Maybe Nintendo could release a new game - Brainchip Investing. The game concept is that strange snippets of information are released and you have to join the dots in real time. Crazyiest dot joiner wins. Slowest dot joiner loses.
BRN Discussion Ongoing
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KiKi
Regular
Pom down under
Top 20
Expectations on getting some real $$$ news this week.
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7für7
Top 20
Chart analysts in the HC forum are like,
“When the coyote runs through the prairie, the rabbit hole is south of the northern spaghetti stalk. Meanwhile, the farmer had five beers at the tavern while his wife and the son’s daughter were watching the rain from the café during the summer sale. Star Trek doesn’t get any more interesting either. … Just my opinion, though—things could turn out completely different.”
That just shows they have no clue… as if the woman would simply let the man drink five beers. She would force him to come along—which, for me, would be a bearish sign.
“When the coyote runs through the prairie, the rabbit hole is south of the northern spaghetti stalk. Meanwhile, the farmer had five beers at the tavern while his wife and the son’s daughter were watching the rain from the café during the summer sale. Star Trek doesn’t get any more interesting either. … Just my opinion, though—things could turn out completely different.”
That just shows they have no clue… as if the woman would simply let the man drink five beers. She would force him to come along—which, for me, would be a bearish sign.
Fullmoonfever
Top 20
Hope this guy has been getting a chance to play with Akida.
• Pilot Digital Assistant of Single Pilot Operation flight deck (Collins Aerospace) • Maintenance, Repair & Overhaul (MRO) applications (Pratt&Whitney)
• Interiors Cabin Analytics (Collins Aerospace)
• Visual Inspection (all RTX BUs)
Bing Han was a PhD student in the C-BRIC (Center for Brain Inspired Computing) at Purdue University. His research focuses on developing energy-efficient and robust deep learning models using both spiking and non-spiking neural networks for computer vision and NLP applications. He has multiple first author papers in top AI conferences such as CVPR, ECCV, and AAAI. He has also explored and built solid foundations in his technical breadth fields such as nano-fabrication, field-and-optics, computer architecture, and circuit-design.
Bing Han
Senior Research Scientist in Neuromorphic Computing
RTX Purdue University
About
Bing conducts fundamental research in energy-efficient deep learning models using temporal encoded Spiking Neural Networks to address the lack of robustness and low-SWaP (Size, Weight and Power) of existing state-of-the art computer vision and large language models (LLMs). Research is applicable to Autonomy, Intelligence, Surveillance, and target acquisition (ISR) Enabling Technologies, Maintenance, Repair & Overhaul, and Model Based Digital Thread. Previous projects include:• Pilot Digital Assistant of Single Pilot Operation flight deck (Collins Aerospace) • Maintenance, Repair & Overhaul (MRO) applications (Pratt&Whitney)
• Interiors Cabin Analytics (Collins Aerospace)
• Visual Inspection (all RTX BUs)
Bing Han was a PhD student in the C-BRIC (Center for Brain Inspired Computing) at Purdue University. His research focuses on developing energy-efficient and robust deep learning models using both spiking and non-spiking neural networks for computer vision and NLP applications. He has multiple first author papers in top AI conferences such as CVPR, ECCV, and AAAI. He has also explored and built solid foundations in his technical breadth fields such as nano-fabrication, field-and-optics, computer architecture, and circuit-design.
Bravo
If ARM was an arm, BRN would be its biceps💪!
Check this out Brain Fam!
Here's a patent for NEUROMORPHIC SENSORS FOR LOW POWER WEARABLES.
The applicant is Rockwell Collins. Date of filing was 5th April 2024.
The patent doesn't mention BrainChip, but as you can see below, Brainchip worked with Rockwell Collins in 2017 on perimeter surveillance, so you'd think they would have to be aware of us.
Rockwell Collins now operates as part of Collins Aerospace, a subsidiary of ...wait for it.... the RTX Corporation (formerly Raytheon Technologies).
EXTRACT ONLY
ENLARGED EXTRACT
Here's a patent for NEUROMORPHIC SENSORS FOR LOW POWER WEARABLES.
The applicant is Rockwell Collins. Date of filing was 5th April 2024.
The patent doesn't mention BrainChip, but as you can see below, Brainchip worked with Rockwell Collins in 2017 on perimeter surveillance, so you'd think they would have to be aware of us.
Rockwell Collins now operates as part of Collins Aerospace, a subsidiary of ...wait for it.... the RTX Corporation (formerly Raytheon Technologies).
EXTRACT ONLY
ENLARGED EXTRACT
NEUROMORPHIC SENSORS FOR LOW POWER WEARABLES - Patent 4451233
NEUROMORPHIC SENSORS FOR LOW POWER WEARABLES - Patent 4451233
data.epo.org
Pom down under
Top 20
CHIPS
Regular
No, I would!Then I will lose for sure
Here is some really heavy-duty stuff, found by Doz.
PDF and audio.
TENNs-PLEIADES:
Building Temporal Kernels
with Orthogonal Polynomials
theintelligenceofinformation.substack.com
PDF and audio.
TENNs-PLEIADES:
Building Temporal Kernels
with Orthogonal Polynomials
Audio for The Information - a first post. TENNs-PLEIADES: Building Temporal Kernels with Orthogonal Polynomials
The Intelligence of Information Audio Podcast Review Research on Artificial Intelligence Research and interesting developments
theintelligenceofinformation.substack.com
Japan launches Michibiki 6 navigation satellite with fifth H3 rocket
HELSINKI — Japan’s flagship H3 rocket successfully launched the Michibiki 6 navigation satellite early Sunday, enhancing the country’s regional GPS capabilities. The Mitsubishi Heavy Industries (MH…
spacenews.com
Sandi Habinc on LinkedIn: #gr712rc #leon3ft #spacecomputing
Yet another successful H3 launch by JAXA: Japan Aerospace Exploration Agency and Mitsubishi Heavy Industries. Liftoff of the fifth H3 rocket, carrying the…
Giulia D'Angelo on LinkedIn: #brainsandmachines
BrainChip 's IP for Targeting AI Applications at the Edge Don’t miss Sunny Bains interviewing M Anthony Lewis, Yan Ru Pei, Olivier Coenen, Kris Carlson and…
Dr Tony Lewis said.....
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Humble Genius
Regular
Murty Gonella on LinkedIn: Are you excited about building high-performant AI/ML software apps for…
Are you excited about building high-performant AI/ML software apps for resource-constrained hardware platforms? Then we're looking for you, at Brainchip…
EdgeAI according to BZAI...Blaize (recent SPAC IPO)
finance.yahoo.com
Blaize Releases Updated Business Outlook and Product Pipeline That Demonstrate Increasing Momentum for its Edge AI Solutions
EL DORADO HILLS, Calif., February 10, 2025--Blaize Holdings, Inc. (NASDAQ: BZAI) ("Blaize"), a provider of purpose-built, artificial intelligence (AI)-enabled edge-optimized solutions, has released financial guidance and new product pipeline details that show increasing momentum in its business...
finance.yahoo.com
Before I was so rudely interrupted, I was about to send this:Check this out Brain Fam!
Here's a patent for NEUROMORPHIC SENSORS FOR LOW POWER WEARABLES.
The applicant is Rockwell Collins. Date of filing was 5th April 2024.
The patent doesn't mention BrainChip, but as you can see below, Brainchip worked with Rockwell Collins in 2017 on perimeter surveillance, so you'd think they would have to be aware of us.
Rockwell Collins now operates as part of Collins Aerospace, a subsidiary of ...wait for it.... the RTX Corporation (formerly Raytheon Technologies).
EXTRACT ONLY
View attachment 77447
ENLARGED EXTRACT
View attachment 77448
View attachment 77449
NEUROMORPHIC SENSORS FOR LOW POWER WEARABLES - Patent 4451233
NEUROMORPHIC SENSORS FOR LOW POWER WEARABLES - Patent 4451233data.epo.org
Hi Bravo,
The earliest filing date ofthe patent is the priority date 20230419.
uiux
Regular
US20240365025 - PROGRAMMABLE EVENT OUTPUT PIXEL
BAE SYSTEMS Information and Electronic Systems Integration Inc
A neuromorphic focal plane array ROIC device for temporal and spatial synchronous and asynchronous image event processing comprising a plurality of pixels, each pixel comprising an input section comprising a Sample and Hold (SH) component; a low offset buffer/comparator section comprising a Switched Capacitor Filter (SCF); and a digital event output section comprising an analog pixel bus whereby temporal and spatial image data are synchronously and asynchronously processed.
This document appears to be a patent application for a neuromorphic focal plane array (FPA) Read Out Integrated Circuit (ROIC) designed for high-speed, low-power, event-based image processing. Below is an analysis of its key points, innovations, and applications.
1. Purpose & Innovation
The disclosed invention improves event-based image processing using neuromorphic technology applied to Focal Plane Arrays (FPA). The key innovations include:
- Spatio-temporal event detection: The system can detect changes in both time (temporal) and space (spatial) within an image.
- Neuromorphic processing: Uses principles inspired by biological neural networks to reduce power consumption and increase efficiency.
- High-speed, low-power design: Essential for applications where large amounts of image data must be processed quickly.
- Event-driven architecture: Unlike traditional image sensors that capture entire frames, this system only processes significant "events" (changes in a scene), reducing data bandwidth.
2. Technical Contributions
A. Neuromorphic FPA & Read-Out Integrated Circuit (ROIC)
- The FPA consists of pixels that receive and process electromagnetic radiation.
- A detector circuit in the analog detection layer processes pixel outputs.
- A digital event processing layer refines the event data.
B. Event Processing Mechanism
- Uses asynchronous logarithmic output and synchronous integrated signal output.
- Implements a threshold-based detection system, where a comparator compares pixel outputs to programmable thresholds.
- Includes a Switched Capacitor Filter (SCF) for offset calibration and spatial comparisons.
- Uses Buffered Direct Injection (BDI) for improved signal fidelity.
C. Pixel-Level Processing & Analog Bus (ABUS)
- Each pixel can process and share data with its neighbors via horizontal and vertical switches.
- This allows for distributed event detection and efficient tracking of changes.
- The ABUS enables pixels to communicate, transferring event data without needing full-frame readout.
D. Multi-Mode Operation
- Can switch between different processing modes based on real-time requirements.
- Features programmable sensitivity tuning for different operational scenarios.
3. Applications
The system is suitable for a wide range of high-performance imaging tasks, including:
- Military & Defense
- Hypersonic detection and tracking (e.g., missile warning systems).
- Naval and aerospace surveillance (e.g., infrared threat detection).
- Industrial & Scientific
- Low-light imaging with reduced power consumption.
- Autonomous vehicle vision systems.
- Medical Imaging
- Could be adapted for high-speed medical diagnostics using neuromorphic vision.
4. Potential Impact
This technology represents a significant leap forward in neuromorphic imaging. By integrating spatial and temporal event detection at the pixel level, it enables faster, more efficient image processing while reducing size, weight, and power (SWAP)—a critical factor in defense and aerospace applications.
Conclusion
This patent presents a novel and sophisticated approach to neuromorphic image processing, making it highly suitable for high-speed, low-power, real-time event detection. The combination of analog and digital processing layers, adaptive pixel interactions, and programmable thresholds makes it a powerful tool for defense, surveillance, and advanced AI-driven imaging systems.
Note the digital neuromorphic processing layer
Raytheon, BAE and Northrop selected for DARPA FENCE project
The US DARPA has selected three teams of researchers to develop event-based (neuromorphic) infrared (IR) camera technologies.
FENCE programme manager Whitney Mason said: “Neuromorphic refers to silicon circuits that mimic brain operation; they offer sparse output, low latency, and high energy efficiency.
“Event-based cameras operate under these same principles when dealing with sparse scenes, but currently lack advanced ‘intelligence’ to perform more difficult perception and control tasks.”
Researchers from Raytheon, BAE, and Northrop will work to develop an asynchronous read-out integrated circuit (ROIC) with low-latency and a processing layer that integrates with the ROIC to detect relevant ‘spatial and temporal signals’.
According to DARPA, the ROIC and processing layer will jointly enable an integrated FENCE sensor to operate on less than 1.5W of power.
Mason added: “The goal is to develop a ‘smart’ sensor that can intelligently reduce the amount of information that is transmitted from the camera, narrowing down the data for consideration to only the most relevant pixels.”
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