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Um, this article doesn't reference BrainChip's patent. It...

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hedges avenue

79 Posts.

15/01/16

22:14

Post #: 16807181

Originally posted by HighPriestess ↑

http://www.ibm.com/blogs/think/2016/01/13/ibms-cognitive-computing-innovation-surges/

IBM’s Cognitive Computing Innovation Surges

IBM’s work in cognitive computing emerged as a major factor among the patents awarded to the company by the US. Patent and Trademark Office. More than 800 of IBM’s 7,355 2015 patents are related to cognitive computing, a 52% increase from the previous year.
Last year, IBM announced that it has realigned its entire business strategy around the promise of cognitive computers, which can learn, reason, and efficiently process diverse data types all while interacting with people in natural and familiar ways.
IBM’s leaders believe cognitive computing will have a profound impact on business and society, helping people to make better decisions in their personal and professional lives, democratizing expertise, and transforming industries and professions.
Simply put, IBM’s innovation agenda calls for developing cognitive solutions delivered via a cloud platform to transform industries.
Here are some highlights among last year’s cognitive computing innovations:
Creating machines that mimic the brain: Conventional computers are good at math, but they can’t tell the difference between a tree and a truck—at least, not without using a truckload of computing power. A invented a new kind of processor chip that draws inspiration from the structure and function of the human brain while exploiting creative possibilities in modern technology — to learn and adapt on the fly, and is 10,000 times more energy efficient than conventional chips. (Patent US8977583) ((cites our patent. see below for all citations))

http://www.google.com.au/patents/US20100076916#legal-events

BrainChip:
Autonomous Learning Dynamic Artificial Neural Computing Device and Brain Inspired System
US 20100076916 A1
ABSTRACT
A hierarchical information processing system is disclosed having a plurality of artificial neurons, comprised of binary logic gates, and interconnected through a second plurality of dynamic artificial synapses, intended to simulate or extend the function of a biological nervous system. The system is capable of approximation, autonomous learning and strengthening of formerly learned input patterns. The system learns by simulated Synaptic Time Dependent Plasticity, commonly abbreviated to STDP. Each artificial neuron consisting of a soma circuit and a plurality of synapse circuits, whereby the soma membrane potential, the soma threshold value, the synapse strength and the Post Synaptic Potential at each synapse are expressed as values in binary registers, which are dynamically determined from certain aspects of input pulse timing, previous strength value and output pulse feedback...

Citing Patent Filing date Publication date Applicant Title

1 US8712940 31 May 2011 29 Apr 2014 International Business Machines Corporation Structural plasticity in spiking neural networks with symmetric dual of an electronic neuron

2 US8843425 29 Jul 2011 23 Sep 2014 International Business Machines Corporation Hierarchical routing for two-way information flow and structural plasticity in neural networks

3 US8868477 29 Mar 2012 21 Oct 2014 International Business Machines Coproration Multi-compartment neurons with neural cores

4 US8892485 8 Jul 2010 18 Nov 2014 Qualcomm Incorporated Methods and systems for neural processor training by encouragement of correct output

5 US8909575 29 Feb 2012 9 Dec 2014 Qualcomm Incorporated Method and apparatus for modeling neural resource based synaptic placticity

6 US8914315 * 27 Jan 2012 16 Dec 2014 International Business Machines Corporation Multi-compartment neuron suitable for implementation in a distributed hardware model by reducing communication bandwidth

7 US8959040 * 8 Mar 2012 17 Feb 2015 Hrl Laboratories, Llc Spike timing dependent plasticity apparatus, system and method

8 US8977583 29 Mar 2012 10 Mar 2015 International Business Machines Corporation Synaptic, dendritic, somatic, and axonal plasticity in a network of neural cores using a plastic multi-stage crossbar switching

9 US8996430 27 Jan 2012 31 Mar 2015 International Business Machines Corporation Hierarchical scalable neuromorphic synaptronic system for synaptic and structural plasticity

10 US9053428 21 Jul 2011 9 Jun 2015 Qualcomm Incorporated Method and apparatus of robust neural temporal coding, learning and cell recruitments for memory using oscillation

11 US9064215 14 Jun 2012 23 Jun 2015 Qualcomm Incorporated Learning spike timing precision

12 US9087302 7 Jun 2012 21 Jul 2015 Samsung Electronics Co., Ltd. Synapse for function cell of spike timing dependent plasticity (STDP), function cell of STDP, and neuromorphic circuit using function cell of STDP

13 US9092735 21 Sep 2011 28 Jul 2015 Qualcomm Incorporated Method and apparatus for structural delay plasticity in spiking neural networks

14 US9111224 * 19 Oct 2011 18 Aug 2015 Qualcomm Incorporated Method and apparatus for neural learning of natural multi-spike trains in spiking neural networks

15 US9111225 8 Feb 2012 18 Aug 2015 Qualcomm Incorporated Methods and apparatus for spiking neural computation

16 US9129220 7 Jul 2010 8 Sep 2015 Qualcomm Incorporated Methods and systems for digital neural processing with discrete-level synapes and probabilistic STDP

17 US9147155 16 Aug 2011 29 Sep 2015 Qualcomm Incorporated Method and apparatus for neural temporal coding, learning and recognition

18 US9183495 8 Aug 2012 10 Nov 2015 International Business Machines Corporation Structural plasticity in spiking neural networks with symmetric dual of an electronic neuron

19 US9189731 24 Mar 2014 17 Nov 2015 International Business Machines Corporation Structural plasticity in spiking neural networks with symmetric dual of an electronic neuron

20 US20110004579 * 29 Sep 2008 6 Jan 2011 Greg Snider Neuromorphic Circuit

21 US20130103626 * 19 Oct 2011 25 Apr 2013 Qualcomm Incorporated Method and apparatus for neural learning of natural multi-spike trains in spiking neural networks

22 US20130198121 * 27 Jan 2012 1 Aug 2013 International Business Machines Corporation Multi-compartment neuron suitable for implementation in a distributed hardware model by reducing communication bandwidth

23 WO2012006592A1 * 8 Jul 2011 12 Jan 2012 Qualcomm Incorporated Methods and systems for neural processor training by encouragement of correct output

24 WO2013059703A1 * 19 Oct 2012 25 Apr 2013 Qualcomm Incorporated Method and apparatus for neural learning of natural multi-spike trains in spiking neural networks

25 WO2013119872A1 * 7 Feb 2013 15 Aug 2013 Qualcomm Incorporated Methods and apparatus for spiking neural computation

The number of times a patent document is cited may be a measure of its technological significance.

Expand

Um, this article doesn't reference BrainChip's patent.

It references only IBM patents for which they have 800+ AI related patents.

BRN Price at posting: 23.0¢ Sentiment: None Disclosure: Held

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