BRN Discussion Ongoing

Ian

Founding Member
@David holland
Be Quiet Season 5 GIF by Friends
 
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Frangipani

Regular
Seeing as my phone won't copy text without having a Spas Attack, which nearly caused it to sail through the window out into the street, you will all have to scroll down to the heading "influential space programs".
Now after all the tantrums and dummy spits I just need someone to say old news mate but good try. 😆

SC

Just DO NOT, I repeat, DO NOT ❌⛔📵☠️under any circumstances look here

https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-333513

… and you and your phone will be fine.

Regards,
An anonymous concerned phone welfare activist
 
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wilzy123

Founding Member
I'll take that your not confident, enjoy your invite to the secret meeting

Classic DH comment 🤡🤡🤡🤡

it's OK if you're miserable buddy... but it's not constructive or helpful if you continue to live that way. Hopefully you reach out for help.
🤡
 
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Slade

Top 20
So with all this valuable information, how long do the group feel something is going to come out,
Or are we still another year away
Calm Down Chill Out GIF
 
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manny100

Regular
Hi Rskiff
I cannot remember that but I believe he had Ericsson as one of the group of companies he used to example as the types of companies they could be working with back then.

Sean Hehir CEO did say they had been approached by a large communication company who wanted to use AKIDA technology for a purpose they had not envisaged. When you read up on 6G as envisaged by Ericsson and its use of Ai/ML and Cognitive Communications it does point in their direction as they are pushing the science in that regard.

My opinion only DYOR
Fact Finder
Hi FF,
Google Vimeo Interview with Sean Hehir.

At circa 28 min mark Sean talks about being heavily engaged with a communication company that may buy the IP. Note words heavily involved and may buy.
I think this was recorded in May'22???
If they did proceed they should be just about through the processes by now????
 
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IloveLamp

Top 20

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Frangipani

Regular
F#$k just $&÷*, $*&=ing F#$%k.

SC

I thought I took that pretty well. 😍

SC

Hi Dodgy,

Radhard memory brings me to Numem. Wonder what happened with their phase 1 using Akida. Contract end date 25/01/23. So 12 months on. I have tried today, to get on their website and can't so either my phone or they haven't paid their bills. They put out new products a few month's ago that I wanted to check but can't get on their site. They also completed an A Funding round so should still be a going concern.

SC

🤣 In case you haven’t destroyed your phone, yet, now use it to go to that Numem website again - looks like it is back up and running! Good luck with your search! 🍀

57896502-D126-4B35-99E4-B2F70E1B3052.jpeg
 
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🤣 In case you haven’t destroyed your phone, yet, now use it to go to that Numem website again - looks like it is back up and running! Good luck with your search! 🍀

View attachment 55961
Thanks mate. Maybe they needed time to get rid of the evidence 🤔

SC
 
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IloveLamp

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IloveLamp

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View attachment 55967 View attachment 55965 View attachment 55966
Will they be using the new commercially available ip of a little Aussie company by the name of BrainChip I wonder or will they wait a few more years to get lohi on board lol.
 
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Good to see the Open Neuromorphic community have us included, as they should. :)

These are also the sorts of people we need testing and pushing our Akidas limits and capabilities.

About the community below and our info after that with some related publications, which I believe we've already sourced independently previously from memory.

Could be a resource checking in on every so often for any snippets.



Open Neuromorphic
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About​

Discover Open Neuromorphic (ONM), a collaborative community for neuromorphic computing enthusiasts. Explore tools, frameworks, and educational content to fuel your passion.
Open Neuromorphic is created by a loose collective of open source collaborators across academia, industry and individual contributors. Most of us have never met in person before but have started contributing to a common or each other’s projects!
What connects us is the love for building tools that can be used in the neuromorphic community and we want to share ownership of this vision. If you feel like that resonates with you, please don’t hesitate to get in touch!
Open Neuromorphic (ONM) provides the following things:
  1. A curated list of software frameworks to make it easier to find the tool you need.
  2. A platform for your code. If you wish to create a new repository or migrate your existing code to ONM, please get in touch with us.
  3. Educational content to get you started in the neuromorphic world.
  4. Events about neuromorphic research and software, with contributions from both academia and industry.
Projects that we list here can fall into this non-exclusive list of categories:
  • Spiking Neural Networks (SNNs) training and/or inference, for both ML and neuroscience application.
  • Event-based sensors data handling.
  • Digital hardware designs for neuromorphic applications.
  • Mixed-signal hardware designs for neuromorphic applications.
Get in touch with us if you wish to give a talk, write an article or to know more about the neuromorphic world.


Akida - BrainChip​

Learn about BrainChip's neuromorphic hardware: Akida

Akida At A Glance​

Announced Date: 2023-01-29
Release Date: 2023-01-29
Status: Released
Chip Type: Digital
Neurons: Configurable
Synapses: 8-Mb SRAM
On-Chip Learning: true
Power: ~30 mW
Software: MetaTF
Applications: Smart sensing, one-shot learning
akida_hu2788f167cc74c288c55f420fd788abf1_382910_0x200_resize_q90_h2_lanczos_3.webp

BrainChip's Akida is an ultra-low-power neuromorphic processor inspired by the brain's neural architecture. It accelerates complex AI at the edge through event-based processing, on-chip learning abilities, and support for advanced neural networks like CNNs, RNNs & custom Temporal Event-based Nets.

Developed By:​

brainchip_hufeac4cdbe97fe0e59b6a261cf2051292_6462_250x0_resize_q90_h2_lanczos_3.webp

BrainChip
company/brainchip-holdings-limited/ @BrainChip_inc BrainChip
Official Product Page

Overview​

Inspired by the human brain’s neural architecture, Akida aims to deliver high-performance artificial intelligence capabilities at the edge while being extremely energy efficient.
The Akida processor is designed to accelerate neural networks including convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs) and Vision Transformers (ViTs) directly in hardware. A key feature is its support for a novel neural network architecture called Temporal Event-based Neural Nets (TENNs) which are optimized for processing complex time-series data efficiently.
Akida employs an event-based processing approach where computations are only performed when new sensory input is received, dramatically reducing the number of operations. This also enables event-based communication between processor nodes without CPU intervention. The architecture further supports on-chip learning, allowing models to adapt without having to connect to the cloud.
The second generation Akida platform adds capabilities such as support for 8-bit weights/activations, improved vision transformer acceleration, multi-pass sequential processing, and configurable local scratchpads to optimize memory access. It is designed to run larger neural networks across multiple chips while minimizing latency.
Akida leverages standard machine learning frameworks like TensorFlow and development platforms like Edge Impulse for model training and deployment. BrainChip also provides complementary software tools like MetaTF to optimize models for the Akida hardware. Pre-built Akida-compatible models are also offered through a model zoo.
Akida targets applications spanning industrial automation, automotive, healthcare, consumer electronics and more. Use cases include predictive maintenance, in-cabin monitoring, vital sign prediction, home automation, surveillance and more. Its efficiency and on-device learning abilities aim to enable a new class of continuously adaptive, secure and private AI implementations at the edge.

Related publications​

DateTitleAuthorsVenue/Source
August 2023Low Power & Low Latency Cloud Cover Detection in Small Satellites Using On-board Neuromorphic ProcessorsChetan Kadway; Sounak Dey; Arijit Mukherjee; Arpan Pal; Gilles BézardIJCNN 2023
August 2023Neuromorphic Medical Image Analysis at the EdgeEbba Bratman, Lucas DowMaster’s course project
October 2022Detection of facial emotions using neuromorphic computationTeodoro Álvarez-Sánchez, Jesús A. Álvarez-Cedillo, Roberto Herrera-Charles
 
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Hi FF,
Google Vimeo Interview with Sean Hehir.

At circa 28 min mark Sean talks about being heavily engaged with a communication company that may buy the IP. Note words heavily involved and may buy.
I think this was recorded in May'22???
If they did proceed they should be just about through the processes by now????

"At circa 28 min mark Sean talks about being heavily engaged with a communication company that may buy the IP. Note words heavily involved and may buy.
I think this was recorded in May'22???
If they did proceed they should be just about through the processes by now????"


200w.gif



"The layoffs at Ericsson will impact 8% of its workforce of 105,529 staff worldwide. The move is part of its cost-cutting measures, the company memo reads. A spokesperson said most layoffs would take effect in the first half of 2023 but could extend into 2024"

So maybe this is the IP deal that got shelved, by the "unknown" Company?
But if so, looks like there's still some Life in it??....
 
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Sirod69

bavarian girl ;-)
Parag Beeraka wrote AND Anil Mankar liked it 🥰😘

We are excited to share that we have been collaborating with several partners to bring real-world use cases for machine learning at the edge. Our work spans natural language processing to vision and we are thrilled to showcase some of our successes. Check out case studies from Plumerai, Himax Technologies, Inc., Grovety Inc., and Sensory, Inc. to see how we are enabling machine learning at the edge. Follow the link to learn more:

 
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Tothemoon24

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IMG_8289.jpeg






 
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