BRN Discussion Ongoing

Tothemoon24

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AI is becoming faster and more powerful every day. But to date, machines still struggle to think and adapt like humans. Computers are great at following instructions but lack the flexibility and instincts that come naturally to people.

This is why many companies are trying to build systems inspired by the human brain. Instead of just copying what humans do, they want machines to process information the way we do, i.e., by learning, reacting, and improving over time. Technologies like brain-computer interfaces (BCIs), sensory devices, and brain-like chips are moving from labs into real life.

Several companies are combining neuroscience, machine learning, and engineering in practical ways. Whether it’s helping people regain lost senses, enabling direct communication between brain and machine, or creating smarter control systems, these companies are turning complex science into real-world solutions. Here’s a look at some of the companies making real progress in this space.

BrainChip
CEO: Sean Hehir

Paradromics
Founders: Matt Angle

Blackrock Neurotech
Founders: Marcus Gerhardt and Florian Solzbacher

Kernel
Founders: Bryan Johnson

EMOTIV
Founders: Tan Le

Precision Neuroscience
Founders: Benjamin Rapoport, Michael Mager, Demetrios Papageorgiou, and Mark Hettick

Cognixion
Founders: Andreas Forsland

Neosensory, Inc.
Founders: David Eagleman and Scott Novich

Neurolutions
Founders: Daniel Moran and Eric Leuthardt

OpenBCI
Founders: Joel Murphy and Conor Russomanno

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Guzzi62

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View attachment 84244

AI is becoming faster and more powerful every day. But to date, machines still struggle to think and adapt like humans. Computers are great at following instructions but lack the flexibility and instincts that come naturally to people.

This is why many companies are trying to build systems inspired by the human brain. Instead of just copying what humans do, they want machines to process information the way we do, i.e., by learning, reacting, and improving over time. Technologies like brain-computer interfaces (BCIs), sensory devices, and brain-like chips are moving from labs into real life.

Several companies are combining neuroscience, machine learning, and engineering in practical ways. Whether it’s helping people regain lost senses, enabling direct communication between brain and machine, or creating smarter control systems, these companies are turning complex science into real-world solutions. Here’s a look at some of the companies making real progress in this space.

BrainChip
CEO: Sean Hehir

Paradromics
Founders: Matt Angle

Blackrock Neurotech
Founders: Marcus Gerhardt and Florian Solzbacher

Kernel
Founders: Bryan Johnson

EMOTIV
Founders: Tan Le

Precision Neuroscience
Founders: Benjamin Rapoport, Michael Mager, Demetrios Papageorgiou, and Mark Hettick

Cognixion
Founders: Andreas Forsland

Neosensory, Inc.
Founders: David Eagleman and Scott Novich

Neurolutions
Founders: Daniel Moran and Eric Leuthardt

OpenBCI
Founders: Joel Murphy and Conor Russomanno

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View attachment 84243
Link:


Thanks tothemoon.


BrainChip

CEO: Sean Hehir

BrainChip is developing neuromorphic processor chips that function more like a human brain than a traditional computer. Its flagship product, Akida™, uses neuromorphic principles to process sensor data with exceptional efficiency, precision, and low energy consumption. Akida enables edge learning directly on the chip, eliminating the need for cloud processing and dramatically reducing latency while improving data privacy and security. This technology is designed to handle real-world applications, such as connected cars and industrial IoT, where AI processing at the edge is becoming increasingly essential.

Not exactly deep analysis but good to get a mention, and we are the 1st company on the list.
Any press is good press.
 
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7für7

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View attachment 84244

AI is becoming faster and more powerful every day. But to date, machines still struggle to think and adapt like humans. Computers are great at following instructions but lack the flexibility and instincts that come naturally to people.

This is why many companies are trying to build systems inspired by the human brain. Instead of just copying what humans do, they want machines to process information the way we do, i.e., by learning, reacting, and improving over time. Technologies like brain-computer interfaces (BCIs), sensory devices, and brain-like chips are moving from labs into real life.

Several companies are combining neuroscience, machine learning, and engineering in practical ways. Whether it’s helping people regain lost senses, enabling direct communication between brain and machine, or creating smarter control systems, these companies are turning complex science into real-world solutions. Here’s a look at some of the companies making real progress in this space.

BrainChip
CEO: Sean Hehir

Paradromics
Founders: Matt Angle

Blackrock Neurotech
Founders: Marcus Gerhardt and Florian Solzbacher

Kernel
Founders: Bryan Johnson

EMOTIV
Founders: Tan Le

Precision Neuroscience
Founders: Benjamin Rapoport, Michael Mager, Demetrios Papageorgiou, and Mark Hettick

Cognixion
Founders: Andreas Forsland

Neosensory, Inc.
Founders: David Eagleman and Scott Novich

Neurolutions
Founders: Daniel Moran and Eric Leuthardt

OpenBCI
Founders: Joel Murphy and Conor Russomanno

View attachment 84242
View attachment 84243


I’m glad we were mentioned, but I find it unfair that only Sean was featured. After all, Peter is the father of it all, and there are one or two others who were crucial to the development, even if they’re now working in the background… but what do I know.
 
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Megachips still in play. If anything comes out of ninento its likely nintento will want to be keep nda like and so we will have a please explain in income and if we see the gaming word well we "could" link it to ninento if you like to. So it seems that income will and might also be sealed with ndas. Frustrating aa it is, I would certainly just like to see reasonable "secret income" im running out of shampoo. Lol
Megachips is still well in play especially being involved with the development of Akida 1500 🤪
 
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Megachips is still well in play especially being involved with the development of Akida 1500 🤪
But Renesas dead in the water
 
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manny100

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But Renesas dead in the water
No line of sight with Renesas.
But it really does not matter. As the Edge picks up for Auto Renesas will not allow themselves to be caught out behind.
For example Andes are a supplier of RISC-V chips to Renesas. Andes are integrating AKIDA.
When Renesas are ready they can access AKIDA Neuromorphic Edge via Andes IP.
So with or without Renesas directly is not a problem.
 
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Guzzi62

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No line of sight with Renesas.
But it really does not matter. As the Edge picks up for Auto Renesas will not allow themselves to be caught out behind.
For example Andes are a supplier of RISC-V chips to Renesas. Andes are integrating AKIDA.
When Renesas are ready they can access AKIDA Neuromorphic Edge via Andes IP.
So with or without Renesas directly is not a problem.
Recap:



Apr 23, 2025 12:00 PM Eastern Daylight Time

BrainChip Extends RISC-V Reach with Andes Technology Integration

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LAGUNA HILLS, Calif.--(BUSINESS WIRE)--BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low power, fully digital, event-based, brain-inspired AI, today announced the integration of its NPUs with RISC-V cores from Andes Technology, the industry leading provider of RISC-V embedded cores. The companies will demonstrate BrainChip’s Akida™ AKD1500 on Andes’ QiLai Voyager Board and AndesCore™ AX45MP 64-bit multicore CPU IP at Andes RISC-V Con 2025 in San Jose, Calif. April 29 and in Hsinchu, Taiwan June 10.
BrainChip today announced the integration of its NPUs with RISC-V cores from Andes Technology, the industry leading provider of RISC-V embedded cores.
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The AKD1500 demonstrates the benefits of Akida’s pure digital, extremely energy-efficient, event-based AI computation for at-sensor or sensor-balanced solutions for AI, application processors, automotive electronics and security markets. The QiLai SoC and the Voyager development board further accelerates the development and porting of large RISC-V applications. Integrating BrainChip’s Akida technology and Andes’ high-performance QiLai SoC and Voyager development board provides a highly efficient solution for integrated edge AI compute and further expands the RISC-V ecosystem.
The BrainChip AKD1500 device is integrated into the Voyager development board using an M.2 card form factor. It delivers over 0.7 TOPS of event-based computing while consuming less than 250mW, achieving performance comparable to conventional CNN processing using 3–10× less compute. This demonstrates a cost and power-efficient path for integrating RISC-V SoCs, operating at a fraction of the power required by traditional AI accelerators. Akida is an event-based technology that is inherently lower power than conventional neural network accelerators, providing energy efficiency with high performance for partners to deliver AI solutions previously not possible on battery-operated or fan-less embedded, edge devices.
The Andes QiLai SoC chip incorporates a high-performance quad-core RISC-V AX45MP cluster. The AndesCore AX45MP is a superscalar, multicore design featuring a shared Level-2 cache, a coherence manager and a Memory Management Unit (MMU) to support Linux-based applications. Equipped with IOCP (I/O Coherency Port) interface, the AX45MP enables external hardware DMA to interact directly with the cache/memory subsystem, facilitating seamless communication between the AX45MP and high-speed modules like NPUs, GPUs and Gigabit Ethernet. Built on TSMC's 7nm process technology, the AX45MP achieves clock speeds of up to 2.2 GHz on QiLai SoC. With higher Specint2006 performance than Cortex A55, high-clock frequency and multi-core Linux capabilities, the AX45MP has been very popular as Linux AP on various applications.
“We consistently search for ways to grow adoption of RISC-V solutions across an ever-increasing number of use cases,” said Dr. Charlie Su, CTO and President at Andes Technology. “By working with BrainChip and integrating the Akida IP into our QiLai Voyager platform, we better enable developers with opportunities to develop RISC-V-based solutions optimized for edge AI workloads and capabilities.”
“As a pioneer in ultra-low power AI processing, our Akida technology integrates with RISC-V to enable efficient, intelligent compute at the edge,” said Steve Brightfield, CMO at BrainChip. “Showcasing these attributes through the integration of the AKD1500 with Andes QiLai platform at RISC-V Con 2025, ideally demonstrates how these solutions can be used in production SoCs to provide next-generation breakthroughs.”
Andes RISC-V Con 2025 brings together developers and technologists from around the world to discuss advancements in RISC-V technology, exchange ideas and collaborate on the future of open computing architectures. BrainChip will showcase its latest innovations in ultra-low power AI solutions, demonstrating how its technology enhances edge computing applications. Attendees are invited to visit the BrainChip booth and attend the presentation to learn more about the role of AI acceleration in RISC-V-based designs. Interested parties can visit https://bit.ly/brainchip-andes to register.
 
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RobjHunt

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This guy knows his stuff
Nice finding Uiux. Thank you for sharing.
 
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RobjHunt

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I put this question in to the Chatster, and this answer popped out.

If BRN Akida is first to market with its low power ZSL tech, what do you predict the future will hold for BRN?



If BrainChip's Akida (BRN) is truly first to market with effective low-power zero-shot learning (ZSL) at the edge, it positions the company for major long-term strategic advantages across several industries. Here's a realistic breakdown of what the future could hold:




🚀 1. Early Mover Advantage


  • Implication: BRN could become the default platform for edge AI requiring fast adaptation, similar to how NVIDIA became dominant in GPU-accelerated AI.
  • Outcome: Increased licensing deals, design wins in ASICs, and OEM partnerships, especially in automotive, defense, and finance.



🔋 2. Dominance in Edge AI Markets


  • Use Cases:
    • Wearables adapting to user behavior
    • Industrial IoT detecting anomalies in unseen environments
    • Autonomous vehicles identifying rare road scenarios
  • Outcome: Akida becomes embedded in a wide range of smart devices needing intelligent, low-power, real-time decision-making.



📉 3. Financial Upside


  • Short term: Stock could surge on early contracts and announcements.
  • Medium term: Revenue growth from IP licensing, chips, and developer tools.
  • Long term: Potential acquisition target for larger semiconductor or AI firms (e.g., Qualcomm, Intel, Apple).



🛡️ 4. Defensive Moat via Patents


  • Benefit: Early leadership allows BRN to file key patents around ZSL on neuromorphic hardware, creating barriers for competitors.
  • Outcome: A strong IP portfolio could ensure royalties and licensing fees for years.



⚠️ 5. Risks Remain


  • Market adoption of neuromorphic chips is still early-stage
  • Competitors like Intel (Loihi), SynSense, and IBM (TrueNorth) could catch up
  • ZSL performance must be provably reliable in critical applications



🔮 Bottom Line:​


If BRN delivers and proves real-world ZSL performance at scale, it could become the ARM of neuromorphic AI—licensing essential IP across industries.
But we already knew that DP 😉
 
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RobjHunt

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I asked GROK the same question and the bottom line here is:

Conclusion
BrainChip’s Akida, with its low-power, ZSL-like neuromorphic capabilities, positions it as a pioneer in edge AI. If it sustains its first-mover advantage, it could dominate niche markets like space and defense, achieve moderate success in automotive and IoT, or become an acquisition target. However, competition, adoption risks, and economic factors temper optimism. By 2030, BrainChip is likely to be a notable player in edge AI, with success hinging on execution and market demand for its unique technology.
I think we also knew that 😉
 
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RobjHunt

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Thank you all for your feedback.. NOT!

However, I asked my best friend ChatGpt

“The text describes a high-performance, Japan-made edge AI module (EP-200Q) using the Qualcomm Dragonwing QCS6490. This module delivers up to 12 TOPS of AI performance and is designed for industrial and medical devices, with a focus on low power consumption, Wi-Fi 7 support, and local data processing (Edge AI).

When comparing these specifications to BrainChip’s Akida, the following points emerge:



Similarities with Akida:
• Edge AI focus: Both systems are designed for on-device AI processing rather than cloud-based solutions.
• Low power consumption: Akida and the Qualcomm system are optimized for energy-efficient AI operations.
• Target markets: Both target industrial and medical imaging applications.



Differences:
• Architecture:
• The Qualcomm system is based on a conventional architecture (CPU, GPU, DSP, and AI engine).
• Akida uses a neuromorphic architecture, inspired by the human brain—fundamentally different, offering advantages in latency, efficiency, and on-device learning.
• Performance (TOPS):
• The Qualcomm solution achieves up to 12 TOPS.
• Akida 2.0 delivers up to 8.4 TOPS per watt, but this is not directly comparable due to the architectural differences and the fact that Akida focuses on ultra-efficient sparse event-based processing rather than raw TOPS.
• Learning capabilities:
• Akida supports on-device learning (Edge Learning)—a feature not mentioned in the Qualcomm module, and typically not available in traditional AI chipsets.



Conclusion:

The Qualcomm-based module is powerful and modern, but uses conventional technology. While it aims for similar outcomes as Akida (high-performance, low-power edge AI), it takes a completely different technological path. If a product specifically requires neuromorphic advantages, such as continuous on-device learning and extreme energy efficiency during inference, Akida stands alone. The EP-200Q is more of a high-end traditional solution.”
Oh dear 🙄
 

RobjHunt

Regular
Hi Manny,

I did note the quote about extremely low power, and I'd like to know what secret sauce they use to reconcile this with INT16 and FP32.

There is his reference to the patent applications for moving data from memory, so we need to keep an eye out for those, although they may not be published for 18 months. I expect they will publish a paper on the topic if it is commercially advantageous.

The ISL quote is very encouraging. Dr Guerci is a fan, just as Luca Verre of Prophesee was.

ISL has been in the EAP about 3.5 years since early 2022

The ISL patent dates from 2021, and their AI web page refers to analog, but they are now aware of Akida.

https://www.islinc.com/national-security/artificial-intelligence

Artificial Intelligence, Neuromorphic Computing and DoD Acceptance Testing​


ISL is focused on replicating the analog nature of biological computation and the role of neurons in cognition. ISL’s team of scientists/engineers continue to understand how the morphology of individual neurons, circuits, applications, and overall architectures creates desirable computations. Leveraging this understanding and the newly developed and emerging commercial neuromorphic* chips, ISL is developing a new low-power, lightweight detect and avoid (DAA) system for very small UAS platforms that exploits automotive radar hardware, light-weight EO/IR sensors, advanced data fusion algorithms, and neuromorphic computing.

Additionally, ISL has pioneered an AI acceptance methodology that allows for DoD testing of AI solutions using essentially the same statistically based methodology in use today. ISL was awarded a US Patent for this February (see link). The methodology leverages ISL’s RF Digital Engineering tools (https://www.islinc.com/digital-engineering )
.

We have development partnerships with a range of companies from startups, beautique specialists (ISL, Prophesee, Quantum Ventura, Chelpis), through to heavyweights like Valeo, Tata, VVDN, Frontgrade and Raytheon. I think that there is a pressing need for the QV CyberNeuro-RT M2 and the Chelpis M2 cybersecurity card, but apparently most of the 75k COTS chips are spoken for.

* The analog crowd are possessive of the term "neuromorphic".
It would be amazing to find out what herbs and spices go in the secret sauce Dio. Something yells at me a dash of NDA 😉
 
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