BRN Discussion Ongoing

[IloveLamp]

Probably worth keeping an eye on

#agirdy #agi #ai #innovation #founders | Philipp Feindert

After 8 incredible years in the Research & Development at Mercedes-Benz, I’m closing this incredible chapter, filled with leading innovation projects, tough challenges, and lots of truly exceptional people. People who inspired, accompanied, and challenged me. Thank you Mercedes-Benz ❤️ I am...

www.linkedin.com

 

[Doz]

Apologies if already posted .

Bodacious Buzz on the Brain-Boggling Neuromorphic Brain Chip Battlefront

Hold onto your hippocampus because the latest neuromorphic marvels are firing on all synapses. To ensure we’re all tap-dancing to the same skirl of the bagpipes, let’s remind ourselves that the ter…

www.eejournal.com

 

[Galaxycar]

This is the reason why the price is dropping shorts over 100 million plus, where they are getting the shares from???NAKED bet yah and the fact there will be another capital raise in the future to support managements high burn rate of cash.

 

[Diogenese]

Apologies if already posted .


View attachment 92767
View attachment 92769

Bodacious Buzz on the Brain-Boggling Neuromorphic Brain Chip Battlefront

Hold onto your hippocampus because the latest neuromorphic marvels are firing on all synapses. To ensure we’re all tap-dancing to the same skirl of the bagpipes, let’s remind ourselves that the ter…

www.eejournal.com

Hi Doz,

Now for some deja vu:

This is great. It addresses my MACs question. We're using MAC-Lite although it does not explain it fully. I'll have to wait for the movie.

I guess this bit is about N-of-M coding from Simon Thorpe's Spikenet:

The name of the game here is “sparse.” We’re talking sparse data (streaming inputs are converted to events at the hardware level, reducing the volume of data by up to 10x before processing begins)

Something else I hadn't realized, although obvious in retrospect, is Akida 1 is also available on the cloud along with the Akida 2 FPGA.

 

[Doz]

For those unaware .

The ASX recently changed the reporting of short positions to save the reporting participants time and money on what they claimed as information that no one used . This eliminated access to the net short positions that was considered more accurate than the gross numbers as used by Shortman for example .

The below is an example of how retail are now exposed to false market information regarding short positions . Over this small example on Brainchip you can clearly see the current issue with accuracy . Due to this new level of abusive corruption in my opinion , I am currently seeking with the ASX to return to the previous method of reporting and to reinstate access to the more accurate net positions .

Note : Anyone thinking Brainchip currently has 100+ million being shorted and that professional shorts are going to be BurNt you may need to do some extra research , especially if you are an amateur retail investor with a current short position relying on the pro’s to protect you .

All in my opinion …..

 

[7für7]

With so many positive things happening in the business at the moment it is hard to fathom why the share price continues to sink.

It’s a complete joke

 

[manny100]

This is the reason why the price is dropping shorts over 100 million plus, where they are getting the shares from???NAKED bet yah and the fact there will be another capital raise in the future to support managements high burn rate of cash. View attachment 92768

Every knows there will be cap raises until revenue is sufficient to self sustain. So there is no surprise with that at all.
I am surprised that you are surprised.
The price is still within the range above the base. We have been to the bottom of the range only a relatively few times over the last 2 years. If we get there again it will only rise off that.
So what is the problem.

 

[HopalongPetrovski]

Hi all.

I asked Grok to "contrast and compare Brainchip's Akida technology with Nanoveu's ECS-DoT AI SoC."

I have a finger in both pies and thought perhaps others may be interested as well.
For what it is worth, here below is it's answer.




Overview

BrainChip's Akida and Nanoveu's ECS-DoT (developed by its subsidiary EMASS) are both ultra-low-power System-on-Chip (SoC) solutions designed for edge AI applications, targeting always-on processing in power-constrained environments like wearables, IoT devices, drones, and industrial sensors. Akida emphasizes neuromorphic computing, mimicking the brain's sparse, event-based processing for efficiency in neural network tasks. In contrast, ECS-DoT focuses on traditional RISC-V-based AI acceleration with non-volatile memory optimizations, prioritizing multimodal sensor fusion and benchmark-proven energy savings. While both enable cloud-free inference, Akida excels in bio-inspired learning, whereas ECS-DoT offers superior raw efficiency in standardized tests.

Key Comparison Table

Aspect	BrainChip Akida	Nanoveu ECS-DoT (EMASS)
Architecture	Neuromorphic (Spiking Neural Networks - SNNs); event-based, digital neuron fabric with sparsity exploitation (neurons fire only on thresholds). Supports CNNs, DNNs, RNNs, ViTs.	RISC-V core with AI accelerators and non-volatile memory (e.g., ReRAM integration); optimized for multimodal fusion (vision, audio, sensors). Traditional ANN focus.
Power Consumption	Ultra-low: ~1 mW (Akida Pico variant); milliwatt-scale for inference. Leverages sparsity for energy savings.	Milliwatt-scale (0.1–10 mW); benchmarks show 90% less energy vs. competitors (e.g., 0.8 µJ/inference in anomaly detection, 20% lower overall vs. peers).
Performance	Up to 1.2M neurons, 10B synapses per chip; scalable to 1,024 chips (1.2B neurons total). 8-bit weights/activations; low latency via multi-pass processing.	Up to 30 GOPS/W; 93% faster execution vs. competitors (e.g., 1.22 ms in anomaly detection, 3.9 ms in keyword spotting). 4 MB on-board SRAM for efficient compute.
Memory	Configurable local scratchpads; supports LPDDR4 SDRAM (e.g., 256M x 16 bytes in dev kits).	4 MB on-board SRAM; non-volatile tech reduces leakage and enables always-on modes.
Learning/Training	On-chip edge learning via reinforcement/inhibition; incremental learning supported.	Primarily inference-focused; on-device training not emphasized (relies on cloud/offline optimization).
Interfaces/Connectivity	PCIe 2.0, ARM Cortex-M4 (300 MHz), GPIO; multi-chip fabric for scaling.	Sensor-integrated (vision/audio); SDKs for IoT integration; partnerships for reference designs.
Applications	Edge vision (e.g., industrial inspection), voice, vibration; automotive, consumer electronics, IoT. Strong in pattern recognition.	Drones (extended flight time), wearables, healthcare (biometrics), smart cities; excels in real-time 2D-to-3D conversion, anomaly detection.
Process Node	28 nm (AKD1000); considering 14 nm.	Not specified; modular for future scaling to 6 nm/4 nm.
Software Ecosystem	MetaTF framework (TensorFlow/Keras integration); Edge Impulse support; cloud dev tools.	Enhanced SDKs/reference designs via Arrow Electronics; RISC-V tools for custom AI.
Maturity/Availability	Commercial since 2022 (AKD1000); dev kits (PCIe/Raspberry Pi) available; partnerships (e.g., Edge Impulse).	Emerged from stealth in 2025; benchmarks completed, OEM integrations underway (e.g., drones); sales reps appointed.
Strengths	Bio-mimetic efficiency for sparse data; on-device adaptability; scalable for larger networks.	Benchmark dominance in speed/energy; multimodal versatility; thermal efficiency (no cooling needed).
Challenges	Higher power in dense workloads; neuromorphic requires model optimization.	Less emphasis on learning; newer market entry may limit ecosystem breadth.

Similarities

• Ultra-Low-Power Edge Focus: Both target milliwatt-level operation for battery-powered, always-on AI, reducing cloud dependency, latency, and privacy risks. They enable real-time sensor processing (e.g., vision/audio) in constrained devices.
• Efficiency-Driven Design: Prioritize sparsity/exploitation of data patterns (Akida via neurons; ECS-DoT via memory optimizations) for 10–100x energy savings over general-purpose chips.
• Scalability and Integration: Modular for multi-chip or application-specific variants; support standard ML workflows (e.g., TensorFlow) and dev tools for rapid deployment.
• Target Markets: Overlap in IoT, wearables, drones, and industrial uses, addressing the growing edge AI market (projected >$20B by 2028).

Differences

• Core Philosophy: Akida's neuromorphic approach provides brain-like adaptability and on-chip learning, ideal for dynamic, sparse environments (e.g., event-driven sensors). ECS-DoT's RISC-V foundation delivers predictable, high-throughput performance in multimodal tasks, with superior benchmark results against incumbents like STMicroelectronics or Syntiant.
• Efficiency Metrics: ECS-DoT claims quantifiable edges (e.g., 287x faster in anomaly detection), positioning it for ultra-constrained apps like extended drone flights. Akida shines in qualitative sparsity gains but lacks direct head-to-head benchmarks here.
• Maturity and Ecosystem: Akida is more established with commercial products and broader partnerships, suiting immediate prototyping. ECS-DoT, as a 2025 newcomer, leverages Nanoveu's display tech synergies (e.g., 3D imaging) but focuses on rapid OEM adoption via distributors like Arrow.
• Innovation Trade-offs: Akida enables unique features like incremental learning for evolving models, while ECS-DoT prioritizes raw speed and thermal simplicity for "set-and-forget" deployments.

In summary, choose Akida for adaptive, brain-inspired AI in vision-heavy or learning-centric apps; opt for ECS-DoT for energy-critical, multimodal inference where benchmarks matter most. Both advance edge AI, but ECS-DoT's recent benchmarks suggest it could disrupt in power-sensitive niches.

 

[manny100]

For those unaware .

The ASX recently changed the reporting of short positions to save the reporting participants time and money on what they claimed as information that no one used . This eliminated access to the net short positions that was considered more accurate than the gross numbers as used by Shortman for example .


View attachment 92770


The below is an example of how retail are now exposed to false market information regarding short positions . Over this small example on Brainchip you can clearly see the current issue with accuracy . Due to this new level of abusive corruption in my opinion , I am currently seeking with the ASX to return to the previous method of reporting and to reinstate access to the more accurate net positions .

Note : Anyone thinking Brainchip currently has 100+ million being shorted and that professional shorts are going to be BurNt you may need to do some extra research , especially if you are an amateur retail invest with a current short position relying on the pro’s to protect you .

View attachment 92771

All in my opinion …..

Agree, gross shorts alone conceal the true directional position (market bet) of a fund. Retail investors do not know what the funds are ultimately betting on. Funds have different strategies eg may have % of shorts to hedge against the long bet but we only see the gross shorts not the long or the net.
If the net position is no where as 'bad' as the gross shorts suggest it actually encourages selling. Retailers can be 'spooked' - hence downrampers on forums.
There are many, many reasons why funds short to profit. For example even those who hold from lower prices and believe in the longer term prospects short price spikes to make some cash on the retrace. We only see the gross shorts figure though.
We saw a recent quick paced rise to 27 cents which was way overbought in relation to the time it took to get there. That was a certainty to be sold/shorted big.
A good news catalyst would be good right now.

 

[Diogenese]

For those unaware .

The ASX recently changed the reporting of short positions to save the reporting participants time and money on what they claimed as information that no one used . This eliminated access to the net short positions that was considered more accurate than the gross numbers as used by Shortman for example .


View attachment 92770


The below is an example of how retail are now exposed to false market information regarding short positions . Over this small example on Brainchip you can clearly see the current issue with accuracy . Due to this new level of abusive corruption in my opinion , I am currently seeking with the ASX to return to the previous method of reporting and to reinstate access to the more accurate net positions .

Note : Anyone thinking Brainchip currently has 100+ million being shorted and that professional shorts are going to be BurNt you may need to do some extra research , especially if you are an amateur retail investor with a current short position relying on the pro’s to protect you .

View attachment 92771

All in my opinion …..

So the gamekeeper is giving the poacher a leg up over the fence?