Brainchip Holdings Ltd. · ASX:BRN
Brainchip — Investor Presentation (November 2015)
56 slides from Brainchip's investor presentation, Nov 24, 2015
Slide 1: Hi, we're BrainChip
For personal use only Hi, we’re
Slide 2: Disclaimer
Disclaimer For personal use only 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 de
Slide 3: You're about to see a brand new technology
For personal use only You’re about to see a brand new technology. There’s a lot to absorb, so get comfy.
Slide 4: Nearly everyone has a smartphone
For personal use only Nearly everyone has a smartphone. But what makes a smartphone smart?
Slide 5: Its brain: phones are programmed to be smart
For personal use only Its “brain”. However, phones are programmed to be smart, using hardware and software.
Slide 6: We have a technology that is truly smart
For personal use only We have a technology that is truly smart. And it’s orders of magnitude faster than current technologies
Slide 7: Spiking Neuron Adaptive Processor technology
For personal use only It’s called Spiking Neuron Adaptive Processor technology. And it has a handy acronym: SNAP.
Slide 8: We've been developing SNAP for years
For personal use only We’ve been developing SNAP for over 10 years and its capabilities go far beyond speed improvements.
Slide 9: So how does it work?
For personal use only So how does it work?
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Slide 14: Autonomous learning curve for neuromodulator
brainchip”™ FOR NEUROMODULATOR 1 <= AUTONOMOUS 5 LEARNING CURVE FOR NEUROMODULATOR 2
Slide 15: Spike timing dependent plasticity (STDP)
For personal use only brainchip™ THIS IS WHAT CHARACTERISES THE PROCESS OF LEARNING: SPIKE TIMING DEPENDANT PLASTICITY (STDP)
Slide 16: Neural modulator diagram
NEURAL MODULATOR = CAR IN FRONT KL SYNAPSE DENDRITE ®@ ») INPUT SPIKE FEEDBACK SPIKE \ \ AXON SYNAPSE DENDRITE HILLOCK R INPUT SPIKE = KK SYNAPSE DENDRITE INPUT SPIKE LATERAL INHIBITION
Slide 17: Orders of magnitude faster
Orders of For personal use only magnitude faster
Slide 18: Orders of magnitude faster, 1/1000 power consumption
Orders of For personal use only magnitude faster 1/1000 power th consumption
Slide 19: Autonomous learning
Orders of For personal use only magnitude faster 1/1000 power th consumption Autonomous learning
Slide 20: Revolutionary digital hardware only design
Revolutionary Orders of Digital Hardware For personal use only magnitude faster only design, no Software 1/1000 power th consumption Autonomous learning
Slide 21: Massive parallel processing
Revolutionary Orders of Digital Hardware For personal use only magnitude faster only design, no Software 1/1000 power th Massive parallel consumption processing Autonomous learning
Slide 22: Standalone or co-processor configurations
Revolutionary Orders of Digital Hardware For personal use only magnitude faster only design, no Software 1/1000 power th Massive parallel consumption processing Autonomous Standalone or learning co-processor configurations
Slide 23: SNAP is true Artificial Intelligence
For personal use only SNAP is true Artificial Intelligence that can learn and operate at speeds close to the human brain.
Slide 24: How SNAP compares to current AI
How SNAP compares For personal use only to current AI.
Slide 25: How SNAP compares to current AI
How SNAP compares For personal use only to current AI. Software Neural Networks
Slide 26: How SNAP compares to current AI
How SNAP compares For personal use only to current AI. Software Neural Networks • High latency with software overhang
Slide 27: How SNAP compares to current AI
How SNAP compares For personal use only to current AI. Software Neural Networks • High latency with software overhang • Designed for very specific tasks
Slide 28: How SNAP compares to current AI
How SNAP compares For personal use only to current AI. Software Neural Networks • High latency with software overhang • Designed for very specific tasks • Requires a huge server facility
Slide 29: How SNAP compares to current AI
How SNAP compares For personal use only to current AI. Software Neural Networks • High latency with software overhang • Designed for very specific tasks • Requires a huge server facility • Relies on cloud-based storage
Slide 30: How SNAP compares to current AI
How SNAP compares For personal use only to current AI. Software Neural Networks SNAP • High latency with software overhang • Designed for very specific tasks • Requires a huge server facility • Relies on cloud-based storage
Slide 31: How SNAP compares to current AI
How SNAP compares For personal use only to current AI. Software Neural Networks SNAP • High latency with software overhang • Extremely low latency • Designed for very specific tasks • Requires a huge server facility • Relies on cloud-based storage
Slide 32: How SNAP compares to current AI
How SNAP compares For personal use only to current AI. Software Neural Networks SNAP • High latency with software overhang • Extremely low latency • Designed for very specific tasks • Learns from a wide variety of inputs • Requires a huge server facility • Relies on cloud-based storage
Slide 33: How SNAP compares to current AI
How SNAP compares For personal use only to current AI. Software Neural Networks SNAP • High latency with software overhang • Extremely low latency • Designed for very specific tasks • Learns from a wide variety of inputs • Requires a huge server facility • A small network of microchips • Relies on c
Slide 34: How SNAP compares to current AI
How SNAP compares For personal use only to current AI. Software Neural Networks SNAP • High latency with software overhang • Extremely low latency • Designed for very specific tasks • Learns from a wide variety of inputs • Requires a huge server facility • A small network of microchips • Relies on c
Slide 35: One SNAP neuron equals 4997 Sigmoid neurons
For personal use only One SNAP neuron is the equivalent to 4997 Sigmoid (Software) neurons. Wolfgang Maass, University of Graz.
Slide 36: Our smarts are our biggest asset
For personal use only Our smarts are our biggest asset. BrainChip is an IP licensing business, so our business model will focus around licensing, engineering fees and royalty streams.
Slide 37: Network of Partners
poctctetses- Industry and Technology Insight — ~-------------------; Network of Partners: Creating products never thought possible before using the BrainChip Development Kit (BDK) Technology Collaboration Meee ee i . . $ License fee Autonomous Learning Devices i Maximum Cyber Security, e.g., in phon
Slide 38: Our market opportunities
For personal use only Our market opportunities. As well as our current discussions with potential technology partners, and series of products in the pipeline, we have identified two key areas of focus. Smartphones and the Internet of Things (IoT).
Slide 39: What Wikipedia says about the Internet of Things
For personal use only What Wikipedia Says about the Internet of things. “ The network of physical objects or "things" embedded with electronics, software, sensors, and network connectivity, which enables these ” objects to collect and exchange data.
Slide 40: What Dave Evans (Cisco) says about the Internet of Things
For personal use only What Dave Evans (Cisco) Says about the Internet of things; “ Experts estimate that the IoT will consist ” of almost 50 billion objects by 2020.
Slide 41: SNAP and the Internet of Things
SNAP and the For personal use only Internet of Things.
Slide 42: SNAP and the Internet of Things
SNAP and the For personal use only Internet of Things. SNAP technology can be embedded in IoT devices paired with various different sensors, like temperature, gas emissions, traffic cameras,CCTV and more.
Slide 43: SNAP and the Internet of Things
SNAP and the For personal use only Internet of Things. SNAP technology can be embedded in IoT The IoT sector is forecast devices paired with various different to be a multi billion dollar sensors, like temperature, gas emissions, market segment. traffic cameras,CCTV and more.
Slide 44: SNAP's future milestones
SNAP’s future milestones. For personal use only
Slide 45: SNAP's future milestones
SNAP’s future milestones. For personal use only Milestone 2 BrainChip Spiking Neural Network SNAP implemented in Hardware Demonstrates the advanced nature of the SNAP technology Enables scalability ✔ Delivery achieved ahead of schedule
Slide 46: SNAP's future milestones
SNAP’s future milestones. For personal use only Milestone 2 Milestone 3 BrainChip Spiking Neural Network SNAP Client / Server API SNAP implemented in Hardware Allows for product deployment on server Demonstrates the advanced nature of the SNAP technology Proves configurability Enables scalability Pr
Slide 47: SNAP's future milestones
SNAP’s future milestones. For personal use only Milestone 2 Milestone 3 Beyond BrainChip Spiking Neural Network SNAP Client / Server API BrainChip Development Kit (BDK) SNAP implemented in Hardware Allows for product deployment on server BrainChip Experimenters Kit (BEK) Demonstrates the advanced na
Slide 48: We plan to build a broad portfolio of global patents
For personal use only We plan to build a broad portfolio of global patents. We have 1 granted patent and five patents pending.
Slide 49: We plan to build a broad portfolio of global patents
For personal use only We plan to build a broad portfolio of global patents. Brainchip has a large number of patents in progress.
Slide 50: The brains behind BrainChip
The brains behind Brainchip For personal use only Mick Bolto Peter van der Made Adam Osseiran Anil Mankar Neil Rinaldi Chairman Executive Director, Non executive Chief Operating Non Executive CTO and Interim CEO Director Officer Director Legal and Corporate background. SNAP inventor, Engineering An
Slide 51: Scientific Advisory Board
Scientific Advisory Board For personal use only The team behind the team Dr. Nicholas Spitzer Dr. Jeffrey Krichmar Dr. Gert Cauwenberghs Neuroscientist Cognitive Scientist Scientist Professor at Professor at Professor University of University of University of California San Diego California San Dieg
Slide 52: Capital Structure
Capital Structure For personal use only Top twenty shareholders hold greater Security Number of Escrowed Performance Unlisted than 75.00% Type shares shares rights options Unrestricted fully paid shares (free float) 239,700,608 54% of structure escrowed for between 1-2 years Restricted fully paid sh
Slide 53: Let's recap
For personal use only Let’s recap.
Slide 54: Let's recap
Let’s recap. For personal use only We’re a team of experienced innovators with a disruptive technology and a diverse revenue model.
Slide 55: Let's recap
Let’s recap. For personal use only We’re a team of experienced This is a global opportunity, innovators with a disruptive we have significant product technology and a diverse development plans, and we’d revenue model. love to have you on board.
Slide 56: Pick our brains. Questions…
For personal use only Pick our brains. Questions… For further enquiries: Neil Rinaldi – Non Executive Director e: nrinaldi@brainchip.com.au Ben Knowles – Australian PR/IR Ted Haberfield – USA PR/IR Walbrook Invetor Relations MZ Group | President – MZ North America e: ben.knowles@walbrookir.com.au e:
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