BRN Discussion Ongoing
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Frangipani
Top 20
Hi @TheFunkMachine,
yes, this article also appeared on Medium four days ago in almost identical form and refers to a paper, in which researchers from universities in China and Australia have used AKD1000 for skin lesion classification.
https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-470544
@Fullmoonfever had previously discovered a GitHub repository called “Akida-Research-Project”, which had been set up by one of the paper’s co-authors.
https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-469934
Your Phone Could Soon Diagnose Skin Cancer—Thanks to a New Kind of AI - NeuromorphicCore.ai
Discover how QANA, a new brain-inspired AI, is bringing fast, private, and accurate skin cancer diagnosis directly to portable devices. Learn how this innovation helps close healthcare gaps, addressing shortages of dermatologists and improving outcomes, especially for underserved communities.
neuromorphiccore.ai
It appears Bradley Susser is the person behind neuromorphiccore.ai
The only changes from the Medium version of the article seem to be the edited picture as well as the middle part called “Cloud vs Edge: A Technology Comparison”, which is here presented in a table format rather than text:
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Intel Corporation and IBM seemed like the biggest players in the neuromorphic field but honestly what did they even do to promote it? | Neuromorphicism
Intel Corporation and IBM seemed like the biggest players in the neuromorphic field but honestly what did they even do to promote it? (All their representatives ignored Neuromorphicism for example) Are we waiting until 2030 to use their hardware commercially? If so many smaller companies can...
Interesting comments.
Frangipani
Top 20
Cecilia Pisano from Nurjana Technologies has repeatedly liked BrainChip posts on LinkedIn, and hence her Sardinia-based company has been mentioned by several forum members as potentially playing with Akida:
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And here’s the proof that it was indeed worth keeping an eye on Nurjana Tech :
Paper submissions now open for EDGE-X: Rethinking Edge Intelligence | Arijit Mukherjee
Paper submissions now open for EDGE-X: Rethinking Edge Intelligence 📍 Co-located with AI-ML Systems Conference 2025 | Chancery Pavilion, Bangalore | October 8, 2025 🧠 Topics include: • On-device learning and inference • ML/DL optimization for memory, latency, and power • Hardware-software...www.linkedin.com
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Home - NurjanaTech
NurjanaTech provides a wide range of engineering capabilities to support a global customer base whose operations and complex environments require a partner that possesses unique expertise and comprehensive solutions.www.nurjanatech.com
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Three weeks ago, Cecilia Pisano shared on LinkedIn that Nurjana Technologies had been “applying Brainchip Akida to real use cases for more than 1 year”, when she commented on a post by Arijit Mukherjee from TCS
.At the time, her profile picture already signalled that she were #Opentowork. However, her posts about being “incredibly proud to be part of Nurjana Technologies” and her involvement in several recent company projects had suggested to me she might be looking for an additional part-time role rather than a new full-time role.
I'm incredibly proud to be part of Nurjana Technologies as we take a giant leap forward in the space industry! | Cecilia Pisano
I'm incredibly proud to be part of Nurjana Technologies as we take a giant leap forward in the space industry! 🚀 Yesterday, at the UK Houses of Parliament, the "𝗚𝗶𝘃𝗲 𝗠𝗲 𝗦𝗼𝗺𝗲 𝗦𝗽𝗮𝗰𝗲!" mission was announced — bringing together top international space companies to showcase cutting-edge tech for...
Forza Nurjana Technologies. | Cecilia Pisano
Forza Nurjana Technologies. Forza ESTECO , Luxembourg Institute of Science and Technology (LIST) , Rafinex , Gradel S.à r.l. . Let’s make the most of this fantastic opportunity 💪💪💪#EDA #stealth #uav #rapidprototyping
It's fantastic to see what Nurjana Technologies is accomplishing. | Cecilia Pisano
It's fantastic to see what Nurjana Technologies is accomplishing. I'm really proud to be part of this journey and to work alongside such brilliant engineers. The growth, the new talent joining the team, and the cutting-edge work in AI and space technology are truly inspiring. Here's to reaching...
It is great to be part of the Staalion EDF project, where some of my ideas around leveraging innovative cameras and processors for edge AI are starting to take shape. | Cecilia Pisano
It is great to be part of the Staalion EDF project, where some of my ideas around leveraging innovative cameras and processors for edge AI are starting to take shape. It’s a privilege to work at Nurjana Technologies, a company that truly supports forward-thinking ideas and gives me the space to...
Today, she posted on LinkedIn about “taking a well-deserved break to focus on personal projects” and that it felt like “the perfect time to work on a patent and prototype a new idea”, but said that at the same time she were “actively exploring new opportunities in technology strategy, research and development”.
She also uploaded her CV, in which she detailed what kind of work she had done during her time as R&D Lead Engineer at Nurjana Technologies before resigning recently, part of which was “developing advanced optical payloads for satellites and drones, including event-based cameras and neuromorphic processors.”
End of a chapter. | Cecilia Pisano
End of a chapter. Taking a well-deserved break to focus on personal projects—this feels like the perfect time to work on a patent and prototype a new idea. At the same time, I’m actively exploring new opportunities in technology strategy, research, and development where I can blend my skills...
It will be interesting to follow up on what she will end up doing in the coming months.
Founding her own startup is one option as well:
#launching a startup program | Cecilia Pisano
#launching a startup program 'Analyze various techniques to develop a product prototype. Conduct effective interviews with potential customers to develop your customer personas. Create and describe a value proposition for a specific product. Develop a go-to-market (GTM) plan, and determine key...
Will her wish to see an Akida 2.0 reference chip be granted?
To date, our CTO has not replied to her comment.
It seems Cecilia Pisano has something specific in mind she could very well use it for…
BrainChip and Raytheon Form Strategic Partnership on #AFRL #Neuromorphic #Radar Project | embedded.com
BrainChip and Raytheon Form Strategic Partnership on #AFRL #Neuromorphic #Radar Project
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Pom down under
Top 20
I’m positive but probably wrong that Sean said at the AGM regarding when we expecting it and he said maybe this year probably next
smoothsailing18
Regular
My recollection is he most definitely said 9 million this year the next question was on royalties which he said would be next year.I’m positive but probably wrong that Sean said at the AGM regarding when we expecting it and he said maybe this year probably next
I can't remember which podcast it was and at what time point Sean made the comment it would be much appreciated if someone could assist on this please ?.
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Honestly, I think Sean’s “$9M revenue” comment at the last AGM was just communicated a bit awkwardly. My takeaway is that he was talking about it as a target, not guaranteed revenue already locked in.
And honestly, it wouldn’t even make sense to casually drop something that pricesensitive when they’re usually so picky about what qualifies for an official ASX announcement.
So I don’t get why people expect the price to suddenly explode when it shows up on paper it’s not “new news,” it’s simply the company working toward that goal. If you believe they’ll hit it, wouldn’t it make more sense to buy now rather than chase the spike later? Unless of course the shorts are just sitting there waiting to hammer it down again…
And honestly, it wouldn’t even make sense to casually drop something that pricesensitive when they’re usually so picky about what qualifies for an official ASX announcement.
So I don’t get why people expect the price to suddenly explode when it shows up on paper it’s not “new news,” it’s simply the company working toward that goal. If you believe they’ll hit it, wouldn’t it make more sense to buy now rather than chase the spike later? Unless of course the shorts are just sitting there waiting to hammer it down again…
Bravo
If ARM was an arm, BRN would be its biceps💪!
That's how I understand it too. The $9M revenue via bookings is definitely not guaranteed, rather it's a target tied to Sean's bonus.
Also, I'm pretty sure I read somewhere that the target is only tied to a percentage of Sean's bonus (50% I beleive), so if the $9M isn't achieved, Sean will still receive the remaining 50% of the bonus.
Sean was also asked about “royalties” this year and he stated that they were unlikely but possible.
Please fee free to correct if this is inaccurate.
maybe it will skyrocket after all… 
smoothsailing18
Regular
FF
brainchip.com
LeadGen_Onsor - LP
Enhancing Ocean Safety with Efficient AI-Powered Detection Arquimea has deployed Akida with a Prophesee camera on a drone to detect distressed swimmers and surfers in the ocean helping lifeguards scale their services for large beach areas, opting for an event-based computing solution for its...
brainchip.com
FF
LeadGen_Onsor - LP
Enhancing Ocean Safety with Efficient AI-Powered Detection Arquimea has deployed Akida with a Prophesee camera on a drone to detect distressed swimmers and surfers in the ocean helping lifeguards scale their services for large beach areas, opting for an event-based computing solution for its...
smoothsailing18
Regular
I wonder if this Propesse and brainchip partnership will lead us to Sony through Propesse already existing partnership with them .
Qualcomm also in the mix.
I want to hold a phone with brainchip inside ,that's my dream that I want to become a reality.
Finger's
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.Qualcomm also in the mix.
I want to hold a phone with brainchip inside ,that's my dream that I want to become a reality.
Finger's
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SERA2g
Founding Member
It was 100% a target and anyone who misunderstood that has their ears painted on.
It was specifically confirmed by Sean and Antonion that Sean's performance bonuses would be tied to a bookings target, which was later revealed as being $9m.
It's been a while since I've looked at the rem reports etc but pretty sure Sean's rem package is a salary of circa $400k + up to 100% of his salary as a bonus pending meeting performance hurdles (in this case $9m bookings). Don't quote me on the 100%, it could be 50%, it could be 75%.
I think the bonus is in shares rather than cash, but that also not sure on that point.
Basically i'm not sure of anything. LOL
Mazewolf
Regular
Each use case below leverages the Akida chip in tandem with either an emerging technology or a widely adopted existing system, while remaining speculative and unannounced by BrainChip.
Why It Works: Textile-integrated IMUs capture motion events; Akida classifies movement anomalies on-device with near-zero latency.
Innovation:
Tech Basis: Voice recognition + federated learning + Akida Pico
Why It Works: Low-power voiceprint analysis embedded in terminals (e.g., ATMs, ticketing kiosks)
Innovation:
Tech Basis: Non-invasive EEG headsets + Akida Pico + AR/VR systems
Why It Works: Spiking data from EEG translated into control signals in real time
Innovation:
Tech Basis: Optical flow sensors + time-of-flight cameras + Akida Pico
Why It Works: Event-based vision allows Akida to detect motion, object proximity, and learn dynamic obstacles inside warehouses
Innovation:
Tech Basis: Facial recognition cameras (standard CMOS) + Akida Pico + AI edge gateways
Why It Works: SNNs are highly efficient in recognizing temporal inconsistencies (e.g., blinking, micro-expressions) that reveal deepfakes or spoof attacks
Innovation:
1. Adaptive Smart Textiles for Athlete Biomechanics
Tech Basis: Wearable smart fabrics + IMU sensors + Akida PicoWhy It Works: Textile-integrated IMUs capture motion events; Akida classifies movement anomalies on-device with near-zero latency.
Innovation:
- Real-time biomechanics monitoring during performance
- SNNs adapt to individual motion signatures over time
- Power-efficient enough to run on body heat/kinetic energy harvesting
- High-value market in elite sports, injury prevention, and physiotherapy
- White-label integration into Nike, Adidas, Under Armour gear
- Potential licensing model with athletic teams & institutions
2. Privacy-Preserving Voice Biometrics in ATMs or Public Kiosks
Tech Basis: Voice recognition + federated learning + Akida Pico
Why It Works: Low-power voiceprint analysis embedded in terminals (e.g., ATMs, ticketing kiosks)
Innovation:
- On-device biometric authentication without transmitting voice data
- Akida enables federated learning: learns user accents without uploading samples
- Resistant to spoofing via real-time pattern analysis of vocal spiking patterns
- Regulatory-compliant (GDPR/HIPAA) biometric security solution
- Marketable to banks, governments, airports
- Vast deployment potential in low-bandwidth regions
3. Brain–Computer Interface Prosthetic Controller
Tech Basis: Non-invasive EEG headsets + Akida Pico + AR/VR systems
Why It Works: Spiking data from EEG translated into control signals in real time
Innovation:
- Akida enables localized learning of brainwave-to-motion patterns
- Eliminates cloud latency for prosthetic or exosuit control
- Integrates with AR HUDs (Hololens, Apple Vision Pro) to give real-time feedback
- Disability tech, military rehab, elder care
- Potential B2B partnerships with neural interface firms (e.g., NextMind, Cognixion)
- Patented BCI controller layer could be monetized
4. Autonomous Microdrones for Indoor Logistics
Tech Basis: Optical flow sensors + time-of-flight cameras + Akida Pico
Why It Works: Event-based vision allows Akida to detect motion, object proximity, and learn dynamic obstacles inside warehouses
Innovation:
- Microdrone fleet coordination through edge-based real-time navigation
- Akida performs on-device object recognition and path optimization
- Scales better than centralized models due to bandwidth-free coordination
- Indoor logistics and inventory management (Amazon, Alibaba)
- SaaS platform for microdrone AI optimization
- New market: drone task-outsourcing in tight/confined environments
5. On-Device Anti-Spoofing for Large-Scale Facial Recognition
Tech Basis: Facial recognition cameras (standard CMOS) + Akida Pico + AI edge gateways
Why It Works: SNNs are highly efficient in recognizing temporal inconsistencies (e.g., blinking, micro-expressions) that reveal deepfakes or spoof attacks
Innovation:
- Real-time liveness detection without cloud connection
- Learns individual user variability (e.g., eye movement cadence)
- Can be integrated in access control systems or consumer phones
- Government-grade ID verification (airports, border control)
- Secure enterprise logins (Zero Trust architecture)
- Plug-and-play anti-deepfake security module for existing surveillance systems
Summary Matrix
| Use Case | Tech Combo | Domain | Revenue Potential | Competitive Edge |
|---|---|---|---|---|
| Smart Textiles | IMU + Akida | Sports Med | High | On-device learning |
| Voice Biometrics | Voice + Federated + Akida | Fintech / Govt | High | Privacy-preserving |
| BCI Prosthetics | EEG + Akida + AR | Medtech | Medium-High | Real-time neuro AI |
| Microdrone AI | Vision + Akida | Logistics | High | Bandwidth-free autonomy |
| Liveness Detection | Vision + Akida | Security | High | Edge deepfake resistance |
Mazewolf
Regular
Here are five high-revenue, Fortune 500-aligned examples where the Akida neuromorphic chip can provide or secure an innovative competitive advantage through integration into core product offerings or internal infrastructure. Each case includes the company's strategic needs, how Akida helps, and the competitive edge it introduces:
Use Case: On-device adaptive hearing personalization in AirPods or future wearable audio devices
Akida’s Role: Ultra-low power neural processing for real-time noise filtering, hearing profile adaptation, and spatial sound tracking using spiking audio data
Strategic Need: Apple seeks tighter integration of personalized, health-linked audio and real-time spatial computing (e.g. Vision Pro ecosystem)
Competitive Edge:
Use Case: Decentralized AI for Echo devices and Kiva robotics, enabling faster and more private local decisions
Akida’s Role: Integrate into Echo speakers and warehouse robots to reduce cloud inference latency and power draw
Strategic Need: Amazon wants to improve energy efficiency and reduce server-side compute costs for Alexa and fulfillment operations
Competitive Edge:
Use Case: Low-power, always-on perception for vision-based driver monitoring systems (DMS) or secondary sensors
Akida’s Role: Run SNN models on driver behavior, in-cabin motion, and fatigue without taxing the main FSD chip
Strategic Need: Tesla’s Dojo and FSD stack are high-powered; offloading low-level, safety-critical perception to an Akida co-processor improves energy and redundancy
Competitive Edge:
Use Case: Smart surgical instruments, diagnostics, or wearables for post-op monitoring that adapt to patient-specific signals
Akida’s Role: Embedded SNN chip for ultra-low power real-time bio-signal classification (e.g., tremor, ECG, EMG)
Strategic Need: J&J is investing in digital surgery (e.g., OTTAVA) and patient-connected devices
Competitive Edge:
Use Case: Store-edge Akida-enabled cameras for shoplifting detection, shelf stock prediction, and employee activity classification
Akida’s Role: Low-cost edge deployment of computer vision at scale; Akida’s SNN excels at temporal events (e.g., repeated suspicious behavior)
Strategic Need: Walmart needs low-cost, privacy-compliant smart retail systems across thousands of stores
Competitive Edge:
1. Apple Inc. – Next-Gen Smart Hearing & Spatial Audio Devices
Use Case: On-device adaptive hearing personalization in AirPods or future wearable audio devices
Akida’s Role: Ultra-low power neural processing for real-time noise filtering, hearing profile adaptation, and spatial sound tracking using spiking audio data
Strategic Need: Apple seeks tighter integration of personalized, health-linked audio and real-time spatial computing (e.g. Vision Pro ecosystem)
Competitive Edge:
- Differentiates AirPods with on-device auditory intelligence
- Enhances privacy (no audio sent to cloud)
- Adds value to Apple's broader Health & Accessibility offerings
Revenue Potential: >$20B segment (Wearables/Home/Accessories)
2. Amazon – Intelligent Edge for Echo & Warehouse Robotics
Use Case: Decentralized AI for Echo devices and Kiva robotics, enabling faster and more private local decisions
Akida’s Role: Integrate into Echo speakers and warehouse robots to reduce cloud inference latency and power draw
Strategic Need: Amazon wants to improve energy efficiency and reduce server-side compute costs for Alexa and fulfillment operations
Competitive Edge:
- Faster local response = better UX
- Lower cost of compute per user interaction
- Scalable privacy-respecting smart home ecosystem
Revenue Potential: -
- ~$200B+ logistics operations savings at scale
3. Tesla – Ultra-Efficient Perception for Autonomous Driving Edge Cases
Use Case: Low-power, always-on perception for vision-based driver monitoring systems (DMS) or secondary sensors
Akida’s Role: Run SNN models on driver behavior, in-cabin motion, and fatigue without taxing the main FSD chip
Strategic Need: Tesla’s Dojo and FSD stack are high-powered; offloading low-level, safety-critical perception to an Akida co-processor improves energy and redundancy
Competitive Edge:
- Compliance with EU/US driver monitoring regs
- Reduced thermal/power burden in vehicles
- Can use temporal learning to personalize driver responses
Revenue Potential: FSD & Hardware upgrades = $12B+ annually
4. Johnson & Johnson – Neuromorphic Edge in Smart Medical Devices
Use Case: Smart surgical instruments, diagnostics, or wearables for post-op monitoring that adapt to patient-specific signals
Akida’s Role: Embedded SNN chip for ultra-low power real-time bio-signal classification (e.g., tremor, ECG, EMG)
Strategic Need: J&J is investing in digital surgery (e.g., OTTAVA) and patient-connected devices
Competitive Edge:
- Enables battery-efficient, real-time closed-loop systems
- Devices learn from patient baselines and adjust responses (e.g., haptic feedback)
- Minimizes cloud dependency = faster FDA path
Revenue Potential: Surgical & Interventional segment >$25B
5. Walmart – Edge AI for Loss Prevention and Shelf Management
Use Case: Store-edge Akida-enabled cameras for shoplifting detection, shelf stock prediction, and employee activity classification
Akida’s Role: Low-cost edge deployment of computer vision at scale; Akida’s SNN excels at temporal events (e.g., repeated suspicious behavior)
Strategic Need: Walmart needs low-cost, privacy-compliant smart retail systems across thousands of stores
Competitive Edge:
- Real-time shrinkage detection without adding cloud expense
- Improve restocking response with adaptive shelf analysis
- Supports high-scale IoT rollout at marginal cost
Revenue Potential: Loss prevention impact >$3B annually; Inventory efficiency could save >$5B
Summary Table
| Company | Use Case | Akida Function | Revenue Domain | Competitive Advantage |
|---|---|---|---|---|
| Apple | Personalized hearing + spatial audio | Adaptive SNNs for audio | $20B+ wearables | Health+privacy differentiation |
| Amazon | Smart devices + robots | Edge inference, energy saving | $200B infra | Latency + cost reduction |
| Tesla | Driver monitoring + sensor fusion | In-cabin perception, low power | $12B+ FSD | Redundancy + compliance |
| J&J | Smart medical systems | Bio-signal adaptation | $25B medtech | FDA-aligned, personalized AI |
| Walmart | Theft & stock control | On-device CV at scale | $8B+ operations | Retail AI at low TCO |
That’s why I pointed it out…somehow it made no sense to me…unfortunately when it comes to money, rational thinking often goes out the window. The brain starts spinning a story that feels plausible in the moment, and once several people share the same view, that idea becomes entrenched and no one questions it anymore.
To make your disappointment more perfect, they will drop a notification for unquoted securities at the same time! BOOM TAKE THAT
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