BRN Discussion Ongoing

[Dhm]

I was just watching an ad for Google Pixel Pro 7 smartphone and one of the features was un bluring of photos. Now I know Qualcomm used Prophesee/Synsense to do the same, but I wonder if Google might use someone else? perhaps like......us??

Edit: on further reflection the ad is talking about de blurring of existing photos, so not as exciting as I first though. But if Google know about what Akida can achieve with taking the original photo then all the better.

 

[mrgds]

I hope the link works?

@MC will be "barred up "............. ............. loves Audi

 

[MrNick]

I was just watching an ad for Google Pixel Pro 7 smartphone and one of the features was un bluring of photos. Now I know Qualcomm used Prophesee/Synsense to do the same, but I wonder if Google might use someone else? perhaps like......us??

Edit: on further reflection the ad is talking about de blurring of existing photos, so not as exciting as I first though. But if Google know about what Akida can achieve with taking the original photo then all the better.

Lytro were the first to move here but couldn’t capture enough market share to succeed.

Lytro - Wikipedia

en.m.wikipedia.org

 

[edski]

Good Lord, this (the new Audi) is wrong on so many levels. But if you got money to burn on such things.............never mind, I'm out.

 

[MDhere]

Do dreams count? had a very vivid dream that we were powering the next arcade game thingy where the player had a plastic gun thing and was shooting at pigs and other flying/pop up things in a field where the pigs would pop up but because ir was powered by akida it would immediately square on target identifying the pig and all u had to do was shoot straight. and on the screen was a Disney pixar symbol. and the best part was it was the quarter page colour ad feature on the left side of a page in this Sundays paper . my only thoughts were should be on the right side of parrier as right side attracts the most attention I better grab a paper i guess to check it for real Bring on Monday $$

 

[TasTroy77]

Is the motley fool short BRN ive never seen so much coverage twice a week

 

[Diogenese]

Is the motley fool short BRN ive never seen so much coverage twice a week View attachment 37349

You shouldn't speak on an empty brain.

 

[Diogenese]

Is the motley fool short BRN ive never seen so much coverage twice a week View attachment 37349

I read the other day that the bum-breathing turtle has extended its habitat range. Now it seems it has learnt to speak:

https://www.fool.com.au/2023/05/28/could-nvidia-destroy-brainchip/
...

Could Nvidia destroy Brainchip?​

When it comes to artificial intelligence (AI), Nvidia has proven itself to be the leader in the field.

Unfortunately for Brainchip, the AI behemoth’s operations also cover edge AI. This is the market that Brainchip is targeting with its Akida chip. And while its first chip was a commercial flop, management continues to believe its technology is the best in the market.

But can it really compete with Nvidia? Probably not, for a number of reasons. But first, let’s take a look at Nvidia’s edge AI capabilities.

The Jetsons family​

No, it’s not that Jetsons family, it’s a set of chips from Nvidia that look set to dominate the edge AI market. The company explains:

NVIDIA Jetson TX2 series modules give you exceptional speed and power-efficiency in an embedded AI computing device. Each supercomputer-on-a-module brings true AI computing to the edge with an NVIDIA Pascal GPU, up to 8 GB of memory and 59.7 GB/s of memory bandwidth, and a wide range of standard hardware interfaces.
The extended Jetson TX2 family of embedded modules provides up to 2.5X the performance of Jetson Nano in as little as 7.5 W. Jetson TX2 NX offers pin and form-factor compatibility with Jetson Nano, while Jetson TX2, TX2 4GB, and TX2i all share the original Jetson TX2 form-factor. The rugged Jetson TX2i is ideal for settings including industrial robots and medical equipment.

The TX2 4GB Module is of particularly interest here. As it this “embedded computer lets you run neural networks with double the compute performance or double the power efficiency of Jetson TX1.” Sound familiar?

But isn’t Brainchip’s Akida chip supposed to be better? Apparently so. Management claims its chip has better performance metrics than rivals.

However, that doesn’t necessarily guarantee sales. Far from it!

If a trusted company like Nvidia has a product on the market that offers “exceptional speed and power-efficiency in an embedded AI computing device”, that will be more than enough for the majority of users. So, why would you take a risk on a product from a company with no track record and a tiny support team? You probably wouldn’t.

This could mean the future is very bleak for Brainchip and its shares. After all, if the company doesn’t generate meaningful revenue in the near future, it will continue to burn through its cash balance and be forced into raising more funds, diluting shareholders yet again, and putting ever more pressure on its share price. Could it ultimately go to zero? I wouldn’t bet against it.

... as little as 30 times as much power as Akida ...

 

[Quatrojos]

I read the other day that the bum-breathing turtle has extended its habitat range. Now it seems it has learnt to speak:

https://www.fool.com.au/2023/05/28/could-nvidia-destroy-brainchip/
...

Could Nvidia destroy Brainchip?​

When it comes to artificial intelligence (AI), Nvidia has proven itself to be the leader in the field.

Unfortunately for Brainchip, the AI behemoth’s operations also cover edge AI. This is the market that Brainchip is targeting with its Akida chip. And while its first chip was a commercial flop, management continues to believe its technology is the best in the market.

But can it really compete with Nvidia? Probably not, for a number of reasons. But first, let’s take a look at Nvidia’s edge AI capabilities.

The Jetsons family​

No, it’s not that Jetsons family, it’s a set of chips from Nvidia that look set to dominate the edge AI market. The company explains:


The TX2 4GB Module is of particularly interest here. As it this “embedded computer lets you run neural networks with double the compute performance or double the power efficiency of Jetson TX1.” Sound familiar?

But isn’t Brainchip’s Akida chip supposed to be better? Apparently so. Management claims its chip has better performance metrics than rivals.

However, that doesn’t necessarily guarantee sales. Far from it!

If a trusted company like Nvidia has a product on the market that offers “exceptional speed and power-efficiency in an embedded AI computing device”, that will be more than enough for the majority of users. So, why would you take a risk on a product from a company with no track record and a tiny support team? You probably wouldn’t.

This could mean the future is very bleak for Brainchip and its shares. After all, if the company doesn’t generate meaningful revenue in the near future, it will continue to burn through its cash balance and be forced into raising more funds, diluting shareholders yet again, and putting ever more pressure on its share price. Could it ultimately go to zero? I wouldn’t bet against it.

... as little as 30 times as much power as Akida ...

Was it RT who alluded to seeing Nvidia as more like partners than competitors? I've often wondered about the veracity of this statement...

 

[Yoda]

It's true

It's true:
View attachment 37329

Because it was America, the bear was armed with an AR-15 Assault Rifle. Now that's what I call a bear market.

On a serious note, agreement on the debt ceiling will calm financial markets so we should see a positive effect on markets both here and in the US next week.

 

[Neuromorphia]

Was it RT who alluded to seeing Nvidia as more like partners than competitors? I've often wondered about the veracity of this statement...

28m 35sec
Making Data Simple: Al and Rob Telson discuss Brainchip and Edge on Apple Podcasts

Edit: from March 3 2022

 

[Sirod69]

28m 35sec
Making Data Simple: Al and Rob Telson discuss Brainchip and Edge on Apple Podcasts

how old is this podcast?

 

[Dhm]

I read the other day that the bum-breathing turtle has extended its habitat range. Now it seems it has learnt to speak:

https://www.fool.com.au/2023/05/28/could-nvidia-destroy-brainchip/
...

Could Nvidia destroy Brainchip?​

When it comes to artificial intelligence (AI), Nvidia has proven itself to be the leader in the field.

Unfortunately for Brainchip, the AI behemoth’s operations also cover edge AI. This is the market that Brainchip is targeting with its Akida chip. And while its first chip was a commercial flop, management continues to believe its technology is the best in the market.

But can it really compete with Nvidia? Probably not, for a number of reasons. But first, let’s take a look at Nvidia’s edge AI capabilities.

The Jetsons family​

No, it’s not that Jetsons family, it’s a set of chips from Nvidia that look set to dominate the edge AI market. The company explains:


The TX2 4GB Module is of particularly interest here. As it this “embedded computer lets you run neural networks with double the compute performance or double the power efficiency of Jetson TX1.” Sound familiar?

But isn’t Brainchip’s Akida chip supposed to be better? Apparently so. Management claims its chip has better performance metrics than rivals.

However, that doesn’t necessarily guarantee sales. Far from it!

If a trusted company like Nvidia has a product on the market that offers “exceptional speed and power-efficiency in an embedded AI computing device”, that will be more than enough for the majority of users. So, why would you take a risk on a product from a company with no track record and a tiny support team? You probably wouldn’t.

This could mean the future is very bleak for Brainchip and its shares. After all, if the company doesn’t generate meaningful revenue in the near future, it will continue to burn through its cash balance and be forced into raising more funds, diluting shareholders yet again, and putting ever more pressure on its share price. Could it ultimately go to zero? I wouldn’t bet against it.

... as little as 30 times as much power as Akida ...

It is articles like this that cast the seed of doubt in my psyche. If someone has a bit of time and knowledge and would like to cheer me up, could they construct a short rebuttal to that fool? I will love you forever.

 

[Diogenese]

It is articles like this that cast the seed of doubt in my psyche. If someone has a bit of time and knowledge and would like to cheer me up, could they construct a short rebuttal to that fool? I will love you forever.

Look at the power, and what is the cost?

 

[supersonic001]

Neuromorphic Computing | Mohd Amirrudin Esa

The [Better] Future of [Real-time] Image Recognition : NEUROMORPHIC Computing Von Neumann is good but it gets slowed down especially with image CNN and causes GPUs to be power-hungry and eventually slows us down. Read on. #future #computing #power BrainChip PROPHESEE SynSense IBM Intel...

www.linkedin.com

 

[Drewski]

Planting a seed of doubt is the fools intention. I hope the author comes to a sorry end.

As Dio said BrainChip uses 30x less power.....we just need to sell it!

Interest in Ai has piqued since last week's Nvidia news, the fool is obviously trying to mitigate any positive price action that my come our way as a result.

 

[Diogenese]

It is articles like this that cast the seed of doubt in my psyche. If someone has a bit of time and knowledge and would like to cheer me up, could they construct a short rebuttal to that fool? I will love you forever.

Nvidia do not know about SNNs.

Wiki says the TX2 is the Tegra X2 processor:

• CPU: Nvidia Denver2 ARMv8 (64-bit) dual-core + ARMv8 ARM Cortex-A57 quad-core (64-bit)
• RAM: up to 8GB LPDDR4[119]
• GPU: Pascal-based, 256 CUDA cores; type: GP10B[120]
• TSMC 16 nm, FinFET process
• TDP: 7.5–15 W[121]

https://en.wikipedia.org/wiki/Tegra#Tegra_X2

Edit: CUDA (or Compute Unified Device Architecture) is a parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for general purpose processing, an approach called general-purpose computing on GPUs (GPGPU). CUDA is a software layer that gives direct access to the GPU's virtual instruction set and parallel computational elements, for the execution of compute kernels.[1]

These are all von Neumann processors.

Their NN patents talk about matrix ALUs (arithmetic logic units), CNNs, all that 20th century stuff.
US2020364508A1 USING DECAY PARAMETERS FOR INFERENCING WITH NEURAL NETWORKS (Priority: 20190514)

1 . A processor, comprising:

one or more arithmetic logic units (ALUs) to be configured to identify one or more digital representations of one or more objects based, at least in part, on one or more neural networks trained using one or more decay parameters.

2 . The processor of claim 1, wherein the one or more ALUs are further to be configured to:

apply the one or more decay parameters to prior state information maintained for the one or more neural networks and used for identifying the one or more objects, a weighting of the prior state information being reduced according to the one or more decay parameters.

3 . The processor of claim 2, wherein the one or more ALUs are further to be configured to:

store the state information external to the one or more neural networks and providing the state information to the one or more neural networks for each set of input to the one or more neural networks.

[0070] … The training manager 712 can be responsible for training the data, such as by using a LARC-based approach as discussed herein. The network can be any appropriate network, such as a recurrent neural network (RNN) or convolutional neural network (CNN), among other such options.

[0072] … If permitted and available, user data may also be collected and used to further train the models, in order to provide more accurate inferences for future requests. Requests may be received through a user interface to a machine learning application 726 executing on the client device 702 in some embodiments, and the results displayed through the same interface. The client device can include resources such as a processor 728 and memory 730 for generating the request and processing the results or response, as well as at least one data storage element 732 for storing data for the machine learning application 726 .

 

[Dozzaman1977]

Is the motley fool short BRN ive never seen so much coverage twice a week View attachment 37349

IMO
This is the same person as shareman
Shareman also goes by the name pigsmightfly (name familiar with longtermers on other site)

It's quite clear why he keeps writing about Brainchip.
He has also compared akida with the jetson chip in the past which in my opinion was quite laughable .
I'm sure Dodgy knees has already compared these two pieces of Tech . Sharemans views are completly biased and without factual correctness.

 

[Getupthere]

I read the other day that the bum-breathing turtle has extended its habitat range. Now it seems it has learnt to speak:

https://www.fool.com.au/2023/05/28/could-nvidia-destroy-brainchip/
...

Could Nvidia destroy Brainchip?​

When it comes to artificial intelligence (AI), Nvidia has proven itself to be the leader in the field.

Unfortunately for Brainchip, the AI behemoth’s operations also cover edge AI. This is the market that Brainchip is targeting with its Akida chip. And while its first chip was a commercial flop, management continues to believe its technology is the best in the market.

But can it really compete with Nvidia? Probably not, for a number of reasons. But first, let’s take a look at Nvidia’s edge AI capabilities.

The Jetsons family​

No, it’s not that Jetsons family, it’s a set of chips from Nvidia that look set to dominate the edge AI market. The company explains:


The TX2 4GB Module is of particularly interest here. As it this “embedded computer lets you run neural networks with double the compute performance or double the power efficiency of Jetson TX1.” Sound familiar?

But isn’t Brainchip’s Akida chip supposed to be better? Apparently so. Management claims its chip has better performance metrics than rivals.

However, that doesn’t necessarily guarantee sales. Far from it!

If a trusted company like Nvidia has a product on the market that offers “exceptional speed and power-efficiency in an embedded AI computing device”, that will be more than enough for the majority of users. So, why would you take a risk on a product from a company with no track record and a tiny support team? You probably wouldn’t.

This could mean the future is very bleak for Brainchip and its shares. After all, if the company doesn’t generate meaningful revenue in the near future, it will continue to burn through its cash balance and be forced into raising more funds, diluting shareholders yet again, and putting ever more pressure on its share price. Could it ultimately go to zero? I wouldn’t bet against it.

... as little as 30 times as much power as Akida ...

Something tells me the fools and their shorter mates are trying to put some cold water and cool down the white hot AI sector.

We are certain to gain new eyes and traction in the second half of the year.

With so much AI news this past week that has the market’s attention.

Speculation got us over $2 in the past, what would speculation and results get us too.

It’s Our time!!

 

[Diogenese]

I read the other day that the bum-breathing turtle has extended its habitat range. Now it seems it has learnt to speak:

https://www.fool.com.au/2023/05/28/could-nvidia-destroy-brainchip/
...

Could Nvidia destroy Brainchip?​

When it comes to artificial intelligence (AI), Nvidia has proven itself to be the leader in the field.

Unfortunately for Brainchip, the AI behemoth’s operations also cover edge AI. This is the market that Brainchip is targeting with its Akida chip. And while its first chip was a commercial flop, management continues to believe its technology is the best in the market.

But can it really compete with Nvidia? Probably not, for a number of reasons. But first, let’s take a look at Nvidia’s edge AI capabilities.

The Jetsons family​

No, it’s not that Jetsons family, it’s a set of chips from Nvidia that look set to dominate the edge AI market. The company explains:


The TX2 4GB Module is of particularly interest here. As it this “embedded computer lets you run neural networks with double the compute performance or double the power efficiency of Jetson TX1.” Sound familiar?

But isn’t Brainchip’s Akida chip supposed to be better? Apparently so. Management claims its chip has better performance metrics than rivals.

However, that doesn’t necessarily guarantee sales. Far from it!

If a trusted company like Nvidia has a product on the market that offers “exceptional speed and power-efficiency in an embedded AI computing device”, that will be more than enough for the majority of users. So, why would you take a risk on a product from a company with no track record and a tiny support team? You probably wouldn’t.

This could mean the future is very bleak for Brainchip and its shares. After all, if the company doesn’t generate meaningful revenue in the near future, it will continue to burn through its cash balance and be forced into raising more funds, diluting shareholders yet again, and putting ever more pressure on its share price. Could it ultimately go to zero? I wouldn’t bet against it.

... as little as 30 times as much power as Akida ...

RETRACTION

It has come to my attention that some people may interpret the above post as drawing a connexion between financial journalists and bum-breathing turtles.

I apologize for any offence to bum-breathing turtles everywhere.