Investig8ed
Regular
My super is at 40% so can't buy anymore hopefully all of our super accounts one day are 80 to 90% BRN
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
Pom down under
Top 20
Hah ... that's nothing! My super is 94% invested in Brainchip.
cosors
👀
good movie
Fact Finder
Top 20
Hi All
Going back over old ground can yield much of interest. In the various interviews shared of Pat Gelsinger speaking at and being interviewed at the Intel Foundry event he mentions the intention to challenge Nvidia’s GPU dominance in the Cloud which has eroded Intel’s CPU market share. He did not say in detail how Intel intended to revive its CPUs to achieve this resurgence.
The following previously highlighted findings by these German Researchers could be pointing to what Intel has planned for AKIDA technology:
“C. Research Directions for SNNs in Machine Learning
As we approach the forefront of the current research, we suggest that the future lies in incorporating SNN-based models into mainstream applications, focusing on extending large- scale applications beyond image classification, refining training techniques, and optimizing mapping strategies for diverse hardware platforms. Efforts in standardization and compati- bility with existing frameworks will enhance SNN adoption across industries. Additionally, delving into novel applications, particularly in real-time scenarios, and further integration with transformer-based models could unlock new frontiers for SNN research. Emphasizing energy efficiency, economic viability, and scalability will be pivotal for solidifying SNNs as a key player in the evolving landscape of machine learning and neuromorphic computing.
V. HARDWARE AND SOFTWARE INTEGRATION
In this section, we discuss the hardware and software challenges for integrating neuromorphic hardware platforms into AI data centres.
A. Hardware integration
1) Status quo: So far, the following neuromorphic sys- tems have been integrated at large scale into data centers: SpiNNaker 1 [20], TrueNorth (NS16-4e) [83], Loihi (Po- hoiki Springs) [84], BrainScaleS-1 [85] and Tianjic [32]. All systems use slide-in modules with custom printed circuit boards (PCBs) for integration into standard 19” server racks. Typically, the neuromorphic chips are accessed via Ethernet, only the TrueNorth NS16e-4 uses PCIe for communication with the host chip. Baseboard Management Controller (BMC) or similar controllers are used for booting and monitoring the boards. All platforms also include field-programmable gate arrays (FPGAs) or system-on-chips (SoCs), most often as middleware between host computers and neuromorphic sys- tems. Some systems have already integrated a host CPU, e.g., Pohoiki Springs or the Tianjic server, while the other systems require external host CPU servers for the configuration and control of the neuromorphic systems and for preprocessing.
As an exception, BrainChip offers PCIe boards for integrating their Akida chips with CPU servers. This represents an- other option for integrating neuromorphic computing systems into data centres, similar to normal GPUs. Note, however, that this might limit the size of neuromorphic models that can be implemented compared to the larger systems discussed above.
2) Conclusion: The above examples show that a variety of neuromorphic systems have been successfully integrated into standard data center server racks. Thus, technically, the hardware integration does not pose a problem. Yet, we observe a diversity in how large neuromorphic systems are assembled into server boards, e.g., many of them leverage FPGAs or SoCs as middleware. These extra devices and the host CPU add a power overhead to the very energy-efficient neuromorphic systems. Optimizing for system-level efficiency of AI compute servers, these components need to be included when perform- ing benchmarking on AI workloads. Another requirement for the industry-level deployment of neuromorphic chips is high reliability and robustness. The chips and boards need to be designed for a 24/7 operation, e.g., the server board should keep working if a single chip or processor fails. Replacement parts should be available for a long period.“
https://arxiv.org/pdf/2402.02521
Watching a little bit of AKIDA magic being added to every Intel CPU on one of the new Intel process nodes would be fun to see as a Brainchip shareholder.
My opinion only DYOR
Fact Finder
Going back over old ground can yield much of interest. In the various interviews shared of Pat Gelsinger speaking at and being interviewed at the Intel Foundry event he mentions the intention to challenge Nvidia’s GPU dominance in the Cloud which has eroded Intel’s CPU market share. He did not say in detail how Intel intended to revive its CPUs to achieve this resurgence.
The following previously highlighted findings by these German Researchers could be pointing to what Intel has planned for AKIDA technology:
“C. Research Directions for SNNs in Machine Learning
As we approach the forefront of the current research, we suggest that the future lies in incorporating SNN-based models into mainstream applications, focusing on extending large- scale applications beyond image classification, refining training techniques, and optimizing mapping strategies for diverse hardware platforms. Efforts in standardization and compati- bility with existing frameworks will enhance SNN adoption across industries. Additionally, delving into novel applications, particularly in real-time scenarios, and further integration with transformer-based models could unlock new frontiers for SNN research. Emphasizing energy efficiency, economic viability, and scalability will be pivotal for solidifying SNNs as a key player in the evolving landscape of machine learning and neuromorphic computing.
V. HARDWARE AND SOFTWARE INTEGRATION
In this section, we discuss the hardware and software challenges for integrating neuromorphic hardware platforms into AI data centres.
A. Hardware integration
1) Status quo: So far, the following neuromorphic sys- tems have been integrated at large scale into data centers: SpiNNaker 1 [20], TrueNorth (NS16-4e) [83], Loihi (Po- hoiki Springs) [84], BrainScaleS-1 [85] and Tianjic [32]. All systems use slide-in modules with custom printed circuit boards (PCBs) for integration into standard 19” server racks. Typically, the neuromorphic chips are accessed via Ethernet, only the TrueNorth NS16e-4 uses PCIe for communication with the host chip. Baseboard Management Controller (BMC) or similar controllers are used for booting and monitoring the boards. All platforms also include field-programmable gate arrays (FPGAs) or system-on-chips (SoCs), most often as middleware between host computers and neuromorphic sys- tems. Some systems have already integrated a host CPU, e.g., Pohoiki Springs or the Tianjic server, while the other systems require external host CPU servers for the configuration and control of the neuromorphic systems and for preprocessing.
As an exception, BrainChip offers PCIe boards for integrating their Akida chips with CPU servers. This represents an- other option for integrating neuromorphic computing systems into data centres, similar to normal GPUs. Note, however, that this might limit the size of neuromorphic models that can be implemented compared to the larger systems discussed above.
2) Conclusion: The above examples show that a variety of neuromorphic systems have been successfully integrated into standard data center server racks. Thus, technically, the hardware integration does not pose a problem. Yet, we observe a diversity in how large neuromorphic systems are assembled into server boards, e.g., many of them leverage FPGAs or SoCs as middleware. These extra devices and the host CPU add a power overhead to the very energy-efficient neuromorphic systems. Optimizing for system-level efficiency of AI compute servers, these components need to be included when perform- ing benchmarking on AI workloads. Another requirement for the industry-level deployment of neuromorphic chips is high reliability and robustness. The chips and boards need to be designed for a 24/7 operation, e.g., the server board should keep working if a single chip or processor fails. Replacement parts should be available for a long period.“
Watching a little bit of AKIDA magic being added to every Intel CPU on one of the new Intel process nodes would be fun to see as a Brainchip shareholder.
My opinion only DYOR
Fact Finder
Vladsblood
Regular
MC @885 million…Soon to be 88.5 billion AND going into the NASDAQ SPLITS by end of 2024 hopefully 
With love from Russia Vlad.
With love from Russia Vlad.
TheDrooben
Pretty Pretty Pretty Pretty Good
Morgan Stanley getting interested in AI at the edge on smartphones.....
Happy as Larry
Happy as Larry
TheUnfairAdvantage
Regular
When you think back on the Intel presentation and just concentrate on the 2 slides showing Brainchip listed as an IP supplier and in bright lights amongst giants of the industry on the Partnership slide - that alone would place a value on Brainchip in the vacinity of $5 Billion USD. I think the US is just now discovering “who the Fcuk is Brainchip”.
We understand. The majority of Australian investment community has no idea. The Yanks sure as hell now know. The message to anyone shorting is about to come through like a tidal wave this week. Hold tight and enjoy what is about to happen. The Yanks are coming for your shares!
We understand. The majority of Australian investment community has no idea. The Yanks sure as hell now know. The message to anyone shorting is about to come through like a tidal wave this week. Hold tight and enjoy what is about to happen. The Yanks are coming for your shares!
DingoBorat
Slim
Very little on the sell side, below 49 cents, indicating no eagerness to do it..
A wall up at 55 cents..
Is it a strong one?
..Let's find out.
TheUnfairAdvantage
Regular
55 cents. Meh.Very little on the sell side, below 49 cents, indicating no eagerness to do it..
A wall up at 55 cents..
Is it a strong one?
Let's find out.
Mercedes drove us beyond $2 on hype. Intel is the real deal. Those share sitting at $1 is the wall
Good Morning Chippers ,
looking a little spicy pre open.
I'm going with an open of $0.53 then a rapid rise to $0.55 then
?????
Note . Mornignstar Quantitive , Random number generator has Undervalued , three star , and fair value at $0.68
ShootingStar , Present Fair Value still sits at $5.22 with five star rating.
Polly Rating , STRONG BUY
Not Financial Advice.
Regards,
Esq.
looking a little spicy pre open.
I'm going with an open of $0.53 then a rapid rise to $0.55 then
?????Note . Mornignstar Quantitive , Random number generator has Undervalued , three star , and fair value at $0.68
ShootingStar , Present Fair Value still sits at $5.22 with five star rating.
Polly Rating , STRONG BUY
Not Financial Advice.
Regards,
Esq.
Boab
I wish I could paint like Vincent
I can smell the blood of shorters. MmmmmmGood Morning Chippers ,
looking a little spicy pre open.
I'm going with an open of $0.53 then a rapid rise to $0.55 then
Note . Mornignstar Quantitive , Random number generator has Undervalued , three star , and fair value at $0.68
ShootingStar , Present Fair Value still sits at $5.22 with five star rating.
Polly Rating , STRONG BUY
Not Financial Advice.
Regards,
Esq.
Umm we hold the key to a revolutionary ip which is slowly but surely taking over the world?
Last edited:
DingoBorat
Slim
That's not the prices they want to buy at.
It just puts them at the front of the queue.
The same happens on the sell side.
It's normal, you probably have just not noticed it before.
Fair enough thanks. All ways thought it would clear at that price if I put on a buy.
Similar threads
