are you telling me that to reset it, I have to kick its ass?"

"Er...yes, sir."

Will This Be Part of the New Palm OS?

[canfirman]

Great, just what I need, an AI app that keeps poping up saying, "You know you should go to that meeting. What do you mean you don't want to go? Did you remember your wedding anniversary? Have you called your wife? Who's this 'Elle' person in your phone book. You should stop playing 'Tetris' so often..."

Re:Will This Be Part of the New Palm OS?

[CodeBuster]

Just wait until it says, "I'm sorry Dave, but I'm afraid that I just can't do that..."

Could this be the key

[affinity]

to the machines taking over...

http://www.forbes.com/technology/personaltech/2005 /03/24/cz_qh_0324numenta.html

All the rage... IBM too...

[tquinlan]

According to news.com.com.com.com, IBM is working on something similar...

neocortex?

[dhbiker]

Numenta is developing a new type of computer memory system modeled after the human neocortex

surely this technology would be incredibly slow? (this is not a troll, read on before you mod me down!)

From what I remember from my neural networks days the human brain/neocortex works so well because of its massively parallel nature (not because of the processing power of any one neuron), and that computers simply aren't able to exploit this as they aren't designed to work like this - They are instead designed to to massively serial operations using extremely powerful chips (neurons) because the overhead of managing these parallel operations synchronously is too great (the human brain/neocortex work asynchronously)

am I wrong about this or am I missing something great that they've stumbled accross?

Re:neocortex?

[AKAImBatman]

From what I remember from my neural networks days the human brain/neocortex works so well because of its massively parallel nature (not because of the processing power of any one neuron), and that computers simply aren't able to exploit this as they aren't designed to work like this

Computers aren't *normally* designed like this. They can be however, and in recent years have been moving in that direction. When neural networks were first being researched, a Cray supercomputer was about the closest you could get to that sort of parallelism. Fast forward to today and we find that Intel (Pentium), AMD (AMD64), Sun (Sparc), and Sony (Emotion Chip) are all building machines that are highly parallel in nature.

Even more interesting is that today you can build yourself a custom, massively parallel computer on a shoestring budget. All you need is a handful of FPGAs, a PCB layout service like Pad2Pad, a few other parts, and reasonable VHDL or Verilog skills. That's more or less what OpenRT did to build their SaarCORE architecture. :-)

Numenta = AI Company?

[bigtallmofo]

It appears the article summary might be misleading. From the first sentence of www.numenta.com:

Numenta is developing a new type of computer memory system modeled after the human neocortex. The applications of this technology are broad and can be applied to solve problems in computer vision, artificial intelligence, robotics and machine learning.

They further go on to say:

Numenta is a technology platform provider rather than an application developer. The Company is creating a scalable software toolkit that will allow developers and partners to configure and adapt HTM systems to particular problems.

My reading on this is that they aren't an AI company - they're just developing a technology that could be used for AI or many, many other uses.

Sounds Similar to Neural Networks

[Anonymous Coward]

By training neurons, they learn to achieve the desired result of a user.

Pretty complex material, anyone wanting to delve into should do some reading on Minsky (proposed neural networks could make dead bodies perform tasks...creepy to say the least) http://en.wikipedia.org/wiki/Marvin_Minsky

When they release a white paper Im sure itll only be the beginning of a prosporus field of study.

~ Jon

A.L.I.C.E Makes for Interesting Conversation

[Spencerian]

FWIW to ya, A.L.I.C.E is an cool webbot AI similar to the old ELIZA bots of old, but with some sophistication that allows it to be programmed to answer specific questions and recognize some words and phrases well. Won't pass a Turing test, but hey, it's free.

The webpage above has an animation that appears to have a bot attached to it. Pretty and cool.

Re:A.L.I.C.E Makes for Interesting Conversation

[Quixote]

Nice try, kid. No, neither A.L.I.C.E. nor anyone else has truly passed the Turing Test (read up about it before commenting further; in particular, read what it means to pass the test). The Loebner prize is designed to be _like_ the Turing Test; but the winner of the Loebner Prize is not the 'bot who passes the Turing Test, but the 'bot who scores the most points. So, if 1 'bot scores 1 point and all the others score 0, then the 'bot with the single point wins.

If a 'bot passes the Turing Test, it will be big news, trust me.

Better than coffee

[Mrs. Grundy]

Nothing starts my day better than the pleasant scent of vaporware wafting from my computer. We live in a great time. This shows what a kid with nothing but a formalism and a dream can accomplish.

Hawkins' Engineering Approach is Clever

[filmmaker]

In the book, Hawkins remarks that AI researchers often took the misguided approach that intelligence is a set of principles or properties, when in fact it's strictly a matter of behavior. To be intelligent is to behave intelligently. If he's right, then it's the act of being, wherein which the brain's primary tool is the continuous analogizing of current circumstances to past situations in order to make good predictive decisions, which constitutes intelligence.

He's the first to claim that he's not looking for sentience or to answer the question of sentience, but is instead only looking for a practical engineering approach to building intelligent machines. I think this is doubly clever since the issue of sentience should not be addressed until well after, as Hawkins often remarks, our own brains are understood first, in terms of how they operate. Why they operate, or what motivates us or what makes us 'cognitive agents' don't enter the equation with his approach.

Foldiak?

[Anonymous Coward]

I'm surprised that the short summary, from my brief perusal, does not include reference to work by Peter Foldiak (1991, 199?) and Wallis (1996). Both these authors published numerous papers on temporal and spatial coherence. My MSc in 1996 was also on the same topic followed by human research on the same problem. All of the computational work was with unsupervised learning algorithms varying whether the temporal processing was at the input our output stage.

I guess I'll have to read the original paper. However, the notion of temporal processing has been around for a long time.

Note: My own human research has yielded reliable data that addresses the acquisition of invariant object recognition.

Now there's a name I haven't heard in a long time

[Dancin_Santa]

Mentifex. The name alone conjures up flamewars of years past on Usenet.

The big question in AI is whether an AI "mind" is more likely to spring up from a handful of rules, or whether a top-down design will bring it about. Mentifex was always in the latter camp.

Those in the former camp, including the Palm founders in the article, always seemed to be on the verge of something, but never seemed to really get any closer to a "mind" than some fuzzy logic.

We're still a long way off from Number 5 Alive.

Re:Somewhat Offtopic

[Anonymous Coward]

That is part of Natural Language Processing, where the goal is to figure out the meaning of sentances. There has been much progress in this field, including programs that can read news articles and then paraphrase the information.

Google "Natural Language Processing".

Re:Somewhat Offtopic

[Shadow Wrought]

HAL: Dave, do I need a penis enlargement?
Dave: For the millionth time HAL, no. You don't have one, remember?
HAL: But if I did, do you think I would get better functionality if I used Viatroxx?
Dave: No. Now Hal...
HAL: Dave, it looks like there's another poor Nigerian who needs my help.
Dave: Aaaaaaaaaaaaaaaaaarrrrrrrrrrrrrrrrgggggg!
HAL: Dave? What are you doing Dave?

A Breakthrough in AI is just 10 years away...

[Cr0w T. Trollbot]

...just the way it was in 1970.

- Crow T. Trollbot

Belief Propagation

[songbo]

The idea seems simple enough. Create a hierarchical inference structure. Train it on some data. Let the nodes learn what are the most frequent data. This forms the basic alphabet set. Propagate this up the hierachy. Learn the conditional probability distribution. Voila, you have a working visual recognition system. Problem is, the system will be slow, unless you have a processor capable of parallel or vector processing. Try implementing the system on Matlab with a 320x200 image, and see your processor crawl to a halt. Now, imagine doing this on a 320x200 video, and pray! Well, that's why we need a different processor architecture to make this work. But the theory is simple.

I'm skeptical that this is ready for prime-time

[DoctoRoR]

The article gives little detail of the technology, and it's not like the general ideas Hawkins describes haven't been explored by people during the many decades of AI/neural networks research. The Numenta website gives the following:

HTM is "hierarchical" because it consists of memory modules connected in a hierarchical fashion. The hierarchy resembles an inverted tree with many memory modules at the bottom of the hierarchy and fewer at the top. HTM is "temporal" because each memory module stores and recalls sequences of patterns. HTM is hierarchical both temporally and spatially. An HTM system is not programmed in a traditional sense; instead it is trained. Sensory data is applied to the bottom of the hierarchy and the HTM system automatically discovers the underlying patterns in the sensory input. You might say it "learns" what objects are in the world and how to recognize them. Time is an essential element of how HTM systems work. First, to learn the patterns in the world, the sensory data must flow over time just as we move our eyes to see and move our hands to feel. Second, because every memory module stores sequences of patterns, HTM systems can be used to make predictions of the future. They not only discover and recognize objects but they can make predictions about how objects will behave going forward in time.

That sounds like a number of neural network approaches, including Stephen Grossberg's work at BU. Although Hawkins seems to be a very bright guy, this field is littered with very bright researchers who made bold claims, and none of those efforts have yielded revolutionary businesses. Anyone remember (Stanford AI researcher) Edward Feigenbaum's Fifth Generation book in the 1980s? Doug Lenat's Cyc project?

Remember the huge difference between one neuron's firing rate and the clock speed for processors. The brain operates in a way that's fundamentally different from how we program and how computers operate: massive parallelism with slow components versus (mostly) serial computation. So when a company says they'll market a software solution to something which scientists haven't figured out yet, I am indeed skeptical. This is really more research effort than commercial venture, and Numenta admits this: "It may well take several years before products based on HTM systems are commercially available."

I hope there's something here. I'd love to see an outsider come in with fresh ideas and create a software platform to explore neuro-inspired programs. But let's be realistic and remember the history of AI. A red flag is the lack of any scientific papers available from the Numenta web site. If they are far enough along to make a software development kit, they should have been publishing results in peer-reviewed journals (with appropriate patent filings if necessary). So far, the only literature published is a trade book: On Intelligence.

Cerdibility ?

[shashark]

None of the founders of Numenta other than Jeff Hawkins have any experience in AI or for that matter have any background in hardcore computer science.

Dileep George is an Electrical Engineering graduate, while the CEO Donna Dubinsky is a hardcore salesperson and holds an MBA. Interestingly, the page also mentions that Jeff Hawkins " currently serves as Chief Technology Officer at palmOne, Inc". Fishy!

Next Generation AI ? Who are we kidding ?

AI Reinasence

[projectNOR]

There are actually quite a few projects now taking similar, cortex-centric approaches to AI hard problems. Are we up to something here? The guys responsible of these projects are not wacko types at all, but established entrepreneurs and/or well-known researchers:

CCortex "A 20-billion neuron simulation of the Human Cortex and peripheral systems."
Cyc a knowledge base with vast collection of facts about the real world and logical reasoning ability. Financed by Paul Allen AI related investment company,Vulcan.
Numenta is developing a new type of computer memory system modeled after the human neocortex.

They seem to we well financed, and knowledgeable. Are we witnessing the start of something big here?