BRN Discussion Ongoing

[TheDrooben]

I agree Larry. Seconded.
Dio is a bloody gem and his bloods worth bottlin'.
But what's with the illusion of him in the bathtub?
What, with a cigar in one hand and a radiator in the other?
Just in case.

Bathtub sounds better than "pithos"

Happy as Larry

 

[HopalongPetrovski]

View attachment 95306

Bathtub sounds better than "pithos"

Happy as Larry

Thanks Larry.
Somehow that reference escaped me.
I must have been pithossed that day in ancient greek class.

 

[Diogenese]

View attachment 95306

Bathtub sounds better than "pithos"

Happy as Larry

I bathe weekly. Sometimes I bathe very weakly.

 

[Bravo]

Well, I finally got around to watching the video (see link below) that Pom posted a few days ago with Jonathan Tapson.

It’s highly technical and, to be honest, a fair bit of it went over my head. That said, there were a few comments that struck me as potential red flags, unless I’ve completely misunderstood what he was saying.

He starts by outlining the core features of neuromorphic chips such as asynchronous, event-based architectures and so on (see slide below). But then he makes the point that asynchronous designs account for less than 1% of commercial electronics, adding that it’s probably closer to 0.00001%!!!!

I could be wrong, but hat doesn't even seem niche to me, it seems effectively non-existent in mainstream commercial terms.

He also notes that just because the performance advantages are clear doesn’t mean adoption automatically follows. In other words, that technical merit doesn’t equal market penetration.

On top of that, Jonathan mentions how very few machine learning engineers have experience with spiking neural networks. So even if the hardware is differentiated, the developer ecosystem is extremely small. Add to that companies’ reluctance to share proprietary datasets and internal models, which he acknowledges makes integration difficult and you start to see how the barriers to adoption stack up.

He does however, mention BrainChip has found a way around the challenge of customers not wanting to provide their proprietary info to third parties, but he emphasises that it's hard work. He also mentioned something about being happy at some earlier decisions BrainChip made, which should help.

Unless I've got this all wrong, I think this video might help explain why commercial traction has been so much slower than many of us hoped.

I’d welcome input from someone with stronger technical expertise, in case I’ve completely misinterpreted any of this. The last thing I’d want to do is draw the wrong conclusions since we're all depressed enough as it is.


Here are some random slides from the preso.

 

[smoothsailing18]

Well, I finally got around to watching the video (see link below) that Pom posted a few days ago with Jonathan Tapson.

It’s highly technical and, to be honest, a fair bit of it went over my head. That said, there were a few comments that struck me as potential red flags, unless I’ve completely misunderstood what he was saying.

He starts by outlining the core features of neuromorphic chips such as asynchronous, event-based architectures and so on (see slide below). But then he makes the point that asynchronous designs account for less than 1% of commercial electronics, adding that it’s probably closer to 0.00001%!!!!

I could be wrong, but hat doesn't even seem niche to me, it seems effectively non-existent in mainstream commercial terms.

He also notes that just because the performance advantages are clear doesn’t mean adoption automatically follows. In other words, that technical merit doesn’t equal market penetration.

On top of that, Jonathan mentions how very few machine learning engineers have experience with spiking neural networks. So even if the hardware is differentiated, the developer ecosystem is extremely small. Add to that companies’ reluctance to share proprietary datasets and internal models, which he acknowledges makes integration difficult and you start to see how the barriers to adoption stack up.

He does however, mention BrainChip has found a way around the challenge of customers not wanting to provide their proprietary info to third parties, but he emphasises that it's hard work. He also mentioned something about being happy at some earlier decisions BrainChip made, which should help.

Unless I've got this all wrong, I think this video might help explain why commercial traction has been so much slower than many of us hoped.

I’d welcome input from someone with stronger technical expertise, in case I’ve completely misinterpreted any of this. The last thing I’d want to do is draw the wrong conclusions since we're all depressed enough as it is.


Here are some random slides from the preso.


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View attachment 95308




View attachment 95309

One thing i have notice about engineering people over the years is their focus isn't general on marketing and 99% of their communication is the obstacles they see which allways seems negative to the unqualified.
I have had this experience many times over the years however there are many ways to look at the overall picture outside of this type of thinking.
We are getting there slowly we are closer than ever before. Keep the faith.

 

[Diogenese]

Well, I finally got around to watching the video (see link below) that Pom posted a few days ago with Jonathan Tapson.

It’s highly technical and, to be honest, a fair bit of it went over my head. That said, there were a few comments that struck me as potential red flags, unless I’ve completely misunderstood what he was saying.

He starts by outlining the core features of neuromorphic chips such as asynchronous, event-based architectures and so on (see slide below). But then he makes the point that asynchronous designs account for less than 1% of commercial electronics, adding that it’s probably closer to 0.00001%!!!!

I could be wrong, but hat doesn't even seem niche to me, it seems effectively non-existent in mainstream commercial terms.

He also notes that just because the performance advantages are clear doesn’t mean adoption automatically follows. In other words, that technical merit doesn’t equal market penetration.

On top of that, Jonathan mentions how very few machine learning engineers have experience with spiking neural networks. So even if the hardware is differentiated, the developer ecosystem is extremely small. Add to that companies’ reluctance to share proprietary datasets and internal models, which he acknowledges makes integration difficult and you start to see how the barriers to adoption stack up.

He does however, mention BrainChip has found a way around the challenge of customers not wanting to provide their proprietary info to third parties, but he emphasises that it's hard work.

Unless I've got this all wrong, I think this video might help explain why commercial traction has been so much slower than many of us hoped.

I’d welcome input from someone with stronger technical expertise, in case I’ve completely misinterpreted any of this. The last thing I’d want to do is draw the wrong conclusions since we're all depressed enough as it is.


Here are some random slides from the preso.


View attachment 95307



View attachment 95308




View attachment 95309

Hi Bravo,

The synchronous/asynchronous thing ... I think the big takeaway is that asynchronous has much lower latency, the response being practically instantaneous. It's like waiting for a bus compared with having an Uber driver as a neighbour, or better yet, having your own e-bike.

Synchronous is a hangover from von Neumann. It is very familiar to engineers and programmers. Old school AI programmers cut their teeth on CNN running on synchronous processors (ARM/Intel/Nvidia) But that is why BRN has MetaTF. It provides an almost seamless transition using software familiar to such programmers. In addition, BRN does provide models which they prepared earlier, and there are BRN partners who provide model development support.

I do think going IP only did push out commercial adoption. Manufacturers plan their product designs years ahead., so IP only builds in that adoption delay.

But I also believe that there were the twin factors of financial constraints and the undisclosed TENNs development which necessitated the drastic move to abandon the infant Akida 1 on the orphanage steps. TENNs was the cuckoo in the nest which ejected the fully fledged Akida 1 and demanded all the developmental attention. So, to add to the metaphor salad, Akida 1 sat quietly on the back burner while the market came to a better appreciation of the power of neuromorphic asychronicity.

So, yes, market unfamiliarity was a part of the delayed adoption, but the unprecedented speed of the technological revolution has, in my opinion, played a larger part. To move from Akida 1 SoC in 2022 to TENNs in 2025 is a massive technological leap. And when TENNs was first unveiled, it was still accompanied by the optional ViT (Vision Transformer). BRN did not understand just how powerful TENNs was. TENNs made Transformers (the brainchild of Google researchers in 2017*) obsolete. Nvidia adopted Transformers in 2017**.

However, the strength of our partnerships and engagements is cause for optimism. The FG GR801 is a great endorsement of Akida tech. The DoE/QV cybersecurity SBIR and subsequent commercial release of the Real-Time cybersecurity Edge Box opens the door to a limitless market. The RTX/USAFRL microDoppler SBIR and the resultant commercial potential of see-in-the dark radar provides another entirely new market. But sadly, the adoption of new tech takes time. That is why I think the cybersecurity implementation provides the shortest path to market. The need is ever present and no new silicon is needed, (except that we will need to produce additional chips to meet the market demand).

* https://en.wikipedia.org/wiki/Transformer_(deep_learning)
** https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-FX-08+V1

 

[7für7]

Well, I finally got around to watching the video (see link below) that Pom posted a few days ago with Jonathan Tapson.

It’s highly technical and, to be honest, a fair bit of it went over my head. That said, there were a few comments that struck me as potential red flags, unless I’ve completely misunderstood what he was saying.

He starts by outlining the core features of neuromorphic chips such as asynchronous, event-based architectures and so on (see slide below). But then he makes the point that asynchronous designs account for less than 1% of commercial electronics, adding that it’s probably closer to 0.00001%!!!!

I could be wrong, but hat doesn't even seem niche to me, it seems effectively non-existent in mainstream commercial terms.

He also notes that just because the performance advantages are clear doesn’t mean adoption automatically follows. In other words, that technical merit doesn’t equal market penetration.

On top of that, Jonathan mentions how very few machine learning engineers have experience with spiking neural networks. So even if the hardware is differentiated, the developer ecosystem is extremely small. Add to that companies’ reluctance to share proprietary datasets and internal models, which he acknowledges makes integration difficult and you start to see how the barriers to adoption stack up.

He does however, mention BrainChip has found a way around the challenge of customers not wanting to provide their proprietary info to third parties, but he emphasises that it's hard work. He also mentioned something about being happy at some earlier decisions BrainChip made, which should help.

Unless I've got this all wrong, I think this video might help explain why commercial traction has been so much slower than many of us hoped.

I’d welcome input from someone with stronger technical expertise, in case I’ve completely misinterpreted any of this. The last thing I’d want to do is draw the wrong conclusions since we're all depressed enough as it is.


Here are some random slides from the preso.


View attachment 95307



View attachment 95308




View attachment 95309

Thank you for the motivational words on Sunday! This makes me confident and looking forward for tomorrow unless I misunderstood your post

 

[Guzzi62]

Don't blame the company for not getting things right, if we can't get it right ourselves.
Kevin has made three video posts.
And he's not finished yet.!!

No 1.
https://www.linkedin.com/posts/acti...p&rcm=ACoAADDiEIwBjYqxVppXuQtYvrrz7uvUft3uTeU

No 2.
https://www.linkedin.com/posts/acti...p&rcm=ACoAADDiEIwBjYqxVppXuQtYvrrz7uvUft3uTeU

No 3.
https://www.linkedin.com/posts/acti...p&rcm=ACoAADDiEIwBjYqxVppXuQtYvrrz7uvUft3uTeU

Free advertising, thank you so much, Mr Johnson.

I hope Mr Hehir sends him a box of chocolate.

 

[smoothsailing18]

Interesting possibilities come on brainchip let's go.

In 2026, the company poised for the most significant mass integration of BrainChip’s technology into a consumer-facing product is Neuralink, alongside strategic industrial integrations from MegaChips and Caterpillar. While BrainChip provides the underlying neuromorphic IP, Elon Musk’s Neuralink has announced plans to ramp up to "high-volume production" of its brain-computer interface (BCI) devices in 2026.[7] These implants require the exact specifications offered by BrainChip’s Akida platform: ultra-low power to prevent tissue heating, real-time event-based processing to interpret neural spikes, and on-chip learning to adapt to the specific neural patterns of individual patients.[1] [8] Musk has stated that the surgical procedure for these chips will become "almost entirely automated" by 2026, facilitating a move toward mass-market medical deployment

While Neuralink has not officially announced a partnership with BrainChip, the industry trend toward "neuromorphic BCIs" suggests that such an integration is a logical step for high-volume production planned for 2026.

 

[TopCat]

Interesting possibilities come on brainchip let's go.

In 2026, the company poised for the most significant mass integration of BrainChip’s technology into a consumer-facing product is Neuralink, alongside strategic industrial integrations from MegaChips and Caterpillar. While BrainChip provides the underlying neuromorphic IP, Elon Musk’s Neuralink has announced plans to ramp up to "high-volume production" of its brain-computer interface (BCI) devices in 2026.[7] These implants require the exact specifications offered by BrainChip’s Akida platform: ultra-low power to prevent tissue heating, real-time event-based processing to interpret neural spikes, and on-chip learning to adapt to the specific neural patterns of individual patients.[1] [8] Musk has stated that the surgical procedure for these chips will become "almost entirely automated" by 2026, facilitating a move toward mass-market medical deployment

While Neuralink has not officially announced a partnership with BrainChip, the industry trend toward "neuromorphic BCIs" suggests that such an integration is a logical step for high-volume production planned for 2026.

Given the genius that is Elon, I really don’t think he’s using any other technology that’s not his

 

[smoothsailing18]

Given the genius that is Elon, I really don’t think he’s using any other technology that’s not his

Very naive to assume Elon doesn't have technology partners. On a quick search see the following partners

Partner Component / Integrated Part Application
Samsung 4nm/7nm FSD ASICs, CMOS Image Sensors Autonomous Driving (Autopilot)
TSMC D1 Dojo Chips, AI5 Processors AI Training & Inference
Panasonic Cylindrical Lithium-ion Cells (2170/4680) Energy Storage & Propulsion
Garmin Integrated GPS and Navigation Modules Vehicle Telematics
Gentex Automatic Dimming Rearview Mirrors/Integrated Electronics Vehicle Safety Systems
Emerson Electric Power Conversion Integrated Systems Charging Infrastructure
STMicroelectronics Power MOSFETs and Microcontrollers Starlink Terminals & Power Electronics
Analog Devices Precision Data Converters & Signal Conditioning Battery Management Systems (BMS)
Infineon Power Semiconductors (IGBTs) Inverters and Motor Controllers

 

[TopCat]

Very naive to assume Elon doesn't have technology partners. On a quick search see the following partners

Partner Component / Integrated Part Application
Samsung 4nm/7nm FSD ASICs, CMOS Image Sensors Autonomous Driving (Autopilot)
TSMC D1 Dojo Chips, AI5 Processors AI Training & Inference
Panasonic Cylindrical Lithium-ion Cells (2170/4680) Energy Storage & Propulsion
Garmin Integrated GPS and Navigation Modules Vehicle Telematics
Gentex Automatic Dimming Rearview Mirrors/Integrated Electronics Vehicle Safety Systems
Emerson Electric Power Conversion Integrated Systems Charging Infrastructure
STMicroelectronics Power MOSFETs and Microcontrollers Starlink Terminals & Power Electronics
Analog Devices Precision Data Converters & Signal Conditioning Battery Management Systems (BMS)
Infineon Power Semiconductors (IGBTs) Inverters and Motor Controllers

Have a look at what he buys and the price he pays. If he thought we were worth it for his BMI or any other project he’s got going, we’re bargain price for him to snap us up

 

[TopCat]

Have a look at what he buys and the price he pays. If he thought we were worth it for his BMI or any other project he’s got going, we’re bargain price for him to snap us up

Don’t get me wrong, I’m desperate for us to skyrocket, but I’m also being a realist and I’m tired of clutching onto false hopes

 

[smoothsailing18]

Don’t get me wrong, I’m desperate for us to skyrocket, but I’m also being a realist and I’m tired of clutching onto false hopes

I don't think you have a clue what your talking about to be honest it certainly doesn't sound like it anyway.
Clutching at false hopes you say that definitely has conitation of giving up. Each to thier own .

 

[TopCat]

I don't think you clue what your talking about to be honest it certainly doesn't sound like it anyway.
Clutching at false hopes you say that definitely has conitation of giving up. Each to thier own .

“ While Neuralink has not officially announced a partnership with BrainChip, the industry trend toward "neuromorphic BCIs" suggests that such an integration is a logical step for high-volume production planned for 2026.”

Look at what what you’re posting! If this comes true this year I’ll sincerely apologise

 

[smoothsailing18]

“ While Neuralink has not officially announced a partnership with BrainChip, the industry trend toward "neuromorphic BCIs" suggests that such an integration is a logical step for high-volume production planned for 2026.”

Look at what what you’re posting! If this comes true this year I’ll sincerely apologise

Look at what what your posting . .

Hang in there buddy all we can do is be patient, have faith or give up and cry.

We'll get there I am % it's just a matter of time and isn't far off now.

 

[Boab]

Hope this song is relevant for this upcoming week.

 

[Jumpchooks]

Tata Group, TCS & OpenAI Announce 100MW AI Infrastructure Partnership On February 19, 2026​

Tata Group, TCS & OpenAI Announce 100MW AI Infrastructure Partnership On February 19, 2026

The Tata Group, Tata Consultancy Services (TCS), and OpenAI on February 19, 2026 announced a multi-dimensional strategic partnership to drive AI-led innovation. The tie-up includes setting up 100MW AI infrastructure in India, expanding Enterprise ChatGPT access to several thousand employees, and...

www.freepressjournal.in

Apologies if this announcement has been posted.

Does this Partnership between Tata Group,TCS and OpenAI have any repercussions for BRN?

 

[SharesForBrekky]

UT San Antonio to launch nation’s first open-access neuromorphic computing hub - UT San Antonio Today

THOR: The Neuromorphic Commons will be the largest neuromorphic platform to be open to the public.

news.utsa.edu

"the MATRIX AI Consortium for Human Well-Being at UT San Antonio plans to launch a new initiative that establishes a national hub for “neuromorphic” computing available for public use."

"The initiative, called THOR: The Neuromorphic Commons, is funded by the National Science Foundation. THOR will make the promising technology available for researchers nationwide to explore and conduct experiments, serving as the largest-ever full-stack neuromorphic platforms to be open to the public."

"Historically, access to large-scale neuromorphic hardware has been exclusive to well-funded industry labs or select universities.

THOR upends that paradigm by making these powerful systems accessible to researchers and students across the United States, said Pandit.

“Our goal is to host neuromorphic hardware developed by the THOR team and our partners, building a specialized center where the community can learn and develop the next generation of neuromorphic systems,” he said.

Much like a public library, anyone can apply for access, and the resources will be free to use. Researchers will be able to enter a queue to run their experiments on the hardware. Once a user finishes his or her work, the system becomes available for the next person, allowing for high utilization of the resource."

"The official launch of THOR is slated for February 23 in the UT San Antonio San Pedro I building, with plans for a live demonstration to showcase the hardware capabilities. Beyond the hardware, the initiative focuses heavily on training and education."

Brainchip is a part of the ecosystem:

THOR Ecosystem

www.neuromorphiccommons.com

 

[Diogenese]

Hope this song is relevant for this upcoming week.

... "if we just wait a while ..."?