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.


View attachment 95307



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.