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M_C

Founding Member
Some would have you believe that the eqxx is only a concept car and Mercedes isn't actually going to use AKIDA.................- I beg to differ

2min40sec "The Vision eqxx is a trailblazer which underlines where our ENTIRE COMPANY IS HEADED" -

 
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HopalongPetrovski

I'm Spartacus!
Some would have you believe that the eqxx is only a concept car and Mercedes isn't actually going to use AKIDA.................- I beg to differ

2min40sec "The Vision eqxx is a trailblazer which underlines where our ENTIRE COMPANY IS HEADED" -


I want one! I want one NOW. :)
 
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I want one! I want one NOW. :)
Well at release which was January, 2022 they said as a straight forward no ifs buts or maybes that it would be road legal and proving the comfortable 1,000 kilometre range in six months. Somewhere else I read an on road price estimate of around $135,000. (Probably US $).

So maybe they will take your deposit. 😂😎🤞

I personally have absolutely no doubt Mercedes will be commercialising Mercedes brand EV’s that leverage AKIDA technology advances.

I even believe Blind Freddie’s theory that Brainchip and Mercedes have conspired to deliver the first AKD2000 with LSTM Mercedes EV that will extrapolate from events and use emergency braking to not run over children chasing balls onto roadways, drunks staggering sideways into traffic and all the while ignoring plastic bags blowing in the wind thus leaving Tesla in their dust.

But don’t tell anyone as they will think Freddie and I have lost our marbles.

My opinion and conspiracy only DYOR
FF

AKIDA BALLISTA
 
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HopalongPetrovski

I'm Spartacus!
Well at release which was January, 2022 they said as a straight forward no ifs buts or maybes that it would be road legal and proving the comfortable 1,000 kilometre range in six months. Somewhere else I read an on road price estimate of around $135,000. (Probably US $).

So maybe they will take your deposit. 😂😎🤞

I personally have absolutely no doubt Mercedes will be commercialising Mercedes brand EV’s that leverage AKIDA technology advances.

I even believe Blind Freddie’s theory that Brainchip and Mercedes have conspired to deliver the first AKD2000 with LSTM Mercedes EV that will extrapolate from events and use emergency braking to not run over children chasing balls onto roadways, drunks staggering sideways into traffic and all the while ignoring plastic bags blowing in the wind thus leaving Tesla in their dust.

But don’t tell anyone as they will think Freddie and I have lost our marbles.

My opinion and conspiracy only DYOR
FF

AKIDA BALLISTA
Well, by my reckoning, $US135k converted to our shekels is 182,000.
So at $5 a share that's only 36,400 for possibly state of the art vehicle technology that I get to drive whilst I'm still young enough to enjoy it.
Bring it BrainChip.
Bring it Merc.
Would be a nice ride to our $5 party :)
 
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Foxdog

Regular
Well, by my reckoning, $US135k converted to our shekels is 182,000.
So at $5 a share that's only 36,400 for possibly state of the art vehicle technology that I get to drive whilst I'm still young enough to enjoy it.
Bring it BrainChip.
Bring it Merc.
Would be a nice ride to our $5 party :)
We'd better talk about colour choices then - I don't want to turn up wearing the same 'dress' 🤣
 
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hamilton66

Regular
Hi SFB,

Biotome and Noisy Gut belt are a couple. Let's hope Nanose is a third.

Here is some information on the NaNose tests from the Technion patent application filed in April 2020.

WO2021214763A1 DEVICE AND METHOD FOR RAPID DETECTION OF VIRUSES

The aim of the study was defined as: Collecting and evaluating data of potential volatile biomarkers in the exhaled air of subjects with and without Covid-19 by the novel sensors of the invention. COVID-19 positive and negative subjects were enrolled. Classification to the 2 study arms was based on a PCR test result. Three medical centers participate in the study: Shamir Health Corporation (“Assaf Harofeh”) in Israel; Northwell Health, Inc. in the United States (“Northwell”); Zayed Military Hospital Abu Dhabi (“Zayed Hospital”).

The study was performed with the sensors installed in 2 devices: 1. The first- generation device with single use units that include the sensors. 2. a device with multi use sensors. The collected data from the devices were analyzed independently by two distinct methods.

The first dataset was collected with the first-generation device with singe use units that include the sensors of the invention. The dataset included subjects tested with the device at two sites: 35 samples from Northwell NY, and 31 samples from Shamir medical center IL. Each test file consisted of responses from duplicated sensor array, and therefore each test file was split into two sample files, based on the sensor sets. Some of the sensors failed to respond, and therefore datasets that included failed sensors were discarded. The total number of sample files that were analyzed after the error- prone samples were discarded is: Northwell - 35 sample files (representing 24 tested subjects - 17 positives, 7 negatives) and Shamir medical center - 31 sample files (representing 21 tested subjects - 14 positives, 7 negatives). The data was analyzed by Brainchip with a Spiking Neural Network, the adjacent confusion matrix shows the results on the test set. The test set included 31 samples- 21 positives and 10 negatives from 21 tested subjects. Zero out of 21 positive samples were identified correctly which represents 100% sensitivity and 4 out of 10 negative samples were identified correctly which represents 40% specificity. The overall accuracy was 80.65% The second study was performed with the multiuse NaNose sensors installed in Sniffphone device. The dataset included 165 samples taken from 141 subjects tested with Sniffphone device at Zayed Military Hospital - 65 samples from 65 COVID-19 positive subjects and 100 samples from 76 COVID-19 negative subjects (Several negative subjects were sampled two or three times). A Linear discriminative analysis was performed. The adjacent confusion matrix shows the results on the test set that that was completely blind to the training and validation of the model. The test set included 37 samples - 8 positive and 29 negative samples from 27 tested subjects. Seven out of eight positive samples were identified correctly which represents 87.5% sensitivity, and 25 out of the 29 negative samples were identified correctly which represents 86.2% specificity. The overall accuracy was therefore 86.5%.

The same data set was analyzed also by the SNN methodology. To make the SNN most efficient, 34 samples were discarded due to noise or improper vector dimensionality. Thus, the dataset included 131 samples taken from 126 subjects tested with Sniffphone device at Zayed Military Hospital- 62 samples from 62 COVID-19 positive subjects and 69 samples from 64 COVID-19 negative subjects (Several negative subjects were sampled two or three times). The adjacent confusion matrix shows the results on the test set that that was completely blind to the training and validation of the model. The test set included 53 samples - 20 positive and 33 negative samples from 53 tested subjects. Nineteen out of 20 positive samples were identified correctly which represents 95% sensitivity and 29 out of 33 negative samples were identified correctly which represents 87.87 % specificity. The overall accuracy was therefore 90.5%.

Two different analysis methods were applied on the dataset and both showed excellent results for the differentiation between COVID positive and COVID negative. While the multiuse sensors achieved a much better specificity (-87%) compared to the single use sensors (40%), this is more likely a result of the vast difference between the datasets: the dataset of the multiuse sensors included 165 samples from 141 subjects while the dataset of the single-use sensors included 66 samples from 45 subjects. During the Clinical study with COVID19 patients the company further improved the 4 components of the device: the mechanical design including the breath collection mechanism, the electronics, the sensors and the classifying algorithm
.

"To make the SNN most efficient, 34 samples were discarded due to noise or improper vector dimensionality." This suggests to me that the accuracy and reliability of the data collected by sensor was not 100%, so there may have been technical issues with the NaNose sensor 2 years ago.
D, thanks for the unwaivering supply of info. Stella. Just poked my head into H/C for the 1st time in ages. Jesus, it's toxic. Basically no info, just downrampers vs the rest. It offers nothing, in terms of analysis, or information. Sad to see.
GLTA
 
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M_C

Founding Member
Wonder what brought this on 🤔😃


Chiplets are a growing concept in the semiconductor design industry, where tiny dies are used instead of one monolithic die.

This has so far been used to split CPUs into several pieces (in the extreme, Intel Ponte Vecchio includes 47 chiplets on a single package). But with interoperability, one could build chips that mix-and-match chiplets from different companies.

Intel and AMD previously trialed this with the ‘Intel 8th Generation Core with Radeon RX Vega M Graphics' chip that included an ‘H-series’ Intel central processor and an AMD Radeon graphics processor as two chiplets on the same package, but true interoperability has been lacking.

UCIe aims to solve that - at least for the companies that have joined.

The consortium launches with founding members Advanced Semiconductor Engineering, Inc. (ASE), AMD, Arm, Google Cloud, Intel Corporation, Meta, Microsoft Corporation, Qualcomm Incorporated, Samsung, and Taiwan Semiconductor Manufacturing Company
 
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miaeffect

Oat latte lover
D, thanks for the unwaivering supply of info. Stella. Just poked my head into H/C for the 1st time in ages. Jesus, it's toxic. Basically no info, just downrampers vs the rest. It offers nothing, in terms of analysis, or information. Sad to see.
GLTA
You've just wasted 100 watt of electricity and 10mb of your precious data.
 
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D

Deleted member 118

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MrNick

Regular
Could our link with TATA have just come into play here…? Clutching at metaphorical straws perhaps.
 
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BaconLover

Founding Member
Screenshot (14).png





An oldie but a goodie.

Major Giant. Not long now.

On another note, @Fact Finder some scientists say Milky Way and Andromeda Galaxy will kiss each other goodbye and there will be a new kid in the block approximately 4.5Billion years from now. So Earth may not get the opportunity to be a hot dude roaming around and trying to tease the Sun. Will be consumed alive by the hunks from Andromeda waayyy before then.
 
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View attachment 2879




An oldie but a goodie.

Major Giant. Not long now.

On another note, @Fact Finder some scientists say Milky Way and Andromeda Galaxy will kiss each other goodbye and there will be a new kid in the block approximately 4.5Billion years from now. So Earth may not get the opportunity to be a hot dude roaming around and trying to tease the Sun. Will be consumed alive by the hunks from Andromeda waayyy before then.
We better send Peter and Anil an email telling them they have half billion less years to save humanity.
🤓 FF
 
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cyber

Member
View attachment 2879




An oldie but a goodie.

Major Giant. Not long now.

On another note, @Fact Finder some scientists say Milky Way and Andromeda Galaxy will kiss each other goodbye and there will be a new kid in the block approximately 4.5Billion years from now. So Earth may not get the opportunity to be a hot dude roaming around and trying to tease the Sun. Will be consumed alive by the hunks from Andromeda waayyy before then.

View attachment 2879




An oldie but a goodie.

Major Giant. Not long now.

On another note, @Fact Finder some scientists say Milky Way and Andromeda Galaxy will kiss each other goodbye and there will be a new kid in the block approximately 4.5Billion years from now. So Earth may not get the opportunity to be a hot dude roaming around and trying to tease the Sun. Will be consumed alive by the hunks from Andromeda waayyy before then.
Well that's finally some good news BL.
Wasn't sure whether I was going to be burnt to death, drowned by rising sea levels or choked by ingesting too much plastic.
Cheers
 
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Diogenese

Top 20
this is a rabbit hole... found one interesting paragraph...
  • Embedded computing and communication platforms (ECCP): This group focuses on distributed embedded systems, real-time systems, time-sensitive networks, model partitioning and optimization, sensor reliability and planning, and edgified machine learning on specialized processors and devices like neuromorphic, RISC-V, FPGA. TCS also looks at distributed computing across the edge, fog and cloud with a focus on optimization of communication cost, execution latency, energy footprint, and so on.

  • Neural networks, where the design topology better fits an FPGA and can accelerate matrix multiplication.



inconclusive Mr Nick...requires more digging...tag... your it.
Interesting point - when we had single bit weights and actuations, we did not do matrix multiplication. Now we can do 4-bit weights and actuations, do we do matrix multiplication?

1647778260244.png
 
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Learning

Learning to the Top 🕵‍♂️
After listening to this podcast with ARK Invest's Cathie Wood just makes me drool just thinking about how incredibly big and dominant Brainchip could potentially become:


AI will grow to 100T by 2030.

I believed we BRN shareholder will benefit.
Screenshot_20220321-091704_Samsung Notes.jpg




Its great to be a shareholder.
 
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Well that's finally some good news BL.
Wasn't sure whether I was going to be burnt to death, drowned by rising sea levels or choked by ingesting too much plastic.
Cheers
Hi Cyber
Thought I should find some good positive news just for you.

In explanation for new investors Cyber is a long term investor who has added great content and perspective over many years. He will immediately recognise that the following link is to Dr. Arijit Mukherjee at Tata Consulting Services.

The Dr. presented for TCS with Brainchip on 14.12.19 AKIDA recognising hand gestures and wrote that he looked forward to building a robot based on an AKIDA technology platform.

Since that time he has coauthored a number of papers and patents which would require an SNN processor to be given life at Tata. Some of these papers have been with Dr. Arpan Pal.

(Dr. Arpan Pal is his immediate supervisor. He obviously has an interest in robotics being head of this area but has coauthored articles and patents for remote health monitoring utilising SNN technology. He appears to have a particular interest in real time monitoring of cardiac health.)

Scrolling down his LinkedIn page you will see his continuing close interest in all things Brainchip including EQXX. His specialty is robotics but as Alex the Rocket Scientist said autonomous drones and automobiles are just other forms of robots.



TATA is as I have said since 2020 an EAP and one company which does require strict adherence to NDA’s because of its publicly stated concerns about Chinese industrial espionage.

My opinion only DYOR
FF

AKIDA BALLISTA
 
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You will need to Google Dr. Arijit Mukherjee TCS and then open his LinkedIn account public page as the above link requires you to be a member. FF
1647815317603.png https://in.linkedin.com › arijit72
Arijit Mukherjee - Tata Consultancy Services


Kolkata, West Bengal, India · Senior Scientist, Embedded Devices & Intelligent Systems at TCS Research · Tata Consultancy Services
Arijit has more than 24 years of industry and academic experience in distributed systems, grid/cloud & MPP systems. Currently he is a
 
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