BRN Discussion Ongoing

[Diogenese]

From a recent video interview with Steve Brighfield.
"The primary difference between brain chip and the Intel and the IBM solutions was they were analog. So they truly tried to match the analog waveforms of the brain, whereas the brain chip made a digital equivalent of the analog waveform. So now you could easily manufacture a computer, digital computer chip using the approach. The chips that you, the analog chips that are made today for neuromorphics, they're notorious for, you know, you have to have them biased and temperature stabilized, and there's all the problems with analog, which is the reason we don't have a lot of analog computers today, or the problems that they're faced with their neuromorphic chips."
"There are other companies that are producing analog Neuromorphic chips, but they're kind of dedicated for a specific market second, like speech wake-up, right? Or a biological wake-up. So they're like function-specific Neuromorphic chips. We have a very digital programmable chip that can use any kind of sensor, so we're kind of unique in that aspect. Build the future of multi-agent software with agency. "
My bold above.

Hi manny,

I'd like your thoughts/corrections to the following.

Tony Lewis mentioned that Akida 3 and GenAI will have a flexible hardware switched communication mesh whereas Akida 1 & 2 have a packet switched type comms mesh, and I'm trying to understand the advantages of the H/W switch.

The packet switched version requires that each event/spike includes an address header to direct it to the destination neuron. This entails transmitting additional bits with each event. increasing latency and power usage.

Thus for a many-to-many neuron connexion, there must be a transistor switch matrix (~ a crossbar switch?). But this only requires one switch per destination neuron compared with a requirement for the header to include the address of each destination neuron. For example, if there were 256 possible destination neurons, then the header would need to include 8 bits per destination neuron. So for 8 destination neurons for example, that would be 64 additional bits (ignoring any protocol overhead). (There may well be a more efficient protocol for this it, but that is above my pay grade).

In contrast, for a hardware switching matrix, only one transistor needs to switch per destination neuron, so, in the above example, that would be 8 switch operations.

In addition, the packet switched mesh protocol needs a larger collision avoidance buffer, to ensure only 1 event is transmitted at a time.

Obviously, the H/W switch will still require additional power/time to set up the switch connexions, but I assume this is a one off for each task.

 

[Diogenese]

See the transcript of the Steve Brightfield interview.
Its a great read for new and 'worn out' investors.

AI Podcast Transcript & Summary - Steven Brightfield: How Neuromorphic Computing Cuts Inference Power by 10x

Transcription: So neuromorphics is really how our biology does complications in our brain. So we don't have circuits, we have neurons,...

podcasttranscript.ai

I wish Steve would speak in paragraphs!

 

[manny100]

Hi manny,

I'd like your thoughts/corrections to the following.

Tony Lewis mentioned that Akida 3 and GenAI will have a flexible hardware switched communication mesh whereas Akida 1 & 2 have a packet switched type comms mesh, and I'm trying to understand the advantages of the H/W switch.

The packet switched version requires that each event/spike includes an address header to direct it to the destination neuron. This entails transmitting additional bits with each event. increasing latency and power usage.

Thus for a many-to-many neuron connexion, there must be a transistor switch matrix (~ a crossbar switch?). But this only requires one switch per destination neuron compared with a requirement for the header to include the address of each destination neuron. For example, if there were 256 possible destination neurons, then the header would need to include 8 bits per destination neuron. So for 8 destination neurons for example, that would be 64 additional bits (ignoring any protocol overhead). (There may well be a more efficient protocol for this it, but that is above my pay grade).

In contrast, for a hardware switching matrix, only one transistor needs to switch per destination neuron, so, in the above example, that would be 8 switch operations.

In addition, the packet switched mesh protocol needs a larger collision avoidance buffer, to ensure only 1 event is transmitted at a time.

Obviously, the H/W switch will still require additional power/time to set up the switch connexions, but I assume this is a one off for each task.

Hi Dio, its above my paygrade but Gen 3 is an upgrade so it has to be an improvement.
Appears ditching the packets will likely improve latency and reduce power costs. It would be designed to work well/better with GenAI.
Basically a guess based on why do it if it's not better and they are key areas.

 

[HopalongPetrovski]

Below is a copy of Marketing Mans recent post over on the crapper.
I am reposting it here because I think it is eloquent and extremely pertinent.
It is in reply to Phil the yank who is a recent blow in, a self proclaimed heavy hitter who, having now "discovered" WBT, seems to be falling out of love with us.

To add, I agree with the core issue you’re highlighting.

The risk isn’t “does Akida work?” it’s whether adoption happens fast enough in a market that often rewards good-enough and easy over better but harder.

That said, a couple of nuances are worth adding.

• First, if neuromorphic adoption is being held back by friction, that friction applies to all neuromorphic approaches, not just BrainChip. In that context, BRN actually appears to be ahead of the pack rather than behind. They’ve invested earlier than most in developer tooling, SDKs, MetaTF to bridge into existing ML workflows, and they’re now explicitly recruiting senior leadership to deepen the software and toolchain side. That doesn’t eliminate friction, but it does suggest management understands exactly where the bottleneck is.

• Second, you’re absolutely right that today BRN’s traction is showing up mainly where SWaP (Space, Weight, and Power) is unavoidable - space, defence, and ultra-low-power wearables like Onsor. That’s not a weakness of the technology; it’s where costs force a different compute approach. In those environments, “good enough” conventional compute doesn't fit. Early adoption almost always starts where the pain is baked-in.

• Third, while much of edge-AI today is advancing quickly on conventional methods, power consumption and heat rejection are becoming high-priority problems even in data centres. We’re already seeing hyper-scalers talk openly about energy limits, cooling constraints, and diminishing returns from brute-force GPUs. For example, several new, large-scale data centres in Western Sydney, particularly projects by AirTrunk, Microsoft, and Amazon in areas like Kemps Creek and Marsden Park, are facing scrutiny over high water consumption for cooling (even though cooling systems are heat-pump based, the cooling towers are typically evaporative). And in the US Microsoft is recommissioning 3-Mile Island Nuclear PLant (the site of one of the worst nuclear accidents before Fukushima and Chernobyl) because their new data centre needs enormous power. Eventually efficiency stops being a “nice to have” and becomes a design constraint.

• Finally, this whole debate has a strong historical echo. Valves weren’t displaced by transistors because transistors were immediately easier. Quite the opposite: valves had a huge industrial base, familiar engineering practices, and plenty of off-the-shelf solutions. Transistors were initially viewed as fragile, unproven, and niche. Yet once power, size, heat and reliability became dominant constraints, the market flipped, slowly at first, then decisively.

None of this guarantees BRN wins.

Adoption speed still matters, and the window isn’t open-ended. But it’s not that BrainChip is falling behind “better” competitors, it’s that the market hasn’t yet been forced to care enough about the problems neuromorphic solves. Where it has been forced, BRN is already seeing traction.

So I agree with your concern, but I’d say the verdict hinges less on near-term elegance or ease of adoption, and more on how fast power, heat, and autonomy constraints tighten across the broader AI landscape. That’s the real time-frame that matters here.

One final point I’d add is that much of what the market currently labels as “AI progress” is still overwhelmingly centred on LLMs and hyperscale cloud infrastructure and that phase is rapidly maturing.

The next leg of AI growth is far more likely to be about where the compute happens, not just how large models become. As AI pushes out of data centres and into autonomous, mobile, always-on systems, edge constraints like power, latency, heat and connectivity become dominant.

That shift doesn’t automatically guarantee success for neuromorphic approaches, but it does materially expand the addressable market where neuromorphic makes sense. In that context, neuromorphic isn’t competing head-to-head with cloud AI; it’s positioned for the phase after cloud-centric AI saturates, which is where a lot of the longer-term optionality sits.

Of course, a big application is battle drones - I saw a Youtube recently that reported that 80% of Kills in the Ukraine-Russia conflict have been executed by drones (of all shapes and sizes). No military budget can ignore this trend. With US isolationism and Trump forcing countries to re-arm drone development (UAVs is the correct term) is at an all time high. And AI that is fast, local, small, reliable, low-power, and cheap is what makes UAVs deadlier.

You don't wait for the conflict to start - you fill warehouses with 'em so you're ready.

That's good news for BRN (and us investors) - but World War III - not so good.

***
I had an AI "Chat" which identified the following edge use cases....
“Autonomous, mobile, always-on” systems share three traits:

• They move through the world
• They must perceive continuously
• They cannot rely on constant connectivity or abundant power

Here are the best, real-world examples, grouped by maturity and importance.

Military & Security (already here, already critical)​

Drones (air, land, sea)​

This is the archetype.

• ISR drones
• Loitering munitions
• Autonomous naval vessels
• Swarm drones

Why they matter:

• Battery-powered
• Highly mobile
• Must sense continuously
• Must react in milliseconds
• Often disconnected or jammed

Cloud AI is impossible here.
Brute-force edge compute is tolerated — but inefficient.

Counter-drone & perimeter defence systems​

• Radar + RF + EO/IR sensing
• Always on
• Must distinguish signal from noise continuously
• False positives are costly

Event-driven, low-power intelligence is a natural fit.

Robotics & Industrial Autonomy (rapidly emerging)​

Mobile robots (AMRs, humanoids, legged robots)​

• Warehouses
• Hospitals
• Field inspection
• Construction sites

Constraints:

• Battery-limited
• Must operate for hours or days
• Continuous perception (vision, lidar, audio)
• Safety-critical decisions

Most current systems are over-provisioned and power-inefficient — by design.

Autonomous vehicles (non-consumer first)​

Not robotaxis — those are cloud-heavy.

But:

• Mining vehicles
• Agricultural machinery
• Military ground vehicles

These:

• Operate in remote areas
• Require deterministic response
• Have limited connectivity

Medical & Human-adjacent Systems (under-appreciated)​

Implantable and wearable medical devices​

Examples:

• Cochlear implants
• Neural stimulators
• Smart insulin pumps
• Continuous monitoring wearables

Why they’re important:

• Always on
• Ultra-low power
• Safety critical
• Privacy sensitive

Cloud AI is a non-starter.
“Good enough” compute often isn’t good enough.

Assistive technologies​

• Prosthetics
• Exoskeletons
• Mobility aids

These require:

• Real-time feedback loops
• Local learning
• Minimal latency

Consumer & Infrastructure (early but inevitable)​

Smart sensors & IoT at scale​

• Environmental monitoring
• Smart cities
• Infrastructure health
• Border security

Thousands or millions of sensors:

• Always on
• Mostly idle
• Occasionally critical

Processing everything centrally is economically insane.

Space systems​

• Satellites
• Spacecraft autonomy
• Debris avoidance
• On-orbit servicing

Constraints:

• Power is scarce
• Communication delayed
• Reliability is existential

The unifying insight (this is the key)​

In all these systems:

• Power is a hard constraint
• Latency is non-negotiable
• Connectivity is unreliable
• Intelligence must be continuous, not episodic

That combination is exactly where:

• Cloud AI fails
• Brute-force edge AI struggles
• Event-driven approaches become interesting

Why this matters for your broader thesis​

These systems are not fringe.

They are:

• Growing in number
• Growing in strategic importance
• Becoming more autonomous over time

And importantly:

They don’t tolerate inefficiency forever.

That’s why this category matters more than benchmarks or demos.

Do you own research.

 

[Diogenese]

Below is a copy of Marketing Mans recent post over on the crapper.
I am reposting it here because I think it is eloquent and extremely pertinent.
It is in reply to Phil the yank who is a recent blow in, a self proclaimed heavy hitter who, having now "discovered" WBT, seems to be falling out of love with us.

To add, I agree with the core issue you’re highlighting.

The risk isn’t “does Akida work?” it’s whether adoption happens fast enough in a market that often rewards good-enough and easy over better but harder.

That said, a couple of nuances are worth adding.

• First, if neuromorphic adoption is being held back by friction, that friction applies to all neuromorphic approaches, not just BrainChip. In that context, BRN actually appears to be ahead of the pack rather than behind. They’ve invested earlier than most in developer tooling, SDKs, MetaTF to bridge into existing ML workflows, and they’re now explicitly recruiting senior leadership to deepen the software and toolchain side. That doesn’t eliminate friction, but it does suggest management understands exactly where the bottleneck is.

• Second, you’re absolutely right that today BRN’s traction is showing up mainly where SWaP (Space, Weight, and Power) is unavoidable - space, defence, and ultra-low-power wearables like Onsor. That’s not a weakness of the technology; it’s where costs force a different compute approach. In those environments, “good enough” conventional compute doesn't fit. Early adoption almost always starts where the pain is baked-in.

• Third, while much of edge-AI today is advancing quickly on conventional methods, power consumption and heat rejection are becoming high-priority problems even in data centres. We’re already seeing hyper-scalers talk openly about energy limits, cooling constraints, and diminishing returns from brute-force GPUs. For example, several new, large-scale data centres in Western Sydney, particularly projects by AirTrunk, Microsoft, and Amazon in areas like Kemps Creek and Marsden Park, are facing scrutiny over high water consumption for cooling (even though cooling systems are heat-pump based, the cooling towers are typically evaporative). And in the US Microsoft is recommissioning 3-Mile Island Nuclear PLant (the site of one of the worst nuclear accidents before Fukushima and Chernobyl) because their new data centre needs enormous power. Eventually efficiency stops being a “nice to have” and becomes a design constraint.

• Finally, this whole debate has a strong historical echo. Valves weren’t displaced by transistors because transistors were immediately easier. Quite the opposite: valves had a huge industrial base, familiar engineering practices, and plenty of off-the-shelf solutions. Transistors were initially viewed as fragile, unproven, and niche. Yet once power, size, heat and reliability became dominant constraints, the market flipped, slowly at first, then decisively.

None of this guarantees BRN wins.

Adoption speed still matters, and the window isn’t open-ended. But it’s not that BrainChip is falling behind “better” competitors, it’s that the market hasn’t yet been forced to care enough about the problems neuromorphic solves. Where it has been forced, BRN is already seeing traction.

So I agree with your concern, but I’d say the verdict hinges less on near-term elegance or ease of adoption, and more on how fast power, heat, and autonomy constraints tighten across the broader AI landscape. That’s the real time-frame that matters here.

One final point I’d add is that much of what the market currently labels as “AI progress” is still overwhelmingly centred on LLMs and hyperscale cloud infrastructure and that phase is rapidly maturing.

The next leg of AI growth is far more likely to be about where the compute happens, not just how large models become. As AI pushes out of data centres and into autonomous, mobile, always-on systems, edge constraints like power, latency, heat and connectivity become dominant.

That shift doesn’t automatically guarantee success for neuromorphic approaches, but it does materially expand the addressable market where neuromorphic makes sense. In that context, neuromorphic isn’t competing head-to-head with cloud AI; it’s positioned for the phase after cloud-centric AI saturates, which is where a lot of the longer-term optionality sits.

Of course, a big application is battle drones - I saw a Youtube recently that reported that 80% of Kills in the Ukraine-Russia conflict have been executed by drones (of all shapes and sizes). No military budget can ignore this trend. With US isolationism and Trump forcing countries to re-arm drone development (UAVs is the correct term) is at an all time high. And AI that is fast, local, small, reliable, low-power, and cheap is what makes UAVs deadlier.

You don't wait for the conflict to start - you fill warehouses with 'em so you're ready.

That's good news for BRN (and us investors) - but World War III - not so good.

***
I had an AI "Chat" which identified the following edge use cases....
“Autonomous, mobile, always-on” systems share three traits:

• They move through the world
• They must perceive continuously
• They cannot rely on constant connectivity or abundant power

Here are the best, real-world examples, grouped by maturity and importance.

Military & Security (already here, already critical)​

Drones (air, land, sea)​

This is the archetype.

• ISR drones
• Loitering munitions
• Autonomous naval vessels
• Swarm drones

Why they matter:

• Battery-powered
• Highly mobile
• Must sense continuously
• Must react in milliseconds
• Often disconnected or jammed

Cloud AI is impossible here.
Brute-force edge compute is tolerated — but inefficient.

Counter-drone & perimeter defence systems​

• Radar + RF + EO/IR sensing
• Always on
• Must distinguish signal from noise continuously
• False positives are costly

Event-driven, low-power intelligence is a natural fit.

Robotics & Industrial Autonomy (rapidly emerging)​

Mobile robots (AMRs, humanoids, legged robots)​

• Warehouses
• Hospitals
• Field inspection
• Construction sites

Constraints:

• Battery-limited
• Must operate for hours or days
• Continuous perception (vision, lidar, audio)
• Safety-critical decisions

Most current systems are over-provisioned and power-inefficient — by design.

Autonomous vehicles (non-consumer first)​

Not robotaxis — those are cloud-heavy.

But:

• Mining vehicles
• Agricultural machinery
• Military ground vehicles

These:

• Operate in remote areas
• Require deterministic response
• Have limited connectivity

Medical & Human-adjacent Systems (under-appreciated)​

Implantable and wearable medical devices​

Examples:

• Cochlear implants
• Neural stimulators
• Smart insulin pumps
• Continuous monitoring wearables

Why they’re important:

• Always on
• Ultra-low power
• Safety critical
• Privacy sensitive

Cloud AI is a non-starter.
“Good enough” compute often isn’t good enough.

Assistive technologies​

• Prosthetics
• Exoskeletons
• Mobility aids

These require:

• Real-time feedback loops
• Local learning
• Minimal latency

Consumer & Infrastructure (early but inevitable)​

Smart sensors & IoT at scale​

• Environmental monitoring
• Smart cities
• Infrastructure health
• Border security

Thousands or millions of sensors:

• Always on
• Mostly idle
• Occasionally critical

Processing everything centrally is economically insane.

Space systems​

• Satellites
• Spacecraft autonomy
• Debris avoidance
• On-orbit servicing

Constraints:

• Power is scarce
• Communication delayed
• Reliability is existential

The unifying insight (this is the key)​

In all these systems:

• Power is a hard constraint
• Latency is non-negotiable
• Connectivity is unreliable
• Intelligence must be continuous, not episodic

That combination is exactly where:

• Cloud AI fails
• Brute-force edge AI struggles
• Event-driven approaches become interesting

Why this matters for your broader thesis​

These systems are not fringe.

They are:

• Growing in number
• Growing in strategic importance
• Becoming more autonomous over time

And importantly:


That’s why this category matters more than benchmarks or demos.

Do you own research.

Hi Hoppy,

The chatbot overlooked my hobbyhorse, cybersecurity. There is an urgent and explosively growing need, and with the QV CyberNeuro-RT/Akida Edge Box (or whatever it's called now), we have a CotS solution which grew out of a DoE SBIR and an associated MDA SBIR. To be fair, cybersecurity does not necessarily meet the requirement to "move through the world".

On "2. Counter drone", false negatives are more costly.

 

[HopalongPetrovski]

Hi Hoppy,

The chatbot overlooked my hobbyhorse, cybersecurity. There is an urgent and explosively growing need, and with the QV CyberNeuro-RT/Akida Edge Box (or whatever it's called now), we have a CotS solution which grew out of a DoE SBIR and an associated MDA SBIR. To be fair, cybersecurity does not necessarily meet the requirement to "move through the world".

On "2. Counter drone", false negatives are more costly.

Thanks Dio and I agree with both the importance regarding cybersecurity and the possibility of it becoming both a lucrative and near term opportunity for us. I assume its implementation would necessarily entail a physical device to provide protection?
Is retrofit protection available through something like a raspberry pie plug in device or would it need to be built in and only available on new specifically designed hardware do you think?

 

[Diogenese]

Thanks Dio and I agree with both the importance regarding cybersecurity and the possibility of it becoming both a lucrative and near term opportunity for us. I assume its implementation would necessarily entail a physical device to provide protection?
Is retrofit protection available through something like a raspberry pie plug in device or would it need to be built in and only available on new specifically designed hardware do you think?

Hi Hoppy,

The first product is the Edge Box, and is designed for small/medium enterprises. I guess Akida will detect it first and then the CyberNeuro software deals with hostile input. The model will be continually updated via federated learning as new threats are detected.

 

[Esq.111]

So to clarify one last time, I am not asking what it costs BrainChip to manufacture the chips, nor am I asking for a margin analysis.

I am pointing out that we cannot determine the revenue from these orders because the announcement states customers will be charged anywhere between $4 and $50 per chip, depending on volume.

What the announcement does not disclose however, is where on that sliding scale these orders actually sit.

Specifically, 1) what volume qualifies as a high volume order 2) at what quantity does pricing move from $50 to $10 to $4? 3) where does an order of 10,000 units or 1,200 units fall on that curve?

Without that information, revenue could be materially different under perfectly reasonable interpretations.

To illustrate by way of demonstration only:

• If BrainChip considers anything above 5,000 units to be a volume order, then 11,200 units could be priced at $4, generating roughly $45k in revenue.
• If instead “volume” means anything exceeding 50,000 units, then the same 11,200 units could be priced far higher — say $20–$30 per chip, resulting in $224k–$336k of revenue.

My point is that until the company clarifies how the volume pricing tiers actually work, any attempt to calculate revenue from these orders is pure guesswork.

Top of the evening Bravo.

Bloody good to see you are still with us , .

On the .... what the farrk are Brn shareholders getting from these initial chip sales , ..

Who would honestly know, fucked if I do , Pretty sure our our Manigement ???? Also have know idea , personally going with a percentage ,per chip , per product .

ie , a Tomahawk missile costs X , incorperate our tech ( one hase to fucking well pay for it ) not $50 Per chip but a percentage per use .

OUR DIRECTORS ??????? ACCORDING TO OUR CHAIRMAN , ARE GETTING CONMENSURATED , WITH A COMPANY RETURNING $20 to $ 30 ODD MILLION ANNUALLY.

FUNNY AS FUCK, THIS CAME FROM KNOWOTHER THAN OUR VERY OWN CHAIRMANS MOUTH , THREE YEARS AGO.

Thay have not even ....remotely approached such levels , yet continue to suck the companys reservs dry without remorse , said it once & will say it again , & will be voting ALL OUT next AGM , AGAIN

Thay have consistently, without fail , showen a compleet disregard , for the °( OUR COMPANYS ) finances to further their own salaries/ perks .

The arrogance showen thus far on many fronts is staggering .

Would be happy to , (and will vote accordingly ,.... again , third year running ) to eject the entire board , then our CEO .


Yep , would be a happy holder employing , not the first, probbibly the forth or fith smartest graduate out of Harved or Stamford Business , a young soul WITH A BITT OF DRIVE .


Not in any way directed at you Bravo , thankyou for ones inpout always appreciated.

Regards,
Esq.

 

[7für7]

Sean when shareholders ask him what he is doing for almost 5 years

 

[Drewski]

SNAFU

The IP is incredibly valuable.

The tech is revolutionary and necessary.

We are told nothing, or there is nothing to tell or they can't tell.

I don't doubt Sean and co are not doing everything within their power to make BRN win.

There are insanely powerfull forces that BRN has to compete with.

Time will tell, for good or bad.

2026 is make or break there is no doubt about it.

 

[7für7]

Top of the evening Bravo.

Bloody good to see you are still with us , .

On the .... what the farrk are Brn shareholders getting from these initial chip sales , ..

Who would honestly know, fucked if I do , Pretty sure our our Manigement ???? Also have know idea , personally going with a percentage ,per chip , per product .

ie , a Tomahawk missile costs X , incorperate our tech ( one hase to fucking well pay for it ) not $50 Per chip but a percentage per use .

OUR DIRECTORS ??????? ACCORDING TO OUR CHAIRMAN , ARE GETTING CONMENSURATED , WITH A COMPANY RETURNING $20 to $ 30 ODD MILLION ANNUALLY.

FUNNY AS FUCK, THIS CAME FROM KNOWOTHER THAN OUR VERY OWN CHAIRMANS MOUTH , THREE YEARS AGO.

Thay have not even ....remotely approached such levels , yet continue to suck the companys reservs dry without remorse , said it once & will say it again , & will be voting ALL OUT next AGM , AGAIN

Thay have consistently, without fail , showen a compleet disregard , for the °( OUR COMPANYS ) finances to further their own salaries/ perks .

The arrogance showen thus far on many fronts is staggering .

Would be happy to , (and will vote accordingly ,.... again , third year running ) to eject the entire board , then our CEO .


Yep , would be a happy holder employing , not the first, probbibly the forth or fith smartest graduate out of Harved or Stamford Business , a young soul WITH A BITT OF DRIVE .


Not in any way directed at you Bravo , thankyou for ones inpout always appreciated.

Regards,
Esq.

Can you imagine? Next week…..

Price

Sensitive








An….

Nounce….

Ment……

 

[manny100]

I Pasted a portion of Steve Brightfield's concerning the Aitforce Research (obviously RTX/US AFRL) interview and asked 'chat' to outline the implications for Brainchip.
Q. " One of the things that was interesting is we got a contract with Air Force research libraries to work on radar using these algorithms, right? And the results actually surprised us and they surprised the contracting agency and now we're expanding that. And we think that we can, you know, add capabilities to radar that weren't there before. Like, for example, radar can detect things, right? But it can't tell you what it is. Well, we can classify objects now with radar in addition to detecting them. We can improve the tracking and the latency of these radars. But we can also make them a lot smaller, right? So it's that size weight and power. Can I put a radar in a robot? So when it's hand has got a radar signal in it and it can basically navigate, you can paint the scene without a camera. You can use it like a camera to paint the scene and recognize and grasp things that a drone. You can fly it inside tunnels or buildings indoors. You can map out where you're going. We see this shrinking of the conventional radar technologies to really go into anything moving because it's all whether it works in the dark. And if it can replicate some of the things in vision, then, you know, you don't have to worry about rain and fog and all the issues that visual, you know, control of robots. Yeah. And are you working with robotic companies or is this still in the research room? It's still in the research. We're working with companies that are creating components or solutions that go to the robotics companies. We are in active conversations with robotic companies today." quote from Steve Brightfield's interview. What are the implications for Brainchip."
My bold above highlighting important area.
Chat rely:
The implications for BrainChip are much bigger than the quote sounds at first glance. Brightfield is essentially revealing that neuromorphic radar is not just a research curiosity—it’s showing unexpectedly strong performance and opening entirely new markets.

Here’s what this really means for BrainChip.

1. Validation From a High‑Credibility Customer (the U.S. Air Force)​

When a defense research agency tests a technology and is surprised by the results, that’s a major signal.

It implies:

• BrainChip’s neuromorphic approach is outperforming traditional radar processing.
• The technology is maturing faster than expected.
• The Air Force sees enough promise to expand the contract.

For a small semiconductor company, this is enormous validation.

2. Neuromorphic Radar Could Become a New Category of Sensor​

Brightfield is describing a capability that traditional radar does not have:

• Object classification, not just detection
• Scene reconstruction (like a camera, but using radar)
• Low‑latency tracking
• Miniaturization (radar small enough for a robot hand)

This implies BrainChip’s Akida architecture can:

• Process radar signals in real time
• Extract features the way a biological brain would
• Do it with extremely low power

If this holds up, BrainChip isn’t just improving radar—they’re enabling a new sensing modality.

3. Robotics Becomes a Natural Market​

He’s hinting at a future where robots use radar the way humans use vision:

• Navigating in darkness
• Operating in smoke, fog, dust, tunnels
• Grasping objects without cameras
• Flying drones indoors or underground

This is a huge implication:

BrainChip could become a foundational chip supplier for next‑generation robotics.​

Robotics companies are already “in active conversations,” which means:

• Early evaluations are underway
• BrainChip is being considered for integration into future platforms
• The company is moving from R&D to commercial engagement

4. Size, Weight, and Power (SWaP) Advantage = Competitive Edge​

Neuromorphic chips excel at:

• Ultra‑low power
• Low heat
• Small footprint

Shrinking radar systems is a massive competitive advantage in:

• Drones
• Autonomous robots
• Wearables
• Defense systems
• Industrial automation

This positions BrainChip as a SWaP‑optimized alternative to GPUs and traditional DSPs.

5. BrainChip Is Moving Up the Value Chain​

He says they’re no longer just giving algorithms—they’re building reference platforms.

This means:

• BrainChip wants to make adoption easier
• They’re packaging hardware + software + demo systems
• They’re targeting OEMs who want turnkey solutions

This is the same strategy NVIDIA used early on: don’t just sell chips—sell ecosystems.

6. Potential for Dual‑Use Technology​

Radar + neuromorphic processing has both:

• Defense applications (surveillance, navigation, targeting)
• Commercial applications (robotics, drones, smart sensors)

Dual‑use tech tends to scale faster because:

• Defense funds early R&D
• Commercial markets drive volume

BrainChip is positioning itself right at that intersection.

 

[Diogenese]

I Pasted a portion of Steve Brightfield's concerning the Aitforce Research (obviously RTX/US AFRL) interview and asked 'chat' to outline the implications for Brainchip.
Q. " One of the things that was interesting is we got a contract with Air Force research libraries to work on radar using these algorithms, right? And the results actually surprised us and they surprised the contracting agency and now we're expanding that. And we think that we can, you know, add capabilities to radar that weren't there before. Like, for example, radar can detect things, right? But it can't tell you what it is. Well, we can classify objects now with radar in addition to detecting them. We can improve the tracking and the latency of these radars. But we can also make them a lot smaller, right? So it's that size weight and power. Can I put a radar in a robot? So when it's hand has got a radar signal in it and it can basically navigate, you can paint the scene without a camera. You can use it like a camera to paint the scene and recognize and grasp things that a drone. You can fly it inside tunnels or buildings indoors. You can map out where you're going. We see this shrinking of the conventional radar technologies to really go into anything moving because it's all whether it works in the dark. And if it can replicate some of the things in vision, then, you know, you don't have to worry about rain and fog and all the issues that visual, you know, control of robots. Yeah. And are you working with robotic companies or is this still in the research room? It's still in the research. We're working with companies that are creating components or solutions that go to the robotics companies. We are in active conversations with robotic companies today." quote from Steve Brightfield's interview. What are the implications for Brainchip."
My bold above highlighting important area.
Chat rely:
The implications for BrainChip are much bigger than the quote sounds at first glance. Brightfield is essentially revealing that neuromorphic radar is not just a research curiosity—it’s showing unexpectedly strong performance and opening entirely new markets.

Here’s what this really means for BrainChip.

1. Validation From a High‑Credibility Customer (the U.S. Air Force)​

When a defense research agency tests a technology and is surprised by the results, that’s a major signal.

It implies:

• BrainChip’s neuromorphic approach is outperforming traditional radar processing.
• The technology is maturing faster than expected.
• The Air Force sees enough promise to expand the contract.

For a small semiconductor company, this is enormous validation.

2. Neuromorphic Radar Could Become a New Category of Sensor​

Brightfield is describing a capability that traditional radar does not have:

• Object classification, not just detection
• Scene reconstruction (like a camera, but using radar)
• Low‑latency tracking
• Miniaturization (radar small enough for a robot hand)

This implies BrainChip’s Akida architecture can:

• Process radar signals in real time
• Extract features the way a biological brain would
• Do it with extremely low power

If this holds up, BrainChip isn’t just improving radar—they’re enabling a new sensing modality.

3. Robotics Becomes a Natural Market​

He’s hinting at a future where robots use radar the way humans use vision:

• Navigating in darkness
• Operating in smoke, fog, dust, tunnels
• Grasping objects without cameras
• Flying drones indoors or underground

This is a huge implication:

BrainChip could become a foundational chip supplier for next‑generation robotics.​

Robotics companies are already “in active conversations,” which means:

• Early evaluations are underway
• BrainChip is being considered for integration into future platforms
• The company is moving from R&D to commercial engagement

4. Size, Weight, and Power (SWaP) Advantage = Competitive Edge​

Neuromorphic chips excel at:

• Ultra‑low power
• Low heat
• Small footprint

Shrinking radar systems is a massive competitive advantage in:

• Drones
• Autonomous robots
• Wearables
• Defense systems
• Industrial automation

This positions BrainChip as a SWaP‑optimized alternative to GPUs and traditional DSPs.

5. BrainChip Is Moving Up the Value Chain​

He says they’re no longer just giving algorithms—they’re building reference platforms.

This means:

• BrainChip wants to make adoption easier
• They’re packaging hardware + software + demo systems
• They’re targeting OEMs who want turnkey solutions

This is the same strategy NVIDIA used early on: don’t just sell chips—sell ecosystems.

6. Potential for Dual‑Use Technology​

Radar + neuromorphic processing has both:

• Defense applications (surveillance, navigation, targeting)
• Commercial applications (robotics, drones, smart sensors)

Dual‑use tech tends to scale faster because:

• Defense funds early R&D
• Commercial markets drive volume

BrainChip is positioning itself right at that intersection.

For a robot, the detection range will normally only need to be <200m, compared with normal radar range >20km, so the radar system will also be low power. So theoretically only about 1 millionth of the power, but the radar receive probably needs a little more than that.

It will use the 8-bit Akida 2, which does use more power than Akida 1 (4-bit).

PS: Prof Google tells me that 10 to 100 kW is the typical peak transmit power for radar.

 

[jrp173]

Top of the evening Bravo.

Bloody good to see you are still with us , .

On the .... what the farrk are Brn shareholders getting from these initial chip sales , ..

Who would honestly know, fucked if I do , Pretty sure our our Manigement ???? Also have know idea , personally going with a percentage ,per chip , per product .

ie , a Tomahawk missile costs X , incorperate our tech ( one hase to fucking well pay for it ) not $50 Per chip but a percentage per use .

OUR DIRECTORS ??????? ACCORDING TO OUR CHAIRMAN , ARE GETTING CONMENSURATED , WITH A COMPANY RETURNING $20 to $ 30 ODD MILLION ANNUALLY.

FUNNY AS FUCK, THIS CAME FROM KNOWOTHER THAN OUR VERY OWN CHAIRMANS MOUTH , THREE YEARS AGO.

Thay have not even ....remotely approached such levels , yet continue to suck the companys reservs dry without remorse , said it once & will say it again , & will be voting ALL OUT next AGM , AGAIN

Thay have consistently, without fail , showen a compleet disregard , for the °( OUR COMPANYS ) finances to further their own salaries/ perks .

The arrogance showen thus far on many fronts is staggering .

Would be happy to , (and will vote accordingly ,.... again , third year running ) to eject the entire board , then our CEO .


Yep , would be a happy holder employing , not the first, probbibly the forth or fith smartest graduate out of Harved or Stamford Business , a young soul WITH A BITT OF DRIVE .


Not in any way directed at you Bravo , thankyou for ones inpout always appreciated.

Regards,
Esq.

Esq. I'm with you. I'm voting no to any resolution the involves director re-electon and absolutely will be voting down the remuneration report.

If the REM report is voted down, this will be the fourth time, and this time we can actually vote on a board spill (must have two consecutive rem repots voted down), and the clock restarts after every second strike. However even if the board spill was successful, unfortunately the one person that remains is the MD (Sean) for continuity.

I actually find it hard to believe that this could be the FOURTH time the rem report is voted down. Shareholders are giving a loud and clear message, but these arrogant directors are basically saying, we don't care what shareholders think, we are still taking the cash even though it was voted down. Check out how many ASX listed companies have had four strikes.. not many... how embarrassing for BRN.

These arrogant people just refuse to listen to shareholders...They have no morals or conscience.

And let's not forget that Sean gets 50% of his bonus regardless of what he achieves. How about you only get a bonus if you actually achieve your target. Im sick of the BS that we have to pay for the best, because we absolutely do not have the best. We just have the greediest.

I'd be happy to see the back of Antonio and the other useless non execs. Absolute oxygen thieves. We need a great board and Chairman who can actually hold Sean to account!

Because at this stage they are all so disgustingly overpaid paid, they support each other and cover for each other, to the detriment of shareholders. Each and everyone of the directors (exec and non-exec) are totally complicit in this absolutely cluster. How can PIA as the head of the Rem Committee actually endorse these salaries? Oh I know why, because she's getting 270K USD. So she's not going to rock the boat is she.... and then the 68K paid to Korn last year, so they could tell us they actually deserve these salaries. They must think we are idiots.

I hope people wake up and are ready to vote in order to save this company and our hard earned investments.

I almost feel physically ill when I re-read the annual reports over the years and see how much money these thieves are taking, whilst providing no significant material results.

I honestly don't know how any of them can even show their faces at the AGM (in front of shareholders) considering how they are absolute fleecing shareholders and destroying this company!

Wouldn't it be nice if they actually had any moral fibre and some of the dead wood actually resigned prior the AGM.

Wouldn't it also be nice if the company actually made significant changes to their salaries this year. However about a huge reduction in salary, and HUGE bonuses if they actually deliver. No issue with huge salaries if they are actually weighted to performance.

Remember 280K AUD to 380K AUD for our non exec directors.. and don't even get me started on Sean.

Absolutely disgraceful, they all should be ashamed.

 

[manny100]

For a robot, the detection range will normally only need to be <200m, compared with normal radar range >20km, so the radar system will also be low power. So theoretically only about 1 millionth of the power, but the radar receive probably needs a little more than that.

It will use the 8-bit Akida 2, which does use more power than Akida 1 (4-bit).

PS: Prof Google tells me that 10 to 100 kW is the typical peak transmit power for radar.

It's hard to believe that AKIDA powered radar can take the place of a camera.
Steve has told that part of the World that viewed the video and/or read the transcript.
I would have thought this information should have been shared a little further.
"Can I put a radar in a robot? So when it's hand has got a radar signal in it and it can basically navigate, you can paint the scene without a camera."
I did not include the below which followed on from the question above asked of Chat.
" We are in active conversations with robotic companies today. And they're in evaluation of this, right? But what we decided was to create reference platforms that demonstrate these more holy rather than having a, you know, here's the algorithm go figured out. We'll build a little prototype. So we're doing reference designs and radar. We're also going to do this in these wearables."
Pretty important stuff. Building prototypes will quicken the path for clients through the pipeline.

 

[Fullmoonfever]

Not long left on this one.

Give or take maybe a couple of months for any delays, over runs and the final assessment of the outcomes I guess.

If all goes exceptionally well with this, I wouldn't be surprised if we secured a full licence agreement or contract in some form with Raytheon / RTX.

Definitive Contract​

PIID​

FA875025CB013

In Progress​

(8 days remain)​

Unlinked Award

---

Awarding Agency​

Department of Defense (DOD)​

Recipient​

BRAINCHIP, INC​

23041 AVENIDA DE LA CARLOTA STE 250

LAGUNA HILLS, CA 92653-1545
UNITED STATES

 

[Diogenese]

It's hard to believe that AKIDA powered radar can take the place of a camera.
Steve has told that part of the World that viewed the video and/or read the transcript.
I would have thought this information should have been shared a little further.
"Can I put a radar in a robot? So when it's hand has got a radar signal in it and it can basically navigate, you can paint the scene without a camera."
I did not include the below which followed on from the question above asked of Chat.
" We are in active conversations with robotic companies today. And they're in evaluation of this, right? But what we decided was to create reference platforms that demonstrate these more holy rather than having a, you know, here's the algorithm go figured out. We'll build a little prototype. So we're doing reference designs and radar. We're also going to do this in these wearables."
Pretty important stuff. Building prototypes will quicken the path for clients through the pipeline.

Yes. I was excited by the original microDoppler SBIR being able to identify objects from their characteristic vibration causing minor modulation of the reflected signal, but I was blown away when they announced the see-in-the-dark radar. Performing the inference in a silicon NN processor with TENNs is able to provide real time responses with great precision and low power.

This may also have application for acoustic feedback for the vision-impaired - literally see-in-the-dark. Radar has a much shorter wavelength than ultrasound, and can thus provide much more detail. Such a system could identify objects and their distance depending on the direction the user was facing.

 

[7für7]

But I have to say, this IBM guy is getting interesting… he likes our partnership with the 300

 

[Fullmoonfever]

Not long left on this one.

Give or take maybe a couple of months for any delays, over runs and the final assessment of the outcomes I guess.

If all goes exceptionally well with this, I wouldn't be surprised if we secured a full licence agreement or contract in some form with Raytheon / RTX.

Definitive Contract​

PIID​

FA875025CB013

In Progress​

(8 days remain)​

Unlinked Award

---

Awarding Agency​

Department of Defense (DOD)​

Recipient​

BRAINCHIP, INC​

23041 AVENIDA DE LA CARLOTA STE 250

LAGUNA HILLS, CA 92653-1545
UNITED STATES

Straight off the RTX site. Seem pretty keen to provide neuromorphic solutions given their statement below.

Transformative Technologies

Raytheon Technologies is defining the future of aerospace and defense with ground-breaking research and development to create transformative technologies that push the limits of known science.

www.rtx.com

Advanced sensing​

We have a deep heritage in developing radio frequency, electro-optical/infrared sensing, communications and electronic warfare systems for space, air, ground, sea and undersea environments.
Advanced sensing

• Our RF systems use higher-power microelectronics, increased processing power and software-defined apertures to achieve next-generation capabilities for radar, electronic warfare, communications and multifunction radio frequency applications.
• We’re advancing electro-optical/infrared and other systems such as space-based multispectral sensors and electro-optical distributed aperture systems variants.
• We are providing increased capability against advanced threats and countermeasures by enhancing high-bandwidth digital waveform generation, AI-enabled intelligent signal processing and advanced neuromorphic processing.
• Our acoustic systems enable advanced mine-hunting and undersea networking capabilities through high sensitivity, directionality, multiple access and multi-mod active and passive capabilities for sonar, communications and navigation.
• Our missile seekers counter a wide range of advanced threats through advanced processing and algorithms, all while achieving low size, weight, power and cost.

 

[Diogenese]

How many has Francis Ford Crappola won?

Anyhow, Frances McDormand has got 3, and Fargo was shot in Minnesota, so she really owes the Trumps one ...