Dharmendra S. Modha

My Work and Thoughts.

Cognitive Computing 2007

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Building on the success of 2006 Almaden Institute on Cognitive Computing, Robert Hecht-Nielsen, Masoud Nikravesh and I are organizing Cognitive Computing 2007. This promises to be an amazing event, and I invite you to register online.

Dates:

May 2-3, 2007

Venue:

Berkeley Art Museum (Auditorium)

Speakers:

Nobelist Donald Glazer, James Anderson, Michael Arbib, Ed Callaway, Robert Hecht-Nielsen, Edgar Koerner, Dharmendra S. Modha, Lotfi A. Zadeh

Panelists:

Jose M. Carmena, Steve Jurvetson, Paul Rhodes, and Lloyd Watts

Registration is free.

Towards real-time, mouse-scale cortical simulations

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Last week, we presented a poster on a fascinating new result at the CoSyNe 2007 conference:

Neurobiologically realistic, large-scale cortical and sub-cortical simulations are bound to play a key role in computational neuroscience and its applications to cognitive computing. One hemisphere of the mouse cortex has roughly 8,000,000 neurons and 8,000 synapses per neuron. Modeling at this scale imposes tremendous constraints on computation, communication, and memory capacity of any computing platform.

We have designed and implemented a massively parallel cortical simulator with (a) phenomenological spiking neuron models; (b) spike-timing dependent plasticity; and (c) axonal delays.  

We deployed the simulator on a 4096-processor BlueGene/L supercomputer with 256 MB per CPU. We were able to represent 8,000,000 neurons (80% excitatory) and 6,300 synapses per neuron in the 1 TB main memory of the system. Using a synthetic pattern of neuronal interconnections, at a 1 ms resolution and an average firing rate of 1 Hz, we were able to run 1s of model time in 10s of real time!

I believe that such cortical simulators are the linear accelerators of neuroscience. We are already able to study extremely large-scale cortical dynamics. This is a developing story…please stay tuned in!

Reference:

James Frye, Rajagopal Ananthanarayanan, and Dharmendra S. Modha, "Towards real-time, mouse-scale cortical simulations," CoSyNe: Computational and Systems Neuroscience, Salt Lake City, Utah, Feb 22-25, 2007 PDF

Google and AI

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The programming language of humans, if you will, would include the workings of your brain, said Google co-founder Larry Page, who offered his hypothesis Friday night during a plenary lecture here at the annual American Association for the Advancement of Science conference. His guess, he said, was that the brain’s algorithms weren’t all that complicated and could be approximated, eventually, with a lot of computational power. Specifically, Page said "When AI happens, it’s going to be a lot of computation, not so much … clever algorithms." Given the size of DNA (~600 MB compressed), the algorithms of the brain are "probably not that complicated."

"…artificial intelligence…I don’t think it’s that far off as people think."

Links:

  1. Press article
  2. Video

Walter Freeman turns 80!

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Walter FreemanProfessor Walter Freeman one of whose academic grandfathers was Nobelist Charles Sherrington and one of whose great great academic grandfathers was Nobelist Thomas Huxley turned 80 years old!

In his honor, his friends, students, and colleagues organized a wonderful “Conference on Brain Network Dynamics“. The conference was incredible, and full of intellectual stimulation. Professor Freeman is intellectually as vigorous as ever. They are hoping to have a similar conference when he turns 100!

“the power of possibilities overwhelms me more than the fear of misuse”

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Yesterday, your’s truly was quoted in CIO.com magazine in a beautiful article by Esther Schindler:

Dharmendra Modha, manager of cognitive computing at the IBM Almaden Research Center, believes that this transition is part of the next hundred years of technology leadership. The current data paradigm is structured data management, but in “real life” we deal with unstructured data (of which emotion is a single element). That is, we recognize a friend’s face no matter how she’s dressed or despite her mood; we detect patterns with a large amount of sensory data and we act appropriately. According to Modha, “We are at a crucial juncture in history where two trends are converging: the tremendous availability of computational power, and the amount of neuroscience knowledge that has exploded over the last few years.”

“Cognitive computing is about engineering the mind by reverse engineering the brain,” Modha explains. If the brain is the biological wetware, a collection of neurons and a set of interconnection between the neurons, then neuron by neuron and synapse by synapse, computer science is putting together the architecture of the mind. Thus, IBM Research is simulating collective dynamics; researchers are studying how a very large population of interconnected neurons evolve in order to characterize them mathematically and then to synthesize them for harnessing in synthetic computations. Says Modha, “Today, on a 4096 processor Blue Gene supercomputer with 256MB of memory per CPU, we are able to simulate 8 million neurons and 50 billion synapses, 10 times slower than real-time.” That’s just a start, but then the Cognitive Computing project is new. A mouse brain has 8 million neurons in one hemisphere and 64 billion synapses.

This research aims to assemble the knowledge to build novel perception machines, or novel sensory systems. Business issues, says Modha, will eventually involve visual recognition, pattern detection in the stock market, or inventory management in neurological devices—systems that underlie a wide variety of applications.

It’s all very blue sky, of course, as research is supposed to be. But those science-fiction computers-get-emotion stories spoke of both opportunity and horror. What dystopia do such researchers worry that they may unleash? Says Modha, “At this stage in science and technology, the power of possibilities overwhelms me more than the fear of misuse.”