Talk Tonight: A Thousand Brains: Jeff Hawkins

  Late to this, but of interest, talked to Jeff in our early AI exploration days.

Neuroscientist and engineer Jeff Hawkins unveils a new biological theory of intelligence that Richard Dawkins calls "exhilarating.".  Presented by Kepler's Literary Foundation.

About this Event, registration.  Registration required. 

Date And Time  Wed, March 10, 2021   9:00 PM – 10:00 PM EST  Online

In a book that biologist Richard Dawkins calls “exhilarating,” author, neuroscientist and engineer Jeff Hawkins unveils a new theory of intelligence with awe-inspiring implications. Get ready for a dynamic and exciting conversation about the brain with Kepler’s.

In a century rife with neuroscientific and biological advances, researchers have made little progress on one very big question: how do the simple cells of the brain create intelligence?

Hawkins, cofounder of the neuroscience research company Numenta, dares to answer with A Thousand Brains. In a compulsively readable book accessible even to the casual science reader, he lays forth a simple and yet mold-breaking theory: that intelligence arises from the interaction of maplike reference frames in the brain, which build hundreds of thousands of interconnected models of everything a person knows. These maplike reference frames can tell you how to achieve goals, how to get from one place to another, who you are and how you’re connected to the world.

Hawkins and his Silicon Valley based research team have studied the neocortex, the part of the brain we associate with everything responsible for intelligence. Now with his “thousand brains” theory of the structure that runs the show, Hawkins proposes answers to some of neurosciences most stubborn questions—including questions about the very nature of consciousness, false beliefs and more.

On March 10th, join us for an online conversation between Jeff Hawkins and award-winning science journalist Anil Ananthaswamy as they share with us A Thousand Brains. Starting with basic information on how the brain works for anyone to understand, they’ll discuss Jeff’s new theory and explore what it could mean not only for advancements in machine intelligence, but also its broader implications for all of us as people. This will be a smart, fun night celebrating a key moment in our understanding of the human brain: don’t miss it!

**Please consider joining with a book or donation to support the production of this event and make it possible for us to continue bringing you great conversations.

Registration will close one hour before the event; please reserve your spot early to guarantee access, as registrations are limited.**   .... 

Semantic Folding and Knowledge Processing

Semantic Folding ...

Note the mention of Jeff Hawkins, who we connected with long ago.   Posts re his Numenta company.  Technical, with intriguing implications.

The Semantic Folding Theory (SFT) is the attempt to develop an alternative computational theory for the processing of language data. While nearly all current methods of processing natural language use word statistics, Semantic Folding uses a neuroscience based mechanism of distributional semantics. After capturing a given semantic universe of a reference set of documents by means of a fully unsupervised mechanism, the resulting semantic space is folded into each and every word-representation vector .... 

These vectors are large, sparsely filled binary vectors. Every feature bit in this vector not only corresponds but also equals a specific semantic feature of the folded-in semantic space and is therefore semantically grounded. The resulting word-vectors are fully conforming to the requirements for valid word-SDRs (Sparse Distributed Representation) in the context of the Hierarchical Temporal Memory (HTM) theory by Jeff Hawkins. While the HTM theory focuses on the cortical mechanism for identifying, memorizing and predicting reoccurring sequences of SDR patterns, the Semantic Folding theory describes the encoding mechanism that converts semantic input data into a valid SDR format, directly usable by HTM networks. ... ' 

Copying Algorithms from the Brain

Followed the Numenta work from the beginning.  Interesting, but never saw it close to being ready for real application.  Now a deeper plunge.  Not just using the inspiration of the brain, like in neural nets, but using their plan directly.  And a considerable investment: " ... IBM Tests Mobile Computing Pioneer’s Controversial Brain Algorithms ... IBM is testing a contentious idea for making computers more intelligent by trying to copy mechanisms from the human brain. ... " 

" ... For more than a decade Jeff Hawkins, founder of mobile computing company Palm, has dedicated his time and fortune to a theory meant to explain the workings of the human brain, and provide a blueprint for a powerful new kind of artificial intelligence software. But Hawkins’s company, Numenta, has made little impact on the tech industry, even as machine learning has become central to companies such as Google. .. " 

Another Style of Artificial Intelligence

Another look at Numenta

Numenta has developed a cohesive theory, core software technology, and numerous applications all based on principles of the neocortex. This technology lays the groundwork for the new era of machine intelligence. Our innovative work delivers breakthrough capabilities and demonstrates that a computing approach based on biological learning principles will make possible a new generation of capabilities not possible with today’s programmed computers. ... "

Previously about Numenta.  And in the Wikipedia.

Building Anticipatory Supply Chains

In Industry Week:  Any company with a robust supply chain must anticipate problems.  " .... Toyota got a wake-up call in March 2011, when an earthquake registering 9.0 hit northern Japan, unleashing a massive tsunami. The human toll was devastating and the rebuilding task a monumental challenge. Later, for Toyota, it became evident how dramatic and far reaching this natural disaster was for its global business. ..."

Numenta: Modeling Based on the Neocortex

I was prompted by client discussions to look again at the Numenta site recently. I previously wrote about Jeff Hawkins' book: On Intelligence and Numenta's early work. They seem to have taken a stronger approach towards doing predictive modeling based on a model of the human neocortex. (An image of a section of this is at the right) An adaptive rather than a procedural technique that appears to be applied to the same areas that 'artificial neural networks' had previously been applied to. Continuing to explore.

' ... Numenta is creating a new type of computing technology modeled on the structure and operation of the neocortex. The technology is called Hierarchical Temporal Memory, or HTM, and is applicable to a broad class of problems from machine vision, to fraud detection, to semantic analysis of text. HTM is based on a theory of neocortex first described in the book On Intelligence by Numenta co-founder Jeff Hawkins, and subsequently turned into a mathematical form by Numenta co-founder Dileep George.

Numenta is a technology tools and platform provider rather than an application developer. We work with developers and partners to configure and adapt HTM systems to solve a wide range of problems ... '.

Numenta: Hawkins Brain Models for Intelligence

I reviewed Jeff Hawkin's book: On Intelligence last year. The founder of Palm Computing suggested a model using the architecture of the brain to build artificially intelligent systems. This is a novel approach, since most AI systems do not attempt to use the brain as structural model. His book was very good, but I suggested that he had considerable work to do to implement his ideas. Its another commendable attempt at the holy grail of machine intelligence.

Now an article in today's WSJ: Next Case for Palm Pilot Creators: The Brain and another in BusinessWeek: Jeff Hawkins' Bold Brainstorm, suggest that some progress has been made. He linked with Dileep George, who has started to implement some mathematics based on Hawkin's ideas, and formed a company called Numenta to work on practical applications. Both articles quote Intel scientist Gary Bradksi who says "Even if he's wrong, his theory is better than nothing. And it's 'attackable' -- and that's a good thing." Likely early applications are in machine vision and drug discovery. See also article in the NYTimes. Well worth tracking.