BRN Discussion Ongoing

[FuzM]

I wouldn’t be surprised if it turned out we’re also somehow connected to South Korean ASIC design house ASICLAND, whose engineers work closely with global partners, including TSMC and Arm.

The fact that both their CMO & Head of Overseas Sales and the company’s Global Strategy Manager “celebrated” this week’s LinkedIn post about our redesigned website with a clapping-hands emoji each is a little too much of a coincidence, don’t you think?

“ASICLAND is a leading design house specializing in application-specific integrated circuit (ASIC) design, offering high-performance, low-power, and cost-optimized design services. As an official Value Chain Alliance (VCA) partner of TSMC—the world’s No.1 foundry—ASICLAND serves as a trusted bridge between customers and TSMC. We deliver full turnkey support, from architecture design to GDS delivery, across a wide range of industries including AI, automotive, IoT, and memory.”


View attachment 86920


View attachment 86922

View attachment 86935

LinkedIn Login, Sign in | LinkedIn

Login to LinkedIn to keep in touch with people you know, share ideas, and build your career.

www.linkedin.com

View attachment 86930

ASICLAND Co., Ltd

ASICLAND is Korea's only TSMC VCA Partner and an ARM ADP, representing a leading global ASIC design solution company.

eng.asicland.com

View attachment 86926 View attachment 86927 View attachment 86928 View attachment 86929


In this context, I was wondering whether the undisclosed “Leading U.S. IDM Company” in yesterday’s press release could by any chance be our licensee Renesas Electronics America, a wholly owned subsidiary of Tokyo-headquartered Renesas Electronics Corporation, which in turn happens to be a global semiconductor player? Just a wild guess, though…

“▶ Strengthening automotive semiconductor design capabilities through collaboration with a global semiconductor client

(…) [2025-06-11] ASICLAND has signed a supply agreement with a leading U.S. integrated device manufacturer (IDM) to jointly target the global automotive semiconductor market.

(…) The U.S. semiconductor company involved is an IDM providing essential chip designs and power management solutions for automotive electronics systems, with active operations across various industrial sectors. Through this collaboration, ASICLAND will expand its technological foundation and expertise in automotive chip design.

(…) Meanwhile, ASICLAND is accelerating efforts to enter global markets by establishing an advanced R&D center in Hsinchu, Taiwan*. The company is actively securing cutting-edge design technologies for 3nm and 5nm process nodes as well as CoWos (Chip-on-Wafer-on-Substrate) packaging technologies.”


*Hsinchu Science Park is Taiwan’s Silicon Valley and home to about 500 high-tech companies, among them TSMC, UMC and MediaTek, as well as our partner Andes Technology.

ASICLAND partners with U.S. IDM for auto semiconductors | ASICLAND posted on the topic | LinkedIn

ASICLAND Hits the Gas in the Global Automotive Semiconductor Market⚙️ ⠀ ASICLAND has signed a semiconductor design supply agreement with a leading U.S. integrated device manufacturer (IDM), accelerating its entry into the global automotive market. ⠀ As the automotive semiconductor sector...

www.linkedin.com

View attachment 86936

NEWS

NEWS

eng.asicland.com

View attachment 86932

Not a surprise after all

 

[jtardif999]

FF

Let’s compare production time lines:

AKD1000
2018 Design work completed and IP tested by select customers leading to decision to completely redesign AKD1000
2019 July redesigned AKD1000 IP released to select customers for feedback
2020 March Feedback received AKD1000 produced in FPGA and tested
2020 April final design sent to Socionext for engineering.
2020 September AKD1000 engineering sample back from TSMC & testing takes place
2020 October AKD1000 engineering samples released to early access customers
2020 December AKD1000 engineering samples released to NASA
2021 March Brainchip announces taking customer feedback into account design changes made to AKD1000 and ready to send to tapeout of reference AKD1000 by TSMC
2021 November AKD1000 reference chips have been received and tested proving redesign shows a 30 percent increase in efficiency over AKD1000 engineering samples.
2023 January After extensive customer engagement Brainchip design a further iteration of the AKD 1000 series named AK1500

AKIDA 2000
2022 Brainchip announce acceleration of the development of AKIDA2.0 IP
2023 March AKIDA2.0 IP announced and released to select customers before general availability to obtain customer feedback.
2023 October AKIDA2.0 IP availability extended
2024 Brainchip prioritises development of models and TENNS software to support AKIDA 2.0
2024 - 2025 Brainchip works on and completes engineering design for demonstrating AKIDA 2.0 on FPGA
2025 Brainchip demonstrates AKIDA 2.0 on FPGA and makes it available for testing by select customers.
2025 August Brainchip announces the AKIDA2.0 FPGA Cloud Access to customers/developers.
2026 February Brainchip announces the refined AKD2.0 named AKIDA2500 to be produced in silicon and taped out on 12nm at TSMC as an engineering sample prior to any sort of volume production.

There is appears to be a certain amount of similarity in the time lines for developing revolutionary neuromorphic technology regardless of who is on the Board, who is the Chair, and who is the CEO of Brainchip.

Note I have excluded references to AKIDA PICO from the timeline for AKIDA2.0 as well as the various platforms such as the Edge Box and M.2 Cards for AKD1000

Bit confusing nomenclature ;

Akida1.0 is the underlying architecture associated with the AKD1000 and AKD1500 chips.

Akida2.0 is the underlying architecture for the AKD2500 chip when it has been fabricated.

AFAIK Akida Pico is a further modification of underlying Akida2.0 architecture allowing one neural processing unit to be the singular unit of processing in the neural fabric (the entire neural fabric) - not limited to one though I think.

Modifications have been made to each of the Akida architectures in line with customer requests as have modifications made directly to the chips themselves.

I hope this makes a bit more sense. I think all of this would be quite confusing to anyone without an engineering background.

 

[Diogenese]

Hi @manny100

Don’t want to be a negative Nelly on the topic but Megachips are also partnered with Quadric and have been pumping their tyres up publicly:

Quadric​

“Chimera General Purpose Neural Processing Unit” (GPNPU), which Quadric independently developed, can provide high performance computing regardless of sensor types. Conventional AI engines usually only run at high speed in neural networks while off-loading pre-processing and boundary processing onto a host system. However, with Quadric’s technology, it is possible to run at high speed with pre-processing, boundary processing, and neural network inference on a single hardware unit.
This unique ability that can support all kinds of data processing will allow for the accommodation of new types of neural networks released in the future without any hardware changes, regardless of the applications.

• 
  Quardric

Features​

• Scalability for both low power consumption and accuracy
• Accelerate entire steps of AI pipeline processing
• Flexible architecture to support the evolution of AI models
• IPs for silicon implementation
• Software development kits available

Proud to represent MegaChips on Quadric's board. Quadric is making great progress! | Douglas Fairbairn

Proud to represent MegaChips on Quadric's board. Quadric is making great progress!

www.linkedin.com

Quadric is really on a role! They have breakout AI IP which consistently beats the competition. Whether in cars, PCs, printers, or ? it's a clear winner | Douglas Fairbairn

Quadric is really on a role! They have breakout AI IP which consistently beats the competition. Whether in cars, PCs, printers, or ? it's a clear winner

www.linkedin.com

Douglas Fairburn who once did a podcast with Brainchip says:

View attachment 95056


I think we need to be realistic that Megachips are possibly using Quadric vs BC.

Love to be wrong of course but I haven’t seen any evidence of that.

Hi SG,

I'd forgotten about the Megachips/Quadric partnership:


Quadric and MegaChips Form Partnership to Bring IP Products to ASIC and SoC Market - Embedded Computing Design

Quadric and MegaChips announced a strategic partnership to deliver ASIC and SoC solutions built on Quadric’s edge AI processor architecture.

MegaChips announced an equity stake in Quadric in January 2022 and is also a major investor in a $21M Series B funding round announced in March through their MegaChips LSI USA Corporation subsidiary. The round aims to help Quadric release the next version of its processor architecture, improve the performance and breadth of the Quadric software development kit (SDK), and roll out IP products to be integrated in MegaChips’ ASICs and SoCs.

I looked at their patents at the time, and, if I recall correctly, was not overly impressed. However they have a new patent which refers to their old patents as Prior Art. (This does not necessarily mean they are obsolete, as it could refer to an improvement):

US20260023715A1 SYSTEMS AND METHODS FOR IMPLEMENTING DIRECTIONAL OPERAND BROADCAST AND MULTIPLY-ACCUMULATE EXECUTION USING A CONFIGURABLE PATCH MESH IN A MULTI-CORE PROCESSING ARRAY OF AN INTEGRATED CIRCUIT 20240719 - Published 20260122

[0099] Each array processing core includes a local register memory 310 that may be logically divided into a broadcast region 309 , a source region 318 , and a destination region 320 . The broadcast region 309 may be configured to hold operand values intended to be fed into a patch operation. In one or more embodiments, the source region 318 preferably stores local data operands to be used in multiply-accumulate computations, while the destination region 320 receives accumulation results.

[0100] A feed path interconnect enables operand values from one or more array processing cores to be routed to the origin core 303 . Once the operand value may be received by the origin core 303 , the operand value may be staged in a broadcast staging register or similar holding buffer. The origin core 303 then initiates a unidirectional wavefront broadcast of the operand value using a patch mesh interconnect fabric 312 .

[0101] In one or more embodiments, the patch mesh interconnect 312 may be configured to propagate operand values from the origin core 303 to other processing cores within the patch region using a wavefront propagation scheme. In one embodiment, the wavefront progresses outward from the origin core 303 in a Manhattan-distance order, such that each processing core within the patch region receives the broadcast value with a fixed delay relative to the number of inter-core hops from the origin core. The broadcast timing model enables deterministic compute scheduling across the patch.

Basically, a pulse originating at 303 (top left) propagates through the matrix with a delay determined by the number pf cores between 303 and the destination core, creating a propagating "wave front".

This sounds to me like it is intended to mimic the propagation of signals through the brain. The reason for the developement is set out here"

[0006] Accordingly, there remains a need in the integrated circuitry field for operand distribution techniques that permit localized, directionally controlled broadcasting of operands to selected subsets of processing elements. There also remains a need for compute scheduling frameworks that enable deterministic multiply-accumulate operations across such subsets while minimizing interconnect congestion and improving temporal alignment of data arrival and compute triggering.


CTO Nigel Drego cut his teeth with cryptocurrency tech.

The Quadric IO webpage has been 404'd. Their last investment round was 20260115.

 

[manny100]

Hi SG,

I'd forgotten about the Megachips/Quadric partnership:


Quadric and MegaChips Form Partnership to Bring IP Products to ASIC and SoC Market - Embedded Computing Design

Quadric and MegaChips announced a strategic partnership to deliver ASIC and SoC solutions built on Quadric’s edge AI processor architecture.

MegaChips announced an equity stake in Quadric in January 2022 and is also a major investor in a $21M Series B funding round announced in March through their MegaChips LSI USA Corporation subsidiary. The round aims to help Quadric release the next version of its processor architecture, improve the performance and breadth of the Quadric software development kit (SDK), and roll out IP products to be integrated in MegaChips’ ASICs and SoCs.

I looked at their patents at the time, and, if I recall correctly, was not overly impressed. However they have a new patent which refers to their old patents as Prior Art. (This does not necessarily mean they are obsolete, as it could refer to an improvement):

US20260023715A1 SYSTEMS AND METHODS FOR IMPLEMENTING DIRECTIONAL OPERAND BROADCAST AND MULTIPLY-ACCUMULATE EXECUTION USING A CONFIGURABLE PATCH MESH IN A MULTI-CORE PROCESSING ARRAY OF AN INTEGRATED CIRCUIT 20240719 - Published 20260122

View attachment 95059

[0099] Each array processing core includes a local register memory 310 that may be logically divided into a broadcast region 309 , a source region 318 , and a destination region 320 . The broadcast region 309 may be configured to hold operand values intended to be fed into a patch operation. In one or more embodiments, the source region 318 preferably stores local data operands to be used in multiply-accumulate computations, while the destination region 320 receives accumulation results.

[0100] A feed path interconnect enables operand values from one or more array processing cores to be routed to the origin core 303 . Once the operand value may be received by the origin core 303 , the operand value may be staged in a broadcast staging register or similar holding buffer. The origin core 303 then initiates a unidirectional wavefront broadcast of the operand value using a patch mesh interconnect fabric 312 .

[0101] In one or more embodiments, the patch mesh interconnect 312 may be configured to propagate operand values from the origin core 303 to other processing cores within the patch region using a wavefront propagation scheme. In one embodiment, the wavefront progresses outward from the origin core 303 in a Manhattan-distance order, such that each processing core within the patch region receives the broadcast value with a fixed delay relative to the number of inter-core hops from the origin core. The broadcast timing model enables deterministic compute scheduling across the patch.

Basically, a pulse originating at 303 (top left) propagates through the matrix with a delay determined by the number pf cores between 303 and the destination core, creating a propagating "wave front".

This sounds to me like it is intended to mimic the propagation of signals through the brain. The reason for the developement is set out here"

[0006] Accordingly, there remains a need in the integrated circuitry field for operand distribution techniques that permit localized, directionally controlled broadcasting of operands to selected subsets of processing elements. There also remains a need for compute scheduling frameworks that enable deterministic multiply-accumulate operations across such subsets while minimizing interconnect congestion and improving temporal alignment of data arrival and compute triggering.


CTO Nigel Drego cut his teeth with cryptocurrency tech.

The Quadric IO webpage has been 404'd. Their last investment round was 20260115.

Its likely horses for courses. Some robot tasks will be suited to AKIDA1000 and other tasks to Quadric.
Its likely both will get a 'gig'.

 

[Stable Genius]

Hi SG,

I'd forgotten about the Megachips/Quadric partnership:


Quadric and MegaChips Form Partnership to Bring IP Products to ASIC and SoC Market - Embedded Computing Design

Quadric and MegaChips announced a strategic partnership to deliver ASIC and SoC solutions built on Quadric’s edge AI processor architecture.

MegaChips announced an equity stake in Quadric in January 2022 and is also a major investor in a $21M Series B funding round announced in March through their MegaChips LSI USA Corporation subsidiary. The round aims to help Quadric release the next version of its processor architecture, improve the performance and breadth of the Quadric software development kit (SDK), and roll out IP products to be integrated in MegaChips’ ASICs and SoCs.

I looked at their patents at the time, and, if I recall correctly, was not overly impressed. However they have a new patent which refers to their old patents as Prior Art. (This does not necessarily mean they are obsolete, as it could refer to an improvement):

US20260023715A1 SYSTEMS AND METHODS FOR IMPLEMENTING DIRECTIONAL OPERAND BROADCAST AND MULTIPLY-ACCUMULATE EXECUTION USING A CONFIGURABLE PATCH MESH IN A MULTI-CORE PROCESSING ARRAY OF AN INTEGRATED CIRCUIT 20240719 - Published 20260122

View attachment 95059

[0099] Each array processing core includes a local register memory 310 that may be logically divided into a broadcast region 309 , a source region 318 , and a destination region 320 . The broadcast region 309 may be configured to hold operand values intended to be fed into a patch operation. In one or more embodiments, the source region 318 preferably stores local data operands to be used in multiply-accumulate computations, while the destination region 320 receives accumulation results.

[0100] A feed path interconnect enables operand values from one or more array processing cores to be routed to the origin core 303 . Once the operand value may be received by the origin core 303 , the operand value may be staged in a broadcast staging register or similar holding buffer. The origin core 303 then initiates a unidirectional wavefront broadcast of the operand value using a patch mesh interconnect fabric 312 .

[0101] In one or more embodiments, the patch mesh interconnect 312 may be configured to propagate operand values from the origin core 303 to other processing cores within the patch region using a wavefront propagation scheme. In one embodiment, the wavefront progresses outward from the origin core 303 in a Manhattan-distance order, such that each processing core within the patch region receives the broadcast value with a fixed delay relative to the number of inter-core hops from the origin core. The broadcast timing model enables deterministic compute scheduling across the patch.

Basically, a pulse originating at 303 (top left) propagates through the matrix with a delay determined by the number pf cores between 303 and the destination core, creating a propagating "wave front".

This sounds to me like it is intended to mimic the propagation of signals through the brain. The reason for the developement is set out here"

[0006] Accordingly, there remains a need in the integrated circuitry field for operand distribution techniques that permit localized, directionally controlled broadcasting of operands to selected subsets of processing elements. There also remains a need for compute scheduling frameworks that enable deterministic multiply-accumulate operations across such subsets while minimizing interconnect congestion and improving temporal alignment of data arrival and compute triggering.


CTO Nigel Drego cut his teeth with cryptocurrency tech.

The Quadric IO webpage has been 404'd. Their last investment round was 20260115.

Probably sick of me banging on about Quadric but whether we like it or not Quadric Is a competitor and a partner of Megachips. Maybe it isn’t as good as Akida but in some cases it must be good enough.


The article attached states Quadric just raised another $30M taking it’s funding to 72M so it’s not going anywhere in a hurry.

Further discussion about the speed of the industry and how technology advancements are quicker than chips can be manufactured which may point to why Brainchip took its time and consulted widely prior to taping out:

Quadric rides the shift from cloud AI to on-device inference — and it's paying off | TechCrunch

Quadric aims to help companies and governments build programmable on-device AI chips that can run fast-changing models locally.

techcrunch.com

I’m still wrapped AKD 2500 has been taped out because it indicates industry has generally approved what BC is building or they wouldn’t spend the $2.5M to produce it.

It’s not going to be a winner takes all scenario anyway. It will eventually be a big TAM!

 

[gex]

Whats the difference between 3 years ago when people were saying where goimg to the moon,
Our company was nothing back then.
Look at us now on how far we have developed and how many varieties of avenues of potential income with the array of products availiable.
Why did people believe then but not now,
Look at the prices? Do yourself a favour

What is satire pleb

 

[Diogenese]

Probably sick of me banging on about Quadric but whether we like it or not Quadric Is a competitor and a partner of Megachips. Maybe it isn’t as good as Akida but in some cases it must be good enough.


The article attached states Quadric just raised another $30M taking it’s funding to 72M so it’s not going anywhere in a hurry.

Further discussion about the speed of the industry and how technology advancements are quicker than chips can be manufactured which may point to why Brainchip took its time and consulted widely prior to taping out:

Quadric rides the shift from cloud AI to on-device inference — and it's paying off | TechCrunch

Quadric aims to help companies and governments build programmable on-device AI chips that can run fast-changing models locally.

techcrunch.com

I’m still wrapped AKD 2500 has been taped out because it indicates industry has generally approved what BC is building or they wouldn’t spend the $2.5M to produce it.

It’s not going to be a winner takes all scenario anyway. It will eventually be a big TAM!

Yes. Akida 2 has TENNs - that's streets ahead of the competition (Applied Brain Research excepted). Akida 3 adds the latency and power benefits of solid state switching mesh v packet switching.

 

[Cardpro]

HAPPY DAYS

View attachment 95046

I remember when they first released announcement for AI Accelerator... Akida...s... I dont know how you guys continue to stay positive, although some of the recent engagements seem somewhat interesting but seeing my investment value going down day by day for years makes me sad... to me, this is another excuse to buy time and justify their pay for a few years...

 

[Frangipani]

Kevin D. Johnson, Field CTO and Principal HPC Cloud Technical Specialist at IBM, just shared his latest IBM Spectrum Symphony&AKD1000-in-harmony demo with his LinkedIn network - this time round it’s about how stock market traders can use voice emotion biometrics during earnings announcements to their advantage:

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

 

[Frangipani]

Akida Pico: The Tiny Brain Making "Always-On" AI a Reality | BrainChip

𝐅𝐨𝐫 𝐲𝐞𝐚𝐫𝐬, 𝐞𝐝𝐠𝐞 𝐀𝐈 𝐡𝐚𝐬 𝐦𝐞𝐚𝐧𝐭 𝐜𝐡𝐨𝐨𝐬𝐢𝐧𝐠 𝐛𝐞𝐭𝐰𝐞𝐞𝐧 𝐭𝐰𝐨 𝐭𝐡𝐢𝐧𝐠𝐬: 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭 𝐝𝐞𝐯𝐢𝐜𝐞𝐬 𝐨𝐫 𝐥𝐨𝐧𝐠 𝐛𝐚𝐭𝐭𝐞𝐫𝐲 𝐥𝐢𝐟𝐞. We just published a breakdown of how that's changing. 𝗢𝘂𝗿 𝗹𝗮𝘁𝗲𝘀𝘁 𝗯𝗹𝗼𝗴 𝗲𝘅𝗽𝗹𝗼𝗿𝗲𝘀: - Why most AI processors consume power even when nothing is happening - How event-based processing drops power...

www.linkedin.com

Akida Pico: The Tiny Brain Making "Always-On" AI a Reality

Akida Pico: The Tiny Brain Making "Always-On" AI a Reality In the world of Edge AI, there’s always been a tradeoff: high intelligence, always-on capability, or long battery life. If you wanted a device to listen for a voice command or monitor something 24/7, you usually had to accept that the...

brainchip.com

Akida Pico: The Tiny Brain Making “Always-On” AI a Reality​

In the world of Edge AI, there’s always been a tradeoff: high intelligence, always-on capability, or long battery life. If you wanted a device to listen for a voice command or monitor something 24/7, you usually had to accept that the battery would be drained just waiting for a command.

Enter Akida Pico.​

Built on BrainChip’s proprietary event-based processing platform, Akida Pico is an ultra-low-power co-processor (or standalone core) designed to give small devices “eyes and ears” without the power-hungry baggage of a traditional CPU tasked with the nuisance of stand-by mode.

Why “Event-Based” is a Game Changer​

Traditional AI processors are like a light that stays on all night, even when the room is empty. They’re constantly crunching numbers regardless of whether anything significant is happening.

Akida Pico uses event-based processing, which mimics the human brain. It only “fires” when it detects a relevant change in data (an “event”). If nothing is happening, it consumes almost zero power. This allows it to operate in the microwatt (uW) to milliwatt (mW) range, making it the leanest NPU core in the industry.

Unlike most chips that need a heavy-duty host CPU, this core can operate entirely standalone, pulling just microwatts to milliwatts of power. Pico stays lean by using “power islands” to make sure its standby mode doesn’t incur the leakage of the whole system.

Real-World Use Cases​

Akida Pico isn’t just a spec sheet; it’s designed for specific, high-impact “extreme edge” applications.

Wake-up Systems
In many designs, Akida Pico acts as a low-power filter. Instead of the main CPU staying awake to listen for a keyword or detect motion, Pico remains on duty. When it identifies a “qualified event,” like a specific voice command, it sends a low-power interrupt to “wake up” the main MCU: perfect for applications like smart appliances, voice assistants, and wearables.

Healthcare
Imagine a wearable that monitors heart health or detects the early onset of a seizure. Because Pico is purely digital and ultra-efficient, it can perform medical anomaly detection locally on the device without ever needing to send data to the cloud. Patients can enjoy prolonged battery life with a monitor that only alerts a doctor when a specific event is detected.

Industrial Predictive Maintenance
In a factory, thousands of motors hum 24/7. Identifying a failing part early can prevent emergency repairs or lost productivity. Akida Pico can be integrated into remote sensors to perform industrial anomaly detection, analyzing vibration patterns or thermal spikes in real-time. An industrial sensor can run for years, only “reporting in” if it hears a problem.

Developer-Friendly: No New Languages Required​

Akida Pico is easy test, train, and deploy with BrainChips Meta TF development tool. MetaTF includes a processor IP simulator for model execution, as well as support for Akida hardware like the AKD1000 reference SoC and Akida 2 FPGA platform. Inspired by the Keras API, MetaTF provides a high-level Python API for neural networks. This API facilitates early evaluation, design, final tuning, and productization of neural network models.

1. Native Support: Works directly with TensorFlow/Keras and PyTorch.
2. Low-Code/No-Code: For those who aren’t AI experts, BrainChip offers turnkey tools to deploy optimized models quickly.

​

The Bottom Line​

Akida Pico is about making the Internet of Things intelligent without the need to tether devices to a charging cable. With its ultra-low power neuromorphic technology at the edge, Pico is proving that you don’t need a massive power budget to have a massive impact.

Ready to check out Akida Pico?​

Join us for a live webinar to see Pico in action on Akida FPGA in the Cloud: execute models, assess accuracy, and benchmark performance all from your desktop with no hardware required.

Register

 

[Yoghesh]

EDGE AI FOUNDATION
25,480 followers
Contact us
2m •
As edge AI systems scale, the limitations of traditional von Neumann computing—separate memory and processing, high data movement, and power inefficiency—are becoming increasingly apparent. Neuromorphic computing offers a fundamentally different approach, inspired by the structure and operation of the human brain, enabling event-driven, ultra-low-power, real-time intelligence at the edge. In this inaugural EDGE AI Neuromorphic Livestream, we bring together industry leaders, researchers, and system builders to explore how neuromorphic AI is moving from research into real-world deployment. The session will examine architectures, sensing and control applications, training methods, and benchmarking practices across both small-scale and large-scale systems. Designed for technologists, researchers, and decision-makers, this livestream will provide practical insights into where neuromorphic AI delivers real value today—and where it is headed next. Tune in for these talks from: - Innatera - University of Southern California - Brainchip - Harvard University - Spinncloud - Delft University

As edge AI systems scale, the limitations of traditional von Neumann computing—separate memory and processing, high data movement, and power inefficiency—are becoming increasingly apparent… | EDGE AI FOUNDATION

As edge AI systems scale, the limitations of traditional von Neumann computing—separate memory and processing, high data movement, and power inefficiency—are becoming increasingly apparent. Neuromorphic computing offers a fundamentally different approach, inspired by the structure and operation...

www.linkedin.com

 

[Esq.111]

Kevin D. Johnson, Field CTO and Principal HPC Cloud Technical Specialist at IBM, just shared his latest IBM Spectrum Symphony&AKD1000-in-harmony demo with his LinkedIn network - this time round it’s about how stock market traders can use voice emotion biometrics during earnings announcements to their advantage:

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

View attachment 95066


View attachment 95067

Evening Frangipani, Chippers.

Boooooom. .

Some scratchings of mine , to put the above into context.

Regards,
Esq.

 

[stockduck]

offtopic

AI Brains Mimic Human Efficiency With New Spiking Neural Network Design

Researchers have developed NeuEdge, a new framework utilising spiking neural networks that achieves up to 312times greater energy efficiency than conventional deep learning on edge devices, such as drones, while maintaining real-time performance through adaptive models and hardware optimisation.

quantumzeitgeist.com

???

 

[stockduck]

offtopic:

FAST-EO: Enhancing Earth Observation with AI and machine learning techniques - [Article Title] | Explore KP Labs' Innovations and Insights

Discover insights from KP Labs in our news update, FAST-EO: Enhancing Earth Observation with AI and machine learning techniques, focusing on key developments and innovations in satellite systems and space exploration.

www.kplabs.space

KP Labs and Simera Sense advance AI optical payload missions

KP Labs and Simera Sense partner to deliver AI optical payloads, combining cameras and onboard data processing for smarter satellite missions.

simera-sense.com

https://www.kplabs.space/solutions/hardware/leopard
....
Quad ARM Cortex-A53 CPU 1.2 GHz
....

???

 

[SiDEvans]

https://www.linkedin.com/posts/acti...urce=social_share_send&utm_campaign=copy_link

 

[smoothsailing18]

Nice

 

[itsol4605]

offtopic

AI Brains Mimic Human Efficiency With New Spiking Neural Network Design

Researchers have developed NeuEdge, a new framework utilising spiking neural networks that achieves up to 312times greater energy efficiency than conventional deep learning on edge devices, such as drones, while maintaining real-time performance through adaptive models and hardware optimisation.

quantumzeitgeist.com

???

Well, nice!
They are using neuromorphic processors (like Intel Loihi2).

"A case study focusing on an autonomous drone workload reveals up to 312x energy savings relative to conventional deep neural networks, all while sustaining real-time operation.
Validation on both Intel Loihi 2 and IBM TrueNorth platforms confirms the real-world applicability of NeuEdge, showcasing significant energy improvements, 312x over GPU baselines and 89x over conventional neural networks on edge CPUs.
These results firmly establish neuromorphic computing as a viable solution for sustainable edge AI systems, offering a pathway towards truly energy-efficient intelligent devices."

 

[7für7]

https://www.linkedin.com/posts/acti...urce=social_share_send&utm_campaign=copy_link

Interesting comment

 

[manny100]

Interesting comment

View attachment 95076 View attachment 95077

If this proves out IBM will be able to sell this as an add on to Symphony to funds, institutions,Banks and Trading brokers etc for a mint.
A licence with a royalty as a % of sales may be go if it plays out.
Analysing voice sentiment is interesting. Another tech small step and AKIDA will pick up BS at meetings, home etc, via a tiny wearable Brain Tag.

 

[Esq.111]

Afternoon Chippers,

Be thinking Kevin D . Johnston may well be a candidate for the NOBEL PEACE PRIZE this year.

* Ability to detect a human emotion shift 2 to 3 seconds before the market explodes 15 times.

Imagine if one will...... every mobile phone has such technology embedded within .... monitoring our partners mood & giving a little alert.

World Peace is finally within our grasp.



On a side note , is anyone able to pinch the vidio off LinkedIn & post on this forum.

I don't have a LinkedIn account , hence can't view it.

Thankyou in advance.

Regards,
Esq.