BRN Discussion Ongoing

[mrgds]

With all this conversation regarding "short selling, algorithuims etc" ................ im just wondering if anyone has checked in on @Bravo
as the last i saw she was sitting in the 0.50c Hot Tube, ................please tell me she is not a shrivalled prune! .........

I know this has been discussed many times before, and @TECH will hate me for bringing it up again, ...........................................BUT
To me this trading recently is feeling more and more like the build up to a "Take Over Offer "..................

To my untrained understanding of the "mercy, dark pools that control the s/p movement " recently the volumes and % increase/decrease
in the s/p has me wondering if a T/O may present itself in the next 3-6 mths ?

We all are witnessing the volativity lately, ...................................... is this for,
Accumulation ...... ( BlackRock, SoftBank )
Confiscation ....... ( From retail )
Manipulation ...... ( Of course, day traders/accumulators )
Consolidation ...... ( IMO...... yes indeedy )
Procrastination ...... ( not the accumulators )
Masterbation ...... ( Well, YES, ............... @TheDrooben showed us his excitment today ................ ................... )

At 1.8 billion SOI, ..................... would the first "bid " come in around $5.00 ?

As with ASX-LTR ( just some lithium in the ground, large deposit/high grade ) ...................... 1st bid at $2.50 ( Albermale ) , currently trading $2.77, been as high as $3.02. ........... SOI 2.2 billion.

DETERMINATION ................. make your own judgement, ....................... but i know where im happily invested and DETERMINED to hang in
through this very exciting period for BRN

AKIDO ( pretty, pretty, pretty happy ) BALLISTO

 

[Cardpro]

I don't get why people are disappointed that it was another punp and dump... it had no reason to go up, the partnership announcement was another one with another small company... it almost feels like we are offering free services to small companies who can't afford the fees... hopefully one or two ends up being successful to pay for our products... only thing that can move our share price is new IP contracts or confirmed deal with massive corporates or cash inflows / revenue...

 

[Sirod69]

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[Cardpro]

Hi @Rach2512

suggest watch ‘GAMESTOCK, Eat the rich’ on NETFLIX.
It explains shorting on there in general terms.

It‘s an eye opener on how corrupt the market is!

We can fk up the shorters if we prove what we worth with revenue or contracts which we were not able to get for past 7 years or so for w/e reasons but hopefully it will happen one day....

 

[The Pope]

no one got it Diog, but im pissing myself, hahahhaha

I certainly did but forgot I should reply to champagne comedy.

 

[Jchandel]

I was looking for some advancements with Prophesee & Brainchip partnership and found the below article from March 2023. This may have been posted earlier, but the last paragraph got me a wee bit excited.

Qualcomm, Prophesee team up to increase camera performance in mobile devices | Edge Industry Review

Qualcomm can utilize Prophesee’s Metavision sensors and software to enhance image quality in low-light settings and fast-moving scenes.

www.edgeir.com

 

[Andy38]

I was looking for some advancements with Prophesee & Brainchip partnership and found the below article from March 2023. This may have been posted earlier, but the last paragraph got me a wee bit excited.

Qualcomm, Prophesee team up to increase camera performance in mobile devices | Edge Industry Review

Qualcomm can utilize Prophesee’s Metavision sensors and software to enhance image quality in low-light settings and fast-moving scenes.

www.edgeir.com

@Bravo surprised this last paragraph hasn’t got you jumping out of your skin!!

 

[Diogenese]

So speaking of shorts, I still can't quite get my head around the whole process. Are institution's lending shares to shorters. The shorters then sell those shares and hope that in the process of selling the borrowerd shares they spook the market so the price drops and they then buy back in and pass the shares back to the institutions having made a profit. If that is the case and the institutions are actually scooping up shares during this process (as their holdings are increasing) then the price is probably not dropping as much as the shorters would like or they could be preventing them from buying back in. Sorry that probably sounds very stupid. Am I missing something or everything!!!

Sounds like the old bootstrap theory - if you pull up on your shoelaces hard enough, you can lift your feet off the ground.

 

[Draed]

My opinion re: games being played on this stock goes as follows. It's a good company with a great innovative technology. But, it takes time to get to market. It will happen, but its just taking longer than hoped. We all know that.

But what has the institutional investors pissed off is the high percentage of retail investors, and stubborn ones at that. They want as many stocks as they can in their hands. For the eventual lift off. I.e when all the testing and validation is done, design production marketing and products on shelves. The institutions love this because ndas are in place and nothing will happen till money starts appearing in the bank. So, they sow the story that it's a dud, the tech isn't going anywhere, no sales are taking place.

and vecause there is a long cycle with low chance of suprise announcements, they sell it down and maintain an aggressive short selling campaign To spook retail into selling at a loss.

One day the price will pump, without an announcement, just like it has multiple times in the last year or so. Some retail investors will think "ahhh another pump and dump". I'll sell for a tidy profit or break even and buy back in at a lower price.

But I'm sure that one time I even think of attempting that, it will be an announcement like ,"ahhh telsa wants to incoperate akida into every car sensor they have"...Or "a new licence with samsung" etc.

This is pure speculation with no research to back it up. But hey, it's just how I think it will play out. Maybe not telsa to start with though.

 

[Fullmoonfever]

Not saying involves us but wondering what's special, if at all, with GF 22nm and neuromorphic? Other than previous connections to NASA preferences on that type as well.

This Uni team presented their work at the recent GOMACTech in the US.

Program HERE

 

[Diogenese]

Not saying involves us but wondering what's special, if at all, with GF 22nm and neuromorphic? Other than previous connections to NASA preferences on that type as well.

This Uni team presented their work at the recent GOMACTech in the US.

Program HERE

View attachment 37968

View attachment 37967

Hi Fmf,

The term "neuromorphic image sensors" is used to refer to event cameras/DVS like Prophesee.

My opinion re: games being played on this stock goes as follows. It's a good company with a great innovative technology. But, it takes time to get to market. It will happen, but its just taking longer than hoped. We all know that.

But what has the institutional investors pissed off is the high percentage of retail investors, and stubborn ones at that. They want as many stocks as they can in their hands. For the eventual lift off. I.e when all the testing and validation is done, design production marketing and products on shelves. The institutions love this because ndas are in place and nothing will happen till money starts appearing in the bank. So, they sow the story that it's a dud, the tech isn't going anywhere, no sales are taking place.

and vecause there is a long cycle with low chance of suprise announcements, they sell it down and maintain an aggressive short selling campaign To spook retail into selling at a loss.

One day the price will pump, without an announcement, just like it has multiple times in the last year or so. Some retail investors will think "ahhh another pump and dump". I'll sell for a tidy profit or break even and buy back in at a lower price.

But I'm sure that one time I even think of attempting that, it will be an announcement like ,"ahhh telsa wants to incoperate akida into every car sensor they have"...Or "a new licence with samsung" etc.

This is pure speculation with no research to back it up. But hey, it's just how I think it will play out. Maybe not telsa to start with though.

That's right. Every day we don't have a licence announcement is a day closer to a licence announcement.

 

[Fullmoonfever]

Also good to see the USAF Space Force program still chasing neuromorphic / cortical solutions and amalgamating the project into another for 2024.

Original paper HERE

 

[Fullmoonfever]

Hi Fmf,

The term "neuromorphic image sensors" is used to refer to event cameras/DVS like Prophesee.

That's right. Every day we don't have a licence announcement is a day closer to a licence announcement.

Cheers.

Yeah, got my head around the Davis and Prophesee solutions and mused as to the "simulations" on a GF 22nm given we provide some Unis the ability to run simulations (think this is correct?) and we taped out on the GF 22nm FDSOI.

I don't expect much to it, was just interesting I thought.

 

[Diogenese]

Also good to see the USAF Space Force program still chasing neuromorphic / cortical solutions and amalgamating the project into another for 2024.

Original paper HERE

View attachment 37969

When did you meet Chelsea Manning?

 

[Fullmoonfever]

When did you meet Chelsea Manning?

 

[Fullmoonfever]

Also see Northrop playing with DVS.

Mention they been working (trying haha) with John's Hopkins for a decade

Was trying to find any link anywhere with us or Prophesee etc to Northrop or JHU.

Maybe they need to get with the Akida program

Couldn't find a date of the article.

Neuromorphic Cameras Provide a Vision of the Future | Northrop Grumman

From enhanced battlefield protection systems to maintaining aerial drone delivery fleets, neuromorphic cameras hold promise for the future.

www.northropgrumman.com

Neuromorphic Cameras Provide a Vision of the Future​

Neuromorphic Cameras Provide a Vision of the Future
From enhanced battlefield protection systems to maintaining aerial drone delivery fleets, neuromorphic cameras hold promise for the future.

By Scott Gourley
From enhanced battlefield protection systems to maintaining aerial drone delivery fleets, neuromorphic cameras have the potential to enhance many future defense, commercial and industrial tasks. When coupled with machine learning, this technology may soon set the stage for dramatic enhancements in how systems operate and how we perceive and understand surrounding environments.

Like the Human Eye​

“Cameras we use today have an array of pixels: 1024 by 768,” explained Isidoros Doxas, an AI Systems Architect at Northrop Grumman. “And each pixel essentially measures the amount of light or number of photons falling on it. That number is called the flux. Now, if you display the same numbers on a screen, you will see the same image that fell on your camera.”
By contrast, neuromorphic cameras only report changes in flux. If the rate of photons falling on a pixel doesn’t change, they report nothing.
“If a constant 1,000 photons per second is falling on a pixel, it basically says, ‘I’m good, nothing happened.’ But, if at some point there are now 1,100 photons per second falling on the pixel, it will report that change in flux,” Doxas said.
“Surprisingly, this is exactly how the human eye works,” he added. “You may think that your eye reports the image that you see. But it doesn’t. All that stuff is in your head. All the eye reports are little blips saying ‘up’ or ‘down.’ The image we perceive is built by our brains.”


You need a lot of energy to send a number from pixel to computer or from eye to brain. And you don’t want to spend all that energy. In fact, that’s why people started thinking about building neuromorphic cameras. They require much less energy because the pixels just report changes and not actual values.”
Isidoros Doxas
Northrop Grumman AI Systems Architect

Advantages of Neuromorphic Cameras​

Doxas identified several advantages in neuromorphic imaging, beginning with reduced power requirements.
“You need a lot of energy to send a number from pixel to computer or from eye to brain,” he said. “And you don’t want to spend all that energy. In fact, that’s why people started thinking about building neuromorphic cameras. They require much less energy because the pixels just report changes and not actual values.”
He continued, “Another important advantage is speed. If you have a million pixels, and you have to send the computer a thousand frames per second, that’s one billion numbers per second. However, usually nothing changes in a scene from one millisecond to the next, so you don’t need to report that entire image.”

Doxas likened the process to compression methods for video entertainment, noting that a 4K-resolution movie represents 8 million pixels, times three colors, times 30 frames per second.
“That’s over a gigabyte per second,” he said. “Yet, you can watch that over an internet connection that’s only a few megabits per second. That’s because little changes from one frame to the next. They leverage that fact and compress frames in the same way. The difference here is that neuromorphic cameras do the compression.”
Decompression is accomplished by computers, where reporting speeds accelerating from one to tens of thousands of frames per second allow for millisecond reaction times. This paves the way for a huge range of different applications — from active combat systems detecting and defeating a bullet, to self-driving cars interpreting dangerous situations almost instantly.
Doxas said that Northrop Grumman has been involved with the technology for more than a decade, highlighting a collaboration with Johns Hopkins University that resulted in the recent design of a readout integrated circuit as well as “the brains that go behind that circuitry.”
Future efforts will include increasing the number of pixels, further lowering power and increasing resolution.

Coupling with Machine Learning​

Optimizing the new camera technology involves the application of machine learning methods that can work directly with the photon plus and minus signals. With self-driving cars, for example, machine learning can construct an image of a cat or dog with just a few pixel pluses or minuses, resulting in much quicker decisions compared with images built by convolutional neural network sensors.
“In the same vein, Northrop Grumman can use this system for non-invasive diagnostics for high-speed parts. This technology will dramatically change power requirements and time to decision across any number of applications,” Doxas concluded.

 

[Fullmoonfever]

Also see Northrop playing with DVS.

Mention they been working (trying haha) with John's Hopkins for a decade

Was trying to find any link anywhere with us or Prophesee etc to Northrop or JHU.

Maybe they need to get with the Akida program

Couldn't find a date of the article.

Neuromorphic Cameras Provide a Vision of the Future | Northrop Grumman

From enhanced battlefield protection systems to maintaining aerial drone delivery fleets, neuromorphic cameras hold promise for the future.

www.northropgrumman.com

Neuromorphic Cameras Provide a Vision of the Future​

Neuromorphic Cameras Provide a Vision of the Future
From enhanced battlefield protection systems to maintaining aerial drone delivery fleets, neuromorphic cameras hold promise for the future.

By Scott Gourley
From enhanced battlefield protection systems to maintaining aerial drone delivery fleets, neuromorphic cameras have the potential to enhance many future defense, commercial and industrial tasks. When coupled with machine learning, this technology may soon set the stage for dramatic enhancements in how systems operate and how we perceive and understand surrounding environments.

Like the Human Eye​

“Cameras we use today have an array of pixels: 1024 by 768,” explained Isidoros Doxas, an AI Systems Architect at Northrop Grumman. “And each pixel essentially measures the amount of light or number of photons falling on it. That number is called the flux. Now, if you display the same numbers on a screen, you will see the same image that fell on your camera.”
By contrast, neuromorphic cameras only report changes in flux. If the rate of photons falling on a pixel doesn’t change, they report nothing.
“If a constant 1,000 photons per second is falling on a pixel, it basically says, ‘I’m good, nothing happened.’ But, if at some point there are now 1,100 photons per second falling on the pixel, it will report that change in flux,” Doxas said.
“Surprisingly, this is exactly how the human eye works,” he added. “You may think that your eye reports the image that you see. But it doesn’t. All that stuff is in your head. All the eye reports are little blips saying ‘up’ or ‘down.’ The image we perceive is built by our brains.”


You need a lot of energy to send a number from pixel to computer or from eye to brain. And you don’t want to spend all that energy. In fact, that’s why people started thinking about building neuromorphic cameras. They require much less energy because the pixels just report changes and not actual values.”
Isidoros Doxas
Northrop Grumman AI Systems Architect

Advantages of Neuromorphic Cameras​

Doxas identified several advantages in neuromorphic imaging, beginning with reduced power requirements.
“You need a lot of energy to send a number from pixel to computer or from eye to brain,” he said. “And you don’t want to spend all that energy. In fact, that’s why people started thinking about building neuromorphic cameras. They require much less energy because the pixels just report changes and not actual values.”
He continued, “Another important advantage is speed. If you have a million pixels, and you have to send the computer a thousand frames per second, that’s one billion numbers per second. However, usually nothing changes in a scene from one millisecond to the next, so you don’t need to report that entire image.”

Doxas likened the process to compression methods for video entertainment, noting that a 4K-resolution movie represents 8 million pixels, times three colors, times 30 frames per second.
“That’s over a gigabyte per second,” he said. “Yet, you can watch that over an internet connection that’s only a few megabits per second. That’s because little changes from one frame to the next. They leverage that fact and compress frames in the same way. The difference here is that neuromorphic cameras do the compression.”
Decompression is accomplished by computers, where reporting speeds accelerating from one to tens of thousands of frames per second allow for millisecond reaction times. This paves the way for a huge range of different applications — from active combat systems detecting and defeating a bullet, to self-driving cars interpreting dangerous situations almost instantly.
Doxas said that Northrop Grumman has been involved with the technology for more than a decade, highlighting a collaboration with Johns Hopkins University that resulted in the recent design of a readout integrated circuit as well as “the brains that go behind that circuitry.”
Future efforts will include increasing the number of pixels, further lowering power and increasing resolution.

Coupling with Machine Learning​

Optimizing the new camera technology involves the application of machine learning methods that can work directly with the photon plus and minus signals. With self-driving cars, for example, machine learning can construct an image of a cat or dog with just a few pixel pluses or minuses, resulting in much quicker decisions compared with images built by convolutional neural network sensors.
“In the same vein, Northrop Grumman can use this system for non-invasive diagnostics for high-speed parts. This technology will dramatically change power requirements and time to decision across any number of applications,” Doxas concluded.

Ok....looks like working with Intel Movidius research chip, as expected I guess.

Though interesting they were / are in negotiations with a small business current team member....that doesn't sound like Intel...maybe someone who uses Intel...or not

Original mid 22 paper HERE

 

[Fullmoonfever]

Wonder if Neil a SH or just checking in occasionally.

Liked one of FNNs posts with Rob Telson last year.

Neil used to work for Northrop for 16 yrs and also Raytheon.

Am I bored

Neil Wigner​

Chief System Engineer at SAIC​

SAICUniversity of Southern California​

Long Beach, California, United States