BRN Discussion Ongoing

[Mea culpa]

Just one day it would be nice to get a decent $$$$ announcement and for a second I thought this was it. Why did I have to open it and ruin my day

View attachment 80090


View attachment 80092

hot crapper, what’s that? The only hot crapper I know was an attractive policewoman I dated for half an hour back in the’60’s… No handcuffs unfortunately and as usual I was given a warning.

 

[manny100]

BeEmotion enjoy a place as an option on our VVDN Edge Box.
" Gesture recognition by BeEmotion , an innovator at the intersection of AI and human behavior that provides cutting-edge solutions to enhance interaction, prevent accidents, and bring enjoyment to the everyday use of technology."
See VVDN Edge Box Ann below dated 8th Jan'25:
News Release
On the 6th January 2024 BRN issued a news release of the Brainchip and NVISO (now Be Emotion.ai) partnership.
News Release
See the BeEmotion.ai website below:
BeEmotion
Given BeEmotion.ai, Quantum Ventura (QV) and Ai Labs are all options on our VVDN Edge Box and the latter 2 already have products it is reasonable to expect BeEmotion is next.
Also apart from BeEmotionai, QV and Ai Labs Sean said in the new release:
" “The Akida Edge Box is a great platform for running AI in standalone edge environments where footprint, cost and efficiency is critical, while not compromising performance,” said Sean Hehir, BrainChip CEO. “We look forward to announcing more partners developing edge AI for their customers’ specific use cases and more importantly, we look forward to the ideas these companies will bring to life with the Akida Edge AI Box.”"
My bold above. Customers can develop models via Edge Impulse and evaluate them on DeGirum.
Brainchip has made it 'childs play' to develop and release products - how good is that.

 

[DingoBorat]

BeEmotion enjoy a place as an option on our VVDN Edge Box.
" Gesture recognition by BeEmotion , an innovator at the intersection of AI and human behavior that provides cutting-edge solutions to enhance interaction, prevent accidents, and bring enjoyment to the everyday use of technology."
See VVDN Edge Box Ann below dated 8th Jan'25:
News Release
On the 6th January 2024 BRN issued a news release of the Brainchip and NVISO (now Be Emotion.ai) partnership.
News Release
See the BeEmotion.ai website below:
BeEmotion
Given BeEmotion.ai, Quantum Ventura (QV) and Ai Labs are all options on our VVDN Edge Box and the latter 2 already have products it is reasonable to expect BeEmotion is next.
Also apart from BeEmotionai, QV and Ai Labs Sean said in the new release:
" “The Akida Edge Box is a great platform for running AI in standalone edge environments where footprint, cost and efficiency is critical, while not compromising performance,” said Sean Hehir, BrainChip CEO. “We look forward to announcing more partners developing edge AI for their customers’ specific use cases and more importantly, we look forward to the ideas these companies will bring to life with the Akida Edge AI Box.”"
My bold above. Customers can develop models via Edge Impulse and evaluate them on DeGirum.
Brainchip has made it 'childs play' to develop and release products - how good is that.

Yeah that's good, but they need to have had developed "in cabin" products by early "last" year.

All new cars manufactured in Europe since July "last" year, have had to incorporate "other" solutions.

It's not as easy, to get traction in a particular market, when someone else has already filled the slot.

It would be interesting to know, what solutions various car manufacturers are using, or whether they've been given a "grace" period, for implementation.

 

[DingoBorat]

Yeah that's good, but they need to have had developed "in cabin" products by early "last" year.

All new cars manufactured in Europe since July "last" year, have had to incorporate "other" solutions.

It's not as easy, to get traction in a particular market, when someone else has already filled the slot.

It would be interesting to know, what solutions various car manufacturers are using, or whether they've been given a "grace" period, for implementation.

Looks like Anyverse, have developed a/the platform for testing of various systems..

Exploring the Technology Behind In-Cabin Monitoring Systems

Discover the technology powering in-cabin monitoring systems. Learn about sensors, cameras, and AI used to enhance passenger safety.

anyverse.ai

Virtual validation data platform for in-cabin monitoring AI | Anyverse

Anyverse offers OEMs, integrators, and suppliers the only shared interface to generate high-quality validation datasets in just a few clicks.

anyverse.ai

 

[supersonic001]

All good Hopalong
My original post, wasn't intended as a statement of fact, just my "feel" of the name, I guess that's why I used that word..

"Although I would hardly call the B17 flying fortress, B29 super fortress or the B52 strato fortress "passenger jet thing's"

View attachment 79932

View attachment 79933
View attachment 79934

You're right, absolutely nothing passenger jetty about "those" planes


"The prototype B-17, with the Boeing factory designation of Model 299, was designed by a team of engineers led by E. Gifford Emery and Edward Curtis Wells, and was built at Boeing's own expense.[12] It combined features of the company's experimental XB-15 bomber and 247 transport."

For anyone that went to the Bicentennial Air Show 1988 Richmond Airforce base NSW, one of these B52 babies flew all the way from Guam US airforce base, came across the Blue Mountains heading east, banked around and flew back west, heading back to Guam in a single flight

Would have been phenomenal to see it on the ground and walk up to it, but the wing span and supporting bogeys simply too wide for the Aussie airforce base hosting the show……

One day …. !

 

[manny100]

BeEmotion enjoy a place as an option on our VVDN Edge Box.
" Gesture recognition by BeEmotion , an innovator at the intersection of AI and human behavior that provides cutting-edge solutions to enhance interaction, prevent accidents, and bring enjoyment to the everyday use of technology."
See VVDN Edge Box Ann below dated 8th Jan'25:
News Release
On the 6th January 2024 BRN issued a news release of the Brainchip and NVISO (now Be Emotion.ai) partnership.
News Release
See the BeEmotion.ai website below:
BeEmotion
Given BeEmotion.ai, Quantum Ventura (QV) and Ai Labs are all options on our VVDN Edge Box and the latter 2 already have products it is reasonable to expect BeEmotion is next.
Also apart from BeEmotionai, QV and Ai Labs Sean said in the new release:
" “The Akida Edge Box is a great platform for running AI in standalone edge environments where footprint, cost and efficiency is critical, while not compromising performance,” said Sean Hehir, BrainChip CEO. “We look forward to announcing more partners developing edge AI for their customers’ specific use cases and more importantly, we look forward to the ideas these companies will bring to life with the Akida Edge AI Box.”"
My bold above. Customers can develop models via Edge Impulse and evaluate them on DeGirum.
Brainchip has made it 'childs play' to develop and release products - how good is that.

To be an option on the VVDN Edge Box BeEmotion would have has to have had completed their software prior to the BRN Jan'25 ann.
It looks as though we are just waiting for BeEmotion to make an announcement of client use.

 

[Fredsnugget]

For anyone that went to the Bicentennial Air Show 1988 Richmond Airforce base NSW, one of these B52 babies flew all the way from Guam US airforce base, came across the Blue Mountains heading east, banked around and flew back west, heading back to Guam in a single flight

Would have been phenomenal to see it on the ground and walk up to it, but the wing span and supporting bogeys simply too wide for the Aussie airforce base hosting the show……

One day …. !

They are impressive to see on the ground but they were even better when they were circling above us in the Ghan waiting for orders to unleash hell and save our arses. They were just dots in the sky but you knew what they could do

 

[HopalongPetrovski]

For anyone that went to the Bicentennial Air Show 1988 Richmond Airforce base NSW, one of these B52 babies flew all the way from Guam US airforce base, came across the Blue Mountains heading east, banked around and flew back west, heading back to Guam in a single flight

Would have been phenomenal to see it on the ground and walk up to it, but the wing span and supporting bogeys simply too wide for the Aussie airforce base hosting the show……

One day …. !

Have to travel to RAAF Tindal (near Katherine in the NT) where they can land and take off and which is being upgraded to host a contingent into the future. Although given the current political instability in the White house and elsewhere nothing has much certainty these days.

 

[manny100]

Was this missed from CES 25?
" BrainChip’s TENNs (Temporal Event Based Neural Nets) can deliver 100x compression and performance gain without compromising accuracy which it forsees as a disruptive force to streamline the migration to Hybrid Edge AI computing."

CES 2025

Check back frequently for updates, as we’ll be adding new information throughout CES 2024 and beyond.

brainchip.com

This could easily position BrainChip as a key player in the evolution of hybrid AI computing.
Advantages include efficiency, power savings, real time, more privacy and security and lower costs via decreased reliance on the cloud.
Also our neuromorphic core supports scalable AI solutions, making it easier to integrate edge and cloud computing seamlessly. This allows businesses to adapt to varying workloads and optimize resource allocation.
This is BRN expanding its footprint. No standing still.

 

[IloveLamp]

#riscv #spacecomputing #riscvinspace | Frontgrade Gaisler

Don't miss out the opportunity to be part of the growing RISC-V in Space community! 1000 followers already! Follow the RISC-V in Space page on LinkedIn to…

www.linkedin.com

 

[CrabmansFriend]

Maybe I have missed it, but has anyone found out already which FPGA provider Brainchip‘s IP has been demoed on?
(I‘m hoping for AMD‘s Xilinx, but Intel‘s Altera would be nice too …)

 

[Guzzi62]

Maybe I have missed it, but has anyone found out already which FPGA provider Brainchip‘s IP has been demoed on?
(I‘m hoping for AMD‘s Xilinx, but Intel‘s Altera would be nice too …)

It's shown in manny100 link 2 posts up what they demoed, in the link:

1:
LLMs + RAG Demo

How we’re advancing large language models (LLMs) with Retrieval-Augmented Generation (RAG) for smarter, real-time AI applications.


2:
Anomaly Detection Demo

Our latest anomaly detection solution running on Raspberry Pi 5. This versatile demo targets multiple verticals, including Industrial IoT, manufacturing, healthcare (wearable devices), cybersecurity, fraud detection, and more.


3:
Building ML Models with
Edge Impulse

Hands-on demos with Edge Impulse, demonstrating how easy it is to build and deploy custom machine learning models directly on the Akida platform.

CES 2025

Check back frequently for updates, as we’ll be adding new information throughout CES 2024 and beyond.

brainchip.com

 

[CrabmansFriend]

Maybe my above question was not formulated clearly enough:

I would like to know on which company‘s FPGA chip aka hardware (e.g. Xilinx, Altera, Lattice Semiconductor, Microchip, …) were used for the „software/algorithm/IP“ demos (the ones that didn’t run on a Akida 1000 or similar).

 

[7für7]

So long text… but…

My new favorite Mercedes is finally here: the most intelligent and most… | Ola Kaellenius | 188 comments

My new favorite Mercedes is finally here: the most intelligent and most efficient we’ve ever made. We launched it in the city of Rome, Italy, a place as… | 188 comments on LinkedIn

www.linkedin.com

 

[manny100]

Possibly been posted before.
See the link to the paper written by Tata. Co Authored by Sounak Dey a Tata Senior Scientist on wearables/implant transforming the diagnosis and treatment of cardiac disorders below.
" ... This system efficiently manages ECG classification tasks, greatly reducing computational complexity without compromising accuracy. Furthermore, Banerjee et al.[96]optimized SNNs for ECG classification in wearable and implantable devices such as smartwatches and pacemakers. Their approach in designing both reservoir-based and feed-forward SNNs, and integrating a new peak-based spike encoder, has led to significant enhancements in network efficiency. ..."
" ... Using these state-of-theart techniques, medical practitioners may better comprehend heart issues 67 , allowing for earlier intervention and more successful treatment regimens. Combining imaging technologies, molecular diagnostics 68 , and ECG analysis offers a viable path toward transforming the diagnosis and treatment of cardiac disorders69, eventually leading to better patient outcomes. ..."
I do not need to state how huge transforming the diagnosis and treatment of cardiac disorders via a wearable or implant would be for both Tata and Brainchip.
(PDF) An SNN Based ECG Classifier For Wearable Edge Devices
I doubt Tata would only be working on one Health wearable.
Also as we know Tata already have a patent on ' gesture classification' for IOT. See link below:
https://www.linkedin.com/posts/soun...chip-akida-activity-7305909010166071296-u0f4/

 

[Diogenese]

Maybe I have missed it, but has anyone found out already which FPGA provider Brainchip‘s IP has been demoed on?
(I‘m hoping for AMD‘s Xilinx, but Intel‘s Altera would be nice too …)

Hi Crabman,

Hadn't given it any thought, although we have used Xilinx in the past.

AMD Versal has been developed for AI:

https://www.xilinx.com/content/dam/...s/xilinx-versal-ai-compute-solution-brief.pdf

The Versal AI Core series solves the unique and most difficult problem of AI inference—compute efficiency—by coupling ASIC-class compute engines (AI Engines) together with flexible fabric (Adaptable Engines) to build accelerators with maximum efficiency for any given network, while delivering low power and low latency. Through its integrated shell—enabled by a programmable network on chip and hardened interfaces— Versal SoCs are built from the ground up to ensure streamlined connectivity to data center compute infrastructure, simplifying accelerator card development.

AI Engines
> Tiled array of vector processors, flexible interconnect, and local memory enabling massive parallelism
> Up to 133 INT8 TOPS with the Versal AI Core VC1902 device, scales up to 405 INT4 TOPS in the portfolio
> Compiles models in minutes based on TensorFlow, PyTorch, and Caffe using Python or C++ APIs
> Ideal for neural networks ranging from CNN, RNN, and MLP; hardware adaptable to optimize for evolving algorithms

I'm out of my depth here, but what is a puzzle to me is that Akida/TENNs has unique NPU architecture, so a pre-baked arrangement might not provide an accurate simulacrum. Maybe we need a more freestyle FPGA so we can build our own NPUs?

 

[CrabmansFriend]

Hi Crabman,

Hadn't given it any thought, although we have used Xilinx in the past.

AMD Versal has been developed for AI:

https://www.xilinx.com/content/dam/...s/xilinx-versal-ai-compute-solution-brief.pdf

The Versal AI Core series solves the unique and most difficult problem of AI inference—compute efficiency—by coupling ASIC-class compute engines (AI Engines) together with flexible fabric (Adaptable Engines) to build accelerators with maximum efficiency for any given network, while delivering low power and low latency. Through its integrated shell—enabled by a programmable network on chip and hardened interfaces— Versal SoCs are built from the ground up to ensure streamlined connectivity to data center compute infrastructure, simplifying accelerator card development.

View attachment 80162


AI Engines
> Tiled array of vector processors, flexible interconnect, and local memory enabling massive parallelism
> Up to 133 INT8 TOPS with the Versal AI Core VC1902 device, scales up to 405 INT4 TOPS in the portfolio
> Compiles models in minutes based on TensorFlow, PyTorch, and Caffe using Python or C++ APIs
> Ideal for neural networks ranging from CNN, RNN, and MLP; hardware adaptable to optimize for evolving algorithms

I'm out of my depth here, but what is a puzzle to me is that Akida/TENNs has unique NPU architecture, so a pre-baked arrangement might not provide an accurate simulacrum. Maybe we need a more freestyle FPGA so we can build our own NPUs?

Thanks for your input. Basically I have no real idea of how an FPGA internally really works. I always imagined some basic I/O (Ram, Network etc.) and a big Lego-like configurable part (+ maybe some kind of Cache).

In the end I‘m by far not knowledgeable enough to estimate which vendor or which product series might be a good fit for running Akida IP.

I‘m just curious about finding out if Akida IP could be run on a potentially wide spread FPGA flavor or if something more „niche“ might be required.

 

[Diogenese]

Thanks for your input. Basically I have no real idea of how an FPGA internally really works. I always imagined some basic I/O (Ram, Network etc.) and a big Lego-like configurable part (+ maybe some kind of Cache).

In the end I‘m by far not knowledgeable enough to estimate which vendor or which product series might be a good fit for running Akida IP.

I‘m just curious about finding out if Akida IP could be run on a potentially wide spread FPGA flavor or if something more „niche“ might be required.

FPGAs are quite inefficient for a commercial product because the architecture is not optimize, and includes a lot of unutilized circuitry which also makes them a more expensive solution.

The main use of FPGAs would be for proof of concept/demonstration.

An Akida compatible FPGA would be one with an adequate number of appropriate components and function blocks to enable the required Akida NPUs to be configured, (which is a circular definition).

 

[Fullmoonfever]

FPGAs are quite inefficient for a commercial product because the architecture is not optimize, and includes a lot of unutilized circuitry which also makes them a more expensive solution.

The main use of FPGAs would be for proof of concept/demonstration.

An Akida compatible FPGA would be one with an adequate number of appropriate components and function blocks to enable the required Akida NPUs to be configured, (which is a circular definition).

Also @CrabmansFriend

Way out of my tech depth but when I did a skim around Prophesee and FPGA compatibility, the project below comes up on GitHub and also a lot of the info on their site and Framos etc all appear to primarily lead back to AMD boards.

Given our blurb on the EW25 demo states we are using the EVK4 Dev Camera and Prophesee support site says the following to a question on the EVK4 vs Kria starter kit, is it given we are using a standalone AMD FPGA via PC?

https://support.prophesee.ai/portal/en/community/topic/d

1. EVK4 is a USB camera that connects directly to a PC, making it ideal for exploring event-based vision, experimenting with sensor tuning, and performing data acquisitions.

Our release:

BrainChip Demonstrates Event-based Vision at Embedded World 2025

BrainChip Demonstrates Event-based Vision at Embedded World 2025

www.businesswire.com

"gesture recognition using the Akida 2 FPGA platform in conjunction with the Prophesee EVK4 development camera."

GitHub - prophesee-ai/fpga-projects: RTL deliveries of the Prophesee Kria project, Prophesee's IP and associated test benches

RTL deliveries of the Prophesee Kria project, Prophesee's IP and associated test benches - prophesee-ai/fpga-projects

github.com

https://www.framos.com/en/?s=Fpga&asp_active=1&p_asid=5&p_asp_data=1&filters_initial=1&filters_changed=0&wpml_lang=en&qtranslate_lang=0&woo_currency=USD&current_page_id=205788

 

[CrabmansFriend]

FPGAs are quite inefficient for a commercial product because the architecture is not optimize, and includes a lot of unutilized circuitry which also makes them a more expensive solution.

The main use of FPGAs would be for proof of concept/demonstration.

An Akida compatible FPGA would be one with an adequate number of appropriate components and function blocks to enable the required Akida NPUs to be configured, (which is a circular definition).

Regarding inefficiency: you‘re absolutely right and even more so if we only consider energy restricted devices or applications.

But the more I‘am reading about the current trends in the semiconductor space (especially chiplets and packaging memory on top of logic etc.) and the increasing statements in industry interviews about the breakneck speed regarding AI/ML development in general and how fast new approaches/algorithms get established, I started wondering if we might see some transition period (on the inference side), at least in areas where energy consumption is not a (primary) problem as long as we‘re not talking GPU levels but flexibility (future proofing). Lets say devices that are plugged but might need updates for 10 years or so (in an area of rapid changes like AI/ML), maybe mobile network base stations, industrial wireless communication systems etc.

I might be totally off, but I could imagine for custom semi customers there might even be a FPGA chiplet option available in the future - e.g integrated into an AMD/Intel CPU (maybe just as a safety net alternative to / or accompanying additional tensor cores or whatever highly specialized accelerator flavor there might be integrated in the future). - So basically a trade off regarding energy consumption & cost in favor of flexibility.

Edit - examples added:

FPGA as a chiplet:

Chiplets Built with Speedcore eFPGA IP | Achronix Semiconductor Corporation

Speedcore™ eFPGA IP can be deployed in various form factors including being integrated into a customer-defined chiplet that can be deployed in a system-in-package (SiP) solution via 2.5D interconnect technology. The following figures show three options for the SiP integration. The first is based...

www.achronix.com

Ultra low power FPGA (starting at 25 µW):

https://www.latticesemi.com/Products/FPGAandCPLD/iCE40