BRN Discussion Ongoing

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HopalongPetrovski

I'm Spartacus!
4ds up 150% today....Brainchip?
Be happy for the poor bastards who hold 4DS.
They've been waiting a long time for the announcement they got today and they've earned it.
They're finally getting a little love.
We are still in the long dark tunnel and are being tested now.
But when our announcement comes it will be just the first in a sequence and followed quickly with money.
We have also been so scrutinised and are on so many watch lists that at the first sign of our success we'll be lucky not to just fucken' explode! 🤣
A bit like I'd do if I got on that bus! 🤣
 
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Bravo

If ARM was an arm, BRN would be its biceps💪!
images.jpeg



If this dude Thomas Fuller is correct, then it should be approximately 6am in the morning, unless we're all stuck in some weird time-space continuum.
 
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Mccabe84

Regular
4ds up 150% today....Brainchip?
But now only up 81%. Still better than BRN though.

I wonder if the big institutions are still accumulating in BRN shares
 
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Damo4

Regular
Yeah I just got modded for baiting - funny how it’s always one sided isn’t it?
I don't even know why that would have copped a moderation. I like to go find myself occasionally one needs to be grounded. Like going on a sabbatical.
It makes them feel like they got something in life mate. Water off a ducks back.

LOL was this the post?
Why would that NOT be modded haha

1692767587340.png
 
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robsmark

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Damo4

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robsmark

Regular
So it's not baiting if you create an acronym?
I wouldn’t have used the acronym if I didn’t receive that unnecessary comment.

I try to avoid getting personnel unless someone swings a fist first.
 
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Damo4

Regular
I wouldn’t have used the acronym if I didn’t receive an unnecessary comment.

I try to avoid getting personnel unless someone swings a fist first.
Doesnt Work That Way Jason Hayes GIF - Doesnt Work That Way Jason Hayes  Seal Team - Discover & Share GIFs
 
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robsmark

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Esq.111

Fascinatingly Intuitive.
Afternoon Robsmark,

Over the years , Very close acquaintances have had to engage high end Lawyers / Solicitors ( QC now known as KC barristers ( Kings Counsel ) & the really big end of town ...Retired High Court Judge ( When you know you are right and really drive it home in a court of law ) to achieve a just outcome.

One thing I found interesting ..... If one starts the conversation with .. WITHOUT PREJUDICE...then hook in ....all is tickety taboo.

Alternately , maybe start with ..... PLEASE.... followed by GFY.


😁


Regards,
Esq.
 
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Tothemoon24

Top 20
Behind the curtain of this technological wonder is a complex process that combines image processing, machine learning and pattern recognition. Cameras photograph products at various stages of the inspection line. These images are then processed through neural networks where patterns and anomalies are detected and compared with the desired parameters. Algorithms are constantly learning and adapting, becoming smarter and more efficient with each check. It's like having an army of Sherlock Holmes at your service, making sure no mystery goes unsolved on the production line.



 
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Today a mini report was released by Cambrian Ai covering the release of AKIDA Second Generation. The significance of this report cannot be overstated. I had held the opinion prior to reading this report that AKIDA Third Generation would be the IP that allowed Brainchip and its shareholders to capitalise on the obsessed CHATGpt technology world but I was clearly wrong.

Thank you Cambrian Ai for disclosing just what makes AKIDA Second Generation a potential love child of CHATGpt or more generally GenAi.

To explain why I hold the opinion that today's reveal by Cambrian Ai is of such significance I have set out here a series of FACTS which I believe justifies my opinion.


From CNN —
The crushing demand for AI has also revealed the limits of the global supply chain for powerful chips used to develop and field AI models.
The continuing chip crunch has affected businesses large and small, including some of the AI industry’s leading platforms and may not meaningfully improve for at least a year or more, according to industry analysts.
The latest sign of a potentially extended shortage in AI chips came
webicon_green.png
in Microsoft’s annual report recently. The report identifies, for the first time, the availability of graphics processing units (GPUs) as a possible risk factor for investors.
GPUs are a critical type of hardware that helps run the countless calculations involved in training and deploying artificial intelligence algorithms.
“We continue to identify and evaluate opportunities to expand our datacenter locations and increase our server capacity to meet the evolving needs of our customers, particularly given the growing demand for AI services,” Microsoft wrote. “Our datacenters depend on the availability of permitted and buildable land, predictable energy, networking supplies, and servers, including graphics processing units (‘GPUs’) and other components.”
Microsoft’s nod to GPUs highlights how access to computing power serves as a critical bottleneck for AI. The issue directly affects companies that are building AI tools and products, and indirectly affects businesses and end-users who hope to apply the technology for their own purposes.
OpenAI CEO Sam Altman, testifying before the US Senate in May, suggested that the company’s chatbot tool was struggling to keep up with the number of requests users were throwing at it.
“We’re so short on GPUs, the less people that use the tool, the better,” Altman said. An OpenAI spokesperson later told CNN the company is committed to ensuring enough capacity for users.
The problem may sound reminiscent of the pandemic-era shortages in popular consumer electronics that saw gaming enthusiasts paying substantially inflated prices for game consoles and PC graphics cards. At the time, manufacturing delays, a lack of labor, disruptions to global shipping and persistent competing demand from cryptocurrency miners contributed to the scarce supply of GPUs,
webicon_green.png
spurring a cottage industry of deal-tracking tech to help ordinary consumers find what they needed."


Cambrian Ai's mini paper on Brainchip and Second Gen AKIDA can be found via Cambrian Ai's Homepage at:
webicon_gray.png
https://cambrian-ai.com/
On their Homepage they state that they work with the following companies: Cerebras, Esperanto Technologies, Graphcore, IBM, Intel, NVIDIA, Qualcomm, Tenstorrent, SiFive, Simple Machines, Synopsys, Cadence and others.

In their mini paper they say many nice things but the significant parts in my opinion are found in the concluding paragraph which I have broken up into three points:


1. The second-generation Akida processor IP is available now from BrainChip for inclusion in any SoC and comes complete with a software stack tuned for this unique architecture.

2. We encourage companies to investigate this technology, especially those implementing time series or sequential data applications.

3. Given that GenAI and LLMs generally involve sequence prediction, and advances made for pre-trained language models for event-based architectures with SpikeGPT, the compactness and capabilities of BrainChip’s TENNs and the availability of Vision Transformer …second-generation Akida could facilitate more GenAI capabilities at the Edge.


In Summary:

There is a massive shortage of GPU chips to run GenAi and this shortage is going to extend into the next year and a half at least.

Cambrian Ai has told the World that they should be looking at AKIDA Second Generation to facilitate GenAi capabilities at the Edge.

If Cambrian Ai only pass on their opinion to their existing customer base this is still a very large portion of the technology market where AKIDA Second Generation could profitably be adopted.


As we all should know AKIDA technology reduces bandwidth by processing data collected at the EDGE into relevant meta data and in so doing reduces processing demand in the Cloud be it public or private.

Peter van der Made is on record stating that AKIDA technology at the EDGE doing its thing can reduce the use of power in the Cloud by up to 97%.


It just makes sense if you cannot get enough GPU’s to handle your GenAi workloads in the Cloud then one solution is to reduce the workload.

Cambrian is only stating the obvious when it asks companies to investigate what AKIDA Second Generation can do for them to facilitate their GenAi capabilities at the EDGE.

In my opinion there is no reason to doubt that Brainchip is finally on the cusp of publicly realising what we all have known for what seems like a lifetime. An EDGE technology revolution.

Validation of AKIDA technology Science Fiction has been coming thick and fast from diverse sources but of late the most impressive was from TATA researchers who found that AKIDA technology was 35 times more power efficient and 3.4 times faster than the Nvidia GPU that they were also trialling. I doubt that such findings by a company with the global presence of TATA will have been missed by those that matter in the technology space.

However this is my opinion only so be sure to DYOR.

Regards
Fact Finder
 
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Today a mini report was released by Cambrian Ai covering the release of AKIDA Second Generation. The significance of this report cannot be overstated. I had held the opinion prior to reading this report that AKIDA Third Generation would be the IP that allowed Brainchip and its shareholders to capitalise on the obsessed CHATGpt technology world but I was clearly wrong.

Thank you Cambrian Ai for disclosing just what makes AKIDA Second Generation a potential love child of CHATGpt or more generally GenAi.

To explain why I hold the opinion that today's reveal by Cambrian Ai is of such significance I have set out here a series of FACTS which I believe justifies my opinion.


From CNN —
The crushing demand for AI has also revealed the limits of the global supply chain for powerful chips used to develop and field AI models.
The continuing chip crunch has affected businesses large and small, including some of the AI industry’s leading platforms and may not meaningfully improve for at least a year or more, according to industry analysts.
The latest sign of a potentially extended shortage in AI chips came
webicon_green.png
in Microsoft’s annual report recently. The report identifies, for the first time, the availability of graphics processing units (GPUs) as a possible risk factor for investors.
GPUs are a critical type of hardware that helps run the countless calculations involved in training and deploying artificial intelligence algorithms.
“We continue to identify and evaluate opportunities to expand our datacenter locations and increase our server capacity to meet the evolving needs of our customers, particularly given the growing demand for AI services,” Microsoft wrote. “Our datacenters depend on the availability of permitted and buildable land, predictable energy, networking supplies, and servers, including graphics processing units (‘GPUs’) and other components.”
Microsoft’s nod to GPUs highlights how access to computing power serves as a critical bottleneck for AI. The issue directly affects companies that are building AI tools and products, and indirectly affects businesses and end-users who hope to apply the technology for their own purposes.
OpenAI CEO Sam Altman, testifying before the US Senate in May, suggested that the company’s chatbot tool was struggling to keep up with the number of requests users were throwing at it.
“We’re so short on GPUs, the less people that use the tool, the better,” Altman said. An OpenAI spokesperson later told CNN the company is committed to ensuring enough capacity for users.
The problem may sound reminiscent of the pandemic-era shortages in popular consumer electronics that saw gaming enthusiasts paying substantially inflated prices for game consoles and PC graphics cards. At the time, manufacturing delays, a lack of labor, disruptions to global shipping and persistent competing demand from cryptocurrency miners contributed to the scarce supply of GPUs,
webicon_green.png
spurring a cottage industry of deal-tracking tech to help ordinary consumers find what they needed."


Today Cambrian Ai released a mini paper on Brainchip and Second Gen AKIDA. Cambrian Ai's Homepage can be found at:
webicon_gray.png
https://cambrian-ai.com/
On their Homepage they state that they work with the following companies: Cerebras, Esperanto Technologies, Graphcore, IBM, Intel, NVIDIA, Qualcomm, Tenstorrent, SiFive, Simple Machines, Synopsys, Cadence and others.

In their mini paper they say many nice things but the significant parts in my opinion are found in the concluding paragraph which I have broken up into three points:


1. The second-generation Akida processor IP is available now from BrainChip for inclusion in any SoC and comes complete with a software stack tuned for this unique architecture.

2. We encourage companies to investigate this technology, especially those implementing time series or sequential data applications.

3. Given that GenAI and LLMs generally involve sequence prediction, and advances made for pre-trained language models for event-based architectures with SpikeGPT, the compactness and capabilities of BrainChip’s TENNs and the availability of Vision Transformer …second-generation Akida could facilitate more GenAI capabilities at the Edge.


In Summary:

There is a massive shortage of GPU chips to run GenAi and this shortage is going to extend into the next year and a half at least.

Cambrian Ai has told the World that they should be looking at AKIDA Second Generation to facilitate GenAi capabilities at the Edge.

If Cambrian Ai only pass on their opinion to their existing customer base this is still a very large portion of the technology market where AKIDA Second Generation could profitably be adopted.


As we all should know AKIDA technology reduces bandwidth by processing data collected at the EDGE into relevant meta data and in so doing reduces processing demand in the Cloud be it public or private.

Peter van der Made is on record stating that AKIDA technology at the EDGE doing its thing can reduce the use of power in the Cloud by up to 97%.


It just makes sense if you cannot get enough GPU’s to handle your GenAi workloads in the Cloud then one solution is to reduce the workload.

Cambrian is only stating the obvious when it asks companies to investigate what AKIDA Second Generation can do for them to facilitate their GenAi capabilities at the EDGE.

In my opinion there is no reason to doubt that Brainchip is finally on the cusp of publicly realising what we all have known for what seems like a lifetime. An EDGE technology revolution.

Validation of AKIDA technology Science Fiction has been coming thick and fast from diverse sources but of late the most impressive was from TATA researchers who found that AKIDA technology was 34 times more power efficient and 3.4 times faster than the Nvidia GPU that they were also trialling. I doubt that such findings by a company with the global presence of TATA will have been missed by those that matter in the technology space.

However this is my opinion only so be sure to DYOR.

Regards
Fact Finder
FF

A perfect return - even if this is a rare appearance ( which I fervently hope is not the case) it’s a very compelling piece you’ve highlighted and one which does demonstrate the increasing penetration BRN is making in the whole AI sphere.
 
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Mccabe84

Regular
Today a mini report was released by Cambrian Ai covering the release of AKIDA Second Generation. The significance of this report cannot be overstated. I had held the opinion prior to reading this report that AKIDA Third Generation would be the IP that allowed Brainchip and its shareholders to capitalise on the obsessed CHATGpt technology world but I was clearly wrong.

Thank you Cambrian Ai for disclosing just what makes AKIDA Second Generation a potential love child of CHATGpt or more generally GenAi.

To explain why I hold the opinion that today's reveal by Cambrian Ai is of such significance I have set out here a series of FACTS which I believe justifies my opinion.


From CNN —
The crushing demand for AI has also revealed the limits of the global supply chain for powerful chips used to develop and field AI models.
The continuing chip crunch has affected businesses large and small, including some of the AI industry’s leading platforms and may not meaningfully improve for at least a year or more, according to industry analysts.
The latest sign of a potentially extended shortage in AI chips came
webicon_green.png
in Microsoft’s annual report recently. The report identifies, for the first time, the availability of graphics processing units (GPUs) as a possible risk factor for investors.
GPUs are a critical type of hardware that helps run the countless calculations involved in training and deploying artificial intelligence algorithms.
“We continue to identify and evaluate opportunities to expand our datacenter locations and increase our server capacity to meet the evolving needs of our customers, particularly given the growing demand for AI services,” Microsoft wrote. “Our datacenters depend on the availability of permitted and buildable land, predictable energy, networking supplies, and servers, including graphics processing units (‘GPUs’) and other components.”
Microsoft’s nod to GPUs highlights how access to computing power serves as a critical bottleneck for AI. The issue directly affects companies that are building AI tools and products, and indirectly affects businesses and end-users who hope to apply the technology for their own purposes.
OpenAI CEO Sam Altman, testifying before the US Senate in May, suggested that the company’s chatbot tool was struggling to keep up with the number of requests users were throwing at it.
“We’re so short on GPUs, the less people that use the tool, the better,” Altman said. An OpenAI spokesperson later told CNN the company is committed to ensuring enough capacity for users.
The problem may sound reminiscent of the pandemic-era shortages in popular consumer electronics that saw gaming enthusiasts paying substantially inflated prices for game consoles and PC graphics cards. At the time, manufacturing delays, a lack of labor, disruptions to global shipping and persistent competing demand from cryptocurrency miners contributed to the scarce supply of GPUs,
webicon_green.png
spurring a cottage industry of deal-tracking tech to help ordinary consumers find what they needed."


Cambrian Ai's mini paper on Brainchip and Second Gen AKIDA can be found via Cambrian Ai's Homepage at:
webicon_gray.png
https://cambrian-ai.com/
On their Homepage they state that they work with the following companies: Cerebras, Esperanto Technologies, Graphcore, IBM, Intel, NVIDIA, Qualcomm, Tenstorrent, SiFive, Simple Machines, Synopsys, Cadence and others.

In their mini paper they say many nice things but the significant parts in my opinion are found in the concluding paragraph which I have broken up into three points:


1. The second-generation Akida processor IP is available now from BrainChip for inclusion in any SoC and comes complete with a software stack tuned for this unique architecture.

2. We encourage companies to investigate this technology, especially those implementing time series or sequential data applications.

3. Given that GenAI and LLMs generally involve sequence prediction, and advances made for pre-trained language models for event-based architectures with SpikeGPT, the compactness and capabilities of BrainChip’s TENNs and the availability of Vision Transformer …second-generation Akida could facilitate more GenAI capabilities at the Edge.


In Summary:

There is a massive shortage of GPU chips to run GenAi and this shortage is going to extend into the next year and a half at least.

Cambrian Ai has told the World that they should be looking at AKIDA Second Generation to facilitate GenAi capabilities at the Edge.

If Cambrian Ai only pass on their opinion to their existing customer base this is still a very large portion of the technology market where AKIDA Second Generation could profitably be adopted.


As we all should know AKIDA technology reduces bandwidth by processing data collected at the EDGE into relevant meta data and in so doing reduces processing demand in the Cloud be it public or private.

Peter van der Made is on record stating that AKIDA technology at the EDGE doing its thing can reduce the use of power in the Cloud by up to 97%.


It just makes sense if you cannot get enough GPU’s to handle your GenAi workloads in the Cloud then one solution is to reduce the workload.

Cambrian is only stating the obvious when it asks companies to investigate what AKIDA Second Generation can do for them to facilitate their GenAi capabilities at the EDGE.

In my opinion there is no reason to doubt that Brainchip is finally on the cusp of publicly realising what we all have known for what seems like a lifetime. An EDGE technology revolution.

Validation of AKIDA technology Science Fiction has been coming thick and fast from diverse sources but of late the most impressive was from TATA researchers who found that AKIDA technology was 34 times more power efficient and 3.4 times faster than the Nvidia GPU that they were also trialling. I doubt that such findings by a company with the global presence of TATA will have been missed by those that matter in the technology space.

However this is my opinion only so be sure to DYOR.

Regards
Fact Finder
If the 2 gen Akida IP is available now shouldn’t there have been an ASX announcement?
 
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mrgds

Regular
Today a mini report was released by Cambrian Ai covering the release of AKIDA Second Generation. The significance of this report cannot be overstated. I had held the opinion prior to reading this report that AKIDA Third Generation would be the IP that allowed Brainchip and its shareholders to capitalise on the obsessed CHATGpt technology world but I was clearly wrong.

Thank you Cambrian Ai for disclosing just what makes AKIDA Second Generation a potential love child of CHATGpt or more generally GenAi.

To explain why I hold the opinion that today's reveal by Cambrian Ai is of such significance I have set out here a series of FACTS which I believe justifies my opinion.


From CNN —
The crushing demand for AI has also revealed the limits of the global supply chain for powerful chips used to develop and field AI models.
The continuing chip crunch has affected businesses large and small, including some of the AI industry’s leading platforms and may not meaningfully improve for at least a year or more, according to industry analysts.
The latest sign of a potentially extended shortage in AI chips came
webicon_green.png
in Microsoft’s annual report recently. The report identifies, for the first time, the availability of graphics processing units (GPUs) as a possible risk factor for investors.
GPUs are a critical type of hardware that helps run the countless calculations involved in training and deploying artificial intelligence algorithms.
“We continue to identify and evaluate opportunities to expand our datacenter locations and increase our server capacity to meet the evolving needs of our customers, particularly given the growing demand for AI services,” Microsoft wrote. “Our datacenters depend on the availability of permitted and buildable land, predictable energy, networking supplies, and servers, including graphics processing units (‘GPUs’) and other components.”
Microsoft’s nod to GPUs highlights how access to computing power serves as a critical bottleneck for AI. The issue directly affects companies that are building AI tools and products, and indirectly affects businesses and end-users who hope to apply the technology for their own purposes.
OpenAI CEO Sam Altman, testifying before the US Senate in May, suggested that the company’s chatbot tool was struggling to keep up with the number of requests users were throwing at it.
“We’re so short on GPUs, the less people that use the tool, the better,” Altman said. An OpenAI spokesperson later told CNN the company is committed to ensuring enough capacity for users.
The problem may sound reminiscent of the pandemic-era shortages in popular consumer electronics that saw gaming enthusiasts paying substantially inflated prices for game consoles and PC graphics cards. At the time, manufacturing delays, a lack of labor, disruptions to global shipping and persistent competing demand from cryptocurrency miners contributed to the scarce supply of GPUs,
webicon_green.png
spurring a cottage industry of deal-tracking tech to help ordinary consumers find what they needed."


Today Cambrian Ai released a mini paper on Brainchip and Second Gen AKIDA. Cambrian Ai's Homepage can be found at:
webicon_gray.png
https://cambrian-ai.com/
On their Homepage they state that they work with the following companies: Cerebras, Esperanto Technologies, Graphcore, IBM, Intel, NVIDIA, Qualcomm, Tenstorrent, SiFive, Simple Machines, Synopsys, Cadence and others.

In their mini paper they say many nice things but the significant parts in my opinion are found in the concluding paragraph which I have broken up into three points:


1. The second-generation Akida processor IP is available now from BrainChip for inclusion in any SoC and comes complete with a software stack tuned for this unique architecture.

2. We encourage companies to investigate this technology, especially those implementing time series or sequential data applications.

3. Given that GenAI and LLMs generally involve sequence prediction, and advances made for pre-trained language models for event-based architectures with SpikeGPT, the compactness and capabilities of BrainChip’s TENNs and the availability of Vision Transformer …second-generation Akida could facilitate more GenAI capabilities at the Edge.


In Summary:

There is a massive shortage of GPU chips to run GenAi and this shortage is going to extend into the next year and a half at least.

Cambrian Ai has told the World that they should be looking at AKIDA Second Generation to facilitate GenAi capabilities at the Edge.

If Cambrian Ai only pass on their opinion to their existing customer base this is still a very large portion of the technology market where AKIDA Second Generation could profitably be adopted.


As we all should know AKIDA technology reduces bandwidth by processing data collected at the EDGE into relevant meta data and in so doing reduces processing demand in the Cloud be it public or private.

Peter van der Made is on record stating that AKIDA technology at the EDGE doing its thing can reduce the use of power in the Cloud by up to 97%.


It just makes sense if you cannot get enough GPU’s to handle your GenAi workloads in the Cloud then one solution is to reduce the workload.

Cambrian is only stating the obvious when it asks companies to investigate what AKIDA Second Generation can do for them to facilitate their GenAi capabilities at the EDGE.

In my opinion there is no reason to doubt that Brainchip is finally on the cusp of publicly realising what we all have known for what seems like a lifetime. An EDGE technology revolution.

Validation of AKIDA technology Science Fiction has been coming thick and fast from diverse sources but of late the most impressive was from TATA researchers who found that AKIDA technology was 34 times more power efficient and 3.4 times faster than the Nvidia GPU that they were also trialling. I doubt that such findings by a company with the global presence of TATA will have been missed by those that matter in the technology space.

However this is my opinion only so be sure to DYOR.

Regards
Fact Finder
Love the statement by Sam Altman ( Open Ai )
"We"re so short on GPUs, the less people that use the tool, the better" ......................... :eek:

Bring on the bottleneck breaker, ........................ AKIDO ? ..................Right Sean? .................;)
 
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Gies

Regular
Today a mini report was released by Cambrian Ai covering the release of AKIDA Second Generation. The significance of this report cannot be overstated. I had held the opinion prior to reading this report that AKIDA Third Generation would be the IP that allowed Brainchip and its shareholders to capitalise on the obsessed CHATGpt technology world but I was clearly wrong.

Thank you Cambrian Ai for disclosing just what makes AKIDA Second Generation a potential love child of CHATGpt or more generally GenAi.

To explain why I hold the opinion that today's reveal by Cambrian Ai is of such significance I have set out here a series of FACTS which I believe justifies my opinion.


From CNN —
The crushing demand for AI has also revealed the limits of the global supply chain for powerful chips used to develop and field AI models.
The continuing chip crunch has affected businesses large and small, including some of the AI industry’s leading platforms and may not meaningfully improve for at least a year or more, according to industry analysts.
The latest sign of a potentially extended shortage in AI chips came
webicon_green.png
in Microsoft’s annual report recently. The report identifies, for the first time, the availability of graphics processing units (GPUs) as a possible risk factor for investors.
GPUs are a critical type of hardware that helps run the countless calculations involved in training and deploying artificial intelligence algorithms.
“We continue to identify and evaluate opportunities to expand our datacenter locations and increase our server capacity to meet the evolving needs of our customers, particularly given the growing demand for AI services,” Microsoft wrote. “Our datacenters depend on the availability of permitted and buildable land, predictable energy, networking supplies, and servers, including graphics processing units (‘GPUs’) and other components.”
Microsoft’s nod to GPUs highlights how access to computing power serves as a critical bottleneck for AI. The issue directly affects companies that are building AI tools and products, and indirectly affects businesses and end-users who hope to apply the technology for their own purposes.
OpenAI CEO Sam Altman, testifying before the US Senate in May, suggested that the company’s chatbot tool was struggling to keep up with the number of requests users were throwing at it.
“We’re so short on GPUs, the less people that use the tool, the better,” Altman said. An OpenAI spokesperson later told CNN the company is committed to ensuring enough capacity for users.
The problem may sound reminiscent of the pandemic-era shortages in popular consumer electronics that saw gaming enthusiasts paying substantially inflated prices for game consoles and PC graphics cards. At the time, manufacturing delays, a lack of labor, disruptions to global shipping and persistent competing demand from cryptocurrency miners contributed to the scarce supply of GPUs,
webicon_green.png
spurring a cottage industry of deal-tracking tech to help ordinary consumers find what they needed."


Cambrian Ai's mini paper on Brainchip and Second Gen AKIDA can be found via Cambrian Ai's Homepage at:
webicon_gray.png
https://cambrian-ai.com/
On their Homepage they state that they work with the following companies: Cerebras, Esperanto Technologies, Graphcore, IBM, Intel, NVIDIA, Qualcomm, Tenstorrent, SiFive, Simple Machines, Synopsys, Cadence and others.

In their mini paper they say many nice things but the significant parts in my opinion are found in the concluding paragraph which I have broken up into three points:


1. The second-generation Akida processor IP is available now from BrainChip for inclusion in any SoC and comes complete with a software stack tuned for this unique architecture.

2. We encourage companies to investigate this technology, especially those implementing time series or sequential data applications.

3. Given that GenAI and LLMs generally involve sequence prediction, and advances made for pre-trained language models for event-based architectures with SpikeGPT, the compactness and capabilities of BrainChip’s TENNs and the availability of Vision Transformer …second-generation Akida could facilitate more GenAI capabilities at the Edge.


In Summary:

There is a massive shortage of GPU chips to run GenAi and this shortage is going to extend into the next year and a half at least.

Cambrian Ai has told the World that they should be looking at AKIDA Second Generation to facilitate GenAi capabilities at the Edge.

If Cambrian Ai only pass on their opinion to their existing customer base this is still a very large portion of the technology market where AKIDA Second Generation could profitably be adopted.


As we all should know AKIDA technology reduces bandwidth by processing data collected at the EDGE into relevant meta data and in so doing reduces processing demand in the Cloud be it public or private.

Peter van der Made is on record stating that AKIDA technology at the EDGE doing its thing can reduce the use of power in the Cloud by up to 97%.


It just makes sense if you cannot get enough GPU’s to handle your GenAi workloads in the Cloud then one solution is to reduce the workload.

Cambrian is only stating the obvious when it asks companies to investigate what AKIDA Second Generation can do for them to facilitate their GenAi capabilities at the EDGE.

In my opinion there is no reason to doubt that Brainchip is finally on the cusp of publicly realising what we all have known for what seems like a lifetime. An EDGE technology revolution.

Validation of AKIDA technology Science Fiction has been coming thick and fast from diverse sources but of late the most impressive was from TATA researchers who found that AKIDA technology was 34 times more power efficient and 3.4 times faster than the Nvidia GPU that they were also trialling. I doubt that such findings by a company with the global presence of TATA will have been missed by those that matter in the technology space.

However this is my opinion only so be sure to DYOR.

Regards
Fact Finder
Nice FF
Thanks for your info
 
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