BRN Discussion Ongoing

[manny100]

Based on our known partnerships, ecosystem, Oncor, Parsons, Frontgrade Gaisler, RTX/USAFRL, Bascom-Hunter, Steve Brightfields recent comments and expected GEN ai and GEN 3 I asked chat to put together a table showing briefly what it all signals to investors.
Its common sense but puts it all together in the one spot.

What BrainChip’s Partnerships & Roadmap Signal to Investors​

Category	Message to Investors
Onsor partnership	Validates Akida in medical‑grade, real‑time, ultra‑low‑power applications (seizure‑detecting glasses). Shows the tech works where latency and power matter most.
Frontgrade Gaisler integration	Confirms Akida is suitable for radiation‑hardened, space‑grade SoCs. Space customers only adopt tech that is extremely reliable and efficient.
Parsons / Blue Ridge Envisioneering	Demonstrates traction in defense edge‑AI systems, where ruggedness, low power, and real‑time inference are mandatory.
Bascom Hunter / Navy SBIR	Shows adoption in DoD‑aligned programs and rugged neuromorphic hardware (SNAP card). Their purchase of Akida‑1500 chips signals real demand.
RTX / USAFRL expansion	A major aerospace/defense contractor expanding trials after “surprising results” is a strong technical endorsement. Suggests Akida outperformed expectations.
Akida‑1500 tape‑out	Indicates BrainChip is executing, not just promising. Tape‑out means the design is real, stable, and ready for manufacturing.
GenAI roadmap	Shows BrainChip is aligning with the biggest trend in tech: on‑device generative AI. Signals long‑term relevance.
Gen3 architecture direction	Confirms BrainChip is not a one‑chip company. A maturing roadmap increases investor confidence in future revenue streams.
Multiple partnerships across sectors	Demonstrates broad applicability: medical, defense, aerospace, industrial, space, consumer. Reduces single‑market risk.
Customers requesting chips before licensing	Strongest sign of commercial readiness. Customers want hardware validation before committing to IP licensing — a normal path toward high‑margin revenue.
Hearing‑aid adoption accelerating	Hearing aids are a high‑volume consumer vertical. Early adoption signals potential for recurring, scalable revenue.

 

[manny100]

At the 25 minute mark of Steve Brightfields interview he said Ear buds will become medically certified hearing aids off the shelf. That is potentially huge.
Disaster for hearing aid producers and sellers?
At 28 min on he says we have a customer with smart glasses and they can detect from brainwave activity whether it be migraine, in this case detecting Epileptic seizures before it happens.
That looks a giveaway that Migraine prediction is being worked on at least - another Onsor project?
Migraine detecton would be huge.

 

[7für7]

At the 25 minute mark of Steve Brightfields interview he said Ear buds will become medically certified hearing aids off the shelf. That is potentially huge.
Disaster for hearing aid producers and sellers?
At 28 min on he says we have a customer with smart glasses and they can detect from brainwave activity whether it be migraine, in this case detecting Epileptic seizures before it happens.
That looks a giveaway that Migraine prediction is being worked on at least - another Onsor project?
Migraine detecton would be huge.

Interesting… but what could someone do against migraine? Take the pill earlier?

 

[manny100]

It's interesting that Arquimea and Brainchip made an agreement concerning water safety and rescue.
" ARQUIMEA has demonstrated BrainChip’s Akida with a Prophesee event-based Metavision® camera on a low-power drone to detect distressed swimmers and surfers, helping lifeguards scale their services for large beach areas."
Edge AI Empowers Search & Rescue Operations
The date of the Brainchip news release was 16th April 2025.
By coincidence Arquimea on 22nd April 2025 announced that on "14th April 2025 that they and Lockheed Martin Skunk Works have successfully completed development of an enhanced anomaly detection for Intelligence, Surveillance and Reconnaissance (ISR) platforms such as Drones and other systems piloted by artificial intelligence agents....."
"neural networks", " using machine learning algorithms, allowing the mission to be readapted".
Neural networks, adaptive on chip learning? Sounds like something AKIDA can do.
Arquimea and Lockheed Martin develop advanced AI surveillance and reconnaissance (ISR) systems
I note that Brainchip has ties with both Lockheed Martin and Arquimea.
I also note that both Lockheed Martin and Arquimea are defense suppliers.

 

[Fullmoonfever]

Seems Honeywell through their owned CAES entity are another defence player looking to develop neuromorphic/ cognitive and would like someone preferably with experience with the likes of Akida / Loihi hardware. My bold.

7 Seven Bridges jobs in United States

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Artificial Intelligence & Machine Learning Systems Engineer-Cognitive Electronic Warfare (EW)​

CAES San Jose, CA
1 week ago Be among the first 25 applicants​

Delivering mission-critical, electronic solutions that protect lives. Use your creativity and critical thinking to take our products from concept to customer.

At CAES by Honeywell, we engineer solutions for the world’s most critical missions. We serve customers in the defense and aerospace markets. Seeking a career that offers challenging, diverse projects and opportunities? Looking for a position with a company that offers long-term professional advancement? Searching for a place that values a diverse, team-based environment? One that values YOU. Consider CAES by Honeywell.

The most important thing we build is TRUST

#CustomerFocus #Values #Leader #TogetherWePioneer

Overview

We’re seeking a highly skilled Artificial Intelligence & Machine Learning Systems Engineer to architect, design, and develop advanced AI/ML systems that power our next generation of products. In this leadership role, you’ll contribute to the technical roadmap, mentor engineering teams, and collaborate with cross-functional teams to deliver intelligent, scalable, and production-ready AI and machine learning technologies. You will be responsible for researching, creating, adapting and evaluating AI/ML techniques to solve complex customer problems with real-time solutions to support our defense customers.

Specifically, we are building next-generation cognitive electronic warfare systems that operate autonomously at the tactical edge in contested, low-SWaP (Size, Weight, and Power), denied, and disconnected environments. This is not a prompt-engineering or GenAI role. We are looking for hardcore AI/ML systems engineers who treat machine learning as a component of a larger, mission-critical, real-time embedded system.

Responsibilities

Major Duties & Responsibilities:

• Design, implement, and harden on-line and continual-learning ML algorithms for RF signal classification, adaptive jamming, cognitive radar, and electronic attack/support decision engines.
• Port, optimize, and deploy ML inference algorithms to edge processors.
• Build and maintain low-latency, deterministic inference pipelines that integrate tightly with real-time RF front-ends and digital signal processing chains.
• Lead the systems integration of AI/ML techniques into mission-critical embedded platforms running real-time operating systems.
• Design and deliver warfighter-focused engineering visualizations and tactical displays (real-time spectrum awareness, threat emitter tracks, cognitive EW decision overlays, confidence heatmaps) using modern web stack frameworks that run natively on embedded tactical processors and dismounted soldier systems.
• Own the MLOps and DevSecOps pipeline for classified EW programs: secure CI/CD, model versioning, containerized build/test/deploy, SBOM generation, and compliance with DoD zero-trust and CNCF security standards.
• Architect and deploy Kubernetes-based edge orchestration clusters (e.g. k3s) that operate in fully air-gapped tactical environments with strict latency and availability requirements.
• Perform end-to-end performance profiling (memory bandwidth, cache coherency, DMA, GPU/TPU/NPU utilization).
• Review code, guide architecture decisions, and mentor the AI/ML engineering team.
• Collaborate with product and engineering teams to identify AI/ML-driven opportunities.
  

Qualifications

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or related field
• 7+ years of professional experience shipping production AI/ML systems, ideally in defense, aerospace, or autonomous systems
• Prior work on DoD cognitive EW programs
• Deep expertise in high-performance and real-time applications (not just scripting wrappers)
• Real-time and embedded application programming (no Python-only backgrounds)
• Proven track record of deploying AI/ML solutions to cloud and edge/constrained devices
• Strong systems engineering background: you understand clocks, interrupts, DMA, cache hierarchies, memory-mapped I/O, and real-time scheduling
• Hands-on experience building and securing CI/CD pipelines for classified or regulated environments
• Expertise with Docker, container hardening, and Kubernetes in disconnected/edge configurations (k3s, microk8s, Rancher Harvester).
• Familiarity with RF/ML intersections: signal detection & classification, modulation recognition, emitter geolocation, fingerprinting, adaptive waveform design, or reinforcement learning for EW
• Proficiency with ML algorithms (including NLP, Computer Vision, time-series), libraries including foundational understanding and expertise in statistics probability theory and linear algebra
• Strong understanding of machine learning fundamentals: supervised/unsupervised learning, deep learning, model evaluation, optimization, feature engineering, etc
• Experience with data engineering workflows and building robust training datasets
  

Preferred Qualifications

• Experience as the technical lead for establishing and accrediting classified AI/ML information systems under the DoD Risk Management Framework (RMF):
  • Author and maintain System Security Plans (SSP), Security CONOPS, and AI/ML-specific risk annexes
  • Build and harden multi-enclave classified development, integration, and operational environments (RHEL 8/9, SELinux enforcing, DISA STIGs, Assured Compliance Assessment Solution (ACAS))
  • Lead the creation of AI/ML-specific artifacts for eMASS packages, including model cards, data provenance, adversarial robustness testing, and continuous monitoring plans
  • Obtain and maintain Authority to Operate (ATO) for classified cognitive EW systems containing advanced GPU/NPU-accelerated AI infrastructure
• Perform Linux systems administration at the classified level: kernel tuning for real-time determinism, custom security hardening, cross-domain solution integration, auditd/ELK stack management, and FIPS 140-3 compliant cryptography
• Deep Linux systems administration and hardening experience in classified environments (RHEL/CentOS, STIG compliance, SELinux policy authoring).
• Hands-on experience authoring RMF packages and obtaining ATOs for systems containing machine learning components for the U.S. Government (Army, Navy, Air Force, or IC customer)
• Expertise with Docker, container hardening (CIS, OSCAP), and Kubernetes in disconnected tactical environments
• Experience or exposure with implementing Government reference architectures
• Experience with neuromorphic or spiking neural network hardware (Intel Loihi, BrainChip Akida)
• Experience with distributed training, GPU acceleration, and high-performance ML compute
• Strong background in foundation algorithms, transformers, or multimodal AI
• Knowledge of automated model monitoring, drift detection, and lifecycle management
• Experience integrating ML models into consumer or enterprise products

 

[Diogenese]

Seems Honeywell through their owned CAES entity are another defence player looking to develop neuromorphic/ cognitive and would like someone preferably with experience with the likes of Akida / Loihi hardware. My bold.

7 Seven Bridges jobs in United States

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www.linkedin.com

Artificial Intelligence & Machine Learning Systems Engineer-Cognitive Electronic Warfare (EW)​

CAES San Jose, CA​

1 week ago Be among the first 25 applicants​

Delivering mission-critical, electronic solutions that protect lives. Use your creativity and critical thinking to take our products from concept to customer.

At CAES by Honeywell, we engineer solutions for the world’s most critical missions. We serve customers in the defense and aerospace markets. Seeking a career that offers challenging, diverse projects and opportunities? Looking for a position with a company that offers long-term professional advancement? Searching for a place that values a diverse, team-based environment? One that values YOU. Consider CAES by Honeywell.

The most important thing we build is TRUST

#CustomerFocus #Values #Leader #TogetherWePioneer

Overview

We’re seeking a highly skilled Artificial Intelligence & Machine Learning Systems Engineer to architect, design, and develop advanced AI/ML systems that power our next generation of products. In this leadership role, you’ll contribute to the technical roadmap, mentor engineering teams, and collaborate with cross-functional teams to deliver intelligent, scalable, and production-ready AI and machine learning technologies. You will be responsible for researching, creating, adapting and evaluating AI/ML techniques to solve complex customer problems with real-time solutions to support our defense customers.

Specifically, we are building next-generation cognitive electronic warfare systems that operate autonomously at the tactical edge in contested, low-SWaP (Size, Weight, and Power), denied, and disconnected environments. This is not a prompt-engineering or GenAI role. We are looking for hardcore AI/ML systems engineers who treat machine learning as a component of a larger, mission-critical, real-time embedded system.

Responsibilities

Major Duties & Responsibilities:

• Design, implement, and harden on-line and continual-learning ML algorithms for RF signal classification, adaptive jamming, cognitive radar, and electronic attack/support decision engines.
• Port, optimize, and deploy ML inference algorithms to edge processors.
• Build and maintain low-latency, deterministic inference pipelines that integrate tightly with real-time RF front-ends and digital signal processing chains.
• Lead the systems integration of AI/ML techniques into mission-critical embedded platforms running real-time operating systems.
• Design and deliver warfighter-focused engineering visualizations and tactical displays (real-time spectrum awareness, threat emitter tracks, cognitive EW decision overlays, confidence heatmaps) using modern web stack frameworks that run natively on embedded tactical processors and dismounted soldier systems.
• Own the MLOps and DevSecOps pipeline for classified EW programs: secure CI/CD, model versioning, containerized build/test/deploy, SBOM generation, and compliance with DoD zero-trust and CNCF security standards.
• Architect and deploy Kubernetes-based edge orchestration clusters (e.g. k3s) that operate in fully air-gapped tactical environments with strict latency and availability requirements.
• Perform end-to-end performance profiling (memory bandwidth, cache coherency, DMA, GPU/TPU/NPU utilization).
• Review code, guide architecture decisions, and mentor the AI/ML engineering team.
• Collaborate with product and engineering teams to identify AI/ML-driven opportunities.

Qualifications

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or related field
• 7+ years of professional experience shipping production AI/ML systems, ideally in defense, aerospace, or autonomous systems
• Prior work on DoD cognitive EW programs
• Deep expertise in high-performance and real-time applications (not just scripting wrappers)
• Real-time and embedded application programming (no Python-only backgrounds)
• Proven track record of deploying AI/ML solutions to cloud and edge/constrained devices
• Strong systems engineering background: you understand clocks, interrupts, DMA, cache hierarchies, memory-mapped I/O, and real-time scheduling
• Hands-on experience building and securing CI/CD pipelines for classified or regulated environments
• Expertise with Docker, container hardening, and Kubernetes in disconnected/edge configurations (k3s, microk8s, Rancher Harvester).
• Familiarity with RF/ML intersections: signal detection & classification, modulation recognition, emitter geolocation, fingerprinting, adaptive waveform design, or reinforcement learning for EW
• Proficiency with ML algorithms (including NLP, Computer Vision, time-series), libraries including foundational understanding and expertise in statistics probability theory and linear algebra
• Strong understanding of machine learning fundamentals: supervised/unsupervised learning, deep learning, model evaluation, optimization, feature engineering, etc
• Experience with data engineering workflows and building robust training datasets

Preferred Qualifications

• Experience as the technical lead for establishing and accrediting classified AI/ML information systems under the DoD Risk Management Framework (RMF):
  • Author and maintain System Security Plans (SSP), Security CONOPS, and AI/ML-specific risk annexes
  • Build and harden multi-enclave classified development, integration, and operational environments (RHEL 8/9, SELinux enforcing, DISA STIGs, Assured Compliance Assessment Solution (ACAS))
  • Lead the creation of AI/ML-specific artifacts for eMASS packages, including model cards, data provenance, adversarial robustness testing, and continuous monitoring plans
  • Obtain and maintain Authority to Operate (ATO) for classified cognitive EW systems containing advanced GPU/NPU-accelerated AI infrastructure
• Perform Linux systems administration at the classified level: kernel tuning for real-time determinism, custom security hardening, cross-domain solution integration, auditd/ELK stack management, and FIPS 140-3 compliant cryptography
• Deep Linux systems administration and hardening experience in classified environments (RHEL/CentOS, STIG compliance, SELinux policy authoring).
• Hands-on experience authoring RMF packages and obtaining ATOs for systems containing machine learning components for the U.S. Government (Army, Navy, Air Force, or IC customer)
• Expertise with Docker, container hardening (CIS, OSCAP), and Kubernetes in disconnected tactical environments
• Experience or exposure with implementing Government reference architectures
• Experience with neuromorphic or spiking neural network hardware (Intel Loihi, BrainChip Akida)
• Experience with distributed training, GPU acceleration, and high-performance ML compute
• Strong background in foundation algorithms, transformers, or multimodal AI
• Knowledge of automated model monitoring, drift detection, and lifecycle management
• Experience integrating ML models into consumer or enterprise products

Hi Fmf,

That's some hardrcore qualifications they are calling for.

This is not your summer intern.

 

[7für7]

Seems Honeywell through their owned CAES entity are another defence player looking to develop neuromorphic/ cognitive and would like someone preferably with experience with the likes of Akida / Loihi hardware. My bold.

7 Seven Bridges jobs in United States

Today's top 7 Seven Bridges jobs in United States. Leverage your professional network, and get hired. New Seven Bridges jobs added daily.

www.linkedin.com

Artificial Intelligence & Machine Learning Systems Engineer-Cognitive Electronic Warfare (EW)​

CAES San Jose, CA​

1 week ago Be among the first 25 applicants​

Delivering mission-critical, electronic solutions that protect lives. Use your creativity and critical thinking to take our products from concept to customer.

At CAES by Honeywell, we engineer solutions for the world’s most critical missions. We serve customers in the defense and aerospace markets. Seeking a career that offers challenging, diverse projects and opportunities? Looking for a position with a company that offers long-term professional advancement? Searching for a place that values a diverse, team-based environment? One that values YOU. Consider CAES by Honeywell.

The most important thing we build is TRUST

#CustomerFocus #Values #Leader #TogetherWePioneer

Overview

We’re seeking a highly skilled Artificial Intelligence & Machine Learning Systems Engineer to architect, design, and develop advanced AI/ML systems that power our next generation of products. In this leadership role, you’ll contribute to the technical roadmap, mentor engineering teams, and collaborate with cross-functional teams to deliver intelligent, scalable, and production-ready AI and machine learning technologies. You will be responsible for researching, creating, adapting and evaluating AI/ML techniques to solve complex customer problems with real-time solutions to support our defense customers.

Specifically, we are building next-generation cognitive electronic warfare systems that operate autonomously at the tactical edge in contested, low-SWaP (Size, Weight, and Power), denied, and disconnected environments. This is not a prompt-engineering or GenAI role. We are looking for hardcore AI/ML systems engineers who treat machine learning as a component of a larger, mission-critical, real-time embedded system.

Responsibilities

Major Duties & Responsibilities:

• Design, implement, and harden on-line and continual-learning ML algorithms for RF signal classification, adaptive jamming, cognitive radar, and electronic attack/support decision engines.
• Port, optimize, and deploy ML inference algorithms to edge processors.
• Build and maintain low-latency, deterministic inference pipelines that integrate tightly with real-time RF front-ends and digital signal processing chains.
• Lead the systems integration of AI/ML techniques into mission-critical embedded platforms running real-time operating systems.
• Design and deliver warfighter-focused engineering visualizations and tactical displays (real-time spectrum awareness, threat emitter tracks, cognitive EW decision overlays, confidence heatmaps) using modern web stack frameworks that run natively on embedded tactical processors and dismounted soldier systems.
• Own the MLOps and DevSecOps pipeline for classified EW programs: secure CI/CD, model versioning, containerized build/test/deploy, SBOM generation, and compliance with DoD zero-trust and CNCF security standards.
• Architect and deploy Kubernetes-based edge orchestration clusters (e.g. k3s) that operate in fully air-gapped tactical environments with strict latency and availability requirements.
• Perform end-to-end performance profiling (memory bandwidth, cache coherency, DMA, GPU/TPU/NPU utilization).
• Review code, guide architecture decisions, and mentor the AI/ML engineering team.
• Collaborate with product and engineering teams to identify AI/ML-driven opportunities.

Qualifications

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or related field
• 7+ years of professional experience shipping production AI/ML systems, ideally in defense, aerospace, or autonomous systems
• Prior work on DoD cognitive EW programs
• Deep expertise in high-performance and real-time applications (not just scripting wrappers)
• Real-time and embedded application programming (no Python-only backgrounds)
• Proven track record of deploying AI/ML solutions to cloud and edge/constrained devices
• Strong systems engineering background: you understand clocks, interrupts, DMA, cache hierarchies, memory-mapped I/O, and real-time scheduling
• Hands-on experience building and securing CI/CD pipelines for classified or regulated environments
• Expertise with Docker, container hardening, and Kubernetes in disconnected/edge configurations (k3s, microk8s, Rancher Harvester).
• Familiarity with RF/ML intersections: signal detection & classification, modulation recognition, emitter geolocation, fingerprinting, adaptive waveform design, or reinforcement learning for EW
• Proficiency with ML algorithms (including NLP, Computer Vision, time-series), libraries including foundational understanding and expertise in statistics probability theory and linear algebra
• Strong understanding of machine learning fundamentals: supervised/unsupervised learning, deep learning, model evaluation, optimization, feature engineering, etc
• Experience with data engineering workflows and building robust training datasets

Preferred Qualifications

• Experience as the technical lead for establishing and accrediting classified AI/ML information systems under the DoD Risk Management Framework (RMF):
  • Author and maintain System Security Plans (SSP), Security CONOPS, and AI/ML-specific risk annexes
  • Build and harden multi-enclave classified development, integration, and operational environments (RHEL 8/9, SELinux enforcing, DISA STIGs, Assured Compliance Assessment Solution (ACAS))
  • Lead the creation of AI/ML-specific artifacts for eMASS packages, including model cards, data provenance, adversarial robustness testing, and continuous monitoring plans
  • Obtain and maintain Authority to Operate (ATO) for classified cognitive EW systems containing advanced GPU/NPU-accelerated AI infrastructure
• Perform Linux systems administration at the classified level: kernel tuning for real-time determinism, custom security hardening, cross-domain solution integration, auditd/ELK stack management, and FIPS 140-3 compliant cryptography
• Deep Linux systems administration and hardening experience in classified environments (RHEL/CentOS, STIG compliance, SELinux policy authoring).
• Hands-on experience authoring RMF packages and obtaining ATOs for systems containing machine learning components for the U.S. Government (Army, Navy, Air Force, or IC customer)
• Expertise with Docker, container hardening (CIS, OSCAP), and Kubernetes in disconnected tactical environments
• Experience or exposure with implementing Government reference architectures
• Experience with neuromorphic or spiking neural network hardware (Intel Loihi, BrainChip Akida)
• Experience with distributed training, GPU acceleration, and high-performance ML compute
• Strong background in foundation algorithms, transformers, or multimodal AI
• Knowledge of automated model monitoring, drift detection, and lifecycle management
• Experience integrating ML models into consumer or enterprise products

Olivier Coenen entered the chat

 

[smoothsailing18]

FF

posted the original paper some months ago before it was reviewed. It has now been reviewed and accepted by Researchgate and published on 18 December, 2025:

https://www.researchgate.net/public...WQiLCJwcmV2aW91c1BhZ2UiOiJwdWJsaWNhdGlvbiJ9fQ

Brainchip’s AKIDA blitzed the field which included Intel’s Loihi achieving 99.18% accuracy running the authors algorithm for threat detection with dramatically reduced latency and energy savings.

 

[manny100]

Interesting… but what could someone do against migraine? Take the pill earlier?

Evidently the idea is you take action as prescribed eg medication, rest, hydration, care with exposure to light until the signal stops. So once you get a signal its trigger avoidance time.
Migraines can very painfull and its not uncommon for a migraine to last several days or more. They can lead to a hospital stay.
There are also silent migraines do not have the same 'head throbbing' experience as migraines but cause alarming symptoms such as nausea, sight issues, dizziness, head fog etc.
Its also a huge global problem.

Migraine Prevalence: Global and Demographic Statistics

Gain a deeper understanding of migraine’s global footprint and its varied impact across different groups, underscoring its broad public health implications.

biologyinsights.com

"

Global and Regional Occurrence​

In 2019, the estimated global prevalence of migraine reached 1.1 billion cases, an increase from 721.9 million cases in 1990. This translates to approximately 14,246.55 cases per 100,000 population in 2021. Headache disorders, including migraines, collectively affect about 40% of the global population, or 3.1 billion people."
My bold above. As shown above its a massive global problem as shown above.
This has the potential to be huge for Brainchip. Also take into account Steve's off the shelf ear buds/hearing aids the Brainchip future in health is starting to look fair at the least.
For the Australian experience see quick comparable chart compiled by 'chat' with links below.

Quick comparison table​

Condition	How Common?	Notes
Migraine (overall)	6.6% of Australians (1.7M people)	One of the most disabling neurological conditions
Silent migraine	~5% of migraine sufferers	Aura symptoms without headache

Chat above provides a quick comparison table with just for Australia. links

Neurological conditions in Australia: Migraine and headaches in Australia

Migraine and headache disorders are among the most common chronic neurological conditions. Migraine is a specific headache disorder characterised by recurrent attacks of severe headache...

www.aihw.gov.au

Silent migraines - https://www.migraine.org.au/mawh?utm_source=copilot.com
Evidently around 75% of migraines are suffered by women. Its a huge problem

 

[JB49]

Loading…

www.indeed.com

Up to 300K USD. Probably enough to tempt some of the decent brainchip staff over to them.

 

[7für7]

Evidently the idea is you take action as prescribed eg medication, rest, hydration, care with exposure to light until the signal stops. So once you get a signal its trigger avoidance time.
Migraines can very painfull and its not uncommon for a migraine to last several days or more. They can lead to a hospital stay.
There are also silent migraines do not have the same 'head throbbing' experience as migraines but cause alarming symptoms such as nausea, sight issues, dizziness, head fog etc.
Its also a huge global problem.

Migraine Prevalence: Global and Demographic Statistics

Gain a deeper understanding of migraine’s global footprint and its varied impact across different groups, underscoring its broad public health implications.

biologyinsights.com

"

Global and Regional Occurrence​

In 2019, the estimated global prevalence of migraine reached 1.1 billion cases, an increase from 721.9 million cases in 1990. This translates to approximately 14,246.55 cases per 100,000 population in 2021. Headache disorders, including migraines, collectively affect about 40% of the global population, or 3.1 billion people."
My bold above. As shown above its a massive global problem as shown above.
This has the potential to be huge for Brainchip. Also take into account Steve's off the shelf ear buds/hearing aids the Brainchip future in health is starting to look fair at the least.
For the Australian experience see quick comparable chart compiled by 'chat' with links below.

Quick comparison table​

Condition	How Common?	Notes
Migraine (overall)	6.6% of Australians (1.7M people)	One of the most disabling neurological conditions
Silent migraine	~5% of migraine sufferers	Aura symptoms without headache

Chat above provides a quick comparison table with just for Australia. links

Neurological conditions in Australia: Migraine and headaches in Australia

Migraine and headache disorders are among the most common chronic neurological conditions. Migraine is a specific headache disorder characterised by recurrent attacks of severe headache...

www.aihw.gov.au

Silent migraines - https://www.migraine.org.au/mawh?utm_source=copilot.com
Evidently around 75% of migraines are suffered by women. Its a huge problem

I know my way around migraines really well. But I honestly can’t imagine how early detection would help me.

Still—trying it once could be worth it, just to see whether it can reduce the pain. But I’ll be straight with you: I’m not one of those people who wants to know in advance when a migraine attack is coming. Psychologically that’s even more stressful, and then the migraine might show up earlier than it normally would.

On top of that, you already have your own internal clock that goes, “Today I’m going to mess you up—get ready,” and at the latest three hours later it starts.

Ocular migraine is a whole other thing anyway—you have to endure the visual impairment no matter what. And yours is gone after 20–30 minutes, followed by mild headaches.

I think as long as there’s no truly effective long-term medication that frees you from it, you just have to push through. But if early detection actually helps make the struggle easier, I’m in.

 

[jrp173]

Here's a very fair question, if you believe that our company will finally, yes finally show revenues that outpace expenses by the 3rd quarter of 2026, no matter from what source, for example, high speed boats that Donald's boy failed to stop across the Pacific etc, well please post a laugh....

Just trying to lighten the mood, many are feeling the pressure of the market at present, that's a very fair assumption.

To be perfectly honest, with no revenue and capital raisings, it's sort of understandable that we currently sit south of 0 20...hang in there, progress is being made and yes, I'm quietly peeved as well.

Tech

Oh no, don't you have any good news or updates from your best mate PVDM???? You'd better got on the blower to him and then just drop hints to all of us plebs about your intriguing conversations.

Maybe you should tell PDVM that you are "quietly peeved"..(not that he'd care, as he is set for life even at today's price).

Or maybe you are too busy with Sean's "watch us now" ....exhausting staying awake all day and night watching the share price fall even more..

Let us all know how go. Can't wait to hear.

 

[manny100]

I know my way around migraines really well. But I honestly can’t imagine how early detection would help me.

Still—trying it once could be worth it, just to see whether it can reduce the pain. But I’ll be straight with you: I’m not one of those people who wants to know in advance when a migraine attack is coming. Psychologically that’s even more stressful, and then the migraine might show up earlier than it normally would.

On top of that, you already have your own internal clock that goes, “Today I’m going to mess you up—get ready,” and at the latest three hours later it starts.

Ocular migraine is a whole other thing anyway—you have to endure the visual impairment no matter what. And yours is gone after 20–30 minutes, followed by mild headaches.

I think as long as there’s no truly effective long-term medication that frees you from it, you just have to push through. But if early detection actually helps make the struggle easier, I’m in.

It have family that suffer from migraines and hospital visits are not uncommon. They are 'shockers'.
A Migraine detection wearable would need to be pass all the regulatory authorities and must demonstrate clinical grade accuracy.
No doubt it will not work for everyone but for a sufferer its worth a try.
I am not sure what clinical accuracy rates are but they likely pretty high.

 

[smoothsailing18]

It have family that suffer from migraines and hospital visits are not uncommon. They are 'shockers'.
A Migraine detection wearable would need to be pass all the regulatory authorities and must demonstrate clinical grade accuracy.
No doubt it will not work for everyone but for a sufferer its worth a try.
I am not sure what clinical accuracy rates are but they likely pretty high.

Reading up on migranes there are studies that lean towards nutrition or the lack of certain minerals that when increased reduce the amount of migrane.
The future of testing for nutritional defisency in the breath would be a game changer if at all feasible. No doubt many moons away for this tho I imagine.

 

[7für7]

Reading up on migranes there are studies that lean towards nutrition or the lack of certain minerals that when increased reduce the amount of migrane.
The future of testing for nutritional defisency in the breath would be a game changer if at all feasible. No doubt many moons away for this tho I imagine.

A massive rise of the share price would already help IMO… no clinical studies no medication


Oh man this would be my medication… 2 dollars a share for beginning

 

[Bravo]

I have a migraine from watching too hard.

 

[manny100]

A massive rise of the share price would already help IMO… no clinical studies no medication


Oh man this would be my medication… 2 dollars a share for beginning

$2 would be nice for starters. Only starters though.

 

[Doz]

Gross borrowed shorts dropped by 24 million on the 16th . Was 100,438,478 or 4.46% on the 15th .

 

[smoothsailing18]

FF



MegaChips Corporation partners with various companies in the semiconductor and AI industries, including
BrainChip, Quadric, Morse Micro, and Acumino, to develop and deliver innovative solutions.
Key partners and their collaborations are outlined below:

• BrainChip: MegaChips has a strategic partnership with BrainChip to develop next-generation edge-based AI solutions using BrainChip's ultra-low power neuromorphic AI IP, known as Akida. This collaboration aims to bring high-performance, power-efficient AI capabilities to a wide range of applications, including industrial IoT, robotics, and smart sensors.
• Quadric: MegaChips and Quadric partner to bring Quadric's on-device AI processing architecture IP products to the ASIC (Application-Specific Integrated Circuit) and SoC (System-on-Chip) markets. This partnership focuses on providing versatile, high-performance processing platforms for customers building edge AI products.
• Morse Micro: MegaChips has an alliance with the Australian company Morse Micro to work on new solutions, market entry strategies, and the growth of Wi-Fi HaLow™ technology, which is known for being fast, small, low-power, and long-range.
• Acumino: In a strategic partnership and investment, MegaChips and Acumino are collaborating to accelerate the deployment of next-generation AI-powered robotic workers in Japan to address labor shortages.
• Foundry Partners: As a fabless semiconductor company, MegaChips outsources product manufacturing to a network of foundry partners to support a wide array of process options and meet diverse customer needs.
• Other Collaborations: Through its venture capital funds and R&D efforts, MegaChips is involved in various other technology and business collaborations to explore new business fields, including infrastructure, logistics, and energy control.

For more detailed information on their partnerships, you can visit the MegaChips Corporation website.

Interesting how MegaChips still presents itself as being partnered with Brainchip

 

[Gazzafish]

Gross borrowed shorts dropped by 24 million on the 16th . Was 100,438,478 or 4.46% on the 15th .



View attachment 93831

This I don’t understand. They dropped by 24m on the 16th yet there were only approx 12m shares traded that day , unless I’m trading it all wrong