BRN Discussion Ongoing

[manny100]

I love it our 1st bit of tech in Akida 1000 is outdated with no success or deals

As far as robotics and many mobile assets the lastest tech is appropriate because if you do not update to it a competitor will.
You have taken my post out of context.
For security and finance Kevin Johnson tests demonstrates that AKIDA1000 is great with a huge ROI. He has said that he will test the 1500 etc later.
Updates for mobile assets including wearables will prove to be money spinner once these assets become entrenched.
BRN has to ensure upgrades are easy and cost efficient and there will be a healthy aftermarket as well as new market.

 

[Fiendish]

hm

#uav #drone #thermalimaging #infrared #dronetechnology #dronesensors #eoir #thermalcamera #uavpayload #dronepayload #infraredcamera #roboticsvision #aerialsurveillance #securitytechnology… | Chris Luo

🚀 Thermal Imaging Module for UAV & Drone Applications – NANO640 We are pleased to introduce a compact 640×512 uncooled VOx thermal imaging module designed for UAV payload integration, drone sensing systems, and EO/IR surveillance platforms. This ultra-compact infrared thermal camera core is...

www.linkedin.com

View attachment 96292 View attachment 96293 View attachment 96294

These specs are standard in the uncooled thermal industry (many Chinese/European modules hit similar numbers). Adding Akida could enable an onboard Ai for object spotting/detection and spotting anomalies. Ai enabled drones is where its at.

 

[7For7]

These specs are standard in the uncooled thermal industry (many Chinese/European modules hit similar numbers). Adding Akida could enable an onboard Ai for object spotting/detection and spotting anomalies. Ai enabled drones is where its at.

Yes, I just figured that out myself. After I shared the post, my algorithm completely shifted toward military and industrial drones. It’s amazing how crowded the market is. As you said, they all seem to have very similar specifications. I’m wondering whether those specs are simply enough for end customers, or whether the next major shift will be Edge AI on board. After all, these systems are relatively easy to hack, which gives opponents a clear advantage. Just my view.

 

[Fiendish]

Yes, I just figured that out myself. After I shared the post, my algorithm completely shifted toward military and industrial drones. It’s amazing how crowded the market is. As you said, they all seem to have very similar specifications. I’m wondering whether those specs are simply enough for end customers, or whether the next major shift will be Edge AI on board. After all, these systems are relatively easy to hack, which gives opponents a clear advantage. Just my view.

Ukraine is already using basic AI for object detection/targeting, switching to cruise mode when traveling through jamming zones ect. Those capabilities are usually thanks to an added raspberry pi.

That has increased their hit rate on vehicles/tanks etc to 70-80% so fair to say the smarter the drone, the more lethal.

These drones are being mads produced for a few hundred bucks each with the added 'smart' aspects costing a few hundred more.

Making cheap effective smart drones is going to be on everyones to do list that doesnt mind the odd spot of war

 

[7For7]

Ukraine is already using basic AI for object detection/targeting, switching to cruise mode when traveling through jamming zones ect. Those capabilities are usually thanks to an added raspberry pi.

That has increased their hit rate on vehicles/tanks etc to 70-80% so fair to say the smarter the drone, the more lethal.

These drones are being mads produced for a few hundred bucks each with the added 'smart' aspects costing a few hundred more.

Making cheap effective smart drones is going to be on everyones to do list that doesnt mind the odd spot of war

Then I have nothing more to say than “go Brainchip”

 

[Pom down under]

Ukraine is already using basic AI for object detection/targeting, switching to cruise mode when traveling through jamming zones ect. Those capabilities are usually thanks to an added raspberry pi.

That has increased their hit rate on vehicles/tanks etc to 70-80% so fair to say the smarter the drone, the more lethal.

These drones are being mads produced for a few hundred bucks each with the added 'smart' aspects costing a few hundred more.

Making cheap effective smart drones is going to be on everyones to do list that doesnt mind the odd spot of war

 

[Bravo]

Ukraine is already using basic AI for object detection/targeting, switching to cruise mode when traveling through jamming zones ect. Those capabilities are usually thanks to an added raspberry pi.

That has increased their hit rate on vehicles/tanks etc to 70-80% so fair to say the smarter the drone, the more lethal.

These drones are being mads produced for a few hundred bucks each with the added 'smart' aspects costing a few hundred more.

Making cheap effective smart drones is going to be on everyones to do list that doesnt mind the odd spot of war

 

[Bravo]

Actually, in all seriousness, the capabilities we’re seeing in drones, AI and electronic warfare are extremely significant. They have the potential to fundamentally change how warfare is conducted, and not necessarily for the better. In many ways, it’s a much more confronting and uncertain future.

In particular, I didn’t intend for my GIF to come across as cavalier about the risks faced by armed forces today. If anything, I find the dual-use nature of this technology quite challenging. The same innovations that can be used for protection and defence can also be used in ways that cause significant harm, and that’s not something I, and I suspect many others here, take lightly.

 

[smoothsailing18]

To invest in brainchip is supporting the country's endeavours against enemy's which is better than not imo. I see brainchip and Ai in general the gateway to the next stage of humanity's evolution like it or not. Hopefully for the better in the long run. Until then plenty of opportunities in improving health diagnostics and prevention which is the upside.

 

[Jacob Kiraz]

As far as robotics and many mobile assets the lastest tech is appropriate because if you do not update to it a competitor will.
You have taken my post out of context.
For security and finance Kevin Johnson tests demonstrates that AKIDA1000 is great with a huge ROI. He has said that he will test the 1500 etc later.
Updates for mobile assets including wearables will prove to be money spinner once these assets become entrenched.
BRN has to ensure upgrades are easy and cost efficient and there will be a healthy aftermarket as well as new market.

Well i cant wait for that day to happen, I feel Brainchip was at the starting line with there Tech but the industry were getting changed in the sheds ,
It takes time its a pity the company strung us along, hopefully 1 day there will be a abundance of annoucements

 

[Pom down under]

Actually, in all seriousness, the capabilities we’re seeing in drones, AI and electronic warfare are extremely significant. They have the potential to fundamentally change how warfare is conducted, and not necessarily for the better. In many ways, it’s a much more confronting and uncertain future.

In particular, I didn’t intend for my GIF to come across as cavalier about the risks faced by armed forces today. If anything, I find the dual-use nature of this technology quite challenging. The same innovations that can be used for protection and defence can also be used in ways that cause significant harm, and that’s not something I, and I suspect many others here, take lightly.

I watched an Iranian drone attack yesterday and like you say @Bravo wars are now at a turning point when you don’t need a 100 million dollar plane to inflict destruction when a drone that does cost less than $1000 with similar capabilities can do similar if not more damage

https://www.news.com.au/technology/innovation/military/insane-iran-drone-attack-changes-everything/news-story/aeb5ceed4ce5cf9b6c12440148dc9927?amp

 

[Pom down under]

Well i cant wait for that day to happen, I feel Brainchip was at the starting line with there Tech but the industry were getting changed in the sheds ,
It takes time its a pity the company strung us along, hopefully 1 day there will be a abundance of annoucements

How’s your day treating you shitstick?

 

[Fiendish]

Actually, in all seriousness, the capabilities we’re seeing in drones, AI and electronic warfare are extremely significant. They have the potential to fundamentally change how warfare is conducted, and not necessarily for the better. In many ways, it’s a much more confronting and uncertain future.

In particular, I didn’t intend for my GIF to come across as cavalier about the risks faced by armed forces today. If anything, I find the dual-use nature of this technology quite challenging. The same innovations that can be used for protection and defence can also be used in ways that cause significant harm, and that’s not something I, and I suspect many

Wars tend to fast track various technologies from lab to mass use quickly. Russia invading Ukraine has kicked off drone warfare in a big way which has inadvertently created perfect conditions for Neuromorphic tech. The russia Ukraine conflict has become a giant war lab.. and wars drive rapid innovation, prototyping, testing and contracts.

I for one am happy our allies seem to be in front of that race though i pity anyone being hunted by a weaponised drone, can think of anything more terrifying than one of those things buzzing around attempting to end me.

Given our partnerships with us air force, raytheon and parsons i think its a given that our favourite little chip is being given some extra war time funding to expediate its usefulness for military application's.

All good tech starts in space, then military and then into your fridge imo.

Going to be a wild year i expect. There is a lit going on out there.

 

[Jacob Kiraz]

How’s your day treating you shitstick?

How’s your day treating you shitstick?

Very Good Witz 123 counting the beat 2,3,4,5

 

[White Horse]

This article provides some food for thought.!

IBM Closes $11 Billion Deal for Confluent
Deal will help companies access their data for AI agents, says IBM CEO Arvind Krishna, as he brushes off AI’s risk to IBM’s business.

To make AI agents work, “you need to be able to get data wherever it is” and get it instantly, IBM Chief Arvind Krishna said. Jorge Gil/Zuma Press

International Business Machines said Tuesday it closed its roughly $11 billion acquisition of the data-streaming company Confluent.

The deal, first announced in December, is intended to help businesses access their data for AI agents, or bots that can take action on their own.

At the moment, corporate data is spread across multiple information-technology systems, from software applications to private data centers and cloud platforms. To make AI agents work, “you need to be able to get data wherever it is” and get it instantly, IBM Chief Executive Arvind Krishna told The Wall Street Journal.

That’s why Confluent “has been something that we have been keeping an eye on for a long time,” Krishna continued.

Armonk, N.Y.-based IBM’s acquisition comes as technology vendors are increasingly selling tools to help businesses use, manage and create AI agents. The bots are sweeping through American corporations even as business tech leaders are struggling to oversee and safely scale those agents.

For IBM, Confluent’s technology will become the “backbone” of its own platform for helping business clients access their data for various AI uses, Krishna said. That’s the same tack IBM took with its $33 billion acquisition of Red Hat, which became IBM’s default technology to help customers update their software applications, he said.

The acquisition is also central to Krishna’s vision of positioning IBM as a leading player in hybrid cloud-computing and AI. It is IBM’s second-largest deal in history, and aims to give businesses a way to make use of their old-school IT systems and data in the AI era.
The Challenges AI Poses for IBM

IBM itself has been sorting through the impact of AI agents on its workforce. About three years ago, IBM began adding AI and AI agents to its internal operations which has since added roughly $4.5 billion in productivity to its bottom line, Krishna said. Over $3 billion of that total has been reinvested in research and development and other areas, he said.

At the moment, AI agents are best suited to “low-risk” areas like software development, customer support, enterprise operations, HR and payroll, Krishna said. Over time, they could be used to directly market a product to a customer.

“There is a whole set of mundane AI use cases that we can keep ourselves busy for the next two, three years just getting those done,” he said.

Looking ahead, rote white-collar work will be “displaced” by work requiring greater human interaction and more decision-making, according to Krishna.

Last year, the company said that bots had begun to do the work of a couple of hundred of its human-resources workers.

Krishna said he expects IBM will maintain or grow its head count in the next five years—mostly in areas like consulting, sales and coding. But, roughly 20% of the company’s enterprise operations and customer-support roles “could see a change” over the next two years, he added.

In February, IBM stock posted its worst decline in 25 years—tumbling sharply on news that Anthropic had released AI tools that could help with modernizing Cobol, a programming language mainly run on IBM mainframe computers.

Krishna said IBM has its own tools to help modernize Cobol applications, and noted that its stock has since rebounded: “I think people also realized that was way exaggerated in terms of its impact,” he said.

More largely, Krishna said he believes IBM is insulated from the perceived risk of AI and AI agents to software businesses. “A lot of what we do is enabling middleware, enabling software. We are not that much in application software, and so I think [volatility] is actually a tailwind for us,” he said.

 

[Frangipani]

https://www.businesswire.com/news/home/20260318799971/en/ForwardEdge-ASIC-Selects-BrainChips-Neuromorphic-Computing-for-Future-ASICs

Mar 18, 2026 9:00 AM Eastern Daylight Time

ForwardEdge ASIC Selects BrainChip’s Neuromorphic Computing for Future ASICs​

Share

---

First Step in a Strategic Collaboration for Cognitive Sensing Solutions in RF and Signal Processing

LAGUNA HILLS, Calif.--(BUSINESS WIRE)--BrainChip Holdings Ltd. (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), a leading developer of ultra-low-power, fully digital, event-based neuromorphic AI, today announced a strategic collaboration with ForwardEdge ASIC, a wholly owned subsidiary of Lockheed Martin (NYSE: LMT) specializing in advanced ASIC architecture and microelectronics development.

“This collaboration demonstrates how BrainChip’s AI technology can be tightly integrated into advanced ASIC and RF platforms to deliver powerful, efficient intelligence at the edge,” Steven Brightfield, CMO at BrainChip.

Together, the companies are combining best-in-class AI technology with deep ASIC and system integration expertise to deliver differentiated edge-processing solutions for demanding aerospace, defense, and advanced technology markets.

A Strategic Collaboration for Intelligent Edge Systems
This collaboration brings together BrainChip’s leadership in neuromorphic AI architecture and ForwardEdge ASIC’s strengths in custom silicon development, heterogeneous integration, and advanced RF systems. The collaboration is focused on tightly coupling AI acceleration with signal processing and RF compute to enable high-performance, low-latency intelligence at the edge.
By embedding BrainChip’s neuromorphic AI engines directly into ForwardEdge ASIC’s architectures, the companies are enabling cognitive processing closer to the sensor—reducing data movement, lowering power consumption, and enabling autonomous operation in complex operational environments.

“ForwardEdge ASIC is focused on architecting and delivering highly integrated silicon solutions that leverage the most advanced technologies available,” said Bill Jenkins, CRO at ForwardEdge ASIC. “BrainChip’s Akida architecture is a strong complement to our ASIC and RF platforms, allowing us to integrate dedicated AI acceleration directly into the silicon. This collaboration enables us to deliver scalable, high-performance low-latency edge solutions that push intelligence closer to the point of sensing.”

Enabling a New Class of Cognitive Sensing Solutions
The joint solution leverages a heterogeneous architecture that combines custom ASIC processing, RF signal chains, and neuromorphic AI acceleration to deliver efficient, real-time detection and classification. Key capabilities include:

• Cognitive RF and Signal Processing: Real-time classification of complex signals with adaptive, AI-driven processing.
• Scalable ASIC Platforms: Architectures designed for reuse across multiple programs and deployment environments.
• Efficient Edge Intelligence: Ultra-low-power AI processing optimized for latency-sensitive and resource-constrained systems.

This collaboration allows both companies to accelerate innovation while reducing integration risk for customers seeking production-ready edge AI solutions.
“ForwardEdge ASIC brings deep system-level design and integration expertise that is essential for deploying neuromorphic AI in real-world applications,” said Steven Brightfield, CMO at BrainChip. “This collaboration demonstrates how BrainChip’s AI technology can be tightly integrated into advanced ASIC and RF platforms to deliver powerful, efficient intelligence at the edge.”

About BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY) BrainChip is the worldwide leader in Edge AI on-chip processing and learning. The company’s first-to-market, fully digital, event-based AI processor, Akida™, uses neuromorphic principles to mimic the human brain, analyzing only essential sensor inputs at the point of acquisition and processing data with unmatched efficiency, precision, and energy economy. BrainChip’s Temporal Event-based Neural Networks (TENNs) build on State-Space Models (SSMs) with time-sensitive, event-driven frameworks that are ideal for real-time streaming applications. These innovations make low-power Edge AI deployable across industries such as aerospace, autonomous vehicles, robotics, industrial IoT, consumer devices, and wearables. Explore more at www.brainchip.com. Follow BrainChip on Twitter or LinkedIn.

About Forward Edge Forward Edge is focused on developing advanced microelectronics and edge processing solutions for leading edge commercial applications and next-generation defense capabilities. Explore more at www.forwardedgeasic.com.

Contacts​

BrainChip Media Contact:
Madeline Coe
prforbrainchip@bospar.com
224-433-9056
BrainChip Investor Contact:
ir@brainchip.com

 

[Diogenese]

This article provides some food for thought.!

IBM Closes $11 Billion Deal for Confluent
Deal will help companies access their data for AI agents, says IBM CEO Arvind Krishna, as he brushes off AI’s risk to IBM’s business.

To make AI agents work, “you need to be able to get data wherever it is” and get it instantly, IBM Chief Arvind Krishna said. Jorge Gil/Zuma Press

International Business Machines said Tuesday it closed its roughly $11 billion acquisition of the data-streaming company Confluent.

The deal, first announced in December, is intended to help businesses access their data for AI agents, or bots that can take action on their own.

At the moment, corporate data is spread across multiple information-technology systems, from software applications to private data centers and cloud platforms. To make AI agents work, “you need to be able to get data wherever it is” and get it instantly, IBM Chief Executive Arvind Krishna told The Wall Street Journal.

That’s why Confluent “has been something that we have been keeping an eye on for a long time,” Krishna continued.

Armonk, N.Y.-based IBM’s acquisition comes as technology vendors are increasingly selling tools to help businesses use, manage and create AI agents. The bots are sweeping through American corporations even as business tech leaders are struggling to oversee and safely scale those agents.

For IBM, Confluent’s technology will become the “backbone” of its own platform for helping business clients access their data for various AI uses, Krishna said. That’s the same tack IBM took with its $33 billion acquisition of Red Hat, which became IBM’s default technology to help customers update their software applications, he said.

The acquisition is also central to Krishna’s vision of positioning IBM as a leading player in hybrid cloud-computing and AI. It is IBM’s second-largest deal in history, and aims to give businesses a way to make use of their old-school IT systems and data in the AI era.
The Challenges AI Poses for IBM

IBM itself has been sorting through the impact of AI agents on its workforce. About three years ago, IBM began adding AI and AI agents to its internal operations which has since added roughly $4.5 billion in productivity to its bottom line, Krishna said. Over $3 billion of that total has been reinvested in research and development and other areas, he said.

At the moment, AI agents are best suited to “low-risk” areas like software development, customer support, enterprise operations, HR and payroll, Krishna said. Over time, they could be used to directly market a product to a customer.

“There is a whole set of mundane AI use cases that we can keep ourselves busy for the next two, three years just getting those done,” he said.

Looking ahead, rote white-collar work will be “displaced” by work requiring greater human interaction and more decision-making, according to Krishna.

Last year, the company said that bots had begun to do the work of a couple of hundred of its human-resources workers.

Krishna said he expects IBM will maintain or grow its head count in the next five years—mostly in areas like consulting, sales and coding. But, roughly 20% of the company’s enterprise operations and customer-support roles “could see a change” over the next two years, he added.

In February, IBM stock posted its worst decline in 25 years—tumbling sharply on news that Anthropic had released AI tools that could help with modernizing Cobol, a programming language mainly run on IBM mainframe computers..

Krishna said IBM has its own tools to help modernize Cobol applications, and noted that its stock has since rebounded: “I think people also realized that was way exaggerated in terms of its impact,” he said.

More largely, Krishna said he believes IBM is insulated from the perceived risk of AI and AI agents to software businesses. “A lot of what we do is enabling middleware, enabling software. We are not that much in application software, and so I think [volatility] is actually a tailwind for us,” he said.

Hi WH,

There is great potential for some sort of sublicence arrangement here.

$11B for what is, compared to Akida, a one trick pony software application. It seems that it is useful in sorting RAG models:

https://www.confluent.io/compare/apache-kafka-vs-confluent/

https://www.geeksforgeeks.org/apache-kafka/apache-kafka/

Apache Kafka is a publish-subscribe messaging system. A messaging system lets you send messages between processes, applications, and servers. Broadly Speaking, Apache Kafka is software where topics (a topic might be a category) can be defined and further processed. Applications may connect to this system and transfer a message onto the topic. A message can include any kind of information from any event on your blog or can be a very simple text message that would trigger any other event.


https://ai-academy.training/2025/07/13/live-retrieval-augmented-generation-rag-with-kafka/


Confluence and Kafka are birds of a feather:

https://www.confluent.io/resources/online-talk/cloud-demo/


Online Talk

Confluent Cloud Demo: Easily Stream Data With Apache Kafka®​

Live Retrieval-Augmented Generation (RAG) with Kafka​

The buzz around Generative AI (GenAI) is undeniable. From crafting compelling marketing copy to generating intricate code, Large Language Models (LLMs) are rapidly transforming workflows. However, beneath the surface of impressive text generation lies a critical challenge: reliability and factual accuracy. Standalone LLMs, trained on vast but static datasets, can hallucinate or provide outdated information, limiting their utility in enterprise environments where truth and timeliness are paramount.

Enter Retrieval-Augmented Generation (RAG).

This powerful paradigm enhances LLMs by equipping them with the ability to access and incorporate external, up-to-date information into their responses. Think of it as giving the LLM a real-time open-book test, ensuring its answers are grounded in verifiable data. But how do we make this “open book” truly dynamic, reflecting the ever-changing landscape of enterprise knowledge? The answer lies in the real-time streaming capabilities of Apache Kafka.


Kafka/Confluence could be used to advantage with Akid. BRN's Provenance is also suited to dehallucinating medium sized models.


So, if Confluence is worth $11B, ... ?

Given Kevin's exploits, as well as the synergies between Confluence/Kafka and Akida for RAG, this could be a live question.

Does Sean have Arvind Krishna's phone number?

 

[itsol4605]

16.03.2026

ForwardEdge ASIC Selects BrainChip’s Neuromorphic Computing for Future ASICs

Together, the companies are combining best-in-class AI technology with deep ASIC and system integration expertise to deliver differentiated edge-processing...

semiiphub.com

 

[Pom down under]

https://www.businesswire.com/news/home/20260318799971/en/ForwardEdge-ASIC-Selects-BrainChips-Neuromorphic-Computing-for-Future-ASICs

Mar 18, 2026 9:00 AM Eastern Daylight Time

ForwardEdge ASIC Selects BrainChip’s Neuromorphic Computing for Future ASICs​

Share

---

First Step in a Strategic Collaboration for Cognitive Sensing Solutions in RF and Signal Processing

LAGUNA HILLS, Calif.--(BUSINESS WIRE)--BrainChip Holdings Ltd. (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), a leading developer of ultra-low-power, fully digital, event-based neuromorphic AI, today announced a strategic collaboration with ForwardEdge ASIC, a wholly owned subsidiary of Lockheed Martin (NYSE: LMT) specializing in advanced ASIC architecture and microelectronics development.



Together, the companies are combining best-in-class AI technology with deep ASIC and system integration expertise to deliver differentiated edge-processing solutions for demanding aerospace, defense, and advanced technology markets.

A Strategic Collaboration for Intelligent Edge Systems
This collaboration brings together BrainChip’s leadership in neuromorphic AI architecture and ForwardEdge ASIC’s strengths in custom silicon development, heterogeneous integration, and advanced RF systems. The collaboration is focused on tightly coupling AI acceleration with signal processing and RF compute to enable high-performance, low-latency intelligence at the edge.
By embedding BrainChip’s neuromorphic AI engines directly into ForwardEdge ASIC’s architectures, the companies are enabling cognitive processing closer to the sensor—reducing data movement, lowering power consumption, and enabling autonomous operation in complex operational environments.

“ForwardEdge ASIC is focused on architecting and delivering highly integrated silicon solutions that leverage the most advanced technologies available,” said Bill Jenkins, CRO at ForwardEdge ASIC. “BrainChip’s Akida architecture is a strong complement to our ASIC and RF platforms, allowing us to integrate dedicated AI acceleration directly into the silicon. This collaboration enables us to deliver scalable, high-performance low-latency edge solutions that push intelligence closer to the point of sensing.”

Enabling a New Class of Cognitive Sensing Solutions
The joint solution leverages a heterogeneous architecture that combines custom ASIC processing, RF signal chains, and neuromorphic AI acceleration to deliver efficient, real-time detection and classification. Key capabilities include:

• Cognitive RF and Signal Processing: Real-time classification of complex signals with adaptive, AI-driven processing.
• Scalable ASIC Platforms: Architectures designed for reuse across multiple programs and deployment environments.
• Efficient Edge Intelligence: Ultra-low-power AI processing optimized for latency-sensitive and resource-constrained systems.

This collaboration allows both companies to accelerate innovation while reducing integration risk for customers seeking production-ready edge AI solutions.
“ForwardEdge ASIC brings deep system-level design and integration expertise that is essential for deploying neuromorphic AI in real-world applications,” said Steven Brightfield, CMO at BrainChip. “This collaboration demonstrates how BrainChip’s AI technology can be tightly integrated into advanced ASIC and RF platforms to deliver powerful, efficient intelligence at the edge.”

About BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY) BrainChip is the worldwide leader in Edge AI on-chip processing and learning. The company’s first-to-market, fully digital, event-based AI processor, Akida™, uses neuromorphic principles to mimic the human brain, analyzing only essential sensor inputs at the point of acquisition and processing data with unmatched efficiency, precision, and energy economy. BrainChip’s Temporal Event-based Neural Networks (TENNs) build on State-Space Models (SSMs) with time-sensitive, event-driven frameworks that are ideal for real-time streaming applications. These innovations make low-power Edge AI deployable across industries such as aerospace, autonomous vehicles, robotics, industrial IoT, consumer devices, and wearables. Explore more at www.brainchip.com. Follow BrainChip on Twitter or LinkedIn.

About Forward Edge Forward Edge is focused on developing advanced microelectronics and edge processing solutions for leading edge commercial applications and next-generation defense capabilities. Explore more at www.forwardedgeasic.com.

Contacts​

BrainChip Media Contact:
Madeline Coe
prforbrainchip@bospar.com
224-433-9056
BrainChip Investor Contact:
ir@brainchip.com

Should close red today then

 

[Frangipani]

The “You can read the paper here” link will take you to the following LinkedIn post @White Horse shared earlier:

Sign Up | LinkedIn

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View attachment 96258


However, the above screenshot does not show the actual 18 page technical paper Kevin D. Johnson posted, so here are some excerpts for the tech nerds among you:


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Page 18: “implementation lineage spans nearly four decades. The demonstrations presented here extend the reference architecture with empirical evidence that its vision is achievable today.”

Sign Up | LinkedIn

500 million+ members | Manage your professional identity. Build and engage with your professional network. Access knowledge, insights and opportunities.

www.linkedin.com