ASX PRESS RELEASE 1 September 2016 Australian Investor Roadshow Presentation BrainChip Holdings Ltd (ASX: BRN) (“ BrainChip ” or “the Company ”), is pleased to release the attached Investor Roadshow Presentation to be made to Australian investors in a roadshow outlining the transaction highlights of the acquisition of Spikenet Technology SAS (“ Spikenet ”), a revenue‐producing, France‐based Artificial Intelligence (AI) company and leader in computer vision technology. END Company Contact: Investor Relations Contacts: Nerida Schmidt Australia: Company Secretary Brendon Lau nschmidt@brainchip.com.au Associate Director Media and Capital Partners Corporate Advisors: brendon.lau@mcpartners.com.au Chris Francis +61 409 341 613 Foster Stockbroking Executive Director USA: +61 2 9993 8167 Greg Falesnik chris.francis@fostock.com.au Senior Vice President MZ North America Media Contact: greg.falesnik@mzgroup.us Ben Grubb +1 949 385 6449 Media and Capital Partners ben.grubb@mcpartners.com.au +61 414 197 508 ______________________________________________________________________________ BrainChip Holdings Ltd ACN 151 159 812 Level 2, 6 Thelma S treet, West Perth WA 6005 T: +61 8 9444 2555 | F: +61 8 9444 1600 | W: www.brainchipinc.com
ASX: BRN Spikenet acquisition September 2016
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 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 occurrence of the events referred to in the presentation will actually occur as contemplated. 1/09/2016 Private & Confidential 2
Overview of BrainChip ASX: BRN BrainChip has developed a revolutionary Spiking Neuron Adaptive Processor (SNAP) technology that learns autonomously and unsupervised, evolves and associates information just like the human brain SNAP technology provides rapid and autonomous learning, KEY MATRIX confirmed in the Autonomous Visual Feature Extraction ASX Code BRN demonstration in March 2016 Market Cap (post Spikenet A$96.7M acquisition) SNAP is deployable across multiple fast‐growing markets Share Price (25 Aug 2016) A$0.13 BrainChip is following a proven Semiconductor industry Issued Shares (post 743.9M Intellectual Property (IP) licensing model to deriving its Spikenet acquisition) revenue from License, Engineering and Royalty fees Options 24.55M Cash (30 Jun 2016) US$2.90M 3
Spikenet acquisition summary BrainChip has acquired France‐based Acquisition summary Computer Vision Technology Company BrainChip has acquired 100% of Spikenet – Spikenet Technology Technology Spikenet was established in 1999, and Acquisition cost was 10.4 million shares in has developed breakthrough software BrainChip and 529,598 euros for artificial vision and visual pattern Includes Spikenet’s product library and related recognition. patent Spikenet provides programs that are Cash component fully funded from internal able to learn to recognise objects, faces resources and patterns. The technology has applications across a range of sectors including security, transport, media, manufacturing and gaming. 1/09/2016 Private & Confidential 4
Transaction highlights Complimentary The combined BrainChip The acquisition provides Expands the BrainChip technology offering with and Spikenet solution an immediate path to offering to include BrainChip focusing on holds the potential to commercialisation for software and hardware embedded hardware create the world’s most BrainChip’s SNAP solutions Artificial Intelligence and technology technically advanced, Spikenet on software only biologically inspired solution computer vision products Expected to give BrainChip can now Attractively priced BrainChip an immediate provide a logical and acquisition (circa $2.2 source of revenue, million) seamless upgrade path recurring income and a for customers moving ready customer base from software to hardware solutions 1/09/2016 Private & Confidential 5
Technological advantage
Spikenet’s breakthrough software The brain uses the order in which neurons fire AI BIOLOGY INSPIRED spikes to code information – Spikenet mimics this HUMAN VISION STRATEGIES process SPIKENET, A NETWORK OF SPIKES Spikenet’s Technology works similar to ASYNCHRONOUS SPIKING NEURON NETWORK BrainChip’s technology but is a software only TEMPORAL CODING, RANK ORDER solution VISUAL PATTERN MATCHING Based on 20 years of research – Spikenet uses image algorithms directly inspired by the strategies used by the human visual system Spikenet’s technology holds the potential to outperform even the most sophisticated machine vision systems (aside from BrainChip) and is able to analyse a complex scene in seconds Spikenet will gain an autonomous learning LEARN function when integrated with BrainChip MEMORIZE RECOGNIZE ANY VISUAL PATTERN, SUPERVISED ‐ UNSUPERVISED LEARNING OBJECT REAL‐TIME 1/09/2016 Private & Confidential 7
The Spikenet advantage Faster Adapts Learning High speed Accuracy deployment to real life capabilities Spikenet can detect Recognition of Software does not Adapts to low Easier to train to more than 5,000 exact image and require a chip to be resolutions, real life recognise visual patterns per second similar patterns produced so it can image conditions, patterns when on a standard PC with minimal false be deployed faster still and moving compared to rival positives cameras and “deep learning” outdoor constraints solutions 1/09/2016 Private & Confidential 8
Spikenet + SNAP = A game changer ? Spikenet's software A combined solution is is predicted to become far expected to create a product more effective when it is that is faster, far more supplemented efficient, requires less with BrainChip’s SNAP computing power and is autonomous learning cheaper than anything technology currently available The company’s objective in combining Spikenet and BrainChip is to provides a game changing technological advantage and a product that is superior to anything else currently in the market 1/09/2016 Private & Confidential 9
Spikenet + SNAP = A game changer ? Rival advance AI systems like IBM’s True North uses “Deep Learning”. Deep Learning networks don’t actually learn; they need extensive programing to “train” the system how to execute a job function. This is very time and resource consuming. A BrainChip/Spikenet solution would go beyond Deep Learning with autonomous learning that would require very little or no training program. This would enable BrainChip to offer solutions that cut the training time by 95% or more in most cases. 1/09/2016 Private & Confidential 10
Case study: Shark Detection & ID Problem Providing an automatic shark detection and identification system that can operate in all water and weather conditions with minimal false positive alerts. Current Use traditional image processing algorithms with systems frame‐based pixel data processing Processing power and are power intensive, particularly if high resolution images and faster frame rates are used in the analysis Industry turning to Convolution Neural Networks (CNNs) with “deep learning” (backed by Google, Microsoft, etc.) But deep learning on CNNs is also resource intensive. Needs massive cloud‐based servers to run CNNs don’t actually learn like humans as it requires a special training programs and thousands of sample photos to recognise objects BrainChip BrainChip is developing a revolutionary solution that is solution able to be “taught” quickly, and be used on drones and other portable platforms to significantly reduce costs. The solution may have wide ranging applications. 1/09/2016 Private & Confidential 11
Case study: Shark Detection & ID Identify all common species of sharks and Phase 2 use an embedded chip solution to achieve greater speed and efficiency. Create a software solution to automatically Phase 1 detect sharks 1/09/2016 12 Private & Confidential
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