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BrainChip September 2018 Quarter Update
BrainChip September 2018 Quarter Update 1 Brainchip OCTOBER 2017 - - PowerPoint PPT Presentation
BrainChip September 2018 Quarter Update 1 Brainchip OCTOBER 2017 | Disclaimer This presentation is not a prospectus nor an offer for securities in any jurisdiction nor a securities recommendation. The information in this presentation is an
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BrainChip September 2018 Quarter Update
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This presentation is not a prospectus nor an offer for securities in any jurisdiction nor a securities recommendation. The information in this presentation is an overview and does not contain all information necessary for investment decisions. In making investment decisions in connection with any acquisition of securities, investors should rely on their own examination of the assets and consult their own legal, business and/or financial advisers. The information contained in this presentation has been prepared in good faith by BrainChip Holdings Ltd, however no representation or warranty expressed or implied is made as to the accuracy, correctness, completeness or adequacy of any statements, estimates, opinions or other information contained in this presentation. To the maximum extent permitted by law, BrainChip Holdings Ltd, its directors, officers, employees and agents disclaim liability for any loss or damage which may be suffered by any person through the use or reliance on anything contained in or omitted in this presentation. Certain information in this presentation refers to the intentions of BrainChip Holdings Ltd, but these are not intended to be forecasts, forward looking statements or statements about future matters for the purposes of the corporations act or any other applicable law. The occurrence of events in the future are subject to risks, uncertainties and other factors that may cause BrainChip’s actual results, performance or achievements to differ from those referred to in this presentation. Accordingly, BrainChip Holdings Ltd, its directors, officers, employees and agents do not give any assurance or guarantee that the
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Announcement of AkidaTM Neuromorphic System-on-Chip (NSOC) Architecture Partnership with Telesikring to deliver AI-powered Video Analytics to Police and Security Customers across Scandinavia Acquistion of License to Cybersecurity technology from Democritus University of Thrace, Greece Gaming Partners International (GPI) Demonstration of Integrated Vision System at the G2E gamining conference in Las Vegas, Nevada
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The Company finished the September 2018 quarter with a cash balance of US$9.995M. Cash receipts for the quarter were US$246,000. Headcount at the end of the quarter was 35 fulltime employees and two fulltime contractors in sales and marketing. In the June quarter the Company invoiced SNTech US$609,135 based
has initiated a full audit of SNTech’s books, records and source code. The results of the audit are expected in November 2018.
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The Company expects an increase in cash receipts from OEMs, System Integrators and other partners in the December quarter of 2018. The Company’s sales pipeline continues to grow and now includes
design wins. The Company currently supports approximately 21 committed or active trials for which most are covered by Non-Disclosure Agreements.
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Automotive
Automobile Manufactures Third Party Vendors
Civil Surveillance
Original Equipment Manufacturers End-Users and System Integrators
Gaming Neuromorphic computing for multiple markets
Vision systems Cybersecurity Financial Technolog Agricultural Technology
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Company will provide investors insight with regard to activity in the following markets:
Industrial – Internet-of-Things (IoT), Agricultural Technology, Financial Technology, Cybersecurity, Robotics, Process Control and Manufacturing Automation, , Surveillance, Gaming Automotive – ADAS and AV Consumer – Internet-of-Things (IoT), Cell Phones, Personal Computing and Home Security
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Source: Tractica Deep Learning Chipsets, Q2 2018
10,000 20,000 30,000 40,000 50,000 60,000 70,000 2018 2019 2020 2021 2022 2023 2024 2025
$M
AI Acceleration Chipset Forecast
Training Inference General Purpose
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Convolutional Neural Networks Spiking Neural Networks
Characteristic Result Characteristic Result Computational functions Matrix Multiplication, ReLU, Pooling, FC layers Math intensive, high power, custom acceleration blocks Threshold logic, connection reinforcement Math-light, low power, standard logic Training Backpropagation off- chip Requires large pre- labeled datasets, long and expensive training periods Feed-Forward, on or
Short training cycles, continuous learning
Math intensive cloud compute Low power edge deployments
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Civil surveillance
French Homeland Security (DGSI) French National Police (Paris, Toulouse)
Custom software deployments
Machine vision
SAFRAN augmented reality
Gaming
Mohegan Sun Las Vegas Trials
10 years of development
Mass-Market Product
Real-time card and chip detection Forensics and live analytics Object recognition
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Exabytes of previously recorded video Low resolution and noisy environments Prohibitively expensive to “Classify” all video using deep learning
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Fo Forensic Object Se Sear arch Fa Face Detection and and Cl Classificati tion
Highly effective
recognition technology in low-resolution environments Automatic face detection and extraction Find suspects across hundreds of videos Uses existing low-fidelity infrastructure for live or recorded forensic search One-Shot learning to rapidly search for patterns/suspects Force multiplier: Single individual can do the scanning of many Facial classification of top matches Targeting the civil defense/police marketplace
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BCS Learn
Visual target to identify BrainChip recognition model Recognition of patterns with similar visual features LEARN RECOGNIZE
It’s all about shape recognition, not biometrics and key points!
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Improved probability of object detection
Fast video scaling
Faster time to results
More channels, faster
Lower total cost of ownership
Lower initial cost, reduced power, and longer MTBF
3 Scales, 1 Model 3 Scales, 4 Models 6 Scales, 4 Models
BrainChip Accelerator FPS Increase Compared to Software Only 6x 5x 6x
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World’s first Neuromorphic System on Chip (NSoC)
Efficient neuron model Innovative training methodologies
Everything required for embedded/edge applications
On-chip processor Data->spike conversion
Scalable for Server/Cloud
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Most efficient spiking neural network implementation
1.2M Neurons 10B Synapses
Able to replicate most CNN functionality
Convolution Pooling Fully connected
Right-Sized for embedded applications 10 classifiers (CIFAR 10)
11 Layers 517K Neurons 616M Synapses
Meets demanding performance criteria
1,100 fps CIFAR-10 82% accuracy
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Relative Implementation Efficiency (Neurons and Synapses) 300X 3X
Fixed neuron model
Right-sized Synapses minimized
6MB compared to 30-50MB
Programmable training and firing thresholds
Flexible neural processor cores
Highly optimized to perform convolutions Also fully connected, pooling
Efficient connectivity
Global spike bus connects all neural processors Multi-chip expandable to 1.2 Billion neurons
Keys to efficiency
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Frames per Second/watt Top-1 Accuracy
Cifar-10 Intel Myriad 2
79% 18 fps/w ~$10
Cifar-10 BrainChip Akida
1.4K fps/w 82% ~$10
Cifar-10 IBM TrueNorth
83% 6K fps/w ~$1,000
Cifar-10 Xilinx ZC709
80% 6K fps/w ~$1,000
Tremendous throughput with low power
Math-lite, no MACs
No DRAM access for weights Comparable accuracy
Optimized synapses and neurons ensures precision
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World’s first NSoC
Low power and footprint of neuromorphic computing Highest performance /w/$
Complete solution for embedded/edge applications – but scalable for cloud/server usage Sampling 2H 2019
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EE Times (Rick Merritt)
https:/https://www.eetimes.com/document.asp?doc_id=1333677/www.ee times.com/document.asp?doc_id=1333677
Electronics Weekly (David Manners)
https://www.electronicsweekly.com/news/business/brainchip-sets-date- soc-2018-09/
Markt & Technik (Heinz Arnold)
https://www.elektroniknet.de/markt-technik/halbleiter/ki-prozessoren- arbeiten-erstmals-gehirnaehnlich-157555.html
Electronic Design (Bill Wong)
https://www.electronicdesign.com/embedded-revolution/snn-news- brainchip-unveils-akida-architecture
Electronicnewstv (Alix Paultre)
https://www.youtube.com/watch?v=Tt6emRbQLj0
Electronik Praxis (Sebastian Gerstl)
https://www.elektronikpraxis.vogel.de/ki-im-embedded-einsatz-erster- neuromorpher-soc-baustein-angekuendigt-a-751920/?cmp=beleg-mail
Sources Security https://www.sourcesecurity.com/news/brainchip-akida- development-environment-neuromorphic-system-on-chip-co- 1524051571-ga-npr.1532608634.html CiE Magazine (Amy Wallington)
http://www.cieonline.co.uk/brainchip-announces-the-akida-architecture-a- neuromorphic-system-on-chip
All Electronics
http://www.dpaonthenet.net/article/159841/Putting-artificial-intelligence- at-the-edge-and-enterprise.aspx
L'embarque
http://www.lembarque.com/brainchip-prevoit-pour-2019-une-puce- systeme-neuromorphique-taillee-pour-lembarque_007839
Design, Products & Applications
http://www.dpaonthenet.net/article/159841/Putting-artificial-intelligence- at-the-edge-and-enterprise.aspx
Embedded Control Europe
http://www.embedded-control-europe.com/article/6503/brainchip-neural- network-acceleration-socs-puts-artificial-intelligence-at-the-edge-and- enterprise
Design and Reuse
https://www.design-reuse.com/news/44711/brainchip-akida- neuromorphic-soc.html
New Electronics
http://www.newelectronics.co.uk/electronics-news/us-company-unveils- first-commercial-spiking-neural-network-architecture/182822/
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Thank You