November 30, 2011Colloquium1 Neurosynaptic computing chips s1160056 Tomotaka Kasahara Colloquium.

Slides:



Advertisements
Similar presentations
Introduction to Neural Networks
Advertisements

Thinking Like A Human – With Memristors
Characteristics of a Microprocessor. The microprocessor is the defining trait of a computer, so it is important to understand the characteristics used.
A new approach to Artificial Intelligence.  There are HUGE differences between brain architecture and computer architecture  The difficulty to emulate.
Neuromorphic Engineering
Using Computers CS French Chapter 1.
Rutgers CS440, Fall 2003 Neural networks Reading: Ch. 20, Sec. 5, AIMA 2 nd Ed.
Hardware Basics: Inside the Box 2  2001 Prentice Hall2.2 Chapter Outline “There is no invention – only discovery.” Thomas J. Watson, Sr. What Computers.
Carla P. Gomes CS4700 CS 4700: Foundations of Artificial Intelligence Prof. Carla P. Gomes Module: Intro Neural Networks (Reading:
How does the mind process all the information it receives?
Carlo Tomasi, Computer Science. Human Vision Computer Vision?
Rohit Ray ESE 251. What are Artificial Neural Networks? ANN are inspired by models of the biological nervous systems such as the brain Novel structure.
Traffic Sign Recognition Using Artificial Neural Network Radi Bekker
Robot design-- Four legged walking robot Instructors: Dr. A
1 Parallel computing and its recent topics. 2 Outline 1. Introduction of parallel processing (1)What is parallel processing (2)Classification of parallel.
Multimedia Specification Design and Production 2013 / Semester 2 / week 8 Lecturer: Dr. Nikos Gazepidis
Anatomy and the Organization of the Human Body Biology 2011.
Artificial Neural Network Theory and Application Ashish Venugopal Sriram Gollapalli Ulas Bardak.
Artificial Neural Nets and AI Connectionism Sub symbolic reasoning.
IE 585 Introduction to Neural Networks. 2 Modeling Continuum Unarticulated Wisdom Articulated Qualitative Models Theoretic (First Principles) Models Empirical.
 The most intelligent device - “Human Brain”.  The machine that revolutionized the whole world – “computer”.  Inefficiencies of the computer has lead.
Artificial Neural Networks. Applied Problems: Image, Sound, and Pattern recognition Decision making  Knowledge discovery  Context-Dependent Analysis.
Brain Computer Interface
CS344 : Artificial Intelligence Pushpak Bhattacharyya CSE Dept., IIT Bombay Lecture 29 Introducing Neural Nets.
What is perception/eyesight and how is it processed in the brain? Tamara Mahony.
CS621: Artificial Intelligence Pushpak Bhattacharyya CSE Dept., IIT Bombay Lecture 41,42– Artificial Neural Network, Perceptron, Capacity 2 nd, 4 th Nov,
Prepared By :. CONTENTS 1~ INTRODUCTION 2~ WHAT IS BLUE BRAIN 3~ WHAT IS VIRTUAL BRAIN 4~ FUNCTION OF NATURAL BRAIN 5~ BRAIN SIMULATION 6~ CURRENT RESEARCH.
SENINAR ON BLUE BRAIN PRESENTED BY BINAYAK SWAIN MCA 4 TH SEM REGD NO:
EE3A1 Computer Hardware and Digital Design
Neural Networks in Computer Science n CS/PY 231 Lab Presentation # 1 n January 14, 2005 n Mount Union College.
WORLD OF THE VIRTUAL BRAIN
Brain Chips.
Artificial Intelligence, Expert Systems, and Neural Networks Group 10 Cameron Kinard Leaundre Zeno Heath Carley Megan Wiedmaier.
AS ICT.  Have an understanding of how organizations use ICT.  Be able to describe a number of uses, giving the hardware and software requirements 
Printing: This poster is 48” wide by 36” high. It’s designed to be printed on a large-format printer. Customizing the Content: The placeholders in this.
Computer Architecture Lecture 26 Past and Future Ralph Grishman November 2015 NYU.
Dr.Abeer Mahmoud ARTIFICIAL INTELLIGENCE (CS 461D) Dr. Abeer Mahmoud Computer science Department Princess Nora University Faculty of Computer & Information.
A Perspective on the Future of Massively Parallel Computing Presented by: Cerise Wuthrich June 23, 2005.
Neuromorphic silicon chips
Artificial Neural Systems. Intro Artificial neural systems try to process information in the same way as the human brain does. Traditional computer systems.
Neural Networks. Background - Neural Networks can be : Biological - Biological models Artificial - Artificial models - Desire to produce artificial systems.
CSC321: Neural Networks Lecture 1: What are neural networks? Geoffrey Hinton
Central Processing Unit (CPU) The Computer’s Brain.
PRESENTATION BY :- SUVIL SHARMA 0832EC Introduction What is BLUE BRAIN?? What is VIRTUAL BRAIN ? Why do we need virtual brain? Function of brain.
BLUE BRAIN. CONTENTS:- 1# INTRODUCTION WHAT IS BLUE BRAIN 3$ WHAT IS VIRTUAL BRAIN 4% FUNCTION OF NATURAL BRAIN 5^^ BRAIN SIMULATION 6!!! CURRENT RESEARCH.
IC 3 BASICS, Internet and Computing Core Certification Computing Fundamentals Lesson 2 How Does a Computer Process Data?
1 Azhari, Dr Computer Science UGM. Human brain is a densely interconnected network of approximately neurons, each connected to, on average, 10 4.
Bionics Help for the disabled.
G.PULLAIAH COLLEGE OF ENGINEERING & TECHNOLOGY. BLUE BRAIN Prepared by, Prepared by, D. Sruthi Reddy, D. Sruthi Reddy, 08AT1A0521, 08AT1A0521, 2 nd CSE.
Brain Chip Technology | Presented to- Dr. Jia Uddin, BRAC University 2 Dung Beetle, Can lift upto 1141 times of it’s own body weight..
Summary Presentation of Cortical Computing with Memrisitve Nanodevices Authored by Greg S. Snider Hewlett-Packard Laboratories Published Winter 2008, SciDAC.
Department of Electronics & Communication CONTENTS INTRODUCTION WHAT IS BLUE BRAIN WHAT IS VIRTUAL BRAIN FUNCTION OF NATURAL BRAIN BRAIN SIMULATION CURRENT.
Brain Computer Interface Presented by V.Uma Shankar 08KD1A1251 IT IV year.
Blue Brain Technology Presented By Vipin.
BLUE BRAIN The future technology
Next page Unit B6 Brain and Mind.
Artificial Intelligence (CS 370D)
Instrumentation and Control Systems
Dr. Unnikrishnan P.C. Professor, EEE
The Nervous System Peripheral Nervous System Central Nervous System.
Session 2: The Biology of the Brain
OVERVIEW OF BIOLOGICAL NEURONS
WELCOME TO SEMINAR ZONE.
G.PULLAIAH COLLEGE OF ENGINEERING & TECHNOLOGY
Intro to Robotics It’s YOUR FUTURE.
CS621 : Artificial Intelligence
Machine Learning.
Summary Presentation of Cortical Computing with Memrisitve Nanodevices
Presentation transcript:

November 30, 2011Colloquium1 Neurosynaptic computing chips s Tomotaka Kasahara Colloquium

2 Contains ・ Back ground ・ What is a Neurosynaptic computing chip? ・ Practical use research works -Application for human work organ -Application for computer ・ Product example ・ Problem ・ Sammary November 30, 2011Colloquium

3 Back ground ・ Development focus on human brain Human brain's mechanism is good at processing of flexible consideration Disadvantage point of usual neumann computer ・ Application of other field This chip work very similar to human nerve Embed in human body with complicated device November 30, 2011Colloquium Neurosynaptic computing chip(Neuro chip) Neuron: Brain's nerve cell Synapse: Connection part between neuron and neuron Possible application to medical

4 Neurosynaptic computing chip November 30, 2011Colloquium ・ Neuro chip build new network constantly oneself -Perception -Action Learning ability -Recognition ・ Recognize any pattern ・ Expectation from experience Fig. Neuro conection Fig. Neuro network on silicon chip

5 Contains ・ Back ground ・ What is a Neurosynaptic computing chip? ・ Practical use research works -Application of human work organ -Application of computer ・ Problem ・ Summary November 30, 2011Colloquium

6 Human work organ November 30, 2011Colloquium Building new networks Possible embed medical parts(pacemaker, biosensor) in human body natural Org an Medical parts Chip Human bodyDevice : Neuron Fig. Neuron put on biochip

7 Human work organ November 30, 2011Colloquium Building new networks Possible embed medical parts(pacemaker, biosensor) in human body natural Org an Medical parts Chip Human bodyDevice : Neuron Fig. Neuron put on biochip

8 Neuro computer November 30, 2011Colloquium ・ Advantage of usual computer -Calculate high speed Many calculation ・ Advantage of Neuro computer -Recognize pattern of figure, sound, etc... -Deciding volition ability Input figure1Input figure2 Same person Can computer judge same person? Front view Input figure1 Side view

9 Product example IBM product “Neurosynaptic core” ・ Have neuro and synapse made silicon - Neuro number is Program synapse number is 262,144 - Learning ability synapse number is 65,536 ・ Run scatter and parallel processsing -Recognize pattern -Remember association -Classification November 30, 2011Colloquium Neuro: calculate work Synapse: memory work

10 Problem ・ Big scale to run parallel scattering process -Have to put many neuman -Occur delay communication between neuman and neuman Process different between human signal and device signal ・ Many neuro's processing speed - Each neuman's process speed is slower than anything digital, but human body make high speed parallel processing use neuron and synapse November 30, 2011Colloquium

11 Summary Neuro chip can process some problem that usual neumann computer can't process good This technology's development affect control problem - Hardware to device Robot control, Figure and sound pattern processing... - human to device Biosensor, artificial retina, artificial arms and legs... November 30, 2011Colloquium

12 References November 30, 2011Colloquium ・ Outline of neuro chip ・ Recent news about neuro chip(Tecknews world) ・ About IBM's neuro chip modeled-on-human-brain/#more-82043