Rise from the ashes
Regular
You seen some of the other use cases on those sbir's? Death rays , dolphins with lasers etc 
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
You seen some of the other use cases on those sbir's? Death rays , dolphins with lasers etc Agree, a fair bit of work to do.
I use the Donchian 20 day high to visually pick up resistance/target prices.
SP just nudging into bullish territory crossing the Donchian mid line.
Its wait and see from here.
We probably need some news follow up from the 2nd Generation Ann to power through those overhead resistance/targets.
Attachments
Rangersman
Member
What happens to my Afterpay stock if it moves to the NASDAQ? - Stockhead
Afterpay is about to list its shares on NASDAQ. Here we will explore what will happen to current ASX investors who are holding APT shares.stockhead.com.au
This is an article about Afterpay's situation 2 years ago.
I have read there are a few other scenarios
I did the same and yea only had to select to stay on ASX. Sorry APT wasn’t good to you. I was very lucky in my timing, getting in at Covid lows and exiting at post Square announcement highs.
Deadpool
hyper-efficient Ai
Yeah I know it's a dilemma I'll just have to live with. I have thought that it's not going to affect me, but all these projects are going to affect someone.
Sam
Nothing changes if nothing changes
The funny part was I told my mate to get on APT and decided to average out my bank shares instead of getting on… this was around march 2020
Rise from the ashes
Regular
It's not a perfect world mate. Some things we just can't change.
Food4 thought
Regular
Hi yaHi Tech We appear to have the same insight of viewing our Board working with stealthy resolve towards a full Nasdaq listing which I thinkis much closer than some think!
Wouldn’t want to be caught with our pants down “lagging “ behind doing the splits on Nasdaq for the whole World to be left wondering just why we are coming late to the Nasdaq explosion party that Brainchip is creating!
The all new World Technology Leader is Brainchip!! $$$$ Vlad
I have a question
Maybe not a great question but anyway.
What would happen to my shares if we were to be listed on the Nasdaq
Do we become dual listed or only on the nasdaq??
Quatrojos
Regular
RASynBoard brings low-power, edge AI processing to embedded sensor applications
Avnet offers compact sensor module and development kit for always-on sensing PHOENIX – The RASynBoard development kit from Avnet (Nasdaq: AVT ) can help hardware and software design engineers and embedded AI developers quickly adopt edge AI capabilities into their products, making them more...
@Kouchkoini from HC presented this...
Deadpool
hyper-efficient Ai
I have thought before that Pete and Anil must have had a sleepless night or 2 thinking with what evil, men could do with this tech, but I suppose it's just like a car is meant to be driven from point A to B, but some have used it to create unthinkable carnage.
Rise from the ashes
Regular
I'm not sure but I thought the Akida PCIe board came with some sort of disclaimer not to use if for nuclear blah etc blah .
Yeah most likely they did mate. But plenty of good will be brought to the world with this technology also. I look forward to a future of being under full surveillance when AI in general proliferation takes over
Deadpool
hyper-efficient Ai
I'm not sure but I thought the Akida PCIe board came with some sort of disclaimer not to use if for nuclear blah etc blah .
Yeah most likely they did mate. But plenty of good will be brought to the world with this technology also. I look forward to a future of being under full surveillance when AI in general proliferation takes over
Goldphish
Emerged
Rise from the ashes
Regular
Nandan Nayampally on LinkedIn: Akida 2nd Generation
Pretty big moment for BrainChip , and yet, just another step on our path to enabling the rapid growth in the #AIoT market. The 2nd generation #Akida platform…
Fullmoonfever
Top 20
Embedded World?Anyone know what EW stands for?
Nandan Nayampally on LinkedIn: Akida 2nd Generation
Pretty big moment for BrainChip , and yet, just another step on our path to enabling the rapid growth in the #AIoT market. The 2nd generation #Akida platform…www.linkedin.com
View attachment 31628
JoMo68
Regular
Just makes you realise what uninformed ‘tools’ our local commentators (aka WANCA’s and Fools) are.Has anyone seen this yet?
Mind-Boggling Neuromorphic Brain Chips (Part 1)
I can’t help myself. I keep thinking about the 1961 musical Stop the World—I Want to Get Off. After opening in Manchester, England, the show transferred to the West End, London, where it ran for 48…www.eejournal.com
Rise from the ashes
Regular
Elementary Watson . I think you got it.
Fullmoonfever
Top 20
Another potential with the addition of VIT to Akida, coupled with all our other advanced bells n whistles 
Vision Transformers for Vein Biometric Recognition
January 2023
IEEE Access PP(99):1-1
DOI:10.1109/ACCESS.2023.3252009
LicenseCC BY-NC-ND 4.0
Authors:
Raul Garcia-Martin
University Carlos III de Madrid
Raul Sanchez-Reillo
University Carlos III de Madrid
In October 2020, Google researchers present a promising Deep Learning architecture paradigm for Computer Vision that outperforms the already standard Convolutional Neural Networks (CNNs) on multiple image recognition state-of-the-art datasets: Vision Transformers (ViTs).
Based on the self-attention concept inherited from Natural Language Processing (NLP), this new structure surpasses the CNN image classification task on ImageNet, CIFAR-100, and VTAB, among others, when it is fine-tuned (Transfer Leaning) after a previous pre-training on larger datasets. In this work, we confirm this theory and move one step further over the CNN structures applied for Vascular Biometric Recognition (VBR): to the best of our knowledge, we introduce for the first time multiple pure pre-trained and fine-tuned Vision Transformers in this evolving biometric modality to address the challenge of the limited number of samples in VBR datasets.
For this purpose, the ViTs have been trained to extract unique image features on the ImageNet-1k and ImageNet-21k and then fine-tuned for the four main existing VBR variants, i.e., finger, palm, hand dorsal, and wrist vein areas. Fourteen existing vascular datasets have been used to perform the vein identification task in the four previously mentioned modalities, based on the True-Positive Identification Rate (TPIR) and 75-25% train-test sets obtaining the following results: HKPU (99.52%), and FV-USM (99.1%); Vera (99.39%), and CASIA (96.00%); Bosphorus (99.86%); PUT-wrist (99.67%), and UC3M-CV1+CV2 (99.67%).
Furthermore, we introduce UC3M-CV3: a hygienic contactless wrist database collected on smartphones and consisting of 5400 images from 100 different subjects. The promising results show the Vision Transformer’s versatility in VBR under Transfer Learning and reinforce this new Neural Network architecture paradigm.
Vision Transformers for Vein Biometric Recognition
January 2023
IEEE Access PP(99):1-1
DOI:10.1109/ACCESS.2023.3252009
LicenseCC BY-NC-ND 4.0
Authors:
Raul Garcia-Martin
University Carlos III de Madrid
Raul Sanchez-Reillo
University Carlos III de Madrid
In October 2020, Google researchers present a promising Deep Learning architecture paradigm for Computer Vision that outperforms the already standard Convolutional Neural Networks (CNNs) on multiple image recognition state-of-the-art datasets: Vision Transformers (ViTs).
Based on the self-attention concept inherited from Natural Language Processing (NLP), this new structure surpasses the CNN image classification task on ImageNet, CIFAR-100, and VTAB, among others, when it is fine-tuned (Transfer Leaning) after a previous pre-training on larger datasets. In this work, we confirm this theory and move one step further over the CNN structures applied for Vascular Biometric Recognition (VBR): to the best of our knowledge, we introduce for the first time multiple pure pre-trained and fine-tuned Vision Transformers in this evolving biometric modality to address the challenge of the limited number of samples in VBR datasets.
For this purpose, the ViTs have been trained to extract unique image features on the ImageNet-1k and ImageNet-21k and then fine-tuned for the four main existing VBR variants, i.e., finger, palm, hand dorsal, and wrist vein areas. Fourteen existing vascular datasets have been used to perform the vein identification task in the four previously mentioned modalities, based on the True-Positive Identification Rate (TPIR) and 75-25% train-test sets obtaining the following results: HKPU (99.52%), and FV-USM (99.1%); Vera (99.39%), and CASIA (96.00%); Bosphorus (99.86%); PUT-wrist (99.67%), and UC3M-CV1+CV2 (99.67%).
Furthermore, we introduce UC3M-CV3: a hygienic contactless wrist database collected on smartphones and consisting of 5400 images from 100 different subjects. The promising results show the Vision Transformer’s versatility in VBR under Transfer Learning and reinforce this new Neural Network architecture paradigm.
stockduck
Regular
Today I stumbled in the www over lot of Spike for GPT....
news.ucsc.edu
".......
However, this transition will require the development of brain-inspired hardware, which is a significant investment. Eshraghian hopes to work with a hardware company such as Intel to host these models, which would allow him to further demonstrate the energy-saving benefits of his SNN.
......"
syncedreview.com
....Kuaishou Technology..... ????
Maybe someone is more keen on than me?
SpikeGPT: researcher releases code for largest-ever spiking neural network for language generation
Assistant Professor of Electrical and Computer Engineering Jason Eshraghian and two students recently released the open-sourced code for the largest language-generating spiking neural network ever, named SpikeGPT.
SpikeGPT: researcher releases code for largest-ever spiking neural network for language generation
March 07, 2023".......
However, this transition will require the development of brain-inspired hardware, which is a significant investment. Eshraghian hopes to work with a hardware company such as Intel to host these models, which would allow him to further demonstrate the energy-saving benefits of his SNN.
......"
Introducing SpikeGPT: UCSC & Kuaishou’s LLM With Spiking Neural Networks Slashes Language Generation Costs | Synced
While the power and performance of today’s large language models (LLMs) are beyond anything previously seen from AI, so too are their massive computational requirements. Spiking neural networks (SNNs) — which only transmit relevant information when a neuron’s threshold is met — have emerged as...
syncedreview.com
....Kuaishou Technology..... ????
Maybe someone is more keen on than me?
Vladsblood
Regular
Hi Food4 thought , we can still be dual listed. Once on Nasdaq we would need to begin splitting our shares example would be maybe 3/1 share so your holding increase three fold or more if say its5/1 split. Hope this helps you out. Vlad
D
Deleted member 118
Guest
BrainChip Readies 2nd Gen Platform For Power-Efficient Edge AI
What customers are looking for is proven AI tech that can run under a watt, and that they can add to a microcontroller for on-board processing.
www.forbes.com
Similar threads
