BRN Discussion Ongoing

[Pom down under]

375 Principal Project Engineer jobs in United States

Today's top 375 Principal Project Engineer jobs in United States. Leverage your professional network, and get hired. New Principal Project Engineer jobs added daily.

www.linkedin.com

Job description​

Who We Are:

Join Our Team! The Tactical Aerospace team is a premier supplier for avionics and aerospace technology for new and legacy DoD systems. If you like avionics, radar systems, or even supporting EW & SIGINT systems, Tactical Aerospace is the place to be. Come Join Us! This position has the option of being a fully remote in the following states: AL, AZ, AR, Dis. of Columbia, FL, GA, MA, MD, MI, MN, NH, NJ, NC, OH, OK, OR, TX, UT, VA, WV only. Alternate work locations are San Antonio, Tx.

Objectives of this Role:

• This role is intended to be a lead over Neuromorphic/Cognitive AI research and development team and will be driving strategies and implementations of our AI solutions to meet our customers’ expectations.
• Lead the development, machine learning (ML), and test of AI as applied to Systems, UAS, Avionics, EW, and/or aerospace subsystems.
• Lead the AI team to create, and implement AI technologies/functionality and deployment strategies
• Direct staff in the performance of Literature reviews, interface with academic institutions, lead the development of proposals and lead the implementation and deployment of those systems.
• Lead a development team in code development (python, C), provide AI training to the internal SwRI Staff, lead the AI test group, implement algorithms, and perform various analysis.
• Lead the AI team in the implementation of Spiking Neural Network (SNN) techniques as well as Generation 2 AI.
  

Daily and Monthly Responsibilities:

• Develop Solutions for AI systems and embedded aerospace/avionics systems and subsystems.
• Will work on 2nd and 3rd Gen AI systems (Cognitive & Neuromorphic AI).
• Develop Solutions for neuromorphic systems, EW, SigInt, Situational Awareness, Drones (UAS/UAV), Avionics, AI/ML sensor correlation/fusion, etc.
• Perform Data Science, Data Flow/Analysis duties, provide simulations, and integrate onto hardware.
• Support business development activities.
• Will also support non-AI programs.

SwRI awarded $35.7 million to support cryptologic systems for U.S. Navy | Southwest Research Institute

Electronic warfare technology intercepts signals of interest during naval missions

www.swri.org

 

[davidfitz]

Interesting news lately about Brainchip

 

[7für7]

Interesting news lately about Brainchip

View attachment 67652

It’s not his fault actually… the media is just too incompetent to name it as it should be called! NEURALINK!! Elon, neuralink and brainchip…. What is that? this is not even helpful for brainchip to be honest.

 

[Gazzafish]

Top Neuromorphic Computing Stocks for 2025: Ranked by Pure-Play Focus

This guide covers the top neuromorphic computing stocks and companies for investors to watch, ranked by their pure-play focus.

exoswan.com

Extract:-
“

Tier 1: Pure-Play Neuromorphic Computing Stocks​

The pure-play neuromorphic computing stocks represent the cutting edge of this nascent industry. These companies stake their entire business model on the potential of these brain-inspired chips. While this focus creates higher risk, it also offers the most direct exposure for investors bullish on neuromorphic computing. With only one public company currently in this tier, it underscores just how early we are in the neuromorphic computing market.

BrainChip Holdings (ASX: BRN)​

BrainChip Holdings (ASX: BRN) is a first-mover in commercial neuromorphic computing, with a focus on energy-efficient edge AI.

Australia-based BrainChip is a pioneer in commercializing neuromorphic computing, focusing on edge AI solutions. The company has developed an Edge AI platform that combines innovative silicon IP, software, and machine learning. This platform includes the Akida neuromorphic processor. Akida is designed to process information in a way that mimics the human brain from a fundamental hardware level. This “imitation” goes beyond the deep neural networks used in today’s AI models.

Brainship enjoys first-mover advantage in commercial neuromorphic computing. The company’s technology has several unique features, including microwatt power consumption and on-chip learning, while being able to support standard machine learning workflows. In fact, it offers a claimed 5-10x improvement in performance-per-watt over traditional AI accelerators. This would make the Akida chip ideal for battery-powered devices, edge computing, and in-sensor intelligence.

The company is pursuing a flexible business model centered on high-margin IP licensing. This strategy involves upfront license fees and ongoing royalties, which could provide steady revenue as adoption grows. BrainChip’s intellectual property portfolio includes 17 granted patents and 30 pending patents. The company’s team consists of 80% engineers, with 15% holding PhDs from leading AI research programs. BrainChip is also building partnerships with system integrators, including MegaChips, Prophesee, and SiFive.”

 

[Evermont]

Intel Foundry Achieves Major Milestones​

Intel 18A powered on and healthy, on track for next-gen client and server chip production next year.

BrainChip is an IP Partner of IFS. Worth reading the second link as well.

Intel Foundry Achieves Major Milestones

Intel 18A powered on and healthy, on track for next-gen client and server chip production next year.

www.intel.com

Kevin O’Buckley Talks Progress on Intel 18A

New Foundry Services leader reveals why he came to Intel, excitement for the foundry business and why Intel 18A matters to the future of computing.

www.intel.com

 

[Smoothsailing]

Regarding this Intel 18A platform if I am reading this correctly it will be the customer whom chooses their particular design and if it is to include BRN Akida , is that correct?.

 

[Diogenese]

Top Neuromorphic Computing Stocks for 2025: Ranked by Pure-Play Focus

This guide covers the top neuromorphic computing stocks and companies for investors to watch, ranked by their pure-play focus.

exoswan.com

Extract:-
“

Tier 1: Pure-Play Neuromorphic Computing Stocks​

The pure-play neuromorphic computing stocks represent the cutting edge of this nascent industry. These companies stake their entire business model on the potential of these brain-inspired chips. While this focus creates higher risk, it also offers the most direct exposure for investors bullish on neuromorphic computing. With only one public company currently in this tier, it underscores just how early we are in the neuromorphic computing market.

BrainChip Holdings (ASX: BRN)​

BrainChip Holdings (ASX: BRN) is a first-mover in commercial neuromorphic computing, with a focus on energy-efficient edge AI.

Australia-based BrainChip is a pioneer in commercializing neuromorphic computing, focusing on edge AI solutions. The company has developed an Edge AI platform that combines innovative silicon IP, software, and machine learning. This platform includes the Akida neuromorphic processor. Akida is designed to process information in a way that mimics the human brain from a fundamental hardware level. This “imitation” goes beyond the deep neural networks used in today’s AI models.

Brainship enjoys first-mover advantage in commercial neuromorphic computing. The company’s technology has several unique features, including microwatt power consumption and on-chip learning, while being able to support standard machine learning workflows. In fact, it offers a claimed 5-10x improvement in performance-per-watt over traditional AI accelerators. This would make the Akida chip ideal for battery-powered devices, edge computing, and in-sensor intelligence.

The company is pursuing a flexible business model centered on high-margin IP licensing. This strategy involves upfront license fees and ongoing royalties, which could provide steady revenue as adoption grows. BrainChip’s intellectual property portfolio includes 17 granted patents and 30 pending patents. The company’s team consists of 80% engineers, with 15% holding PhDs from leading AI research programs. BrainChip is also building partnerships with system integrators, including MegaChips, Prophesee, and SiFive.”

Hi Gazza,

Thanks for this. We've seen a couple of articles along this line, which allow me to maintain my illusion about software as a product.

As you may or may not know, I've been posting about the possibility of our EAPs using Akida simulation software, particularly after the emergence of Akida 2 + TeNNs more than 30 months ago, with Valeo and MB using software for signal processing. This sentence from the article again adds more grist to that rumor mill:

"The company has developed an Edge AI platform that combines innovative silicon IP, software, and machine learning."

To repeat myself, no potential user would commit to Akida 2 in silicon while the tech was in a state of flux. The use of software AI is not so problematic in ICEs as it is in EVs, but from what we've heard about TeNNs, the power and latency could be tolerated in EVs using TeNNs in software. Of course, the software would sensibly include the full Akida 2 simulation including TeNNs, or TeNNs could be used on its own. Software can be readily updated as new developments are implemented, whereas silicon is set in stone.

It's been several months since Anil announced the proposed tapeout of Akida 2, which suggests that the development had reached a satisfactory plateau of stability sufficient for the company to commit to silicon. The tapeout was subsequently "delegated" to a mysterious "other" - the rest is silence.

The SPP talks about developing a cloud-based FPGA demonstration setup, again, not a tapeout. This would be a cheaper way to obtain customer feedback than taping out and making a batch of "engineering sample" chips.

Presumably the mysterious "other" would want to be in on the results of the cloud feedback before going to silicon.

Does this mean that we need to wait for the cloud FPGA venture to provide meaningful results before the tapeout can be implemented? - sigh!

Does it follow that BRN will become a software provider, at least in the short term?

 

[MadMayHam | 合氣道]

Hi Gazza,

Thanks for this. We've seen a couple of articles along this line, which allow me to maintain my illusion about software as a product.

As you may or may not know, I've been posting about the possibility of our EAPs using Akida simulation software, particularly after the emergence of Akida 2 + TeNNs more than 30 months ago, with Valeo and MB using software for signal processing. This sentence from the article again adds more grist to that rumor mill:

"The company has developed an Edge AI platform that combines innovative silicon IP, software, and machine learning."

To repeat myself, no potential user would commit to Akida 2 in silicon while the tech was in a state of flux. The use of software AI is not so problematic in ICEs as it is in EVs, but from what we've heard about TeNNs, the power and latency could be tolerated in EVs using TeNNs in software. Of course, the software would sensibly include the full Akida 2 simulation including TeNNs, or TeNNs could be used on its own. Software can be readily updated as new developments are implemented, whereas silicon is set in stone.

It's been several months since Anil announced the proposed tapeout of Akida 2, which suggests that the development had reached a satisfactory plateau of stability sufficient for the company to commit to silicon. The tapeout was subsequently "delegated" to a mysterious "other" - the rest is silence.

The SPP talks about developing a cloud-based FPGA demonstration setup, again, not a tapeout. This would be a cheaper way to obtain customer feedback than taping out and making a batch of "engineering sample" chips.

Presumably the mysterious "other" would want to be in on the results of the cloud feedback before going to silicon.

Does this mean that we need to wait for the cloud FPGA venture to provide meaningful results before the tapeout can be implemented? - sigh!

Does it follow that BRN will become a software provider, at least in the short term?

@Diogenese what do you mean by "The tapeout was subsequently "delegated" to a mysterious "other" - " ?

 

[Frangipani]

Researchers at UC Irvine’s Cognitive Anteater Robotics Laboratory (CARL), led by Jeffrey Krichmar, have been experimenting with AKD1000:

CARL: Home Page

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

GitHub - UCI-CARL/CARLsimPP

Contribute to UCI-CARL/CARLsimPP development by creating an account on GitHub.

github.com

https://arxiv.org/pdf/2404.08726

 

[FJ-215]

Hi Gazza,

Thanks for this. We've seen a couple of articles along this line, which allow me to maintain my illusion about software as a product.

As you may or may not know, I've been posting about the possibility of our EAPs using Akida simulation software, particularly after the emergence of Akida 2 + TeNNs more than 30 months ago, with Valeo and MB using software for signal processing. This sentence from the article again adds more grist to that rumor mill:

"The company has developed an Edge AI platform that combines innovative silicon IP, software, and machine learning."

To repeat myself, no potential user would commit to Akida 2 in silicon while the tech was in a state of flux. The use of software AI is not so problematic in ICEs as it is in EVs, but from what we've heard about TeNNs, the power and latency could be tolerated in EVs using TeNNs in software. Of course, the software would sensibly include the full Akida 2 simulation including TeNNs, or TeNNs could be used on its own. Software can be readily updated as new developments are implemented, whereas silicon is set in stone.

It's been several months since Anil announced the proposed tapeout of Akida 2, which suggests that the development had reached a satisfactory plateau of stability sufficient for the company to commit to silicon. The tapeout was subsequently "delegated" to a mysterious "other" - the rest is silence.

The SPP talks about developing a cloud-based FPGA demonstration setup, again, not a tapeout. This would be a cheaper way to obtain customer feedback than taping out and making a batch of "engineering sample" chips.

Presumably the mysterious "other" would want to be in on the results of the cloud feedback before going to silicon.

Does this mean that we need to wait for the cloud FPGA venture to provide meaningful results before the tapeout can be implemented? - sigh!

Does it follow that BRN will become a software provider, at least in the short term?

Hi @Diogenese,

One question I would have for Sean, is, how do we provide yield numbers for Akida 2 without proving it out in silicon? Yes, we have AKD 1000/1500 from two different foundries but no commercial runs to speak of.

If I remember the ARM history correctly, they were on their 4th or 5th run of commercial chips before going down the IP route that BRN is trying to copy.

 

[FiveBucks]

Hi @Diogenese,

One question I would have for Sean, is, how do we provide yield numbers for Akida 2 without proving it out in silicon? Yes, we have AKD 1000/1500 from two different foundries but no commercial runs to speak of.

If I remember the ARM history correctly, they were on their 4th or 5th run of commercial chips before going down the IP route that BRN is trying to copy.

Did we jump the gun by going the IP route?

Or are we ahead of the game?

 

[FJ-215]

Did we jump the gun by going the IP route?

Or are we ahead of the game?

Who knows, maybe a mix of the two.

 

[Frangipani]

Researchers at UC Irvine’s Cognitive Anteater Robotics Laboratory (CARL), led by Jeffrey Krichmar, have been experimenting with AKD1000:








View attachment 67694

CARL: Home Page

View attachment 67690


View attachment 67691

View attachment 67692

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

View attachment 67693

GitHub - UCI-CARL/CARLsimPP

Contribute to UCI-CARL/CARLsimPP development by creating an account on GitHub.

github.com

View attachment 67695

https://arxiv.org/pdf/2404.08726

https://arxiv.org/pdf/2404.08726

This is the paper I linked in my previous post, co-authored by Lars Niedermeier, a Zurich-based IT consultant, and the above-mentioned Jeff Krichmar from UC Irvine.

The two of them co-authored three papers in recent years, including one in 2022 with another UC Irvine professor and member of the CARL team, Nikil Dutt (https://ics.uci.edu/~dutt/) as well as Anup Das from Drexel University, whose endorsement of Akida is quoted on the BrainChip website:

Lars Niedermeier’s and Jeff Krichmar’s April 2024 publication on CARLsim++ (which does not mention Akida) ends with the following conclusion and the acknowledgement that their work was supported by the Air Force Office of Scientific Research - the funding has been going on at least since 2022 -

UCI-led team uses robots to study brain’s ability to switch between first-person experience and global map

and a UCI Beall Applied Innovation Proof of Product Award (https://innovation.uci.edu/pop/)

and they also thank the regional NSF I-Corps (= Innovation Corps) for valuable insights.

Their use of an E-Puck robot (https://en.m.wikipedia.org/wiki/E-puck_mobile_robot) for their work reminded me of our CTO’s address at the AGM in May, during which he envisioned the following object (from 22:44 min):

“Imagine a compact device similar in size to a hockey puck that combines speech recognition, LLMs and an intelligent agent capable of controlling your home’s lighting, assisting with home repairs and much more. All without needing constant connectivity or having to worry about privacy and security concerns, a major barrier to adaptation, particularly in industrial settings.”

Possibly something in the works here?

The version the two authors were envisioning in their April 2024 paper is, however, conceptualised as being available as a cloud service:

“We plan a hybrid approach to large language models available as cloud service for processing of voice and text to speech.”


The authors gave a tutorial on CARLsim++ at NICE 2024, where our CTO Tony Lewis was also presenting. Maybe they had a fruitful discussion at that conference in La Jolla, which resulted in UC Irvine’s Cognitive Anteater Robotics Laboratory (CARL) team experimenting with AKD1000, as evidenced in the video uploaded a couple of hours ago that I shared in my previous post?

NICE 2024 - Agenda

GCtronic

www.gctronic.com

 

[Frangipani]

https://arxiv.org/pdf/2404.08726

View attachment 67696

This is the paper I linked in my previous post, co-authored by Lars Niedermeier, a Zurich-based IT consultant, and the above-mentioned Jeff Krichmar from UC Irvine.


View attachment 67703

The two of them co-authored three papers in recent years, including one in 2022 with another UC Irvine professor and member of the CARL team, Nikil Dutt (https://ics.uci.edu/~dutt/) as well as Anup Das from Drexel University, whose endorsement of Akida is quoted on the BrainChip website:

View attachment 67702


View attachment 67700




View attachment 67701

Lars Niedermeier’s and Jeff Krichmar’s April 2024 publication on CARLsim++ (which does not mention Akida) ends with the following conclusion and the acknowledgement that their work was supported by the Air Force Office of Scientific Research - the funding has been going on at least since 2022 -

UCI-led team uses robots to study brain’s ability to switch between first-person experience and global map

and a UCI Beall Applied Innovation Proof of Product Award (https://innovation.uci.edu/pop/)

and they also thank the regional NSF I-Corps (= Innovation Corps) for valuable insights.

View attachment 67699



View attachment 67704


Their use of an E-Puck robot (https://en.m.wikipedia.org/wiki/E-puck_mobile_robot) for their work reminded me of our CTO’s address at the AGM in May, during which he envisioned the following object (from 22:44 min):

“Imagine a compact device similar in size to a hockey puck that combines speech recognition, LLMs and an intelligent agent capable of controlling your home’s lighting, assisting with home repairs and much more. All without needing constant connectivity or having to worry about privacy and security concerns, a major barrier to adaptation, particularly in industrial settings.”

Possibly something in the works here?

The version the two authors were envisioning in their April 2024 paper is, however, conceptualised as being available as a cloud service:

“We plan a hybrid approach to large language models available as cloud service for processing of voice and text to speech.”


The authors gave a tutorial on CARLsim++ at NICE 2024, where our CTO Tony Lewis was also presenting. Maybe they had a fruitful discussion at that conference in La Jolla, which resulted in UC Irvine’s Cognitive Anteater Robotics Laboratory (CARL) team experimenting with AKD1000, as evidenced in the video uploaded a couple of hours ago that I shared in my previous post?

NICE 2024 - Agenda

View attachment 67705

GCtronic

www.gctronic.com

View attachment 67716

While I was out running errands just now, I recalled that we had some sort of connection to UCI through one of our research scientists - and bingo!

Kristofor Carlson was a postdoc at Jeff Krichmar‘s Cognitive Robotics Lab a decade ago and co-authored a number of research papers with both Jeff Krichmar and Nikil Dutt over the years, the last one published in 2019:

 

[charles2]

Changes are being made.

Big ones

BrainChip Appoints New CMO, Enhances Scientific Advisory Board

LAGUNA HILLS, Calif., August 07, 2024--BrainChip Appoints New CMO, Enhances Scientific Advisory Board

finance.yahoo.com

 

[charles2]

And huge capitulation on NASDAQ for BRCHF.

Over 700k on offer and sizable share dumps as low as 10 cents (US)

Usually capitulation is a good sign.....the weak hands give up at any price.

(He says wistfully).

 

[Diogenese]

Intel Foundry Achieves Major Milestones​

Intel 18A powered on and healthy, on track for next-gen client and server chip production next year.

View attachment 67663

View attachment 67664


BrainChip is an IP Partner of IFS. Worth reading the second link as well.

View attachment 67665

Intel Foundry Achieves Major Milestones

Intel 18A powered on and healthy, on track for next-gen client and server chip production next year.

www.intel.com

Kevin O’Buckley Talks Progress on Intel 18A

New Foundry Services leader reveals why he came to Intel, excitement for the foundry business and why Intel 18A matters to the future of computing.

www.intel.com

Hi Evermont,

Interesting development.

Could it be that the tapeout of Akida 2 has been delayed so it can be adapted for Intel's 18A process?


https://www.intel.com/content/www/u...ndry-achieves-major-milestones.html#gs.dahsjf

What’s New: Intel today announced that its lead products on Intel 18A, Panther Lake (AI PC client processor) and Clearwater Forest (server processor), are out of the fab and have powered-on and booted operating systems. These milestones were achieved less than two quarters after tape-out, with both products on track to start production in 2025. The company also announced that the first external customer is expected to tape out on Intel 18A in the first half of next year.
...
More on Intel 18A: In July, Intel released the 18A Process Design Kit (PDK) 1.0, design tools that enable foundry customers to harness the capabilities of RibbonFET gate-all-around transistor architecture and PowerVia backside power delivery in their designs on Intel 18A. Electronic design automation (EDA) and intellectual property (IP) partners are updating their offerings to enable customers to begin their final production designs.
...
How Customers are Involved: In gaining access to the Intel 18A PDK 1.0 last month, the company’s EDA and IP partners are updating their tools and design flows to enable external foundry customers to begin their Intel 18A chip designs. This is a critical enabling milestone for Intel’s foundry business.

The "A" in 18A is Angstrom, a measurement unit = 0.1 nm, so 18A = 1.8 nm. At these distances you're starting to get close to where parasitic quantum effects can influence the operation of the transistors, and the impedance of the connecting "wires" becomes a significant source of power loss. I would think that this will need a whole new design system. Intel are using gate-all-around transistors which are very different from our planar CMOS technology - no wonder Anil is retiring!

Akida's SNN sparsity would help overcome the connector wire impedance loss by sending electrical impulses less frequently than MACs.

 

[CHIPS]

There is new hope on the horizon!

BrainChip Appoints New CMO, Enhances Scientific Advisory Board

BrainChip Appoints New CMO, Enhances Scientific Advisory Board Laguna Hills, Calif. – August 7th, 2024 – BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low power, fully digital, event-based, neuromorphic AI, today announced that it...

brainchip.com

BrainChip Appoints New CMO, Enhances Scientific Advisory Board​

Laguna Hills, Calif. – August 7th, 2024 – BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low power, fully digital, event-based, neuromorphic AI, today announced that it has hired Steven Brightfield as its new chief marketing officer and has re-envisioned its Scientific Advisory Board (SAB) by bringing on company founder Peter van der Made, Dr. Jason K. Eshraghian and Dr. André van Schaik.

Brightfield has a depth of tech industry knowledge and experience within the AI semiconductor industry. He previously led marketing at several AI focused technology companies, such as SiMa.ai, X-Silicon and Wave Computing combined with deep experience within the semiconductor sector, including executive leadership positions at LSI Logic, Qualcomm, Zoran and others. One of Brightfield’s first priorities at BrainChip will be to oversee the development of a marketing strategy for the new TENNs product, an advanced, ultra efficient neural network architecture and integrate it into the Akida technology platform.

The Scientific Advisory Board provides independent advice and expert consultation for the executive staff of Brainchip to guide the scientific and technical aspects of the company’s short-and long-term goals. The SAB also reviews and evaluates the research and development programs of BrainChip with respect to quality and scope. The re-envisioned SAB provides new perspectives from key industry leaders in AI with increasing focus under the leadership of Dr. Tony Lewis.

van der Made has been at the forefront of computer innovation for 45 years. One of the founders of BrainChip, he designed the first generations of digital neuromorphic devices on which the Akida™ chip was based. van der Made previously served as chief technology officer for BrainChip until his retirement last year. He remains a member of the company’s board of directors.

Eshraghian is an Assistant Professor with the Department of Electrical and Computer Engineering, University of California, Santa Cruz. He serves as the Secretary of the Neural Systems and Applications Technical Committee. His research interests are in large-scale neuromorphic computing. Dr. Eshraghian is the developer of snnTorch, a widely used Python library with more than 150,000 downloads used to train and model spiking neural networks, and his lab developed several high-profile language models, including SpikeGPT, and the MatMul-
Free LLM.

Van Schaik is a pioneer of the field of neuromorphic engineering. He is a professor of electrical engineering at the Western Sydney University and director of the International Centre for Neuromorphic Systems, also in Australia. His research focuses on neuromorphic engineering and computational neuroscience. Dr. Van Schaik has authored more than 300 publications, invented more than 35 patents and is a founder of four start-up companies: VAST Audio, Personal Audio, Heard Systems and Optera.

“I am pleased to add new team members with the skills, experience and credentials to advance BrainChip’s adoption in the market” said Sean Hehir, BrainChip’s CEO. “Leveraging Steve’s expertise as a technology marketer and expanding our Scientific Advisory Board with some of the keenest minds in the industry, better positions us to achieve our goals. I am eager to work closely with each of them.”

 

[Diogenese]

Changes are being made.

Big ones

BrainChip Appoints New CMO, Enhances Scientific Advisory Board

LAGUNA HILLS, Calif., August 07, 2024--BrainChip Appoints New CMO, Enhances Scientific Advisory Board

finance.yahoo.com

Hi Charles,

I think our new CMO should invest in a quality pair of garters because he's about to have, or probably already has had, his socks blown off. He will be doing a crash course in digital SNNs.

His earlier foray into AI marketing at Wave Computer* was based on MACs and one of his muses is Yan le Cun who is not a fan of SNNs.

US11227030B2 Matrix multiplication engine using pipelining 20190401

a matrix multiplication engine using pipelining are disclosed. A first and a second matrix are obtained for matrix multiplication. A first matrix multiply-accumulate (MAC) unit is configured, where a first matrix element and a second matrix element are presented to the MAC unit on a first cycle. A second MAC unit is configured in pipelined fashion, where the first element of the first matrix and a second element of the second matrix are presented to the second MAC unit on a second cycle, and where a second element of the first matrix and the first element of the second matrix are presented to the first MAC unit on the second cycle. Additional MAC units are further configured within the processor in pipelined fashion. Multiply-accumulate operations are executed in pipelined fashion on each of n MAC units over additional k sets of m cycles.


*WC recently emerged from Chapter 11 bankruptcy.

 

[Frangipani]

Changes are being made.

Big ones

BrainChip Appoints New CMO, Enhances Scientific Advisory Board

LAGUNA HILLS, Calif., August 07, 2024--BrainChip Appoints New CMO, Enhances Scientific Advisory Board

finance.yahoo.com

… and small ones, too:

Merci beaucoup et au revoir, Sébastien Crouzet…

… and welcome to another University of Washington summer intern - Justin-Pierre Tremblay!

FNU Sidharth, a Graduate Student Researcher from the University of Washington in Seattle, will be spending the summer as a Machine Learning Engineering Research Intern at BrainChip:




View attachment 66341

View attachment 66342

View attachment 66344


Bingo!

https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-425543

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