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Implementing Neural Network Algorithms on Neuromorphic Processors | SBIR.gov

This one is only 6 weeks away from end date.
Something to look forward to.
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We are proud to present the Neurospace Project: a collaboration between Frontgrade Gaisler and BrainChip supported by the European Space Agency - ESA. | Frontgrade Gaisler
We are proud to present the Neurospace Project: a collaboration between Frontgrade Gaisler and BrainChip supported by the European Space Agency - ESA. At its center: GR801, our first neuromorphic AI solution for space. GR801 is built on the radiation-hardened NOEL-V processor and powered by...www.linkedin.com
There is a 2 min movie talking up the collaboration but it want copy across so have to view it in the LinkedIn link!
We are proud to present the Neurospace Project: a collaboration between Frontgrade Gaisler and BrainChip supported by the European Space Agency - ESA.
At its center: GR801, our first neuromorphic AI solution for space.
GR801 is built on the radiation-hardened NOEL-V processor and powered by BrainChip's Akida.
It delivers ultra-low power, real-time pattern recognition, and onboard decision-making without requiring Earth contact.
This is more than a milestone.
It's a paradigm shift for AI at the edge of space exploration.
Learn more: https://lnkd.in/dMq9sxkp
And https://lnkd.in/dSx8_mTQ
Also available on YouTube: https://lnkd.in/dC6_aWR2
#NeuromorphicAI #SpaceTech
Fantastique.![]()
We are proud to present the Neurospace Project: a collaboration between Frontgrade Gaisler and BrainChip supported by the European Space Agency - ESA. | Frontgrade Gaisler
We are proud to present the Neurospace Project: a collaboration between Frontgrade Gaisler and BrainChip supported by the European Space Agency - ESA. At its center: GR801, our first neuromorphic AI solution for space. GR801 is built on the radiation-hardened NOEL-V processor and powered by...www.linkedin.com
There is a 2 min movie talking up the collaboration but it want copy across so have to view it in the LinkedIn link!
We are proud to present the Neurospace Project: a collaboration between Frontgrade Gaisler and BrainChip supported by the European Space Agency - ESA.
At its center: GR801, our first neuromorphic AI solution for space.
GR801 is built on the radiation-hardened NOEL-V processor and powered by BrainChip's Akida.
It delivers ultra-low power, real-time pattern recognition, and onboard decision-making without requiring Earth contact.
This is more than a milestone.
It's a paradigm shift for AI at the edge of space exploration.
Learn more: https://lnkd.in/dMq9sxkp
And https://lnkd.in/dSx8_mTQ
Also available on YouTube: https://lnkd.in/dC6_aWR2
#NeuromorphicAI #SpaceTech
Maybe I have missed it, but has anyone found out already which FPGA provider Brainchip‘s IP has been demoed on?
(I‘m hoping for AMD‘s Xilinx, but Intel‘s Altera would be nice too …)
Maybe my above question was not formulated clearly enough:
I would like to know on which company‘s FPGA chip aka hardware (e.g. Xilinx, Altera, Lattice Semiconductor, Microchip, …) were used for the „software/algorithm/IP“ demos (the ones that didn’t run on a Akida 1000 or similar).
Looking Back: Early Nvidia Investors (1999–2005)I was talking with ChatGPT about Brainchip and endet up with this …
My post:
I’ve said it before on TSE .. none of this makes any sense to me anymore.
BrainChip has so many well-known partners, licensees, universities, and experts who speak positively about Akida and its potential. Everyone keeps saying it’s a game-changer, with unmatched energy efficiency and real-world applications. The potential is enormous.
And yet… the share price is utterly pathetic.
The management seems to do nothing but quote musicals, say things like “we hope that…” or “we see our product in every device” .but they take no actual steps to get real attention on the stock.
What’s going on? What are they waiting for?
Response:
You’re definitely not alone in feeling this. Many long-term holders are asking the same question: How can a company with such revolutionary tech and such a powerful network be valued so poorly?
Let’s break it down:
The contradiction:
- Tech: Akida is brilliant. Ultra-low power, edge-native, ideal for AIoT. Validated by experts, research labs, and devs worldwide.
- Partners: ARM, Edge Impulse, Mercedes-Benz hints, NASA references, universities.
- Potential: Everyone says “this chip could be in everything” – phones, cars, sensors, wearables.
- Reality: Sub-€0.10 stock, constant dilution, and nearly zero trust from the broader market. Why?
What’s wrong?
1. No significant revenue yet.
Lots of partners, yes – but none seem to have converted into real, meaningful licensing income. Without that, the market sees only R&D, not business.
2. Vague communication.
Management loves to say:
“We see Akida in all devices”
“We believe the world will see its value”
But there’s rarely anything concrete – no hard deals, no revenue numbers, no OEM names.
3. Dilution kills confidence.
The constant use of ATMs, performance rights, and stock options has deeply eroded investor trust. More shares, same pie.
4. Weak investor communication.
Other tech firms do roadshows, PR pushes, interviews, demos. BrainChip gives us Broadway quotes and philosophical posts – but no strategic IR campaign.
5. Market suspicion.
Too much promise, too little delivery. Until an OEM ships actual products with Akida inside – and BrainChip reports real revenue – the market stays skeptical.
So what is the management waiting for?
- Option 1: They do have something but are under strict NDAs – waiting for their partners to launch products before they can speak.
- Option 2: There simply isn’t anything major yet. Just more talks, demos, trials – and no conversions.
- Option 3: They’re trying to avoid overhyping, aiming for long-term trust… but forgot that even long-term investors need clarity and communication.
Bottom line:
You’re right: the gap between Akida’s perceived value and BRN’s actual market cap is absurd – but not accidental.
Management is either silent because they’re legally obligated – or because there’s simply nothing new to say.
Either way, it’s costing them trust, momentum, and shareholder confidence.
Until we see:
- Real, named customers
- Public revenue from licenses
- Clear product integrations
…the market will stay on the sidelines.
It’s not fair. But it’s how the game works.
Yes. Intel would be high on the probabilities list. We are partnered with IFS (or in their ecosystem).Hi @CrabmansFriend,
when googling for more information on BrainChip’s Aether Core LLM accelerator on FPGA (cf. https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-469022), I came across a few links to a recent (now expired) BrainChip job ad for a Hardware Engineering intern that says “Our current demo utilizes Intel x86 in conjunction with Aether Core LLM for showcasing our platform. This internship project aims to create an advanced proof-of-concept platform by integrating the LLM with a high-end ARM series. This innovation will serve as an impressive showcase at various demo and trade shows, highlighting our LLM capabilities with ARM technology”.
Can we infer from the info that the current LLM FPGA Tech Demonstrator runs on an Intel x86 CPU, it is highly likely / must be based on an Altera FPGA or would it be entirely possible to mix and match? I have no idea…
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Altera® FPGA Products - FPGA and SoC FPGA Devices and Solutions
Altera® FPGAs offer a wide variety of configurable embedded SRAM, high-speed transceivers, DSP blocks, high-speed I/Os, logic blocks, and routing.www.intel.com
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New repository set up yesterday on GitHub by NeuroSyd with the title:
Akida-Seizure.
Nothing added as yet but you'd suspect given what they do at the facility it would be our Akida they either been or will be playing with.
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NeuroSyd Research Laboratory
NeuroSyd Research Laboratory at the Faculty of Engineering, The University of Sydney, is where emerging paradigms in computing, data science, neuro/bio-engineering and nanotechnology collide. NeuroSyd research is highly multidisciplinary and span over a wide range of fields from Device to Data,sites.google.com
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Omid Kavehei
The University of Sydney - Cited by 6,901 - nanoelectronics - medical electronics - affective computing - learning machines - integrated circuit designscholar.google.com
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Hi @Fullmoonfever,
I found this October 2024 paper titled “Neuromorphic neuromodulation: Towards the next generation of closed-loop neurostimulation” - co-authored by Omid Kavehei - that describes what the research relating to the NeuroSyd GitHub repository is likely going to be about.
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Does Table 1, where Akida is falsely labeled as analog, seem somehow familiar?!
Turns out it was you who commented on this error after you had spotted that same table in an earlier version of that paper by the same co-authors in August 2023:
https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-338409
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One of the co-authors happens to be Jason Eshraghian, who has been a Member of our Scientific Advisory Board since August 2024 and was a guest on one of the “This is Our Mission” podcasts shortly after the above 2024 paper was submitted (3 May 2024). I trust he has since found out that Akida is digital.
A corrigendum would have been nice, though.
But maybe he is too busy with other things, such as collaborating with Intel Labs’ researchers on this recent paper titled “Neuromorphic Principles for Efficient Large Language Models on Intel Loihi 2”?
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Found a brand new University of Sydney PhD thesis, which is highly likely related to the GitHub “Akida Seizure” repository that one of the two thesis supervisors, Omid Kavehei, had set up under the GitHub name NeuroSyd just over two months ago (which seems to have disappeared since or has possibly been renamed?), spotted by @Fullmoonfever at the time.
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Student Profile
www.sydney.edu.au
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University of Sydney PhD candidate Andre Zainal, who has a B.Eng. (Biomedical) & B.MedSci background, embarked on his Research PhD in Biomedical Engineering just a week ago, “researching AI-driven neuromorphic hardware for early seizure detection”.
The title of his thesis is “Optimizing Training Algorithms for Neuromorphic Hardware: Enhancing In-Memory Computing with FPGA and Akida Neural Processors for Epileptic Seizure Detection”.
Akida doesn’t have “in-memory-computing”, though?
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Andre Zainal’s first PhD supervisor Omid Kavehei has been conducting epilepsy research for years:
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Staff Profile
www.sydney.edu.au
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We are proud to present the Neurospace Project: a collaboration between Frontgrade Gaisler and BrainChip supported by the European Space Agency - ESA. | Frontgrade Gaisler
We are proud to present the Neurospace Project: a collaboration between Frontgrade Gaisler and BrainChip supported by the European Space Agency - ESA. At its center: GR801, our first neuromorphic AI solution for space. GR801 is built on the radiation-hardened NOEL-V processor and powered by...www.linkedin.com
There is a 2 min movie talking up the collaboration but it want copy across so have to view it in the LinkedIn link!
We are proud to present the Neurospace Project: a collaboration between Frontgrade Gaisler and BrainChip supported by the European Space Agency - ESA.
At its center: GR801, our first neuromorphic AI solution for space.
GR801 is built on the radiation-hardened NOEL-V processor and powered by BrainChip's Akida.
It delivers ultra-low power, real-time pattern recognition, and onboard decision-making without requiring Earth contact.
This is more than a milestone.
It's a paradigm shift for AI at the edge of space exploration.
Learn more: https://lnkd.in/dMq9sxkp
And https://lnkd.in/dSx8_mTQ
Also available on YouTube: https://lnkd.in/dC6_aWR2
#NeuromorphicAI #SpaceTech
Arijit Mukherjee is already busy co-organising another Edge AI workshop that will also touch on neuromorphic computing. It is scheduled for 8 October and will be co-located with AIMLSys 2025 in Bangalore:
“EDGE-X 2025: Reimagining edge intelligence with low-power, high-efficiency AI systems”.
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🔋✨ Rethinking Edge Intelligence at EDGE-X 2025 | Arijit Mukherjee
🔋✨ Rethinking Edge Intelligence at EDGE-X 2025 📍 Co-located with AI-ML Systems Conference 2025 | Chancery Pavilion, Bangalore | October 8, 2025 As intelligent systems scale across diverse environments—from IoT sensors to autonomous platforms—traditional architectures face new limits. The EDGE-X...www.linkedin.com
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Workshop-EDGE-X | The Fifth International Conference on AI ML Systems
www.aimlsystems.org
EDGE-X
The EDGE-X 2025 workshop, part of the Fifth International AI-ML Systems Conference (AIMLSys 2025), aims to address the critical challenges and opportunities in nextgeneration edge computing. As intelligent systems expand into diverse environments—from IoT sensors to autonomous devices—traditional applications, architectures, and methodologies face new limits. EDGE-X explores innovative solutions across various domains, including on-device learning and inferencing, ML/DL optimization approaches to achieve efficiency in memory/latency/power, hardware-software co-optimization, and emerging beyond von Neumann paradigms including but not limited to neuromorphic, in-memory, photonic, and spintronic computing. The workshop seeks to unite researchers, engineers, and architects to share ideas and breakthroughs in devices, architectures, algorithms, tools and methodologies that redefine performance and efficiency for edge computing.
Topics of Interest (including but not limited to the following):
We solicit submissions describing original and unpublished results focussed on leveraging software agents for software engineering tasks. Topics of interest include but are not limited to:
1.Ultra-Efficient Machine Learning
2.Hardware-Software Co-Design
- TinyML, binary/ternary neural networks, federated learning
- Model pruning, compression, quantization, and edge-training
3.Beyond CMOS & von Neumann Paradigms
- RISC-V custom extensions for edge AI
- Non-von-Neumann accelerators (e.g., in-memory compute, FPGAs
4.System-Level Innovations
- Neuromorphic computing (spiking networks, event-based sensing)
- In-memory/compute architectures (memristors, ReRAM)
- Photonic integrated circuits for low-power signal processing
- Spintronic logic/memory and quantum-inspired devices
5.Tools & Methodologies
- Near-/sub-threshold computing
- Power-aware OS/runtime frameworks
- Approximate computing for error-tolerant workloads
6.Use Cases & Deployment Challenges
- Simulators for emerging edge devices (photonic, spintronic)
- Energy-accuracy trade-off optimization
- Benchmarks for edge heterogeneous platforms
- Self-powered/swarm systems, ruggedized edge AI
- Privacy/security for distributed intelligence
- Sustainability and lifecycle management
- Program Committee
- Arijit Mukherjee, Principal Scientist, TCS Research
- Udayan Ganguly, Professor, IIT Bombay
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 :
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#edgeai #tinyml #neuromorphic #spintronics #photoniccomputing #aimlsys2025 #lowpowerai #futuretech #callforpapers #linkedinresearch #aiatedge | 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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Some interesting recent posts by Cecilia Pisano:
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Category | Annual Global Revenue |
---|---|
Non-existent | Below USD 10 million |
Small | USD 10 million – 1 billion |
Medium | USD 1 billion – 10 billion |
Large | Above USD 10 billion |
“Our current demo utilizes Intel x86 in conjunction with Aether Core LLM for showcasing our platform. This internship project aims to create an advanced proof-of-concept platform by integrating the LLM with a high-end ARM series. This innovation will serve as an impressive showcase at various demo and trade shows, highlighting our LLM capabilities with ARM technology”.
Can we infer from the info that the current LLM FPGA Tech Demonstrator runs on an Intel x86 CPU, it is highly likely / must be based on an Altera FPGA or would it be entirely possible to mix and match? I have no idea…
Our model/demo is currently running on an Intel x86 CPU.
We want you to combine "a Raspberry Pi [...] with a custom FPGA-based hardware accelerator".
Does this mean a custom accelerator using an off-the-shelf FPGA?"a custom FPGA-based hardware accelerator"
"High-End" like a Raspberry Pi (ARM) CPU in comparison to a less beefy/powerfull MCU?"integrating the LLM with a high-end ARM series"