BRN Discussion Ongoing

[Deleted member 118]

View attachment 38423

Now wouldn’t it be nice if this rumour involved megachips in someway

 

[alwaysgreen]

AMDs latest AI heavy presentation.

No mention of Brainchip.

 

[goodvibes]

Rob Telson likes it…me too.

Introducing the Mercedes-Benz Vision One-Eleven: Redefining automotive excellence.

#mercedesbenz #visiononeeleven #c111 | Mercedes-Benz AG | 232 comments

Introducing the Mercedes-Benz Vision One-Eleven: Redefining automotive excellence. We are thrilled to introduce the world to the Mercedes-Benz Vision One-Eleven, a paradigm-shifting sports car concept that epitomizes the fusion of design, technology and sustainability. As a progressive...

www.linkedin.com

We are thrilled to introduce the world to the Mercedes-Benz Vision One-Eleven, a paradigm-shifting sports car concept that epitomizes the fusion of design, technology and sustainability. As a progressive interpretation of the 1970s icon, the Vision One-Eleven pays homage to the legendary C 111 experimental vehicles, while propelling us into a new era of automotive excellence. With the inclusion of YASA's axial flux motors, the Vision One-Eleven achieves remarkable power density and efficiency, outperforming radial motors of similar nature.

This visionary masterpiece is showcasing a highly dynamic design language and innovative all-electric drive technology. Experience the pinnacle of ICONIC LUXURY as we redefine the boundaries of what's possible in the automotive industry

Experience more on mb4.me/MBVision111
#mercedesbenz #VisionOneEleven #C111

 

[Deleted member 118]

Only 2 patents I can find any relevance to Nintendo but I guess these have been look at before

SYSTEMS AND METHODS FOR MACHINE LEARNED IMAGE CONVERSION - NINTENDO CO., LTD.

<div p-id="p-0001">A computer system is provided for converting images through use of a trained neural network. A source image is divided into blocks and context data is added to each pixel block. The

www.freepatentsonline.com

SYSTEMS AND METHODS FOR MACHINE LEARNED IMAGE CONVERSION - NINTENDO CO., LTD.

<div p-id="p-0001">A computer system is provided for converting images through use of a trained neural network. A source image is divided into blocks and context data is added to each pixel block. The

www.freepatentsonline.com

 

[TheFunkMachine]

https://www.linkedin.com/posts/chro...4-tzYU?utm_source=share&utm_medium=member_ios

Do we think this solution from Ultraleap in partnership with Prophesee and Sony could have Akida inside?

It does say #neuromorphic

 

[SharesForBrekky]

Interesting steps Mercedes Benz is taking, looking to incorporate ChatGPT into their infotainment system:

Mercedes-Benz is bringing ChatGPT into cars for the first time

Its MBUX AI will be able to hold conversations with drivers

www.techradar.com

 

[Euzor]

Interesting steps Mercedes Benz is taking, looking to incorporate ChatGPT into their infotainment system:

Mercedes-Benz is bringing ChatGPT into cars for the first time

Its MBUX AI will be able to hold conversations with drivers

www.techradar.com

Yes was just about to post the same. Mentions hey mercedes voice system but not BRN explicitly.
The share price could do with some love...

 

[IloveLamp]

Interesting steps Mercedes Benz is taking, looking to incorporate ChatGPT into their infotainment system:

Mercedes-Benz is bringing ChatGPT into cars for the first time

Its MBUX AI will be able to hold conversations with drivers

www.techradar.com

 

[Tuliptrader]

Only 2 patents I can find any relevance to Nintendo but I guess these have been look at before

SYSTEMS AND METHODS FOR MACHINE LEARNED IMAGE CONVERSION - NINTENDO CO., LTD.

<div p-id="p-0001">A computer system is provided for converting images through use of a trained neural network. A source image is divided into blocks and context data is added to each pixel block. The

www.freepatentsonline.com

SYSTEMS AND METHODS FOR MACHINE LEARNED IMAGE CONVERSION - NINTENDO CO., LTD.

<div p-id="p-0001">A computer system is provided for converting images through use of a trained neural network. A source image is divided into blocks and context data is added to each pixel block. The

www.freepatentsonline.com

Nice find @Rocket577

It definitely shows that Nintendo are playing in our "sandbox". Still talking back propagation though.

I highlighted a paragraph I found interesting.

US20230019874A1 - Systems and methods of neural network training - Google Patents

A computer system is provided for training a neural network that converts images. Input images are applied to the neural network and a difference in image values is determined between predicted image data and target image data. A Fast Fourier Transform is taken of the difference. The neural...

patents.google.com

Systems and methods of neural network training​

Abstract​

A computer system is provided for training a neural network that converts images. Input images are applied to the neural network and a difference in image values is determined between predicted image data and target image data. A Fast Fourier Transform is taken of the difference. The neural network is trained on based the L1 Norm of resulting frequency data.

• TECHNICAL OVERVIEW
• [0002]
  The technology described herein relates to machine learning and training machine learned models or systems. More particularly, the technology described includes subject matter that relates to training neural networks to convert or upscale images by using, for example, Fourier Transforms (FTs).
• INTRODUCTION
• [0003]
  Machine learning can give computers the ability to “learn” a specific task without expressly programming the computer for that task. An example of machine learning systems includes deep learning neural networks. Such networks (and other forms of machine learning) can be used to, for example, help with automatically recognizing whether a cat is in a photograph. The learning takes place by using thousands or millions of photos to “train” the network (also called a model) to recognize when a cat is in a photograph. The training process can include, for example, determining weights for the model that achieve the indicated goal (e.g., identifying cats within a photo). The training process may include using a loss function in a way (e.g., via backpropagation) that seeks to train the model or neural network that will minimize the loss represented by the function. Different loss functions include L1 (Least Absolute Deviations) and L2 (Least Square Errors) loss functions.
• [0004]
  It will be appreciated that new and improved techniques, systems, and processes are continually sought after in these areas of technology, such as technology that is used to train machine learned models or neural networks.
• SUMMARY
• [0005]
  In some examples, computer system for training a neural network that processes images is provided. In some examples, the system is used to train neural networks to upscale images from one resolution to another resolution. The system may include computer storage that stores image data for a plurality of images. The system may be configured to generate, from the plurality of images, input image data and then apply the input image data to a neural network to generate predicted output image data. A difference between the predicted output image data and target image data is calculated and that difference may then be transformed in frequency domain data. In some examples, the L1-loss is then used on the frequency domain data calculated from the difference, which is then used to train the neural network using backpropagation (e.g., stochastic gradient descent). Using the L1 loss may encourage sparsity of the frequency domain data, which may also be referred to, or part of, Compressed Sensing. In contrast, using the L2 loss on the same frequency domain data may generally not produce in good results due to, for example, Parseval's Theorem. In other words, the L2 loss of frequency transformed data, using a Fourier Transform, is the same as the L2 loss of the data—i.e., L2(FFT(data))=L2(data). Thus, frequency transforming the data when using an L2 loss may not produce different results.

TT

 

[Tuliptrader]

Nice find @Rocket577

It definitely shows that Nintendo are playing in our "sandbox". Still talking back propagation though.

I highlighted a paragraph I found interesting.

US20230019874A1 - Systems and methods of neural network training - Google Patents

A computer system is provided for training a neural network that converts images. Input images are applied to the neural network and a difference in image values is determined between predicted image data and target image data. A Fast Fourier Transform is taken of the difference. The neural...

patents.google.com

Systems and methods of neural network training​

Abstract​

A computer system is provided for training a neural network that converts images. Input images are applied to the neural network and a difference in image values is determined between predicted image data and target image data. A Fast Fourier Transform is taken of the difference. The neural network is trained on based the L1 Norm of resulting frequency data.

• TECHNICAL OVERVIEW
• [0002]
  The technology described herein relates to machine learning and training machine learned models or systems. More particularly, the technology described includes subject matter that relates to training neural networks to convert or upscale images by using, for example, Fourier Transforms (FTs).
• INTRODUCTION
• [0003]
  Machine learning can give computers the ability to “learn” a specific task without expressly programming the computer for that task. An example of machine learning systems includes deep learning neural networks. Such networks (and other forms of machine learning) can be used to, for example, help with automatically recognizing whether a cat is in a photograph. The learning takes place by using thousands or millions of photos to “train” the network (also called a model) to recognize when a cat is in a photograph. The training process can include, for example, determining weights for the model that achieve the indicated goal (e.g., identifying cats within a photo). The training process may include using a loss function in a way (e.g., via backpropagation) that seeks to train the model or neural network that will minimize the loss represented by the function. Different loss functions include L1 (Least Absolute Deviations) and L2 (Least Square Errors) loss functions.
• [0004]
  It will be appreciated that new and improved techniques, systems, and processes are continually sought after in these areas of technology, such as technology that is used to train machine learned models or neural networks.
• SUMMARY
• [0005]
  In some examples, computer system for training a neural network that processes images is provided. In some examples, the system is used to train neural networks to upscale images from one resolution to another resolution. The system may include computer storage that stores image data for a plurality of images. The system may be configured to generate, from the plurality of images, input image data and then apply the input image data to a neural network to generate predicted output image data. A difference between the predicted output image data and target image data is calculated and that difference may then be transformed in frequency domain data. In some examples, the L1-loss is then used on the frequency domain data calculated from the difference, which is then used to train the neural network using backpropagation (e.g., stochastic gradient descent). Using the L1 loss may encourage sparsity of the frequency domain data, which may also be referred to, or part of, Compressed Sensing. In contrast, using the L2 loss on the same frequency domain data may generally not produce in good results due to, for example, Parseval's Theorem. In other words, the L2 loss of frequency transformed data, using a Fourier Transform, is the same as the L2 loss of the data—i.e., L2(FFT(data))=L2(data). Thus, frequency transforming the data when using an L2 loss may not produce different results.

TT

A question for @Diogenese

Could the Fast Fourier Transform (FFT) action in this patent be effectively replaced and improved by Akida 2.0

TT

 

[Esq.111]

Good Morning Chippers,

Quick reminder,

Today is Quadruple Witching Day on our market.

Should see elevated volume transacting today with rebalancing from Funds, Indexes & Hedge Funds ballancing their portfolio.

Evident by pre market trades on alot of Australia shares already.

Regards,
Esq.

 

[buena suerte :-)]

Good Morning Chippers,

Quick reminder,

Today is Quadruple Witching Day on our market.

Should see elevated volume transacting today with rebalancing from Funds, Indexes & Hedge Funds ballancing their portfolio.

Evident by pre market trades on alot of Australia shares already.

Regards,
Esq.

And positive markets to run with also !!

 

[supersonic001]

#mercedesbenz #visiononeeleven #c111 | Mercedes-Benz AG | 232 comments

Introducing the Mercedes-Benz Vision One-Eleven: Redefining automotive excellence. We are thrilled to introduce the world to the Mercedes-Benz Vision One-Eleven, a paradigm-shifting sports car concept that epitomizes the fusion of design, technology and sustainability. As a progressive...

www.linkedin.com

RT likes this, so do I

 

[Vladsblood]

And all happening on a Friday too!
We need the yankee Bull Market to continue through tonight and into their Monday to get a good run going though !
Nvidia is now one of the big players Trillion Plus Club and they are very aware of Brainchip/Akida.
By end of 23’ we should be moving forward rapidly IMO.
Wish I had more money at the current price .
Avagreatweegend Chippers Vlad.

 

[Diogenese]

A question for @Diogenese

Could the Fast Fourier Transform (FFT) action in this patent be effectively replaced and improved by Akida 2.0

TT

Que?

https://tenor.com/view/fawlty-towers-fawltytowers-manuel-know-gif-9682901

 

[Iseki]

Now wouldn’t it be nice if this rumour involved megachips in someway

great Find!
Hopefully the neuromorphic component will be more about a game recognizing a player's strategy, and learning to fight that strategy so making each person's game experience much richer - the game player will need to keep adapting to the ever learning game.
I think it was you @Rocket577 who said a few years back IF only a game would come out using akida, that would open others to using it everywhere.

Whatever change Nintendo are coming up with it will be big because they have held off bringing out new versions for a long time. Only cloud is that they currently use NVIDIA chips, and while akida is processor agnostic, NVIDIA never seems to work with others.

great find and great source of hope

 

[TheFunkMachine]

https://www.linkedin.com/posts/vign...5-zE6S?utm_source=share&utm_medium=member_ios

Our Boy Sean Heir sitting at the seat with the big Boys. I want to hear the discussion!

 

[buena suerte :-)]

https://www.linkedin.com/posts/vign...5-zE6S?utm_source=share&utm_medium=member_ios

Our Boy Sean Heir sitting at the seat with the big Boys. I want to hear the discussion!

 

[buena suerte :-)]

https://www.linkedin.com/posts/vign...5-zE6S?utm_source=share&utm_medium=member_ios

Our Boy Sean Heir sitting at the seat with the big Boys. I want to hear the discussion!

Nice find TFM .....

 

[robsmark]

View attachment 38444

Discussion - Automotive Supply Chain Challanges

Panel: “So Mr Hehir, what have your recent automotive supply chain challenges been?”

Sean Hehir: “Yeah, we’re finding it a challenge to find an automotive manufacturer to supply our product to… so yeah…”

JK, kinda