BRN Discussion Ongoing

[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]

Mercedes-Benz AG on LinkedIn: #mercedesbenz #visiononeeleven #c111 | 232 comments

Introducing the Mercedes-Benz Vision One-Eleven: Redefining automotive excellence. We are thrilled to introduce the world to the Mercedes-Benz Vision… | 232 comments on LinkedIn

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

 

[Bravo]

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

The patent refers to ASICs. And MegaChips is now delivering its full-service ASIC solution in the US and offering off-the-shelf access to industry-standard IP components, such as ours. So couldn't they just squish AKIDA 1500 into the ASIC so the existing patent would still be applicable?

PS: I'm not an engineer and I frequently have no idea what I'm talking about.

 

[GDJR69]

It's all slowly coming together and in the not so distant future I believe the days of little or no revenue will be a distant memory . . .

 

[IloveLamp]

Intel Announces Major Brand Update Ahead of Upcoming Meteor Lake...

Biggest brand update in 15 years ushers in a new era for Intel Core, Intel Evo and Intel vPro brands.

www.intel.com

“Our client roadmap demonstrates how Intel is prioritizing innovation and technology leadership with products like Meteor Lake, focused on power efficiency and AI at scale. To better align with our product strategies, we are introducing a branding structure that will help PC buyers better differentiate the best of our latest technology and our mainstream offerings.”

–Caitlin Anderson, Intel vice president and general manager of Client Computing Group Sales

 

[Deleted member 118]

The patent refers to ASICs. And MegaChips is now delivering its full-service ASIC solution in the US and offering off-the-shelf access to industry-standard IP components, such as ours. So couldn't they just squish AKIDA 1500 into the ASIC so the existing patent would still be applicable?

PS: I'm not an engineer and I frequently have no idea what I'm talking about.



View attachment 38447
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[IloveLamp]

https://www.thestreet.com/technology/elon-musk-makes-an-offer-to-toyota

 

[mrgds]

https://www.thestreet.com/technology/elon-musk-makes-an-offer-to-toyota

No need for Musk to "offer Toyota" ...................... In time "all other OEMs will approach Tesla.

 

[Bennysmadness]

Very Interesting

 

[Diogenese]

https://www.thestreet.com/technology/elon-musk-makes-an-offer-to-toyota

The headline reminds me of the ant floating on a leaf down the river on his back with an erection shouting "Raise the drawbridge!"

 

[Bravo]

My carrots are bigger than yours!

 

[IloveLamp]

The headline reminds me of the ant floating on a leaf down the river on his back with an erection shouting "Raise the drawbridge!"

 

[IloveLamp]

A plug-and-play edge ML device

BrickML is a low-power high-performance self-contained embedded device designed to run machine learning operations at the edge in ....

www.eenewseurope.com