BRN Discussion Ongoing

Frangipani

Top 20
New video about the TENNs Eye-Tracking Model powered by Akida:


C8CBB322-07A1-4FE5-9534-E994378FFC82.jpeg





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43642240-59A6-4B07-89C9-34189A816B6B.jpeg



But why did our company choose to end this video about “BrainChip’s ultra-efficient Eye Tracking model powered by Akida” using TENNs by showing excerpts from a video about the epileptic seizure-predicting NEXA smart glasses by Onsor (without naming them or referring to that specific healthcare use case) 👇🏻 that use an AKD1500 chip?! 🤔

While the words accompanying the video’s last 13 seconds are catchy
(“BrainChip makes smart glasses smarter. Integrate Akida into your eye-tracking solution. Start building with BrainChip.”), showing smart glasses using Akida 1.0 technology doesn’t make sense in this context, given TENNs cannot run on Akida 1.0…

21107947-7427-47F0-ABDD-B5BFDC4360F6.jpeg
 
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Diogenese

Top 20
How about all of us agree on a really cool product idea that isn't in the market already, that leverages Akida’s neuromorphic edge AI capabilities?

Then we can each get one day's worth of access to the Akida cloud at $1 a day and pass on any learnings or development tasks to the next forum member on the list, so they can keep working on it on their day's worth of access.

Here's an idea that I think could work.

SnackSentinel - Saving the world from over-eating, one Tim Tam at a time.

What it does:

Smart pantry/fridge clip that notices hand movement + time + day + patterns.

Imagine you're trying to sneak some snacks at 11pm, it makes a really loud alarm sound or it issues stern voice commands such as: “Do you really need that big piece of cheesecake, Maureen?” or "No more beer for you Roger".

Use cases:
  • Weight loss support
  • Behavioral therapy
  • Impulse control for ADHD
We'll need to use our collected data to label things like:
  • “Snack attempt”
  • “Normal door use”
  • “Repeated snack pattern” (e.g., 3 visits in 15 minutes).

Should be pretty easy since I go to the fridge quite a lot over the course of a day.








Well, first of all, we have to develop the model which requires millions of repetitions of the action to be detected, so I'll do that part.
 
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Diogenese

Top 20
Well, first of all, we have to develop the model which requires millions of repetitions of the action to be detected, so I'll do that part.
Bugger! I just remembered - Akida is one-shot learning!
 
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Deadpool

Did someone say KFC
That's me in the back, in that little black dress.
You in that dress? The plot twist no one saw coming, see you at Mardi Gras darling, I,ll be the one wearing fishnets.
 
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How about all of us agree on a really cool product idea that isn't in the market already, that leverages Akida’s neuromorphic edge AI capabilities?

Then we can each get one day's worth of access to the Akida cloud at $1 a day and pass on any learnings or development tasks to the next forum member on the list, so they can keep working on it on their day's worth of access.

Here's an idea that I think could work.

SnackSentinel - Saving the world from over-eating, one Tim Tam at a time.

What it does:

Smart pantry/fridge clip that notices hand movement + time + day + patterns.

Imagine you're trying to sneak some snacks at 11pm, it makes a really loud alarm sound or it issues stern voice commands such as: “Do you really need that big piece of cheesecake, Maureen?” or "No more beer for you Roger".

Use cases:
  • Weight loss support
  • Behavioral therapy
  • Impulse control for ADHD
We'll need to use our collected data to label things like:
  • “Snack attempt”
  • “Normal door use”
  • “Repeated snack pattern” (e.g., 3 visits in 15 minutes).

Should be pretty easy since I go to the fridge quite a lot over the course of a day.








Sorry Bravo, but no ones going to tell me I can't gave more beer.🍻🍻
 
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Sorry Bravo, but no ones going to tell me I can't gave more beer.🍻🍻
Sorry that should read "can't have". Guess I made a BRN announcement mistake. My apologies.
 
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Diogenese

Top 20
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HopalongPetrovski

I'm Spartacus!
You in that dress? The plot twist no one saw coming, see you at Mardi Gras darling, I,ll be the one wearing fishnets.
I thought everyone was already aware that I am a smoking hot sexbot with an insatiable lust for fat, bald and irascible old men who have an irrational love for BrainChip. Come, let me oil up that hair bereft noggin you reside in.

 
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Tothemoon24

Top 20
Interesting read from Toshiba.
Didn’t we have a long bow link at some point

IMG_1368.jpeg


IMG_1367.jpeg


More to read here ;
 
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TheDrooben

Pretty Pretty Pretty Pretty Good
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Jimmy17

Regular
How about all of us agree on a really cool product idea that isn't in the market already, that leverages Akida’s neuromorphic edge AI capabilities?

Then we can each get one day's worth of access to the Akida cloud at $1 a day and pass on any learnings or development tasks to the next forum member on the list, so they can keep working on it on their day's worth of access.

Here's an idea that I think could work.

SnackSentinel - Saving the world from over-eating, one Tim Tam at a time.

What it does:

Smart pantry/fridge clip that notices hand movement + time + day + patterns.

Imagine you're trying to sneak some snacks at 11pm, it makes a really loud alarm sound or it issues stern voice commands such as: “Do you really need that big piece of cheesecake, Maureen?” or "No more beer for you Roger".

Use cases:
  • Weight loss support
  • Behavioral therapy
  • Impulse control for ADHD
We'll need to use our collected data to label things like:
  • “Snack attempt”
  • “Normal door use”
  • “Repeated snack pattern” (e.g., 3 visits in 15 minutes).

Should be pretty easy since I go to the fridge quite a

Sorry Bravo, but no ones going to tell me I can't gave more beer.🍻🍻
Fortunately whisky is not kept in the fridge eh
 
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They couldn’t even arrange a piss up in a brewery 😂
To be fair they may very well be able to organise the piss up.

The problem is the board would choose not to announce it so no one would turn up!...
 
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Esq.111

Fascinatingly Intuitive.
Interesting read from Toshiba.
Didn’t we have a long bow link at some point

View attachment 89394

View attachment 89393

More to read here ;
Evening Tothemoon24 ,

Loose connection dating back to 15th March 2023 ,

Relating to a company announcement on a new partner , IPSOLON , thay also let slip Toshiba , Cisco & Linaro , then quickly deleted the last three.

Someone may have captured said announcement , before it was eddited.

1754558306133.jpeg


Regards,
Esq.
 
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Evening Tothemoon24 ,

Loose connection dating back to 15th March 2023 ,

Relating to a company announcement on a new partner , IPSOLON , thay also let slip Toshiba , Cisco & Linaro , then quickly deleted the last three.

Someone may have captured said announcement , before it was eddited.

View attachment 89399

Regards,
Esq.
This would be the screenshot mate care of @stuart888


 
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Diogenese

Top 20
No wonder ASX is dirty on tech (no relation):

https://www.abc.net.au/news/2025-08...boe-as-tpg-mishap-adds-10-year-woes/105623428
...

In 2015, the ASX began scouting for a replacement to the ageing technology it used to settle trades on the exchange.

Two years later, it created global headlines. In a market abuzz with talk of cryptocurrency and its open source ledger system, the ASX announced it would build the world's first industrial scale blockchain for financial services applications.

The timeline was always ambitious. It was supposed to be online by 2020.

But the project became ever-more complex as fights developed between various information providers about how they would interact with the new system.

Shares do not simply change hands between buyers and sellers — there are share registries, custodians and a host of other players, many of whom became concerned the new system would steal their business.

By the time the fifth delay to the rollout time was announced, it was obvious the project was on the rocks. At the end of 2022, it was canned, forcing the ASX to announce a $250 million write-off.

Brokers and investment houses had spent vast amounts too, replacing their systems to integrate with the blockchain dream that ultimately turned into a blocked drain.

Dominic Stevens, the ASX chief executive who commissioned the project, had left at the start of the year, leaving then chair Damian Roche to clean up the mess and to appoint Accenture to independently review what had gone wrong.

"On behalf of ASX, I apologise for the disruption experienced in relation to the CHESS replacement project over a number of years," he said at the time.


The original story was about letting the a Chicago mob set up a rival stock exchange to break ASX monopoly after a monumental cock up ...

" ASX faces losing virtual monopoly as TPG bungle adds to a decade of woes "

On Wednesday, the ASX confused a listed company with a similarly-named foreign owned private equity group that was engaged in a huge takeover.

The mistake resulted in TPG Telecom shares plummeting 5 per cent, wiping $400 million from its market value, even though it had nothing to do with the $645 million takeover of automotive software group Infomedia.

If the original mix-up was bad, the inability of the ASX to rectify the situation turned it into a debacle, as traders pounded TPG Telecom's stock for hours.

And it's unlikely to be the last the operator hears from TPG, with the telco understood to be considering its legal options.



So maybe we are moving to the Chicago exchange ... ?
 
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dippY22

Regular
What exactly do you regard is the catalyst for increasing volume?
Ah,....Hop. Nice try.

Growing interest. It will be growing interest in Brainchip that increases volume.

Actually I have no idea what the catalyst will be. I just know the volume will be huge.
 
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CHIPS

Regular
Thanks mate. Still can't read it but I do need new glasses. Missus tried too but could only get half of it. Will keep an eye on Booz Allen. Interesting stuff.


SC

Even with better glasses, you won't be able to read it, I guess. I can't read all of it either. I could not get a better picture.
 
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7für7

Top 20
Thanks mate. Still can't read it but I do need new glasses. Missus tried too but could only get half of it. Will keep an eye on Booz Allen. Interesting stuff.


SC
ChatGPT was able to read it



TOP TITLE:

C2BMC

Command and Control, Battle Management, and Communications

Subtitle (below C2BMC):

The Command and Control, Battle Management, and Communications (C2BMC) program is the hub of the layered Missile Defense System. It is a vital operational system that enables the President, Secretary of Defense and Combatant Commanders at strategic, regional and operational levels to systematically plan missile defense operations, to collectively see the battle develop, and to dynamically manage shielded networked sensors and weapons systems to achieve global and regional mission objectives.


TOP COMMAND STRIP (color-coded):
  • NMCC
  • USSPACECOM
  • USNORTHCOM
  • USINDOPACOM
  • USEUCOM
  • USCENTCOM

MAIN TITLE (center of the image):

THE SYSTEM OF ELEMENTS


DEFENSE SEGMENTS (left to right):

BOOST

Defense Segment
(Shows missiles launching)


ASCENT / MIDCOURSE

Defense Segment
(Depicts missile intercept systems)
  • GBI
    Ground-Based Interceptor
  • SM-3 IIA
    Standard Missile
  • SM-3 IA/IB
    Standard Missile
  • AEGIS
    SHIP & ASHORE
    Ballistic Missile Defense

TERMINAL

Defense Segmen
  • THAAD
    Terminal High Altitude Area Defense
  • SM-6
    Standard Missile
  • AEGIS
    (Standard Missile)
  • PAC-3
    Patriot Advanced Capability
BOTTOM SECTION: SENSORS


Title:
SENSORS

Descriptive Text:

An effective layered defense relies on timely sensor information provided by space and ground-based assets. Sensors provide critical tracking and discrimination data to help warfighters see the threat, track it and engage it effectively.

Sensor Types (with icons):

  • SATELLITE SURVEILLANCE SYSTEMS
  • UPGRADED EARLY WARNING RADARS
  • FORWARD-BASED RADARS
  • SPY RADARS
  • DISCRIMINATING RADARS
 
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Thesis just out of KTH.

Haven't downloaded to read it but just the abstract was enough for me on the confirmation of how just our AKD1000 First Gen stacked up and clearly showed its "edge" in the edge space over NVIDIA GPU.

Think it's a given that as complexity increases the processing power shifts however the power usage is still an advantage.

Be interesting to see how it goes when they focus on fully customised models.

Would also be great to see what step up AKD1500 / Gen 2 / TENNs etc is capable of in a comparison given this was just Gen 1.




Comparison of Akida Neuromorphic Processor and NVIDIA Graphics Processor Unit for Spiking Neural Networks

Chemnitz, Carl​

KTH, School of Electrical Engineering and Computer Science (EECS).

Ermis, Malik​

KTH, School of Electrical Engineering and Computer Science (EECS).

2025 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Jämförelse av neuromorfisk processor Akida och NVIDIA grafikkort för Spiking Neural Networks (Swedish)

Abstract [en]​


This thesis investigates the latency, throughput and energy efficiency of the BrainChip Akida AKD1000 neuromorphic processor compared to a NVIDIA GeForce GTX 1080 when running two different spiking neural network models on both hardwares. Spiking neural networks is a subset of neural networks that are specialized for neuromorphic processor. The first model is a simple image classification model (GXNOR on MNIST), and the second is a more complex object detection model (YOLOv2 on Pascal VOC). The models were trained and quantized to 2-bit and 4-bit weight precision, respectively, enabling spiking execution both on Akida AKD1000 and on GTX 1080, for the GPU CUDA was used. Results show that Akida achieved significant reductions in energy consumption and clock cycles for both models, consistent with prior findings within the field. Specifically, for the simple classification model the AKD1000 achieved 99.5 % energy reduction with 76.7 % faster inference times, despite having a clock rate 91.5 % slower than the GPU. However, for the more complex object detection model, the Akida took 118.1 % longer per inference, while reducing the energy expenditure by 96.0 %. For the MNIST model the AKD1000 showed no correlation in both cycles & time and cycle & energy. While for the YOLOv2 model it had a 0.2 correlation for both previous mentioned ratios. Suggesting that as model complexity increases, the Akida’s behaviour converges toward the GPU’s linear correlation patterns. In conclusion, the AKD1000 processor demonstrates clear advantages for low-power, edge-oriented applications where latency and efficiency are critical. However, these benefits diminish with increasing model complexity, where GPUs maintain superior scalability and performance. Due to limited documentation of the chosen models, a 1-to-1 comparison was not possible. Future work should focus on fully customized models to further explore the dynamics.
 
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