BRN Discussion Ongoing

[Diogenese]

Hi Chapman,

I generally agree with what you said but have a couple of differing opinions.

Firstly, I don't think the project manager job advertisement mentioning an immediate 2.0 launch confirms AKD2000 is tracking on time and will be ready in a few months. Assuming that AKD2000 is still going to an optimised AKD1500, this likely won't be finalised until after the first AKD1500 reference chip is back and tested. My guess is AKD2000 will be ready closer to a year from now.

Keeping in mind that this project manager job reports to the CMO, I think it's more likely to be referring to either a brand refresh or the launch of marketing for the new AKD1500 chip (job ad includes mentions of user manuals and training materials). AKD1500 will bring a lot of new functionality - hopefully transformers (which I suspect it will from the changelogs) as this will allow use cases with advanced predictive capabilities and may attract some of the attention currently focussed on ChatGPT. So with that comes a lot of great new marketing opportunities.

Secondly, while I get the potential link with Global Foundries and NASA / DARPA, I wouldn't expect the choice of GF 22nm FDSOI to be their request. A large reason for this is that governments generally take the slow but safer route. Decision making is usually slower and I also don't recall seeing any SBIRs awarded for neuromorphic / SNN transformers. In my view it's more likely that NASA will wait for the reference chip to produced, do internal testing and then decide what they want to do with it. I'm also not convinced they would care about such a low nm node size.
My guess is it's more likely to be a request from the other EAPs like Mercedes, one of the most advanced early adopters. The below link about a joint STMicro and GF facility offers some perspective in favour of this.

Pure speculation, DYOR

STMicroelectronics and GlobalFoundries to advance FD-SOI ecosystem with new 300mm manufacturing facility in France | GlobalFoundries

New jointly-operated, high-volume manufacturing facility to support European and global customers’ demand as the world transitions to digitalization and decarbonization […]

gf.com

“This new manufacturing facility will support our $20 billion+ revenue ambition. Working with GF will allow us to go faster, lower the risk thresholds, and reinforce the European FD-SOI ecosystem. We will have more capacity to support our European and global customers as they transition to digitalization and decarbonization” said Jean-Marc Chery, President and CEO of STMicroelectronics. “ST is transforming its manufacturing base. We already have a unique position in our 300mm wafer fab in Crolles, France which will be further strengthened by today’s announcement. We continue to invest into our new 300mm wafer fab in Agrate (near Milan, Italy), ramping up in H1 2023 with an expected full saturation by end 2025, as well as in our vertically integrated silicon carbide and gallium nitride manufacturing.”

“Our customers are seeking broad access to 22FDX® capacity for auto and industrial applications.

Temporary Project Manager

Hi Idd,

You are correct that, in the past NASA has opted for proven technology, but in the last week or so someone posted a NASA SBIR calling for 22nm FD-SOI and complaining about the wasted silicon in having a built-in processor - pretty much what Akida 1500 provides.

Akida 1000 has an ARM Cortex (licenced from ARM) and several comms interfaces, none of which form part of the Akida IP.

It may be that, for a specific purpose, only one comms interface would be needed.

Such a pared down Akida would need an off-chip processor for configuration, but this would not significantly affect performance as Akida does not need any processor for inference, and, if memory serves, no more than 5% of CNN2SNN processing is done on the processor.

This frees up Akida to work with SiFive, Intel or any other processor without the need to pay an additional licence royalty to ARM. It also reduces the silicon footprint so more Akida 1500s can fit on a wafer.

The Akida IP includes the NN array and the CNN2SNN conversion hardware, and the configuration software.

The US DoD has reacted to the Sino-Russian situation. The US has a new Chips Bill compelling Intel and others to repatriate chip manufacturing.

That said, your STM article indicates that there is significant demand for the GF tech from industry as well.

 

[IndepthDiver]

Hi Idd,

You are correct that, in the past NASA has opted for proven technology, but in the last week or so someone posted a NASA SBIR calling for 22nm FD-SOI and complaining about the wasted silicon in having a built-in processor - pretty much what Akida 1500 provides.

Akida 1000 has an ARM Cortex (licenced from ARM) and several comms interfaces, none of which form part of the Akida IP.

It may be that, for a specific purpose, only one comms interface would be needed.

Such a pared down Akida would need an off-chip processor for configuration, but this would not significantly affect performance as Akida does not need any processor for inference, and, if memory serves, only 5% of CNN2SNN processing is done on the processor.

This frees up Akida to work with SiFive, Intel or any other processor without the need to pay an additional licence royalty to ARM. It also reduces the silicon footprint so more Akida 1500s can fit on a wafer.

The Akida IP includes the NN array and the CNN2SNN conversion hardware, and the configuration software.

The US DoD has reacted to the Sino-Russian situation. The US has a new Chips Bill compelling Intel and others to repatriate chip manufacturing.

That said, your STM article indicates that there is significant demand for the GF tech from industry as well.

Hi D,

Thanks, I must have missed that SBIR. That explains why there's been talk about not needing a processor.
The timing of the SBIR and the annoucement of our 22nm AKD1500 GF reference chip does align very nicely.


For anyone else that missed it:

Deep Neural Net and Neuromorphic Processors for In-Space Autonomy and Cognition | SBIR.gov

www.sbir.gov

Release Date:
January 10, 2023
Open Date:
January 10, 2023
Application Due Date:
March 13, 2023
Close Date:
March 13, 2023 (closing in 29 days

The preference is for a prototype processor fabricated in a technology node suitable for the space environment, such as 22-nm FDSOI, which has become increasingly affordable.


Neuromorphic and deep neural net software for point applications has become widespread and is state of the art. Integrated solutions that achieve space-relevant mission capabilities with high throughput and energy efficiency is a critical gap. For example, terrestrial neuromorphic processors such as Intels Cooporation's LoihiTM, Brainchip's AkidaTM, and Google Inc's Tensor Processing Unit (TPUTM) require full host processors for integration for their software development kit (SDK) that are power hungry or limit throughput. This by itself is inhibiting the use of neuromorphic processors for low SWaP space missions.

 

[Boab]

Hi D,

Thanks, I must have missed that SBIR. That explains why there's been talk about not needing a processor.
The timing of the SBIR and the annoucement of our 22nm AKD1500 GF reference chip does align very nicely.


For anyone else that missed it:

Deep Neural Net and Neuromorphic Processors for In-Space Autonomy and Cognition | SBIR.gov

www.sbir.gov

Release Date:
January 10, 2023
Open Date:
January 10, 2023
Application Due Date:
March 13, 2023
Close Date:
March 13, 2023 (closing in 29 days

The preference is for a prototype processor fabricated in a technology node suitable for the space environment, such as 22-nm FDSOI, which has become increasingly affordable.


Neuromorphic and deep neural net software for point applications has become widespread and is state of the art. Integrated solutions that achieve space-relevant mission capabilities with high throughput and energy efficiency is a critical gap. For example, terrestrial neuromorphic processors such as Intels Cooporation's LoihiTM, Brainchip's AkidaTM, and Google Inc's Tensor Processing Unit (TPUTM) require full host processors for integration for their software development kit (SDK) that are power hungry or limit throughput. This by itself is inhibiting the use of neuromorphic processors for low SWaP space missions.

And remember Dio's response.

• Feb 5, 2023

• Edit bookmark
• #45,813

Deep Neural Net and Neuromorphic Processors for In-Space Autonomy and Cognition | SBIR.gov​

www.sbir.gov
A nice mention for brainchip

I suppose that's ok on the "No publicity is bad publicity" principle.

" ... terrestrial neuromorphic processors such as Intels Cooporation's LoihiTM, Brainchip's AkidaTM, and Google Inc's Tensor Processing Unit (TPUTM) require full host processors for integration for their software development kit (SDK) that are power hungry or limit throughput. This by itself is inhibiting the use of neuromorphic processors for low SWaP space missions."

The redeeming feature is:

"The preference is for a prototype processor fabricated in a technology node suitable for the space environment, such as 22-nm FDSOI, which has become increasingly affordable."

So, suddenly, Global Foundries is about to make Akida 1500 in FD-SOI, without the encumbrance of a full host processor.

 

[Quatrojos]

Hi Chapman,

I generally agree with what you said but have a couple of differing opinions.

Firstly, I don't think the project manager job advertisement mentioning an immediate 2.0 launch confirms AKD2000 is tracking on time and will be ready in a few months. Assuming that AKD2000 is still going to an optimised AKD1500, this likely won't be finalised until after the first AKD1500 reference chip is back and tested. My guess is AKD2000 will be ready closer to a year from now.

Keeping in mind that this project manager job reports to the CMO, I think it's more likely to be referring to either a brand refresh or the launch of marketing for the new AKD1500 chip (job ad includes mentions of user manuals and training materials). AKD1500 will bring a lot of new functionality - hopefully transformers (which I suspect it will from the changelogs) as this will allow use cases with advanced predictive capabilities and may attract some of the attention currently focussed on ChatGPT. So with that comes a lot of great new marketing opportunities.

Secondly, while I get the potential link with Global Foundries and NASA / DARPA, I wouldn't expect the choice of GF 22nm FDSOI to be their request. A large reason for this is that governments generally take the slow but safer route. Decision making is usually slower and I also don't recall seeing any SBIRs awarded for neuromorphic / SNN transformers. In my view it's more likely that NASA will wait for the reference chip to produced, do internal testing and then decide what they want to do with it. I'm also not convinced they would care about such a low nm node size.
My guess is it's more likely to be a request from the other EAPs like Mercedes, one of the most advanced early adopters. The below link about a joint STMicro and GF facility offers some perspective in favour of this.

Pure speculation, DYOR

STMicroelectronics and GlobalFoundries to advance FD-SOI ecosystem with new 300mm manufacturing facility in France | GlobalFoundries

New jointly-operated, high-volume manufacturing facility to support European and global customers’ demand as the world transitions to digitalization and decarbonization […]

gf.com

“This new manufacturing facility will support our $20 billion+ revenue ambition. Working with GF will allow us to go faster, lower the risk thresholds, and reinforce the European FD-SOI ecosystem. We will have more capacity to support our European and global customers as they transition to digitalization and decarbonization” said Jean-Marc Chery, President and CEO of STMicroelectronics. “ST is transforming its manufacturing base. We already have a unique position in our 300mm wafer fab in Crolles, France which will be further strengthened by today’s announcement. We continue to invest into our new 300mm wafer fab in Agrate (near Milan, Italy), ramping up in H1 2023 with an expected full saturation by end 2025, as well as in our vertically integrated silicon carbide and gallium nitride manufacturing.”

“Our customers are seeking broad access to 22FDX® capacity for auto and industrial applications.

Temporary Project Manager

Perhaps PVDM's availability for a chat on twitter (or whatever it is) is indicative that he's now kicking back with some spare time...

 

[jtardif999]

Renesas and Megachips alone can easily give us 2% market share and more which would be enough to make BRN successful and profitable.

These are bonuses: NASA, Valeo, Mercedes Benz, Intel, ISL, US Airforce Research, ARM, SiFive, Edge Impulse, MOSCHIPS, VVDN, Prophesee, Nviso, Numera, Tata, SOCIONEXT, Biotome

Just curious, how do you arrive at the 2 percent? I would hope that they could potentially provide us with more market share than that. I believe BRNs tech is good enough to have a profound impact on the market - no matter who is first in doing the delivery. AIMO.

 

[Learning]

This certainly put Brainchip's Neuromorphic in the box seat. "Beneficial AI" better for the planet.

Neuromorphic Computing - NVISO

HUMAN BEHAVIOUR AI NEUROMORPHIC COMPUTING NVISO empowers system integrators to build AI-driven human machine interfaces to transform our lives using neuromorphic computing. Understand people and their behavior in real-time without an internet connection to make autonomous devices safe, secure...

www.nviso.ai

Redirecting

Learning 🏖

 

[cosors]

How many chips are in a Range Rover? “A modern car can have anywhere from 1,500 to 3,000 chips in up to 80 separate electronic control units with the luxury vehicles built by Jaguar Land Rover being at the higher end of the spectrum.

How many computer chips does an electric car have?


3,000 chips

During his remarks, Biden said the average electric vehicle uses about 3,000 chips, meaning EV will need more than double the amount of what's in a non-electric car.

It is not only the chip itself that is embedded and supplied by a periphery. Perhaps the more important argument for me in your train of thought is the footprint in manufacturing. As an engineer I like to think: as little as possible as much as necessary which ultimately helps the climate and still ensures that everything necessary is addressed and this approach reduces costs at the same time.

 

[thelittleshort]

As an engineer, I like to think: as little as possible as much as necessary

@cosors “as little as possible, as much as necessary”

 

[cosors]

Akida: beyond Nvidia.

I keep having this crude thought that some big player is behind our unpleasantness. I know, a conspiracy theory thought. But before Intel, Nvidia would have a bigger motive in this my broken thought. Actually, this belongs in the other thread.

Perhaps it may have been a humiliation for him. Hands up off and Hey Mercedes. And the system runs via Nvidia.

 

[cosors]

This certainly put Brainchip's Neuromorphic in the box seat. "Beneficial AI" better for the planet.

View attachment 29371

Neuromorphic Computing - NVISO

HUMAN BEHAVIOUR AI NEUROMORPHIC COMPUTING NVISO empowers system integrators to build AI-driven human machine interfaces to transform our lives using neuromorphic computing. Understand people and their behavior in real-time without an internet connection to make autonomous devices safe, secure...

www.nviso.ai

Redirecting

Learning 🏖

For me a very important thought even if most end users who may be green minded do not face this. It is so comfortable not to reflect one's own behavior.
I've spend to much time with such matter and the againsts with TLG

 

[Tony Coles]

This certainly put Brainchip's Neuromorphic in the box seat. "Beneficial AI" better for the planet.

View attachment 29371

Neuromorphic Computing - NVISO

HUMAN BEHAVIOUR AI NEUROMORPHIC COMPUTING NVISO empowers system integrators to build AI-driven human machine interfaces to transform our lives using neuromorphic computing. Understand people and their behavior in real-time without an internet connection to make autonomous devices safe, secure...

www.nviso.ai

Redirecting

Learning 🏖

This certainly put Brainchip's Neuromorphic in the box seat. "Beneficial AI" better for the planet.

View attachment 29371

Neuromorphic Computing - NVISO

HUMAN BEHAVIOUR AI NEUROMORPHIC COMPUTING NVISO empowers system integrators to build AI-driven human machine interfaces to transform our lives using neuromorphic computing. Understand people and their behavior in real-time without an internet connection to make autonomous devices safe, secure...

www.nviso.ai

Redirecting

Learning 🏖

That’s impressive @Learning, we are witnessing BRN getting mentioned in articles a little more often now, hopefully it’s just a good start for 2023. Have a great day all.

 

[Rise from the ashes]

Another Rob telson like. Lol do people really get bothered by the likes he does on LinkedIn?

 

[Goldphish]

Following the theme of the big problem the likes of ChatGPT brings to the world:

This fundie saw the AI boom coming. Now he sees a problem

I.e. the massive amounts of energy used needs to be resolved......

 

[Deadpool]

Following the theme of the big problem the likes of ChatGPT brings to the world:

This fundie saw the AI boom coming. Now he sees a problem

I.e. the massive amounts of energy used needs to be resolved......

Hi Goldie can you copy and paste the article, as you need a subscription to access, or share your login, I won't tell anyone.

 

[Rise from the ashes]

Hi Goldie can you copy and paste the article, as you need a subscription to access, or share your login, I won't tell anyone.

Post in thread 'A.I and Geopolitics' https://thestockexchange.com.au/threads/a-i-and-geopolitics.48093/post-80914

 

[Sirod69]

There is certainly nothing about our Akida here, but Mercedes is always happy to remind everyone of this car. I'm curious to see when we'll appear again in the reports from VISION EQXX. The more love him the better.


Mercedes-Benz AG
5 Std.

Fusion of tech and aesthetic: The interplay of design and aerodynamics in the VISION EQXX.

Aerodynamic drag can have a big impact on range. On a regular long-distance drive, a typical electric vehicle dedicates almost two thirds of its battery capacity to cutting its way through the air ahead, which is why the VISON EQXX has an ultra-sleek and slippery drag coefficient of 0.17.

A huge amount of work went into painstakingly integrating the passive and active aerodynamic features into the external form of the VISION EQXX. The remarkable result was achieved on an impressively short timescale. The inter-disciplinary team used advanced digital modelling techniques to reach a compromise that reduces drag while retaining the sensual purity of the Mercedes-Benz design language and the practicalities of a road car.

Despite the practical challenges and the compressed timescale, the success of the collaboration is clearly evident in the sophistication and poise of the exterior design. The surfaces of the VISION EQXX run smoothly from the front, developing powerful yet sensual shoulders above the rear wheel arches. This natural flow concludes with a cleanly defined, aerodynamically effective tear-off edge accentuated by a gloss-black end trim, punctuated by the rear light clusters.

Learn more about the VISION EQXX: https://lnkd.in/dtddQ8rK

 

[jtardif999]

Renesas full year report came out on Feb 9. They had some explaining to do!

Notice Concerning the Difference between Financial Results for the Year Ended December 31, 2022 and Results in the Previous Period​

February 09, 2023 01:00 AM Eastern Standard Time
TOKYO--(BUSINESS WIRE)--Renesas Electronics Corporation (TSE: 6723, “Renesas”), a premier supplier of advanced semiconductor solutions, today announced the difference between its consolidated financial results for the year ended December 31, 2022 (January 1, 2022 to December 31, 2022), which it disclosed on February 9, 2023, and the financial results in the previous period (January 1, 2021 to December 31, 2021).
The forecasts for the above period are not based on IFRS, therefore the differences are shown as the actual figures.

1. Difference between consolidated financial results for the year ended December 31, 2022 and the year ended December 31, 2021
					In millions of yen
	Revenue	Operating Profit	Profit before tax	Profit	Profit attributable to owners of parent
Year ended December 31, 2021	993,908	173,827	142,718	119,687	119,536
Year ended December 31, 2022	1,500,853	424,170	362,299	256,787	256,632
Difference	506,945	250,343	219,581	137,100	137,096
Difference (%)	51.0%	144.0%	153.9%	114.5%	114.7%

2. Background to the difference
Consolidated revenue for the year ended December 31, 2022 was 1,500.9 billion yen, a 51.0% increase year on year. This was mainly due to a sales increase effect from the consolidation of Dialog Semiconductor Plc acquired on August 31, 2021 and yen depreciation, in addition to an increase in revenue in the Automotive Business supported by continued growth in semiconductor contents per vehicle as well as an increase in revenue in the Industrial/Infrastructure/IoT Business from demand expansion in the infrastructure market such as datacenters.
The gross profit increased from improvements in product mix in addition to growth in revenue. In addition, the operating profit, profit before tax, profit, and profit attributable to owners of parent for the year ended December 31, 2022 significantly exceeded the results from the previous period, supported by the company’s efforts to streamline business operations.

 

[stuart888]

This guy is a 20 year programmer, hard core, deep learning engineer. Sharp guy, good videos.

He says he now uses ChatGBT to do 80% of his coding now. That is disruptive. He supervises the code and learns from it.

Thought it was interesting. Plus he summarizes ChatGBT and Transformer Neural Networks, "Attention is all you need". Famous Google article as they created Transformers in 2017.

I feel Brainchip is going to win in TinyML, as you don't need big data to train edge AI on Industrial patterns, ultra low power.

https://hub.packtpub.com/paper-in-two-minutes-attention-is-all-you-need/

 

[stuart888]

Australian Space TV, he is a Neural-Spiker! The first published (non-secret) SNN application in space, I believe first started here.

Good video, yeah Australia!

Same thing, you don't need big data to train SNN edge AI on Industrial patterns, ultra-low power.

 

[stuart888]

Really glad we have Transformers high on the Brainchip radar. This stuff is too deep, for me, I really don't need to know all the Fancy Math Equations.

The transformer math takes time to unpack. Forget about that part.

When dealing with text/speaking: the human language has lots of double meaning words, that in certain parts of the sentence mean one thing. Yet the same word, with the same spelling can mean something different later in the same paragraph.

This solves that, so ChatGBT is like a teenage, that can be further trained in specific industries, say to automatically print out the legal paperwork documents required for signing when buying a house.

I would skip it, just know "Attention is all you need".