BRN Discussion Ongoing

[KMuzza]

Low-Power Image Classification With the BrainChip Akida Edge AI Enablement Platform

Hi Dio,

I'm aware that MB played with both chips Akida 1000 and as recently as last October Akida 1500. It could be for various trials so I understand your software point.

.................-------.....

So if we have valeo and MB using software it should generate revenue to degree but not as elevated as hardware sales.

So the big question is did Sean say we are not putting 2.0 out as they do not want to compete with a customer who ever this customer is would need to be pretty secure to wait.

As for the 1000 and 1500 they really should put more production in as they have demand or will it all now have to be 2.0 and the ones using Akida ESaa Ant61 VVDN Unigen and others have to purchase a 2.0 variant for the products?

Hi Sirod69/Kachoo,

The Edge Impulse/Brainchip on Demand Webinar - is really worth a watch again- and great to see Edge Impulse so out there
with Brainchip Akida 1 and Akida 2.

AKIDA BALLISTA UBQTS.

 

[Diogenese]

Question for the more technically intelligent on BRN and mobile phones.
How do you see Akida being used in mobile phones apart from a possible integration with the Prophesse camera.

Is there any opportunities with Cyber security or any other way to integrate Akida do you think ?.

Ever since the days of DUTH, I've been hanging out for a USB cybersecurity dongle so every PC/Notepad could be protected, so I would thing a mobile phone version would not be too much of a stretch.

Hi Dio,

I'm aware that MB played with both chips Akida 1000 and as recently as last October Akida 1500. It could be for various trials so I understand your software point.

We also know that there has been a tonne of talk about the software in the last few year. We also know and have been told that many put Akida development on 1000 on hold for 2.0 which is much superior in performance and meets what the target audience want.

So this would highlight the exit of Chris Stevens comments in sales how they hardware product was not ready hence his departure.

So is it easy enough to implement the Akida 2.0 hardware once it reaches a stage of readiness?

Clearly MB has not abandoned BRN as we are trusted only thing is the relationship has not been clearly defined as its fluid.

So if we have valeo and MB using software it should generate revenue to degree but not as elevated as hardware sales.

So the big question is did Sean say we are not putting 2.0 out as they do not want to compete with a customer who ever this customer is would need to be pretty secure to wait.

As for the 1000 and 1500 they really should put more production in as they have demand or will it all now have to be 2.0 and the ones using Akida ESaa Ant61 VVDN Unigen and others have to purchase a 2.0 variant for the products?

Hi Kachoo,

I don't know so much about the tons of stuff about software as a commercial product.

When I asked Marcus the naive question about NN software, I was expecting him to say "No. We are using a NN SoC."

Certainly it's been a hard sell for the sales group, especially when we went IP only. There would have been no commissions for the chip sales people.

Implementing Akida 2 in silicon would be no more difficult than Akida 1. In fact, having the Akida 1 template would greatly simplify the Akida 2 tape-out. And, of course, we have Anil.

I'm quietly confident both Valeo and Mercedes are using Akida software, but I don't know this to be a fact.

By the way Ford also use software NNs.

As far as dropping the Akida 2 silicon (if that is what has happened), I'm guessing that would be at the behest of a Teir 1 chip maker. I doubt that it would be worth our while for even a bug customer like Mercedes or Valeo, or Prophesee.

We do have engineering (test) runs of 1000 and 1500, but not commercial production.

Edge box is "Sold out" on the BRN web page, but whether this is 100 units or 1000 units, we do not know.

I wonder if Sean spoke to Rosie Lee in Malaysia?

Top Neuromorphic Computing Stocks for 2024: The Next AI Frontier

The quest for smarter, faster AI is relentless. Our world is generating a staggering amount of data, and traditional computers are struggling—and guzzling energy to keep up. Neuromorphic computing offers a novel solution. By emulating the brain’s network of neurons and synapses, the goal is to...

buff.ly

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[Smoothsailing]

Diogenese I wrote to Rob Telson prior to his departure asking him about cyber security for mobile phones and he said he couldn’t say to much because of the NDA but to watch this space with Quantum Ventures. I am not technically able to
Clarify what quantum ventures have recently announced however it seems they are more focused around the development for defence force and national security what are your thoughts on this please, could their recent development be turned in to the Dongle for PC/ IPads and for iPhones integration ?.
MY GUESS IS YES

 

[KMuzza]

Sometimes one has to JUST WONDER.

and this with CSIRO Aus-

CSIRO study identifies AI models to improve automated chest X-ray diagnoses

The research from CSIRO's Australian e-Health Research Centre demonstrates the potential for AI to better support clinicians.

www.csiro.au

 

[Bravo]

Sometimes one has to JUST WONDER.

View attachment 64171

and this with CSIRO Aus-

CSIRO study identifies AI models to improve automated chest X-ray diagnoses

The research from CSIRO's Australian e-Health Research Centre demonstrates the potential for AI to better support clinicians.

www.csiro.au

Here's a "recentish" paper on SNN's and X-Ray Diagnoses. Traditional X-Ray diagnosis systems are computationally complex thus requiring high power. Neuromorphic can achieve similar, if not superior results with much lower energy consumption.

Efficient Pneumonia Detection Method and Implementation in Chest X-ray Images Based on a Neuromorphic Spiking Neural Network

Deep Learning has solved numerous problems in image recognition and information processing, and is currently being employed in tackling the coronavirus disease (COVID-19) which has become a pandemic. Incisively, deep learning models are utilized in diagnosis systems...

link.springer.com

 

[Fullmoonfever]

Appears our friends at TCS Research Lab were presenting their work with Akida at the recent Morpheus event

Chetan Kadway on LinkedIn: #spacetech #satellite #edgecomputing #orbital #ai #neuromorphic #snn… | 10 comments

Last week, I had the incredible opportunity to visit the Netherlands (with my colleague Sounak Dey) on a business trip that turned out to be much more than I… | 10 comments on LinkedIn

www.linkedin.com

Chetan Kadway
ML Researcher at TCS Research Labs | Computer Vision | SpaceTech | Edge AI | Neuromorphic Computing | Azure ML | ML-Ops | Streamlit Applications
2w Edited

Last week, I had the incredible opportunity to visit the Netherlands (with my colleague Sounak Dey) on a business trip that turned out to be much more than I expected.

Primary purpose of the visit was to present our research work (as invited speakers) at Morpheus Edge AI & Neuromorphic Computing workshop (https://lnkd.in/g-z-dAxJ) organised by Laurent Hili at ESA/ESTEC (European Space Research & Technology Centre). It was well rounded workshop where we got to meet SpaceTech stakeholders that a innnovating towards embedding intelligence onboard satellites (startups, soc manufacturers, european university researchers, ESA project leaders, etc). Excellent work by workshop organiser and the presenting participants.

Unexpectedly, I also met Sir Ananth Krishnan (Tata Consultancy Services Ex-CTO) on his post retirement holiday. And the first thing that came to my mind was his retirement speech address at our IIT-KGP Research Park office: He motivated us to make products & services that are 1] Usable (should pass Grandma test) 2] Trustworthy/Reliable 3] Frugal (Space & Time resource efficient, think of bits & bytes). His advice still guides us in our research work.

The research work we presented was done in colllboration with our friends at BrainChip (Gilles Bézard and Alf Kuchenbuch). Brief introduction to our work that got deployed on Brainchip AKIDA neuromorphic processor:

Currently, there is a delay of many hours or even days to draw actionable insights from satellite imagery (due to mismatch between data volume acquisition & limited comms bandwidth). We observed that end-users either need RAW images or Analytics-ready meta-data as soon as possible. Therefore, embedding intelligence (Edge AI) onboard satellites can result in quicker business decision making across business verticals that rely on geo-spatial data.

To address this, guided by the foresight of Dr. Arpan Pal we built a bundle of tech capabilities that helps send RAW data & Analytics-ready meta-data as soon as possible to ground station. These tech capabilites include:

1) Cloud Cover Detection Model (high-accuracy, low-latency, low-power).
2) DL based Lossless Compression (around 45% compression ratio).
3) RL based Neural Architecture Search Algorithm (quickly search data+task+hardware specific optimal DL models).

We also had a chance to visit TCS Paceport in Amsterdam, hoping to showcase our research prototype there soon. Looking forward to more future collaborations with Edge AI/Neuromorphic hardware accelelator designers & space-grade SoC manufacturers.

Would like to thank Tata Consultancy Services - Research for such great opportunity to build future tech for future demand. Would also like to thank our Edge & Neuromorphic team: Arijit Mukherjee, Sounak Dey, Swarnava Dey, Abhishek Roy Choudhury, Shalini Mukhopadhyay, Syed Mujibul Islam, Sayan Kahali and our academic research advisor Dr. Manan Suri. #spacetech #satellite #edgecomputing #orbital #AI #neuromorphic #SNN #AKIDA #TCS

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[Frangipani]

The University of Washington in Seattle, interesting…

UW’s Department of Electrical & Computer Engineering had already spread the word about a summer internship opportunity at BrainChip last May. In fact, it was one of their graduating Master’s students, who was a BrainChip intern himself at the time (April 2023 - July 2023), promoting said opportunity.

I wonder what exactly Rishabh Gupta is up to these days, hiding in stealth mode ever since graduating from UW & simultaneously wrapping up his internship at BrainChip. What he has chosen to reveal on LinkedIn is that he now resides in San Jose, CA and is “Building next-gen infrastructure and aligned services optimized for multi-modal Generative AI” resp. that his start-up intends to build said infrastructure and services “to democratise AI”… He certainly has a very impressive CV so far as well as first-hand experience with Akida 2.0, given the time frame of his internship and him mentioning vision transformers.

Brainchip Inc: Summer Internship Program 2023

I am Rishabh Gupta, I am a 2nd year ECE PMP masters student and currently working at Brainchip.

advisingblog.ece.uw.edu

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Meanwhile, yet another university is encouraging their students to apply for a summer internship at BrainChip:

BrainChip– Internship Program 2024 - USC Viterbi | Career Services

BrainChip– Internship Opportunity! Apply Today! About BrainChip: BrainChip develops technology that brings commonsense to the processing of sensor data, allowing efficient use for AI inferencing enabling one to do more with less. Accurately. Elegantly. Meaningfully. They call this Essential AI...

viterbicareers.usc.edu

View attachment 63100


I guess it is just a question of time before USC will be added to the BrainChip University AI Accelerator Program, although Nandan Nayampally is sadly no longer with our company…

Maybe from general interest:

I have just heard an interesting R&D report on the radio about Ai improved noise cancelling. It was noted that other big companies are certainly still developing this exciting technology too.
The idea is to let sounds through the cancelling. Until now, there has been no system that allows the user to individually set, define or let learn which sounds the Ai should filter out. The headphones have to learn what the person wants to hear, without cloud, obvious. To do this, the team uses the time differences between the left and right headphones and the noise source. This team solves this as follows: if the person with noise cancelling headphones points their face in the direction of what they want to hear despite the suppression, the Ai or electronics learns within around three seconds that the source is being targeted because it recognises the runtime differences from left to right and lets these sounds through.
So far with app on the smartphone. He also says that the team is working on button (? small) headphones, which they want to introduce in about 6 to 8 months.
Up to now this is being done with the phone he said, but I can very well imagine that the neural network will be placed directly in the headphones, drastically reducing latency even further.
I'm on the road and my research options with the phone are limited, but it's about Shyam Gollakota's team at the University of Washington.

KEYWORDS
Augmented hearing, auditory perception, spatial computing
PDF:

https://homes.cs.washington.edu/~gshyam/Papers/tsh.pdf

______
Older status:

New AI noise-canceling headphone technology lets wearers pick which sounds they hear

A team led by researchers at the University of Washington has developed deep-learning algorithms that let users pick which sounds filter through their headphones in real time. Either through voice...

www.washington.edu

_______

Shyam Gollakota - UW CSE

Shyam Gollakota is a professor at UW CSE focusing on mobile intelligence.

homes.cs.washington.edu

___
Webuild an end-to-end hardware system that integrates a noisecanceling headset (Sony WH-1000XM4), a pair of binaural microphones (Sonic Presence SP15C) with our real-time target speech hearing network running on an embedded IoT CPU (Orange Pi 5B).

We deploy our neural network on the embedded device by converting the PyTorch model into an ONNX model using a nightly
PyTorch version (2.1.0.dev20230713+cu118) and we use the python package onnxsim to simplify the resulting ONNX model.

IMO there is a good chance that Akida will be utilised in future versions of that UW prototype @cosors referred to.

AI headphones let wearer listen to a single person in a crowd, by looking at them just once

A University of Washington team has developed an artificial intelligence system that lets someone wearing headphones look at a person speaking for three to five seconds to “enroll” them. The...

www.washington.edu

“A University of Washington team has developed an artificial intelligence system that lets a user wearing headphones look at a person speaking for three to five seconds to “enroll” them. The system, called “Target Speech Hearing,” then cancels all other sounds in the environment and plays just the enrolled speaker’s voice in real time even as the listener moves around in noisy places and no longer faces the speaker.

The team presented its findings May 14 in Honolulu at the ACM CHI Conference on Human Factors in Computing Systems. The code for the proof-of-concept device is available for others to build on. The system is not commercially available.”


While the paper shared by @cosors (https://homes.cs.washington.edu/~gshyam/Papers/tsh.pdf) indicates that the on-device processing of the end-to-end hardware system UW professor Shyam Gollakota and his team built as a proof-of-concept device is not based on neuromorphic technology, the paper’s future outlook (see below), combined with the fact that UW’s Paul G. Allen School of Computer Science & Engineering* has been encouraging students to apply for the BrainChip Summer Internship Program for the second year in a row, is reason enough for me to speculate those UW researchers could well be playing around with Akida at some point to minimise their prototype’s power consumption and latency.


*(named after the late Paul Gardner Allen who co-founded Microsoft in 1975 with his childhood - and lifelong - friend Bill Gates and donated millions of dollars to UW over the years)

The paper was co-authored by Shyam Gollakota (https://homes.cs.washington.edu/~gshyam) and three of his UW PhD students as well as by AssemblyAI’s Director of Research, Takuya Yoshioka (ex-Microsoft).

AssemblyAI (www.AssemblyAI.com) sounds like an interesting company to keep an eye on:

 

[itsol4605]

To say it again loud and clear:
A study says nothing at all!
A study is by no means a product with sales in the millions!!

 

[IloveLamp]

To say it again loud and clear:
A study says nothing at all!
A study is by no means a product with sales in the millions!!

 

[IloveLamp]

 

[itsol4605]

IMO there is a good chance that Akida will be utilised in future versions of that UW prototype @cosors referred to.

AI headphones let wearer listen to a single person in a crowd, by looking at them just once

A University of Washington team has developed an artificial intelligence system that lets someone wearing headphones look at a person speaking for three to five seconds to “enroll” them. The...

www.washington.edu

“A University of Washington team has developed an artificial intelligence system that lets a user wearing headphones look at a person speaking for three to five seconds to “enroll” them. The system, called “Target Speech Hearing,” then cancels all other sounds in the environment and plays just the enrolled speaker’s voice in real time even as the listener moves around in noisy places and no longer faces the speaker.

The team presented its findings May 14 in Honolulu at the ACM CHI Conference on Human Factors in Computing Systems. The code for the proof-of-concept device is available for others to build on. The system is not commercially available.”


While the paper shared by @cosors (https://homes.cs.washington.edu/~gshyam/Papers/tsh.pdf) indicates that the on-device processing of the end-to-end hardware system UW professor Shyam Gollakota and his team built as a proof-of-concept device is not based on neuromorphic technology, the paper’s future outlook (see below), combined with the fact that UW’s Paul G. Allen School of Computer Science & Engineering* has been encouraging students to apply for the BrainChip Summer Internship Program for the second year in a row, is reason enough for me to speculate those UW researchers could well be playing around with Akida at some point to minimise their prototype’s power consumption and latency.


*(named after the late Paul Gardner Allen who co-founded Microsoft in 1975 with his childhood - and lifelong - friend Bill Gates and donated millions of dollars to UW over the years)

View attachment 64177
View attachment 64203 The paper was co-authored by Shyam Gollakota (https://homes.cs.washington.edu/~gshyam) and three of his UW PhD students as well as by AssemblyAI’s Director of Research, Takuya Yoshioka (ex-Microsoft).

AssemblyAI (www.AssemblyAI.com) sounds like an interesting company to keep an eye on:

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Nice game or maybe study.
Where is the revenue for Brainchip??
A study has no value - Sorry!!

 

[IloveLamp]

Nice game or maybe study.
Where is the revenue for Brainchip??
A study has no value - Sorry!!

Your mums calling you in for breakfast itso, run along home now

 

[Gies]

Nice game or maybe study.
Where is the revenue for Brainchip??
A study has no value - Sorry!!

When there is revenue, your to late.

 

[Kachoo]

View attachment 64212

I don't get it. I get it and understand the importance of revenue and growth.

I guess some are to fixated for some reason to not see the bigger picture.

Let's put it simple the product works and it works great. It has been proven multiple times.

The revenue is dependant on our product in a product that an end consumer pays $$ for and then we see dollars.

The papers and research collaborations that are comming out on Akida have never come out this fast in our history. SNN is taking the stage also.

So what would logically be next is the build and design of the products. The 2 to 5 years they talk about is the past. You will see faster adoption of SNN and we hope Akida is part of this growth.

People just need to get over the past what PVDM and Louis Said about $$ comming in before they were too early to the party really. This does not mean Akida won't succeed it just ment that end users and partners were not ready to give go full steam ahead.

So yeah all these papers are absolutely relevant to our success.

I found another lead on SNN at the university of Tennessee.

I think I even those positive outlooknposter are waitingnfor the drop of news too but we don't whinge all day.

 

[7für7]

It amuses me that some people ignore all the posts which shows progress for potential products with akida, and the postings from exhibitions and Edge Impuls and ANT1 etc.

but when someone posts a study from a research team, they scream out “ITS JUST A RESEARCH WHERE IS THE REVENUE???”

It’s kind of weekend comedy thanks for the entertainment

 

[Guzzi62]

To say it again loud and clear:
A study says nothing at all!
A study is by no means a product with sales in the millions!!

True but it's where it begins, revenue will very likely follow.

We see more and more of those studies meaning the interest/awareness is growing, a very good sign.

If no one are doing research using Akida in some form, we should be very worried.

You don't have to be a rocket scientist to see that, or?

 

[Kachoo]

View attachment 64213

True but it's where it begins, revenue will very likely follow.

We see more and more of those studies meaning the interest/awareness is growing, a very good sign.

If no one are doing research using Akida in some form, we should be very worried.

You don't have to be a rocket scientist to see that, or?

Absolutely right! All this study and reseach going into Akida SNN is a very very positive sign.

If we were not seeing the universities joining grow or the first 2 dropped Akida it mean the technology is shyte. But the interest is growing.

The reality is IP we are selling IP technology that is quite amazing actually. This will take time as we are not the product developer.

I will say this it's pretty cut clear that Akida is successful 100% all products they produced sold all chips sold and are sold out. It it was crap people would not have bought VVDN boxes all the pcl cards what ever.

If BRN went to sell chips we would have seen much stronger revenues at the start but it's actually possible that these little sales would have pushed off some partners maybe your crowding their space. I don't know.

But seeing 10 to 20 million in revenue compared to 100 million is a big deal 100 million makes the start of a big company. Now I'm nor saying we will make 100 million on a deal but they are looking at a bigger fish.

The complexity of what is being sold is beyond most of our comprehension and even the most knowledgeable here would admit to not knowing the whole commercial cycle. This is alittle more complicated then finding nan ore body digging it up refine it and sell the commodity.

 

[entretec]

New Youtube video from Edge Impulse.

After being stunned by the capabilities of ChatGpt 4o i find it truly exciting to think that the a tiny LLM could possibly run with such ease on a Akida IP/chip



Lots of geeky goodness

 

[Smoothsailing]

To say it again loud and clear:
A study says nothing at all!
A study is by no means a product with sales in the millions!!

To say it again loud and clear
A study says everything to support BRN
A study is by far the best reassurance for future sales in the millions

 

[manny100]

I don't get it. I get it and understand the importance of revenue and growth.

I guess some are to fixated for some reason to not see the bigger picture.

Let's put it simple the product works and it works great. It has been proven multiple times.

The revenue is dependant on our product in a product that an end consumer pays $$ for and then we see dollars.

The papers and research collaborations that are comming out on Akida have never come out this fast in our history. SNN is taking the stage also.

So what would logically be next is the build and design of the products. The 2 to 5 years they talk about is the past. You will see faster adoption of SNN and we hope Akida is part of this growth.

People just need to get over the past what PVDM and Louis Said about $$ comming in before they were too early to the party really. This does not mean Akida won't succeed it just ment that end users and partners were not ready to give go full steam ahead.

So yeah all these papers are absolutely relevant to our success.

I found another lead on SNN at the university of Tennessee.

I think I even those positive outlooknposter are waitingnfor the drop of news too but we don't whinge all day.

Exactly, that is why Sean said they are talking to BRNs' potential customers clients...... and of course the clients of those testing AKIDA.