He’s a turd. When zeebot recently did the clean out I thought awesome, see ya. But then to see him post again ,I’m convinced Wilzy is zeebotThat's the best you can do wilzy123456....Gifs, comments about other posters comments, never actually putting up any solid research,
yes, you have on the odd occasion, even emailing me personally a number of years ago, how about changing your ..... and start becoming a
genuine contributor, be that positive or negative, as in, focus on the stock not the individuals whom have genuine intent.
At least the Green Baby with the beer or the Rocket zooming over the clouds got a laugh from the staff in the US, but I'd like you to focus
on some research, for example, have you been in contact with the Professor at your University since you last spoke with him about Brainchip ?
Nothing personal, just business.
Best regards....Tech
BRN Discussion Ongoing
- Thread starter TechGirl
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Tothemoon24
Top 20
Tuesday October 10th ;
Big Chief from TATA!!!!
a little Brainchip mention be handy big dog
Next we will introduce Neuromorphic Computing and Spiking Neural Networks (SNN) as a means towards ultra-low power intelligent processing at edge. We cover design and implementation of both efficient spike encoders and spiking neural models on neuromorphic chipsets. We will present application use cases around gesture recognition for human-robot interaction [3] and lossless image compression onboard nano satellites [4] and present some interesting results.
Finally we will conclude with technology trends we see in this area that also relates to sustainable analytics to negate the ever-increasing energy consumption trends in computation.
[1] Ishan Sahu, Arijit Ukil, Sundeep Khandelwal, and Arpan Pal, “LTH-ECG: Lottery Ticket Hypothesis-based Deep Learning Model Compression for Atrial Fibrillation Detection from Single Lead ECG On Wearable and Implantable Devices,” 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022
[2] Shalini Mukhopadhyay, Swarnava Dey, Avik Ghose, Pragya Singh, and Pallab Dasgupta. 2023. Generating Tiny Deep Neural Networks for ECG Classification on Micro-controllers, IEEE International Conference on Pervasive Computing and Communications (PerCom), 2023
[3] Arun M. George, Dighanchal Banerjee, Sounak Dey, Arijit Mukherjee and P. Balamurali, “A Reservoir-based Convolutional Spiking Neural Network for Gesture Recognition from DVS Input,” International Joint Conference on Neural Networks (IJCNN), 2020
[4] Sayan Kahali, Sounak Dey, Chetan S. Kadway, Arijit Mukherjee, Arpan Pal and Manan Suri, “Low-Power Lossless Image Compression on Small Satellite Edge Using Spiking Neural Network,” International Joint Conference on Neural Networks (IJCNN), 2023
Biosktech: Arpan Pal has more than 30 years of experience in the area of Intelligent Sensing, Signal Processing &AI, Edge Computing and Affective Computing. Currently, as Distinguished Chief Scientist and Research Area Head, Embedded Devices and Intelligent Systems, TCS Research, he is working in the areas of Connected Health, Smart Manufacturing, Smart Retail and Remote Sensing. He is on the editorial board of notable journals like ACM Transactions on Embedded Systems, Springer Nature Journal on Computer Science and is on the TPC of notable conferences like IEEE Sensors, ICASSP and EUSIPCO. He has filed 180+ patents (out of which 95+ granted in different geographies) and has published 160+ papers and book chapters in reputed conferences and journals. He has also written three complete books on IoT, Digital twins in Manufacturing and Application AI in Cardiac screening.
He is on the governing/review/advisory board of some of the Indian Government organizations like CSIR, MeitY, Educational Institutions like IIT, IIIT and Technology Innovation Hub. He is two times winner of Tata Group top Innovation award in Tata Innovista under Piloted technology category. Prior to joining Tata Consultancy Services (TCS), Arpan had worked for DRDO, India as Scientist for Missile Seeker Systems and in Rebeca Technologies as their Head of Real-time Systems. He is a B.Tech and M. Tech from IIT, Kharagpur, India and PhD. from Aalborg University, Denmark.
Frangipani
Top 20
They got it!
#edhpc #esa #spacetech #space #brain #ai #obdp | EDGX
Pass by our booth at the European Data Handling & Data Processing Conference 2023 to talk about brain inspired spacetech, look at some of our early prototypes and what it could mean for the future of next generation satellites. #EDHPC #ESA #spacetech #space #brain #AI #OBDP
Could it be akida 1500 or even akida 2 (2000)
Dyor
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robsmark
Regular
Now now… let’s not resort to a new set of conspiracy theories…. Regards, wilzy
That actually was pretty funny. But I have to ask Zee, why does Wilzy get away with the constant baiting? Others would’ve been, and are long gone by now.
Hi HG, Thanks for posting this.
Just on terminology (which changes more frequently than I change socks), NPU as used by BRN) meant network processing unit, 4 of which are combined in a node. Akida 1000 had 80 nodes. It also included an ARM Cortex processor for configuring the NN, but which does not get involved in the business of the NN in classifying objects or other input signals.
This is the NPU from US11468299:
As you show, the Raspberry Pi or other PCIe host would have its own CPU on the mother board.
Hi HG,
We are licensing the Akida IP which is the design of the silicon hardware which can be integrated with any processor, so, if the processor is an Nvidia GPU based processor, Akida can be combined with it as part of the hardware, but we do not have confirmation that Akida has been combined with the MB.OS processor (yet), although AI and ML point to Akida, but water cooling ... ?.
Haha well played wilzyNow now… let’s not resort to a new set of conspiracy theories…. Regards, wilzy
Labsy
Regular
Might be dolci buying back in...Yes buena suerte. noticed that myself. and I have noticed also that around 1.20pm (2.20PM NSW time) there
seems to be when a line will get hit. Somebody wants our shares, and let's hope they and a lot of others will
want BRN shares when they are at $1.95!
Could this be akida 1500 or even akida 2 (2000)
#edhpc #esa #spacetech #space #brain #ai #obdp | EDGX
Pass by our booth at the European Data Handling & Data Processing Conference 2023 to talk about brain inspired spacetech, look at some of our early prototypes and what it could mean for the future of next generation satellites. #EDHPC #ESA #spacetech #space #brain #AI #OBDPwww.linkedin.com
Dyor
HALP: A method to adapt convolutional neural networks to NVIDIA DRIVE Orin™. | NVIDIA DRIVE posted on the topic | LinkedIn
Check out HALP (Hardware-Aware Latency Pruning), our method designed to adapt convolutional neural networks (#CNNs) and #transformer-based architectures for…
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Investig8ed
Regular
And Akida sits on top of the stack hmmm
, DYOR)
wilzy123
Founding Member
cosors
👀
Dr. Arpan Pal will be presenting on the following topics at the 30th IEEE International Conference on Image Processing in Kuala Lumpur on 8-11 October:
"IES #5
Title: Low Power Image Processing on Constrained Devices Using Tiny ML and Neuromorphic Approach
Speaker: Arpan Pal, TCS Research, Tata Consultancy Services, India
Abstract: More and more of IoT based intelligent systems demand embedding the analytics and AI on the edge device. This is driven by the needs of low latency, network unavailability/unreliability and a need for inherent privacy/security. However, edge devices are usually constrained in terms of compute, memory and power which poses challenges for such deployments.
In this presentation we will first introduce a Tiny Edge Wizard that can take large Deep Neural Network models and try to reduce their size / improve their latency automatically using an innovative integrated approach that uses both reduction using pruning using Lottery Ticket Hypothesis (LTH) [1] and synthesis using Neural Architecture Search (NAS) [2]. The automation helps in reducing development time, helps reducing over-parameterised models and minimises the human-expert time. We will take example use cases of medical image processing and manufacturing shop-floor inspection to demonstrate the efficacy of our proposed system.
Next we will introduce Neuromorphic Computing and Spiking Neural Networks (SNN) as a means towards ultra-low power intelligent processing at edge. We cover design and implementation of both efficient spike encoders and spiking neural models on neuromorphic chipsets. We will present application use cases around gesture recognition for human-robot interaction [3] and lossless image compression onboard nano satellites [4] and present some interesting results.
Finally we will conclude with technology trends we see in this area that also relates to sustainable analytics to negate the ever-increasing energy consumption trends in computation." Hear ye!
https://2023.ieeeicip.org/industry-expert-sessions/
@Frangipani
(Even though the article [3] probably refers to IBM)
[3] Arun M. George, Dighanchal Banerjee, Sounak Dey, Arijit Mukherjee and P. Balamurali, “A Reservoir-based Convolutional Spiking Neural Network for Gesture Recognition from DVS Input,” International Joint Conference on Neural Networks (IJCNN), 2020
[4] Sayan Kahali, Sounak Dey, Chetan S. Kadway, Arijit Mukherjee, Arpan Pal and Manan Suri, “Low-Power Lossless Image Compression on Small Satellite Edge Using Spiking Neural Network,” International Joint Conference on Neural Networks (IJCNN), 2023
I remember
here also Dr. Arpan Pal
https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-371567
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wilzy123
Founding Member
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