BRN Discussion Ongoing

Was googling some search words as I do and this person's CV came up. No longer with BRN but was, back in mid 2023, for 3 mths as a ML Intern working on MB EQXX.

What I found interesting is that it appears MB maybe weren't just testing or playing with Akida for "Hey Mercedes" KWS but also driver distraction via sensors if I read correctly?

AND...over a year after the EQXX demo in early 2022 if this person's dates are correct.

Nice to see pretty damn good anomaly detection performace against a high end, though slightly older, GTX 1080 GPU.


IMG_20250801_220906.jpg


HERE
 
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Hi Smoothsailing 18.
Im just not completely trusting of Chat GPT or others, though obviously very good tools in the right context. See the Renesas announcement from december 2020.
First Akida IP License Agreement
cheers
With those kind of "tools" when you ask a question, the way the answer is given, depends a lot on how the question is asked, especially when you are seeking "its" opinion.
It seems to me, they are programmed to be a bit like a dog, that is eager to please and be pat on the head.

Screenshot_20250802-021757_Firefox.jpg


If you ask something like "what is the likelihood" it "knows" you are seeking confirmation of something and will try to supply evidence to confirm what you want.

A more reliable way to use it, as I understand it, would be to ask the question in a negative manner, like "what is the argument against" such and such a thing and you will possibly get a more helpful response (if you look at the results in a positive way, if you know what I mean, or even better ask the question in both/multiple ways).

That's just the way I see it currently and don't give much weight to it's "opinion".
Although it can be useful and now it's getting better, I intend to use it more in the Future, I'm getting kind of sick of seeing ChatGPT etc analysis everywhere...
 
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Tothemoon24

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IloveLamp

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stockduck

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Innatera claims world’s first mass-market neuromorphic microcontroller for the sensor edge​

Interviews | May 21, 2025


"The Pulsar chip has a heterogenous architecture that combines analog and digital neuromorphic blocks with a traditional convolutional neural network accelerator and a RISC-V core. "
....

I really would like to know what kind of IP this "digital neuromorphic block" looks like?:unsure:

The last 4c announcement gives me some hope.....
 
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FuzM

Member

View attachment 89251

Didn't realise that state space models was developed by Prof Chris Eliasmith from University of Waterloo.

The very same person that Mercedes has signed an MoU for research collaboration with.

Mercedes MoU
 
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Diogenese

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Didn't realise that state space models was developed by Prof Chris Eliasmith from University of Waterloo.

The very same person that Mercedes has signed an MoU for research collaboration with.

Mercedes MoU
Hi Fuz,

Now there's a bit of morphic resonance.

It was only 3 days ago that I mentioned Eliasmith:
in relation to this:

TENNs-PLEIADES: Building Temporal Kernels with Orthogonal Polynomials​

Yan Ru Pei, Olivier Coenen

https://arxiv.org/html/2405.12179v3

...

The seminal work proposing a memory encoding using orthogonal Legendre polynomials in a recurrent state-space model is the Legendre Memory Unit (LMU) [33], where Legendre polynomials (a special case of Jacobi polynomials) are used. The HiPPO formalism [11] then generalized this to other orthogonal functions including Chebyshev polynomials, Laguerre polynomials, and Fourier modes. Later, this sparked a cornucopia of works interfacing with deep state space models including S4 [12], H3 [2], and Mamba [10], achieving impressive results on a wide range of tasks from audio generation to language modeling. There are several common themes among these networks that PLEIADES differ from. First, these models typically only interface with 1D temporal data, and usually try to flatten high dimensional data into 1D data before processing [12, 37], with some exceptions [21]. Second, instead of explicitly performing finite-window temporal convolutions, a running approximation of the effects of such convolutions are performed, essentially yielding a system with infinite impulse responses where the effective polynomial structures are distorted [31, 11]. And in the more recent works, the polynomial structures are tenuously used only for initialization, but then made fully trainable. Finally, these networks mostly use an underlying depthwise structure [14] for long convolutions, which may limit the network capacity, albeit reducing the compute requirement of the network.
[33]↑Aaron Voelker, Ivana Kajić, and Chris Eliasmith.Legendre Memory Units: Continuous-time representation in recurrent neural networks.Advances in neural information processing systems, 32, 2019. [Uni of Waterloo]


Our Pleiades paper differentiates our SSM from the Legendre polynomial which Eliasmith proposed.
 
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Bravo

If ARM was an arm, BRN would be its biceps💪!

Arm has started working on solutions for SoftBank relating to Stargate but unable to provide specifics in terms of products or timelines at this time.


Arm to develop its own chips, says Stargate offers “huge potential” for “different design opportunities”​


Comments made on company’s Q1 2026 earnings call
July 31, 2025 By Charlotte Trueman

Arm is looking to develop its own chips, CEO Rene Haas said during the company’s Q1 2026 earnings call.
Seemingly confirming reports from earlier this year, Haas told analysts on the call that Arm was “continuing to explore the possibility of moving beyond our current platform into additional compute to subsystems, chiplets, and potentially full end solutions.”

ARM-based chips in developement

– TSMC
He said that the company had accelerated its investment in R&D to “ensure that these opportunities are executed successfully,” adding that owners SoftBank had expanded its IP licensing and design services agreements with Arm, and Arm was working with the Japanese conglomerate to help them build towards its “greater, broader AI vision.”
When asked if the expanded licensing and design service agreements with SoftBank related to Stargate, Haas was somewhat coy.
“At a very high level, Stargate, which is a joint investment venture between SoftBank and OpenAI, is looking to scale up to 10GW over the next number of years in terms of overall investment. That is a lot of compute, and there's a huge potential for lots of different design opportunities,” he said. “SoftBank has a very broad AI vision. We're looking to help them with that.
Again, without mentioning specific products and application spaces, you can imagine in a data center that size, running different workloads around inference training and such, and today, all of the Stargate opportunities use Arm as the core CPU.

“We have a unique opportunity to provide solutions there. So a lot of that work has now started, but we're not able to give you any specifics in terms of products or timelines,” Haas said.
Despite the news, shares in Arm fell by around eight percent after the company posted its Q1 2026 results.
Revenue for the quarter was up 12 percent year-on-year (YoY) to $1.05 billion, but missed analysts ’ expectations of $1.06bn. Of that total, royalty revenue was $585 million, up 25 percent YoY, but below the $595m projected, while licensing revenue for the quarter was $468m, down one percent YoY.
“Royalty revenue is growing across all target end markets, including smartphones, data center, automotive, and IoT,“ Haas said, adding that during the quarter, Arm had signed three additional compute subsystems (CSS) licenses with its five existing customers, which included two data center licenses.
Introduced in 2023, Arm’s Neoverse CSS simplifies and accelerates the adoption of Arm Neoverse-based technology into new compute solutions by enabling its partners to build specialized silicon more affordably and quickly than previous discrete IP solutions.
Haas also reiterated comments made by the company in July, saying the number of customers using Arm-based chips in data centers has increased 14x since 2021, while its data center customers have reached 70,000. The company said it had also seen a 12x increase in the number of startups using Arm chips during the same period.
For Q2 2026, Arm is projecting revenues of between $1.01bn - $1.11bn, with estimates again hitting $1.06bn.

 
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TheDrooben

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7für7

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Newly published patent from Digimarc in which we get a mention..........

US20250245465 LASER MARKING OF MACHINE-READABLE CODES https://patentscope.wipo.int/search/en/detail.jsf?docId=US460152523&_cid=P21-MDTM9J-81491-1

View attachment 89258 View attachment 89259 View attachment 89260


Happy as Larry


Yes… but Akida is only mentioned here as part of a list of hardware examples that could be used to implement the described algorithms. It has nothing to do with the patent itself.

It’s basically like a coach explaining to a soccerplayer that the game is called soccer and is played with balls… and then listing that you could use balls from Adidas, Umbro, or other brands…

“Still another type of processor hardware is a neural network chip, e.g., the Intel Nervana NNP-T, NNP-I and Loihi chips, the Google Edge TPU chip, and the BrainChip Akida neuromorphic SoC.”

The mention of Akida here is purely descriptive – the patent would work the exact same way without it.
 
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TheDrooben

Pretty Pretty Pretty Pretty Good
Yes… but Akida is only mentioned here as part of a list of hardware examples that could be used to implement the described algorithms. It has nothing to do with the patent itself.

It’s basically like a coach explaining to a soccerplayer that the game is called soccer and is played with balls… and then listing that you could use balls from Adidas, Umbro, or other brands…

“Still another type of processor hardware is a neural network chip, e.g., the Intel Nervana NNP-T, NNP-I and Loihi chips, the Google Edge TPU chip, and the BrainChip Akida neuromorphic SoC.”

The mention of Akida here is purely descriptive – the patent would work the exact same way without it.
The reason I posted this is it shows an increasing awareness of the capabilities of Akida......I never mentioned the patent definitely involved using Akida. The mere mention in the patent makes this worth posting IMO especially alongside the other processors mentioned

Happy as Larry
 
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The reason I posted this is it shows an increasing awareness of the capabilities of Akida......I never mentioned the patent definitely involved using Akida. The mere mention in the patent makes this worth posting IMO especially alongside the other processors mentioned

Happy as Larry
Thanks for sharing, it's a possibility which is good to see.
 
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7für7

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The reason I posted this is it shows an increasing awareness of the capabilities of Akida......I never mentioned the patent definitely involved using Akida. The mere mention in the patent makes this worth posting IMO especially alongside the other processors mentioned

Happy as Larry

Don’t worry… I just wanted to trigger haters … just kidding…

But jokes aside… I wrote that because some people just don’t read through what’s written and immediately assume that this patent has something to do with Akida. It wasn’t directed at you… more as a clarification.
 
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manny100

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Thanks for sharing, it's a possibility which is good to see.
Agree, it's good see as it demonstrates growth is underway in the Neuromorphic Edge AI industry.
Without a growing industry BRN will not do well.
If the industry grows as expected as the Tech leader we should do very well.
We will either be swallowed up by a bigger fish for our tech or we will grow into a huge business.
It all comes down to the industry growing and thriving.
 
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Innatera claims world’s first mass-market neuromorphic microcontroller for the sensor edge​

Interviews | May 21, 2025


"The Pulsar chip has a heterogenous architecture that combines analog and digital neuromorphic blocks with a traditional convolutional neural network accelerator and a RISC-V core. "
....

I really would like to know what kind of IP this "digital neuromorphic block" looks like?:unsure:

The last 4c announcement gives me some hope.....
Innatera is 100% pure competition.
There is no "hope" of them using any BrainChip IP.

They just found another way to "skin the cat" is all.
 
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Innatera is 100% pure competition.
There is no "hope" of them using any BrainChip IP.

They just found another way to "skin the cat" is all.
How does this compare to Akida is the big question ?.
 
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How does this compare to Akida is the big question ?.
My knowledge is virtually non existent on this, but my biased (but probably correct) layman's opinion is that AKIDA is on a completely different (higher) level to Innatera's technology, but in direct comparison for specific use cases (that Innatera's is used for) it's going to simply come down to which solution is "chosen".
If the OEMs want an OTS (off the shelf) solution, then Innatera are supplying the chips for that.

Our comparable tech, would possibly be AKIDA E or AKIDA Pico?..
But that's offered as IP only at this stage.
 
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