BRN Discussion Ongoing

[FrederikSchack]

Ok, we got to 5 million in revenue a year later than I had estimated or hoped back in mid 2020, but hey, we live in a dynamic world and we can't predict it in details. Does anybody remember that we just went through some pretty wild world events? How many predicted them in detail? Neither can the management of the Brainchip team.

If you define the future from your expectations, you're more than 99% guaranteed to be disappointed, because there's always deviations at least at some level of detail.

I completely understand that it's tempting to let out the frustrations here and it seems the frustrations keeps circling around the point that management seemed to promise more than we got. Well, we got 5 million USD in revenue last year and I don't really think Brainchip promised anything specific.

A better approach than complaining is to reevaluate and adapt when the situation changes. We're where we are now and we can't do a damn thing about the past. So, let's look at the future, how does it look now?

Personally I've never been more optimistic about Brainchip than now and no amount of complaining about the past can change that, because I only evaluate Brainchip on the future. If I would have evaluated that Brainchip wouldn't cut it, then I would have cut my losses and sold it. Now, what I did recently is to increase my stake in Brainchip, because it's never been looking better to me.

These are some of my reasons:

1) AI got super focus after ChatGPT, Dale-E, Stable Diffusion e.t.c. and the amount of companies that are making something similar is exploding and many more billions will be poured into AI. We're at the accelerating part of the technological S-curve in AI. That's super positive for us, we're right in the middle of a revolution that IS changing the world right now.

2) We can't keep running AI on von Neuman hardware (nVidia, Cerebras e.t.c.), in the future, lest we want to end up consuming a great part of the worlds electricity solely for training AI models. We need a fundamental hardware change and it's never been more urgent. It's not just an environmental thing, it's also an economical thing. Only insane companies would run their models on nVidia hardware if they could run it on neuromorphic hardware and save heaps of money in investments and also save heaps of money on power consumption.

3) Neuromorphic computing is the best solution to point 2 that we have. I'm not saying that Neuromorphic chips will replace von Neuman architecture in all AI, but where it's feasible it will.

4) Neuromorphic computing is more than just energy savings and economic savings, it's new things that we can do, that we couldn't do before. We're opening up entirely new markets, that only neuromorphic computing is suited for.

5) It's crazy to send all the data from our devices to the cloud to have it analyzed there and having sent back the results to our devices, clogging up the veins of the Internet and delaying the respons, when we can do it on the device. Who can't see this? Neuromorphic computing can really bring some of todays data center capabilities to the device.

6) There are only two really promising Neuromorphic companies on the market and that's Brainchip and GrAI Matter Labs. We're in the middle of a startup dream situation, we only have one real competitor in our space. Everybody would love to have no competition at all, but a situation with one competitor is also really good.

7) We're dead center in the Industrial Revolution 4.0, nothing is more central than AI, AI pervades all the themes of Industrial Revolution 4.0. Who still can't see this? I saw this back in the middle of 2020 when reading "Symbiotic Autonomous Systems White Paper III" by IEEE, AI is in almost every trend they mention. Further as explained in the points above, neuromorphic computing is destined to play a continuously larger role in AI.

Also look at this Gartner Graph. I marked with green where neuromorphic computing is the absolute winner and blue where we definitely are going to make an impact.

So, to summarize, we're in the absolute dead center core of the Industrial Revolution 4.0, AI is taking off exponentially, neuromorphic computing is the economic and environmental solution to AI and neuromorphic computing is the enabler of many new things. Further, we're on the neuromorphic market and we have one real competitor?

Besides that our partners love us and say so publicly on many occasions, we're winning the PR game in this exploding market.

Does it take time to convince everybody? Yes. Does it take time for our industry partners to understand the new technology? Yes. Does it take time for our industry partners to design our chip into their hardware? Yes. But we are here now, our chips are being designed into various products, we're winning at least a part of the game.

Please, tell me where my logic fails about the future and don't tell me about the past, because I know the past at least as well as you. Tell me what I don't see about the future.

 

[FrederikSchack]

I will agree that the time lines have changed.

But let's step back to 2021.
1. Revenue projected in late 2022.
2. Breakeven 2023.

Now what kinda activity and partnerships did we have in 2021?

Was Akida being advertised or marked as a great product back in 2021 by partners and universities?

Now let's look April 2023.
1. Revenue projections pushed to back end 2023 maybe early 2024
2. Breakeven not sure yet rather.

We do have a lot of partnerships now with we all know who.

We are busy hitting marks and adding new partnerships.

Universities are studying SNN.

IP purchaser will be taping our IP on chip.
We have increase the range of our products.

Lets not kid our selves we have come a long way from 2021.

Yes one final part revenue is missing i will agree.

Have they moved goal posts and timelines yes.

Will we have revenue in the next 12 months yes.

Are there lots of possible products in the works that have Akida yes.

We are comercial yes but the uptake has not yet begun.

There is a whole cycle that need to happen to bring comercial product on that I believe many of us have underestimated the time.

Believe me I thought I would have been sipping drinks full time by now in 2020 but it's been a long road long road.

I Will add in that I think when Management increased the LDA draw back in the day they knew the timeline changed. Will they announce the delays no nobody does let's be honest about that.

Are the delays a result of BRN staff the awnser is no. My understanding is they meet there deadlines on development pretty well.

Are there delays in their customer base or up take yes. Why? Well these people run businesses and they need to be fiscally responsible minimize risk. There are So many challenges in the world post covid shortages and delays that these companies need to keep there owners happy and making a healthy profit. So development of new innovative risky investment are not always a priority.

Once some adopt Akida there will be a rush by others it's the first few contracts that take time.

So laying blame on management sales is not actually solving anything.

As it stand as investors responsible for our own actions we have to options:

1. Buy stock
2. Sell stock

This is what is in our control.

If you feel that BRN will not meet exceed it's old highs or you have belief of better returns elsewhere you know what you have to do. If your angry about buying higher trapped you need to looknat why you bought when you bought and say why i paid 1.70 a share i was thinking we would get to 10. But now the timline does not suit your strategies you need to fix that come up with options to correct things.

If you feel we are under valued THEN YOU to know what to do.

Sticking around complaining complaining so never solve your dilemma. Those that have been complaining on HC regarding BRN being a poor investment for 2 plus years you need to really think about thier motive. Who will for 2 years keep telling you to sell it's crap. Believe me they don't care about your welfare.

The reason there is so much less action and dialog is cause the long term investor is studing their market reading the thousands of articles on SNN and Akida referanced articles. We did not have this vast number of leads and reports to go though in 2021 or 2022 for the greater part. Things are building.

Your watching the AI revolution AIOT start. This is how a company is built not with Yatchs Parties and all the stuff you see on TV. Through hard work network and a bit of luck.

Very well said, that is the right focus to have.

 

[Fullmoonfever]

Don't recall this short vid being posted?...probs a double up but I hadn't seen it.

Nothing major, was just a catch up by the Group Editor of Electronics Weekly while he was at EW 23 with Nandan & another Co MikroE in late March.

One thing though and someone can correct me if has been recently listed somewhere, I hadn't noticed or seen that our HD Vid Object Detection at 30fps and < 75 milliwatts was being done on 16nm.....if I heard Nandan correctly at around the 8 min mark.

Last time I saw a 16nm reference was from a 2019 Linley Group paper stating BRN running MobileNet simulation on a 16nm Akida.

Who's using 16nm that we were running / testing on or just a reference to the earlier simulations?

I thought we've only been playing on 28 & 22nm more recently and that we were more involved with Edge Impulses FOMO which is much quicker that MobileNet from what I've read.

Let's Talk Electronics: MikroE and BrainChip on remote development and neuromorphic computing​

24 March 2023

Electronics Weekly's Group Editor, Clive Couldwell, caught up with MikroE and BrainChip in Nuremberg at Embedded World 2023 to discuss their technologies in more depth. With Nandan Nayampally - CMO of BrainChip - he discussed neuromorphic computing

 

[dippY22]

Here are the early beginnings of NVIDIA when they went public on January 22, 1999, with an IPO of $12/share (eventually settling around $0.82/share).

View attachment 34273

Look how much time has elapsed since then. It seems to me we started to see a nice rise around 2016 when VR became usable thanks to the improvement in the technology, and AI was picking up (See Accelerating AI with GPUs: A New Computing Model, circa 2016).

I don't think BrainChip has as long a wait to become a worthwhile investment in the AI sector, but as you can see, it did not happen for NVIDIA overnight. I think that BrainChip, for as long as they have been around already, has commercialized at a time when AI is on its way to becoming mainstream.

As neuromorphic computing (although not a new concept in and of itself) is not as widespread as GPUs but is now on that journey to getting there due to BrainChip's efforts. It has already shown it can compete with GPUs for similar AI inference along with the added benefit of being ideal for Edge computing where cost, privacy, security, and power considerations are a concern.

If people are uncomfortable holding this stock for at least another two to five years, they will constantly be second-guessing their investment in BrainChip. As others have said before, everyone's situation is different.

If one can hold onto this stock for ten to twenty years, it is my opinion that they will find the risk is worth the reward. However, I cannot read tea leaves or tarot cards. Anything can happen for better or for worse.

Good and reasonable posts from you are good to see Unemotional, realistic and forward thinking. You apparently work in the tech industry from what I recall so your views are appreciated. Thanks and keep up the good posting,....the forum will benefit from what you think. Regards, dippY

 

[SERA2g]

FYI for the Perth crew, there’s an event that Peter is speaking at in May.

He spoke at the last AI summit for Innovate Australia, which I went to. It was good. Adam is on the board for IA for what that’s worth.

Tickets are free for anyone willing to take a couple hours off work to go. I’ve booked a ticket but it’ll be a see how I’m going work wise closer to the date type of situation.

Would be keen to organise some beers in the city afterwards for anyone keen to go. Flick me a message and I’ll get everyone that reaches out into a chat so we can sort it out a little closer.

Apologies if this has already been posted - it’s 11pm here and I’m off to bed so couldn’t be bothered to check

Innovate Australia's Artificial Intelligence (AI) Innovation Summit

Explore the World of AI, Machine Learning, and ChatGPT. Learn and Engage with a Diverse Panel of AI Professionals and Advocates.

www.eventbrite.com.au

 

[DingoBorat]

Good presentation.

A few notes below based on my interpretation and understanding only. These are not intended as advice, guidance, recipe instructions etc. Recommend waiting for the recording and tuning in for yourself.

Cheers.

Presentation

• Edge AI – The Right compute model
• Customer Driven. Market Driven. Generations Ahead.
• Akida - in the market now, real customers and gaining traction.
• Chips, boards & systems available which people can try.
• New chip available late Summer, early Fall
• Market likes what they did with the first chip, have put additional technology into the second.
• Sean has brought on board a number of high-level industry leaders.
• Closed a set of licences already (assume MegaChips and Renesas).
• Can’t build a product without an ecosystem.
• Auto industry has a lot of interest in AI, and a lot of interest in BrainChip.
• BrainChip seeing a lot of interest from healthcare as well.
• Power consumption from data centres is unsustainable. Must move to edge market.
• Market getting stronger every single day.
• BrainChip seeing absolute interest in all markets – industrial, auto, health, home/consumer.
• Fully digital and event based is critical – allows customers to move/deploy to any technology.
• Easy to convert existing models to Akida IP.
• Gen 1 product focused on grey boxes (ie. Akida-E)
• Gen 2 product focuses on addressing orange and blue boxes (ie. Akida-S & P). This results in more functions and more Customers.
• Tech partners – lubricates the sales cycle.
• Customers want to know that varying foundries can be used.
• Selling some chips as a secondary revenue stream.
• MegaChips can build chips on behalf of other Customers.
• Renesas releasing chip in coming months.
• Neuromorphic standard will emerge over coming years - BrainChip intend to be part of that standard.
• Primary revenue is IP licensing.
• Royalties are powerful revenue streams.
• Big market, favourable trend in the edge.
• Gen 2 - Very strong positive reviews from analysts, very strong interest from Customers.
• Working with marquee brands.
• Strong team.
• Real product, real market, real Customers. Attractive business model.

Q&A

• Gen 2 – On pace for Q3 release, maybe earlier - development going well. BrainChip developing hardware and software at same time. Too early to sign customers but seeing high interest level from new prospects and existing customers.
• Future earnings guidance – not at this time. IP licensing model is lumpy and includes a long sales cycle. Hard to predict but as BrainChip matures they will provide forecasts. Complex evaluation cycles ongoing, all going well but can’t time exactly when these will land.
• When will break even be achieved – Similar to above, BrainChip is not forward projecting. Sean has a multi-year board approved plan.
• Akida 1500 – expected to sell some of these to integrators. AKD1000 chip is essentially a demo chip. Never intended to be a revenue stream itself.Akida 1500 – expected to sell some of these to integrators. AKD1000 chip is essentially a demo chip. Never intended to be a revenue stream itself.Akida 1500 – expected to sell some of these to integrators. AKD1000 chip is essentially a demo chip. Never intended to be a revenue stream itself.

• Akida 1500 – expected to sell some of these to integrators. AKD1000 chip is essentially a demo chip. Never intended to be a revenue stream itself.

Hey @Foxdog, you mentioned about AKIDA1000 being essentially a demo chip, as being a "red flag" I think you've misconstrued what the Company means here (respecting that this is @Evermonts notes and takeaways).

AKIDA1000 has not been a "product" really, since Sean Hehir took the helm and decided on a basically pure IP model (obviously AKIDA1500, now looks like it will be sold as a chip product).

Saying "Never intended" is a bit of a stretch though, as it was, but the word "never" is often used, without the true appreciation of its meaning..
But again these are @Evermonts words and may not have been verbatim, by the Company.

This is not to say, that AKIDA 1.0 IP (which made AKIDA1000 and also makes AKIDA1500) was "never" intended to be a revenue stream, as it's also in the Renesas MCU and is what MegaChips has sold licences to, to at least 2 of its customers.

Too many 2s ..

My read, is that they are saying AKIDA1500 as a product, is an additional revenue strategy.
One that was basically abandoned with AKIDA1000.

Remember that the additional cost and risk of producing AKIDA1000 chips at the time, may not have been favorable.

AKIDA1500 is a bit of a different kettle of fish, as the Company is in a different more comfortable stage of its commercialisation and this chip was designed with and in conjunction with, specific customer needs and specifications.

No one should be peed, that the Company is sometimes changing tact.
This Company has been changing tact, since its inception.
It's part of the beauty, of being still small enough to do so.

I hope we always retain that ability, while being a Behemoth of course!

Kodak couldn't change tact, despite actually inventing the new direction..

Those who have been around a few years, have seen all the challenges and obstacles in our path and we are slowly but surely surmounting them.

This is one of the many strengths of BrainChip and one of the reasons, why I have confidence in our "visible" success.

 

[M_C]

I like our chances here.......

The company have mentioned Raspberry Pi before

Opinion only. Dyor

Redirecting

 

[SERA2g]

I like our chances here.......

Opinion only. Dyor

Redirecting

View attachment 34285 View attachment 34286

This could be one of the most important pieces of content found recently.

If it can perform computations on-chip without connection to the cloud then the chip powering the sensor may be a neuromorphic chip.

If Sony have not developed their own neuromophic chip then they are using someone elses neuromorphic chip.

There are many companies developing neuromorphic chips, but as far as I’m aware, there is only one commercially available neuromophic chip.

Quack, quack.

Akida Ballista.

IMO DYOR

 

[SERA2g]

This could be one of the most important pieces of content found recently.

If it can perform computations on-chip without connection to the cloud then the chip powering the sensor is a neuromorphic chip.

If Sony have not developed their own neuromophic chip then they are using someone elses neuromorphic chip.

There are many companies developing neuromorphic chips, but as far as I’m aware, there is only one commercially available neuromophic chip.

Quack, quack.

Akida Ballista.

IMO DYOR

Intelligent Vision Sensors (AI Sensor) | Technology | Sony Semiconductor Solutions Group

Sony Semiconductor Solutions Group develops device business which includes Micro display, LSIs, and Semiconductor Laser, in focusing on Image Sensor.

www.sony-semicon.com

Sorry to pull you in @Diogenese

Wondering if you’ve done any previous research on the logic chip powering Sony’s Intelligent Vision Sensor?

Aitrios is equipped with the IVS technology so it seems to me if the IVS doesn’t contain akida then this duck is actually a pigeon.

IVS technology was announced May 2020…

 

[SERA2g]

Intelligent Vision Sensors (AI Sensor) | Technology | Sony Semiconductor Solutions Group

Sony Semiconductor Solutions Group develops device business which includes Micro display, LSIs, and Semiconductor Laser, in focusing on Image Sensor.

www.sony-semicon.com

Sorry to pull you in @Diogenese

Wondering if you’ve done any previous research on the logic chip powering Sony’s Intelligent Vision Sensor?

Aitrios is equipped with the IVS technology so it seems to me if the IVS doesn’t contain akida then this duck is actually a pigeon.

IVS technology was announced May 2020…

Post in thread 'BRN Discussion Ongoing'
https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-186708

Sorry @Diogenese

Looks like you’ve covered this already.

It’s sounding like pigeon pie for dinner tonight.

Sorry to spoil the party @M_C

 

[manny100]

Good presentation.

A few notes below based on my interpretation and understanding only. These are not intended as advice, guidance, recipe instructions etc. Recommend waiting for the recording and tuning in for yourself.

Cheers.

Presentation

• Edge AI – The Right compute model
• Customer Driven. Market Driven. Generations Ahead.
• Akida - in the market now, real customers and gaining traction.
• Chips, boards & systems available which people can try.
• New chip available late Summer, early Fall
• Market likes what they did with the first chip, have put additional technology into the second.
• Sean has brought on board a number of high-level industry leaders.
• Closed a set of licences already (assume MegaChips and Renesas).
• Can’t build a product without an ecosystem.
• Auto industry has a lot of interest in AI, and a lot of interest in BrainChip.
• BrainChip seeing a lot of interest from healthcare as well.
• Power consumption from data centres is unsustainable. Must move to edge market.
• Market getting stronger every single day.
• BrainChip seeing absolute interest in all markets – industrial, auto, health, home/consumer.
• Fully digital and event based is critical – allows customers to move/deploy to any technology.
• Easy to convert existing models to Akida IP.
• Gen 1 product focused on grey boxes (ie. Akida-E)
• Gen 2 product focuses on addressing orange and blue boxes (ie. Akida-S & P). This results in more functions and more Customers.
• Tech partners – lubricates the sales cycle.
• Customers want to know that varying foundries can be used.
• Selling some chips as a secondary revenue stream.
• MegaChips can build chips on behalf of other Customers.
• Renesas releasing chip in coming months.
• Neuromorphic standard will emerge over coming years - BrainChip intend to be part of that standard.
• Primary revenue is IP licensing.
• Royalties are powerful revenue streams.
• Big market, favourable trend in the edge.
• Gen 2 - Very strong positive reviews from analysts, very strong interest from Customers.
• Working with marquee brands.
• Strong team.
• Real product, real market, real Customers. Attractive business model.

Q&A

• Gen 2 – On pace for Q3 release, maybe earlier - development going well. BrainChip developing hardware and software at same time. Too early to sign customers but seeing high interest level from new prospects and existing customers.
• Future earnings guidance – not at this time. IP licensing model is lumpy and includes a long sales cycle. Hard to predict but as BrainChip matures they will provide forecasts. Complex evaluation cycles ongoing, all going well but can’t time exactly when these will land.
• When will break even be achieved – Similar to above, BrainChip is not forward projecting. Sean has a multi-year board approved plan.
• Akida 1500 – expected to sell some of these to integrators. AKD1000 chip is essentially a demo chip. Never intended to be a revenue stream itself.

Is a video of the presentation available on the website or elsewhere?

 

[goodvibes]

Chris Stevens gave it a like…dot line to amd?

Sean Gardner on LinkedIn: Another exciting product helping to address the media processing needs of…

Another exciting product helping to address the media processing needs of the M&E space.

www.linkedin.com

Very proud of our team and excited to be introducing the AMD Radeon PRO W7900 & W7800 Graphics Cards.

Designed for professionals and creators, these workstation graphics feature dedicated AI acceleration, 2nd generation ray-tracing, and AMD's advanced chiplet design.

 

[wilzy123]

Is a video of the presentation available on the website or elsewhere?

Brainchip Holdings Ltd. (OTCQX: BRCHF | ASX: BRN): Virtual Investor Conferences

Live stream the Brainchip Holdings Ltd. (OTCQX: BRCHF | ASX: BRN) presentation from the April 13, 2023 Technology Virtual Investor Conference. To join the ev...

www.youtube.com

 

[goodvibes]

Rob Telson liked this.

RECOGNI https://www.recogni.com/

See Better, Farther, Faster​

Enabling ADAS to Autonomy

The World’s Most Robust Vision Inference System​

Highest Performing Perception Inference​

The world’s first Peta-Op class inference solution. With this performance, we enable superhuman object detection accuracy up to 1000m in real-time under various road and environment conditions, with our ability to process multiple streams of ultra-high resolution & very high frame rate cameras.

Lowest Latency​

Best-in-class Power Consumption​

Vehicles of The Future: Marc Bolitho Of Recogni On The Leading Edge… | Recogni

The key factor here is the availability of purpose-built compute solutions with low latency and low power with the capability to interface with a multitude of…

www.linkedin.com

Vehicles of The Future: Marc Bolitho Of Recogni On The Leading Edge Technologies That Are Making Cars & Trucks Smarter, Safer, and More Sustainable​

An Interview With David Leichner​

Always be willing to learn. This includes in your own job role and outside your role. Technology changes over time, so spend the effort to keep up to date.

The automotive industry has been disrupted recently with new exciting technologies that have made cars and trucks much smarter, much safer, and much more sustainable and more environmentally friendly.
What other exciting disruptive technologies will we see in the next few years? How much longer will fossil fuel powered cars be produced? When will we see fully autonomous vehicles? Can we overcome the challenge of getting stuck in traffic? As cars become “moving computers”, do we have to worry about people hacking our cars? How else will our driving experience be different over the next five years? To address these questions, Authority Magazine started a new interview series about “Exciting Leading Edge Technologies That Are Making Cars & Trucks Smarter, Safer, and More Sustainable.” In this series we are talking to leaders of automotive companies, automotive tech companies, EV companies, and other tech leaders who can talk about the vehicles of the future. As a part of this series, I had the pleasure of interviewing Marc Bolitho, CEO of Recogni.
Marc Bolitho is the CEO of Recogni, the leader in AI-based perception purpose-built for autonomous vehicles. He has 28 years of experience in automotive electronics. As the Senior Vice President of ZF Group, he was responsible for the ADAS business unit with $2B in annual revenue and a global team of 5000.

Thank you so much for joining us in this interview series! Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started in the automotive industry?
From an early age, I wanted to understand how things worked and admired people that could solve problems. I made the decision early that I wanted to study engineering. I attended the University of Michigan and received my degree and started my career as a product engineer with an automotive supplier in sensor design for electronic braking and steering systems. I progressed into engineering and business leadership positions for automotive electronic safety systems covering occupant safety, braking, steering, and ADAS (Advanced Driver Assistance Systems). Today, I am CEO at Recogni, a semiconductor and software company focused on solving problems to enable autonomous mobility.
Can you share the most interesting story that happened to you since you began your career?
I have been in the industry for nearly 30 years now and have been through a few business cycles. However, the most interesting was the recent pandemic. The entire industry had to transition from in person work to remote work. At the beginning it was not clear how successful we would be at this. Fortunately, the communication tools like video conferencing were available to facilitate this. If this had happened a few years earlier, the unavailability of these tools would have hindered performance. When there are difficult times, I am always impressed that high functioning teams can accomplish more than they expected they could. This was the case in the pandemic and proved that you can run a business and product development remotely for a significant time.
Ok wonderful. Let’s now shift to the main focus of our interview. Can you tell our readers about the most interesting projects you are working on now?
I am very excited to work on overcoming barriers that the industry faces with autonomous driving. We are taming two diametrically opposing factors being high compute capability for AI processing while minimizing power consumption, effectively enhancing the driving range of electric vehicles. Our current projects are mainly centered around these pillars which are fundamental to realizing autonomous driving.
How do you think this might change the world?
This can change the world by enabling safe and sustainable autonomous driving. High compute capability allows for the full processing of the data from high resolution sensors. This allows the vehicle to detect cars and trucks at greater distance and vulnerable road users over a wide field of view. This leads to a high level of safety. Low power consumption of this processing leads to a longer driving range or less demand on the battery capacity as well as vehicle weight, minimizing the carbon footprint.
Keeping “Black Mirror” in mind, can you see any potential drawbacks of this technology that people should think more deeply about?
Two of the megatrends in the mobility industry are autonomous driving and electric vehicles. One potential drawback that the automotive industry is now comprehending is the computation capability that you need for safe autonomous driving is high. When you increase the compute, you increase the power required. This can have a significant impact on the range of electric vehicles and the carbon footprint.
Achieving driving autonomy requires technology development on many different fronts, including efficient processing, intelligent AI algorithms, and low power consumption on one side, as well as the development of high capacity, low weight batteries, and judicious, purpose-built autonomous system designs. The interdependencies of seemingly orthogonal technologies needs to be addressed to reduce or eliminate the “Black Mirror” effect.
At Recogni, the focus is on purpose-built processors for autonomous driving applications with high compute capacity, low power consumption, and very low latency. High compute capacity facilitates a fewer number of required components, feature upgradability over time, and enabling software-defined vehicles. Low power consumption significantly reduces the burden on the vehicle battery, leading to a longer range of operation and a lower carbon footprint. Low latency allows for faster vehicle reaction times, leading to a higher level of safety.
What are a few things that most excite you about the automotive industry as it is today? Why?
The automotive industry has traditionally been slow paced in development with minor evolutionary changes over time. We are now at an inflection point where OEMs are striving to bring vehicles to the market at an accelerated pace to be competitive. Given the rapid iteration cycle of tech companies — as the tech industry’s role in the development of vehicles continues to grow, innovation will propagate in the automotive industry.
I am excited to see Recogni effectively serving this major inflection point in automotive compute processing with its disruptive and purpose-built solution that resonates well with the top tier OEMs and tier ones.
What are a few things that most concern you about the automotive industry as it is today? What must be done to address these challenges?
One challenge that the industry faces is the transition to electric vehicles while increasing features on the vehicle that consume power and reduce driving range. These are not only ADAS features, but also includes AI assistant features, digital cockpit, and augmented reality.
These systems must be innovative, and purpose built for the task in the vehicle to minimize impact to range anxiety.
Based on your vantage point as an insider in the automotive industry, what other exciting disruptive technologies will we see in the next few years? Can you share some of the new developments that will make vehicles smarter, safer, and more sustainable?
Environmental awareness both outside and inside of the vehicle cabin is crucial for safety and efficient operation. We see the need for vehicle compute increase with the need for processing more environmental data, as noted earlier, in a low power profile, where there is no additional demand for battery capacity and weight.
In your opinion, how much longer will fossil fuel powered cars be produced? When do you think EVs will be the majority of vehicles in use? Can you explain?
From a mass market perspective, we see a conversion from ICE to electric vehicles year over year. In 2022 alone, while California electric passenger vehicle sales were 16%, other states had an adoption rate between 3 to 9 percent. As OEMs grow their EV offerings at various price points, we expect to see a faster conversion rate in the coming years as consumers look to purchase new models.
The time frame of EV adoption is reliant on multiple factors including consumer choices and preferences, price points, governmental policy. Currently, 6% of vehicles sold in the United States are EVs. Assuming a year over year doubling of the EV penetration rate, one could hypothesize that the majority of vehicles will be EVs within 10 years.
When do you think we will see fully autonomous vehicles deployed in a mainstream way? What do you think are the main barriers to reaching that stage?
For AVs to become commonplace, they must be able to navigate as safely as an alert driver in all weather, terrain, and lighting conditions. Existing implementations do not address the environmental sustainability issue at its core. Compute architectures are mostly general purpose and built for applications other than automotive. The key factor here is the availability of purpose-built compute solutions with low latency and low power with the capability to interface with a multitude of sensory functions.
How else will our driving experience be different over the next five years?
Going forward, vehicles will be defined by the software features that are enabled and overall user experience. This includes Advanced Driver Assistance Systems and In-Vehicle Infotainment systems. There will be an increase in the subscription model to enable these features on vehicles. To facilitate this, high performance central computing is needed that allows headroom for feature growth over time.
What are your “5 Things You Need To Create A Highly Successful Career In The Automotive Industry?

1. Have a continuous learning mindset.

• Always be willing to learn. This includes in your own job role and outside your role. Technology changes over time, so spend the effort to keep up to date.
• Go outside your comfort zone.

2. Be a great team member and help to cover gaps to make projects successful.

• Understand your role and how it interfaces with the roles around you.
• You are successful if the team is successful.

3. Maintain optimism.

• Always be optimistic, you and your team can always achieve more than seems possible at the beginning.

4. Focus on the customer and the end consumer.

• Customer proximity is important to ensure you are solving the problems that are important.
• Understand how the end consumer uses your products.

5. Identify market trends and innovate.

• Create market scenarios and innovate to cover future market gaps.
• Be bold and take a risk.

You are a person of great influence. If you could inspire a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger.

Outside of day-to-day work and business, there seems to be an increasing amount of divisiveness in the world. More time needs to be spent listening and finding common ground to create sustainable solutions for the future.

How can our readers further follow your work online?

You can follow me at: https://www.linkedin.com/in/marc-bolitho-2107346/ and Recogni at: https://www.linkedin.com/company/recogni/ and https://www.recogni.com/.

Thank you so much for the time you spent doing this interview. This was very inspirational, and we wish you continued success.

 

[goodvibes]

Post in thread 'BRN Discussion Ongoing'
https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-186708

Sorry @Diogenese

Looks like you’ve covered this already.

It’s sounding like pigeon pie for dinner tonight.

Sorry to spoil the party @M_C

Sony is looking for neuromorphic-computing-research-intern

Spiking neural network on Neuromorphic hardware…

Sony Europe sucht Neuromorphic Computing Research Intern (m/f) in Schlieren, Zürich, Schweiz | LinkedIn

19:44:14 gepostet. Neuromorphic Computing Research Intern (m/f/d)Stuttgart Laboratory 1, Advanced Sensors & Modelling…. Sehen Sie sich dieses und weitere Jobangebote auf LinkedIn an.

ch.linkedin.com

 

[Rise from the ashes]

CARLsim: GPU-accelerated Spiking Neural Network (SNN) simulator

View attachment 34272

Old mate use to be with Brn early on as a scientific advisor whatchamacallit.

 

[supersonic001]

Renesas Electronics on LinkedIn: Renesas on Panthronics Acquisition and Synopsys' Cloud EDA and Multi-die…

The latest episode of EE Times | Electronic Engineering Times Embedded Edge podcast, hosted by Embedded.com’s Editor in Chief, Nitin Dahad, just dropped. This…

www.linkedin.com

 

[perceptron]

Enjoyed listening to our CEO's investor podcast for the OTC market. Clear and concise. Moreover, I feel the company has direction and good leadership. Looking forward to the results of the long term strategy.

 

[IloveLamp]

 

[TechGirl]

Good article about ARMs M85

No mention of brainchip but in the article they mention accelerators, ML etc and they mention Renesas’s working silicon as an example.

“Arm’s partners have endorsed Cortex-M85 and already announced their plans to bring their M85-based devices to the market in the next year. For example, Renesas announced that it will demonstrate the first working silicon based on Cortex-M85.”

Cortex-M85: Safety and performance updates

This blog outlines new updates to the Arm Cortex-M85 CPU to improve safety, flexibility and performance for IoT and automotive markets.

community.arm.com

Cortex-M85: Enabling safety and boosting flexibility and performance even higher​

Dimos Rossidis
March 8, 2023


7 minute read time.

Released in 2022, Arm Cortex-M85 has been the highest performing CPU in the Cortex-M portfolio. With scalar performance of more than 6 CoreMark/MHz and 3 DMIPS/MHz, Cortex-M85 has been an excellent fit for high-performance IoT, industrial control and automotive applications. At the same time, due to the implementation of the Arm Helium Technology, Cortex-M85 demonstrates significantly higher machine learning (ML) and digital signal processing (DSP) capabilities than Cortex-M7. These benefits make Cortex-M85 a very powerful core for microcontroller (MCU) applications where compute performance is key.

The deterministic operation (due to the Tightly Coupled Memories – TCMs) combined with the high compute capabilities make Cortex-M85 an ideal CPU choice for applications where intelligence is being increasingly pushed to the edge. The processor can enable endpoint devices to not only sense and collect data, but also perform a significant amount of computation, and even execute sophisticated ML algorithms on the CPU within a predictable time frame.

There is also a rising demand for this high performance to address new workloads, and be deployed in safety critical applications where the IP needs to be capable of managing and detecting any faults.

This is why we are delighted to announce that at the end of 2022, Arm released Cortex-M85 revision 1. Cortex-M85 r1 introduces the following:

• Important functional safety features. The functional safety support helps in achieving both ASIL D/SIL 3 and, with lower hardware overhead, ASIL B/SIL2 safety requirements.
• The implementation of Arm Custom Instructions (ACI). ACI is a key feature that increases software flexibility by allowing user-defined instructions, and can also boost performance even higher by enabling accelerators that are tightly coupled with the datapath of the processor.
• Improved streaming performance, which is very important for workloads making increased memory accesses.

Cortex-M85: The first safety ready high-performing Cortex-M​

Automotive and industrial control products rely on safety standards, which ensure that each individual electrical or electronic component integrated into the product meet functional safety requirements. Arm’s Safety Readyportfolio is based on the ISO 26262 (for automotive) / IEC 61508 (for industrial) safety standards. ISO 26262 / IEC 61508 are risk-based standards that aim to address potential hazards caused by the malfunction of these systems. They provide frameworks and guidelines that should be followed during the development of a system and determine Automotive Safety Integrity Level (ASIL) / Safety Integrity Level (SIL) based on a risk assessment analysis.

In the automotive industry, Cortex-M85 can be used for diverse applications with varying safety needs. Some applications demand ASIL D for the highest safety integrity levels. One example are the high torque traction motors, where the significant growth in vehicle electrification has led to demand for more actuation across the vehicle. Other applications demand a lower safety integrity level, such as ASIL B. This is the case for vehicle cockpit displays incorporating cluster information.

Safety Ready logo
Cortex-M85 r1 is equipped with multiple safety features to address these varying safety needs. To meet the demands of ASIL D single point fault detection, Cortex-M85 can be implemented as a Dual Core Lockstep (DCLS) pair of processors, with one copy of the logic used to detect faults in the other. Although a DCLS configured Cortex-M85 can be deployed to achieve the diagnostic coverage needed for lower safety levels, the processor also supports mechanisms where this can be achieved with greater power and area efficiency. This is done through a combination of self-test functions and the ability of the Cortex-M85 r1 to detect Transient Faults. Self-testing through the use of Arm Software Test Libraries (STLs) can be used to detect permanent faults in the logic by periodically and flexibly executing the STLs on the processor. The flops in the design can be protected with the Transient Fault Protection (TFP) feature, which is able to identify a single bit fault in groups of flops. The cache memories are protected against faults with Error Correcting Code (ECC) providing Single Error Correction Double Error Detection (SECDED). In combination, these mechanisms can help deliver a more efficient solution for applications with ASIL B requirements.

Furthermore, Cortex-M85 r1 provides hardware which enables the in-field and on-line testing of the internal processor memories with Memory Built-in Self-Test (MBIST). A software Programmable MBIST Controller (PMC) can be integrated into the design to access, exercise, and test these memories while the processor continues to execute. Protection is also offered to transactions into and out of the processor by using interface protection. This is an extension to Arm’s Advanced Microcontroller Bus Architecture (AMBA) protocol and guards the transactions with parity protection against undetected corruption in the transaction between the core and the receiving interface, like the interconnect.

Arm has performed safety assessments on many of our Cortex-M processors using independent third-party assessors that issue certificates for the IP. Cortex-M85 will follow this same path. It has a safety package which provides information and evidence for partners to use in the development of products with safety requirements. For Cortex-M85, this planned assessment will evaluate both its systematic development and diagnostic capabilities for ASIL D and ASIL B.

Boosting flexibility and performance with Arm Custom Instructions​

The compute and processing requirements in recent embedded systems have increased significantly. This is especially true in the IoT space where the market is pushing the compute requirements to the endpoint devices (such as smart sensors/cameras, agricultural drones, etc.) of the IoT system.

The continuous need for higher processing capabilities results in the implementation of high performing processors, like Cortex-M85. At the same time, this raises the need for custom hardware accelerators, and the necessity for easy integration to the existing CPU. Accelerators are treated as memory-mapped IPs, through an internal coprocessor interface. Legacy Cortex-M CPUs, like Cortex-M33, implement such an interface, allowing the hardware accelerators to be closely integrated to the processor, and reducing the latency in data and instruction transfers. However, some applications require the execution of specialized data processing functions on the CPU, so that they can operate directly on general-purpose registers.

This need is addressed through Arm Custom Instructions (ACI), with Cortex-M85 – alongside Cortex-M55 – also implementing this feature. ACI allows chip designers to include custom defined data processing instructions directly on the Cortex-M processor, and enables the users to implement their own instructions by using the existing Cortex-M85 hardware.

Diagram showing how ACI combines with Cortex-M85 to meet the requirements for acceleration

Moreover, with ACI on Cortex-M85, the user does not have to turn to alternative architectures to implement a desired instruction encoding. Instead, this can now be done on CPUs that are based on the Arm architecture, with Cortex-M85 being the first high-performing microcontroller to provide this option. Through ACI, the user is given the power to innovate within the proven Arm architecture, while maintaining the ecosystem advantages of the Cortex-M CPUs.

All of the above makes ACI a powerful feature, as it provides a performance boost for low-latency instructions, easy integration with an existing software ecosystem and scalability across Cortex-M processors. ACI is the perfect fit for applications using specialized bit field processing, trigonometric functions, and image pixel manipulations. It can also be applied to accelerate frequently used data processing functions.

Upgraded streaming performance​

Cortex-M85 r1 has an enhanced datapath to deliver significantly higher streaming performance compared to the legacy Cortex-M processors. Specifically, Cortex-M85 r1 delivers about 2x higher streaming performance than Cortex-M55 and Cortex-M7 using LMbench. This enhancement is very important for any workload that requires continuous memory access across the AXI interface. For example, large footprint code that requires external memory access.

Cortex-M85 based products to be brought in the market soon​

Arm’s partners have endorsed Cortex-M85 and already announced their plans to bring their M85-based devices to the market in the next year. For example, Renesas announced that it will demonstrate the first working silicon based on Cortex-M85.

Through Cortex-M85 r1, Arm partners can now use all the enhanced features for improved performance and safety, and apply them in the IoT, automotive and industrial markets through their next-generation MCU products.

For more information, visit the Cortex-M85 page below.