Feeds

Why can't a computer be more like a brain?

Or even better?

Intelligent flash storage arrays

Why can't a computer be more like a brain? Jeff Hawkins asked at Emerging Technology this week.

Hawkins is most familiar as founder of Palm and Handspring and creator of the handwriting recognition system Graffiti. His other long-term interest is neuroscience, and he believes he has the answer to that My Fair Lady question.

Hawkins' starting point was the class of problems we have so far failed to build into successful machines: computer vision, adaptive behaviour, auditory perception, touch, languages, planning, and thinking.

There are four reasons commonly given why computers fail at these simple human tasks: they aren't powerful enough; brains are too complex to understand; brains work on some unknown principle we haven't yet discovered; brains are magic (they have souls).

Saying brains are too complex, Hawkins argued, just means we don't understand them. He believes, however, that he does understand enough. His latest company, Numenta, is attempting to build practical applications of the theories in his 2004 book On Intelligence.

For the purposes of this discussion, intelligence is the memory-based ability to predict the future, and resides in the neocortex, which wraps around the rest of the brain like a thin sheet. Its densely packed cells are organised into increasingly abstract hierarchical layers that build models of the world by exposure to changing sensory patterns.

Numenta copies this design in software it calls NuPIC (for Numenta Platform for Intelligent Computing), and reports some success in getting its program to recognise deformed versions of the pictures it already knows. Increasing the number of hierarchies should improve the complexity of the models it can handle. The key is these hierarchies.

The company is working on improving the system's predictive ability by adding higher-order temporal knowledge. It's not sure what the next step after that will be; for one thing it isn't sure which other parts of the brain it might need to model and integrate.

With the latest release, training the full network takes about 18 minutes. Each level of the network is trained on hundreds of thousands of iterations of the images – only a year ago this was taking days. Inference per image is down to about 10 milliseconds. A research version running on Linux or Mac OS X is available for free download and experimentation, along with white papers, learning algorithms, programmers' guides, and other documentation. A Windows version is in progress.

The company also still isn't sure what applications might find this approach valuable, though they list a wide range.

"It's like building the first computers," said Hawkins. "You knew it was an important idea, but you didn't have the CPU, compiler, or disk drive yet." He believes that: "We should be able to build machines that can become deeper experts than we are. I want to build machines that are really good thinkers."

Humans become experts by long study; a machine that could emulate that process could work at things that humans are physically unsuited for, such as the physics of the very small or very large. "I want a machine that inherently thinks about physics better than humans do." ®

Security for virtualized datacentres

More from The Register

next story
Boffins who stare at goats: I do believe they’re SHRINKING
Alpine chamois being squashed by global warming
What's that STINK? Rosetta probe shoves nose under comet's tail
Rotten eggs, horse dung and almonds – yuck
Comet Siding Spring revealed as flying molehill
Hiding from this space pimple isn't going to do humanity's reputation any good
Experts brand LOHAN's squeaky-clean box
Phytosanitary treatment renders Vulture 2 crate fit for export
Kip Thorne explains how he created the black hole for Interstellar
Movie special effects project spawns academic papers on gravitational lensing
LONG ARM of the SAUR: Brachially gifted dino bone conundrum solved
Deinocheirus mirificus was a bit of a knuckle dragger
prev story

Whitepapers

Choosing cloud Backup services
Demystify how you can address your data protection needs in your small- to medium-sized business and select the best online backup service to meet your needs.
Forging a new future with identity relationship management
Learn about ForgeRock's next generation IRM platform and how it is designed to empower CEOS's and enterprises to engage with consumers.
Security for virtualized datacentres
Legacy security solutions are inefficient due to the architectural differences between physical and virtual environments.
Reg Reader Research: SaaS based Email and Office Productivity Tools
Read this Reg reader report which provides advice and guidance for SMBs towards the use of SaaS based email and Office productivity tools.
Storage capacity and performance optimization at Mizuno USA
Mizuno USA turn to Tegile storage technology to solve both their SAN and backup issues.