Mccabe84
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I got the feeling they won’t make an announcement on it.
BRN Discussion Ongoing
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Is it allowed to reply to ones own post??? I was thinking hard about my previous comments,.....
"Back in August, Sirod69 posted a clip (post # 27,174) of an Emily Chang interview on Bloomberg TV with Renee Haas, ARM CEO, who was making the rounds at the time (Fox Business, CNBC, etc). In that interview at around the 3 minute + mark he said something to the effect of from product idea to actual product production takes about 4 years."
Maybe, Mr. Haas was meaning that when ARM wants to introduce a change to THEIR technology it takes THEM about 4 years to go from the drawing board to the production line.
Maybe to incorporate Akida into one of ARM's customers chips it can be done much quicker. That is a more hopeful perspective, no?
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This is intresting, I wonder which Neuromorphic Computing/ Spiking Neural Network (SNNSs) was used?. 
After last night post from thelitteshort, it's most probably Brainchip's Akida. As their are no neuromorphic chips commercially available, other than Brainchip.
www.linkedin.com
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After last night post from thelitteshort, it's most probably Brainchip's Akida. As their are no neuromorphic chips commercially available, other than Brainchip.
Arijit Mukherjee on LinkedIn: #neuromorphic #physicalsciences #collaborative #research #problemsolving…
There's an interesting story behind this paper. That was a time when we were presenting our findings on neuromorphic at a workshop attended by many…
Sounak Dey on LinkedIn: #neuromorphiccomputing #tcsresearch #neurips #neuralnetworks #research…
Spiking Neural Networks, coupled with Neuromorphic computing platforms, promises low-power training and inference at battery driven Edge devices. In a recent…
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Rise from the ashes
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Been walking down memory Lane again and tripped over this.This is intresting, I wonder which Neuromorphic Computing/ Spiking Neural Network (SNNSs) was used?.
After last night post from thelitteshort, it's most probably Brainchip's Akida. As their are no neuromorphic chips commercially available, other than Brainchip.
View attachment 23171 View attachment 23174
View attachment 23173
Arijit Mukherjee on LinkedIn: #neuromorphic #physicalsciences #collaborative #research #problemsolving…
There's an interesting story behind this paper. That was a time when we were presenting our findings on neuromorphic at a workshop attended by many…Sounak Dey on LinkedIn: #neuromorphiccomputing #tcsresearch #neurips #neuralnetworks #research…
Spiking Neural Networks, coupled with Neuromorphic computing platforms, promises low-power training and inference at battery driven Edge devices. In a recent…
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When Robot?
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I have posted about this since reading the address of the CEO of Tata to shareholders back in 2020.
In short he was apologising to shareholders for the need to maintain strict secrecy around their projects and customers until product release because of Chinese sponsored industrial espionage.
After the Brainchip and Tata Consulting Services joint presentation on 14.12.19 showing AKIDA performing live gesture identification of hand signals from audience members things went completely quiet.
The usual crowd used this silence to claim the relationship had ended in failure despite the clear statement by Tata’s CEO and despite the scientific papers being published by TCS members.
While it is speculation on my part the fact that Dr. Arijit Mukherjee and colleagues are being more outspoken could signal that they are close to releasing something involving AKIDA perhaps even his predicted robot.
My opinion only DYOR
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AKIDA BALLISTA
Tomorrow
Rise from the ashes
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US Patent Application for SYSTEM AND METHOD FOR REAL-TIME RADAR-BASED ACTION RECOGNITION USING SPIKING NEURAL NETWORK(SNN) Patent Application (Application #20210365778 issued November 25, 2021) - Justia Patents Search
This disclosure relates generally to action recognition and more particularly to system and method for real-time radar-based action recognition. The classical machine learning techniques used for learning and inferring human actions from radar images are compute intensive, and require volumes of...
patents.justia.com
Yes I recall that discussion imo they are definitely still working with us.
I'm terrible at snipping so maybe someone could pick out the juicy parts of the patent
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Rise from the ashes
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Oh good I'll save five bucks then
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The truth is tomorrow will never come for AKD 2000 as the AKD 1000, 2000, 3000, 4000 & 5000 series was cancelled everyone should have received a memo.
The AKIDA 1.0 replaced AKD 1000 however it could well be that there will be a further reimagining of the brand for the LSTM Edition IP.
I personally would expect that as the CEO Sean Hehir made a price sensitive announcement as follows at the AGM:
“For the short term, you can expect another major release of next generation IP and another reference chip prior to the next AGM.”
and the half yearly report accounted for monies paid for IP to produce the final engineering for the reference chip things are still moving ahead as planned.
So it is a question what does in the near term mean for the IP? At the very least it is before next years AGM and before the reference chip so my bet is before Christmas.
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AKIDA BALLISTA
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I have never doubted. It was either that or Dr. Arijit Mukherjee constantly updating his LinkedIn with all things Brainchip was because he wanted a job and a house with a view of the Harbour and Opera House in Sydney.US Patent Application for SYSTEM AND METHOD FOR REAL-TIME RADAR-BASED ACTION RECOGNITION USING SPIKING NEURAL NETWORK(SNN) Patent Application (Application #20210365778 issued November 25, 2021) - Justia Patents Search
This disclosure relates generally to action recognition and more particularly to system and method for real-time radar-based action recognition. The classical machine learning techniques used for learning and inferring human actions from radar images are compute intensive, and require volumes of...
Yes I recall that discussion imo they are definitely still working with us. View attachment 23183
I'm terrible at snipping so maybe someone could pick out the juicy parts of the patent
My opinion only DYOR
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AKIDA BALLISTA
Rise from the ashes
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Yep damn obvious things are a goer with Tata. I'm just waiting for Dr. Arijit Mukherjee to update his profile pic showing off his new Akida tattoo for further confirmationI have never doubted. It was either that or Dr. Arijit Mukherjee constantly updating his LinkedIn with all things Brainchip was because he wanted a job and a house with a view of the Harbour and Opera House in Sydney.
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AKIDA BALLISTA
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The other influencing factor is that Dr. Arpan Pal Head of the Robotics group and to whom Dr.Arijit Mukherjee reports directly publishes papers one of which if memory serves was titled ‘Monitoring the Health of Man and Machine’ and all of this series of the proposals/solutions would be enhanced by SNN produced by a low powered semiconductor capable of working autonomously without connection.Yep damn obvious things are a goer with Tata. I'm just waiting for Dr. Arijit Mukherjee to update his profile pic showing off his new Akida tattoo for further confirmation
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AKIDA BALLISTA
Rise from the ashes
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Is this the one you are talking about?
Rise from the ashes
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While we're here let's boost his numbers
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My first thought was a WANCA re-education chip but even at AKIDA’s low power it would probably be too powerful and fry their remaining synapse.
So back to the drawing board.
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Yes but there was/is a series of papers on this point Dr. Arpan Pal has a special interest in remote health monitoring particularly for cardiac health and also aftermarket implementation for monitoring machines using vision and Neuromorphic computing (SNN).
Anyway he has delivered lectures and written numerous papers with similar titles to the one you have located.
Regards
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AKIDA BALLISTA
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The following link takes you to Dr. Arpan Pal’s many, many Google citations:
scholar.google.com
This is but one of dozens:
System and method for real-time radar-based action recognition using spiking neural network (snn)
Inventors
DEY Sounak, Arijit Mukherjee, Dighanchal Banerjee, RANI Smriti, Arun George, Tapas Chakravarty, Arijit Chowdhury, Arpan Pal
Publication date
2021/11/25
Patent office
US
Application number
17122041
Description
This disclosure relates generally to action recognition and more particularly to system and method for real-time radar-based action recognition. The classical machine learning techniques used for learning and inferring human actions from radar images are compute intensive, and require volumes of training data, making them unsuitable for deployment on network edge. The disclosed system utilizes neuromorphic computing and Spiking Neural Networks (SNN) to learn human actions from radar data captured by radar sensor (s). In an embodiment, the disclosed system includes a SNN model having a data pre-processing layer, Convolutional SNN layers and a Classifier layer. The preprocessing layer receives radar data including doppler frequencies reflected from the target and determines a binarized matrix. The CSNN layers extracts features (spatial and temporal) associated with the target's actions based on the…
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AKIDA BALLISTA
Dr. Arpan Pal
Distinguished Chief Scientist and Research Area Head, Embedded Systems, TCS Research, TCS - Cited by 5,729 - Embedded Systems - Computational Sensing - Signal/Image Processing and ML - Edge Computing and Edge AI
This is but one of dozens:
System and method for real-time radar-based action recognition using spiking neural network (snn)
Inventors
DEY Sounak, Arijit Mukherjee, Dighanchal Banerjee, RANI Smriti, Arun George, Tapas Chakravarty, Arijit Chowdhury, Arpan Pal
Publication date
2021/11/25
Patent office
US
Application number
17122041
Description
This disclosure relates generally to action recognition and more particularly to system and method for real-time radar-based action recognition. The classical machine learning techniques used for learning and inferring human actions from radar images are compute intensive, and require volumes of training data, making them unsuitable for deployment on network edge. The disclosed system utilizes neuromorphic computing and Spiking Neural Networks (SNN) to learn human actions from radar data captured by radar sensor (s). In an embodiment, the disclosed system includes a SNN model having a data pre-processing layer, Convolutional SNN layers and a Classifier layer. The preprocessing layer receives radar data including doppler frequencies reflected from the target and determines a binarized matrix. The CSNN layers extracts features (spatial and temporal) associated with the target's actions based on the…
My opinion only DYOR
FF
AKIDA BALLISTA
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