BRN Discussion Ongoing

[Guzzi62]

LOL, that was quite funny to watch.

A CNET reviewer are not sure if he wants to spend 800 bucks on such an oddity.

I can't really see the point of getting distracted by those glasses when out and about, but I am old school. If I go to a café, I sit a watch the world around me and not a screen.

The glasses BRN are involved in makes much more sense to me, they serve a purpose and can be life-saving.

Initial reviews below are generally positive.

I Wore Meta's New Ray-Ban Display Glasses and Neural Band. I Feel Augmented

Meta's AR glasses, available Sept. 30 for $799, have a neural wristband and a wide range of AI and app functions. They dream big, but their future is unclear.

www.cnet.com

I regret to inform you Meta’s new smart glasses are the best I’ve ever tried

I am agog, I am aghast, are smart glasses truly good at last?

www.theverge.com

Ray-Ban Meta (Gen 2) hands-on: I'm a skeptic, but I'd wear these AI glasses

These smart specs look slick in person

www.tomsguide.com

 

[HopalongPetrovski]

Reminds me of when Elon's friend threw a projectile through the cyber trucks window. Embarrassing, and you'd think all of this stuff would be so well rehearsed and the presentations so well polished, that this stuff just couldn't happen. But seems to be the par with tech promotions. Everything from wrinkled tablecloths to Billionaires looking stupid on stage.
Still, this reviewer was digging the attention and its easy to chuck brickbats from the cheap seats.

 

[Fullmoonfever]

Speaking of glasses.

@Frangipani & others had posted some info previously that involved Luxottica and Nuance Audio in glasses.

Also about an interview with Steve Brightfield on smart glasses too.

BRN Discussion Ongoing

https://www.linkedin.com/posts/edgx-space_happy-to-welcome-edgx-as-a-satsearch-trusted-activity-7330955537976598528-g7I_?utm_source=share&utm_medium=member_ios&rcm=ACoAADXcDGoBrlbyjzyvD2JFuq1hoU6lQFpxvLA Happy to welcome EDGX as a satsearch trusted supplier. Introducing the EDGX DPU, a...

thestockexchange.com.au

Well, Francesca Palermo, Research Principal Investigator at Luxottica will be presenting at Embedded Vision around now on their next product being Ego Vision Devices on smart glasses.

"Enabling Ego Vision Applications on Smart Eyewear Devices," a Presentation from EssilorLuxottica - Edge AI and Vision Alliance

Francesca Palermo, Research Principal Investigator at EssilorLuxottica, presents the “Enabling Ego Vision Applications on Smart Eyewear Devices” tutorial at the May 2025 Embedded Vision Summit. Ego vision technology is revolutionizing the capabilities of smart eyewear, enabling applications that...

www.edge-ai-vision.com

Enabling Ego Vision Applications on Smart Eyewear Devices - 2025 Summit

Ego vision technology is revolutionizing the capabilities of smart eyewear, enabling applications that understand user actions, estimate human pose and provide spatial awareness through simultaneous localization and mapping (SLAM). This presentation will dive into the latest advancements in...

embeddedvisionsummit.com

This is a computer vision application obviously and different from the Nuance glasses.

I also believe that Luxottica might be doing the frames for Onsors glasses if correct?

In March this year herself and other authors released a paper titled:

Advancements in Context Recognition for Edge Devices and Smart Eyewear: Sensors and Applications.

Makes for an interesting read through when discussing Arm Cortex M0, M33 and A53 regards to power, processing etc of which we are compatible with.

@Diogenese will probs be able to glean more from the document.

No mention of Akida at this point however under Optimised Algos the below excerpt indicates that exploration of neuromorphic should occur.

I'd expect these sorts of devices would be an excellent fit for something like Akida, TENNs, Pico?

To fully harness the potential of TinyML, future work must focus on designing ultra-efficient algorithms tailored for specific sensor types and exploring energy-efficient hardware accelerators to support TinyML workloads. Future work should also explore neuromorphic computing and event-driven processing architectures, which mimic biological neural systems to achieve ultra-low power consumption for always-on context recognition. Successfully integrating TinyML into edge devices will be a crucial step toward delivering responsive, personalized, and context-aware functionalities while overcoming the limitations of current edge AI systems.

When I had a look at her background and education she appears no stranger to SNN after studying them as below.

Resume

francescapalermo.github.io

• October 2011 - December 2014: B.Sc. in Computer and Automation Engineering, University of Rome “La Sapienza”, Rome, Italy, Italian Mark 95/110, 2010-2014
  • Analysis and development of spiking neural network Izhikevich models

https://ieeexplore.ieee.org/document/10943217

Abstract:​

Edge devices have garnered significant attention for their ability to process data locally, providing low-latency, context-aware services without the need for extensive reliance on cloud computing. This capability is particularly crucial in context recognition, which enables dynamic adaptation to a user’s real-time environment. Applications range from health monitoring and augmented reality to smart assistance and social interaction analysis. Among edge devices, smart eyewear has emerged as a promising platform for context recognition due to its ability to unobtrusively capture rich, multi-modal sensor data. However, the deployment of context-aware systems on such devices presents unique challenges, including real-time processing, energy efficiency, sensor fusion, and noise management. This manuscript provides a comprehensive survey of context recognition in edge devices, with a specific emphasis on smart eyewear. It reviews the state-of-the-art sensors and applications for context inference. Furthermore, the paper discusses key challenges in achieving reliable, low-latency context recognition while addressing energy and computational constraints. By synthesizing advancements and identifying gaps, this work aims to guide the development of more robust and efficient solutions for context recognition in edge computing

 

[HopalongPetrovski]

Here is an update on the Ghost Bat. AI generated and a little clunky but provides an overview for anyone interested.

 

[Diogenese]

Here is an update on the Ghost Bat. AI generated and a little clunky but provides an overview for anyone interested.

The video talks about refuelling. So does this patent:

US2025147515A1 SYSTEMS AND METHODS FOR CONTROLLING AIRCRAFT DURING IN-FLIGHT REFUELING 20231106

[0048] In at least one example, all or part of the systems and methods described herein may be or otherwise include an artificial intelligence (AI) or machine-learning system that can automatically perform the operations of the methods also described herein. For example, the control unit 112 can be an artificial intelligence or machine learning system. These types of systems may be trained from outside information and/or self-trained to repeatedly improve the accuracy with how data is analyzed to automatically determine economy speeds. Over time, these systems can improve by determining such information with increasing accuracy and speed, thereby significantly reducing the likelihood of any potential errors. For example, the AI or machine-learning systems can learn and determine features of aircraft, fuel ports, and/or the like to automatically determine locations within scanned data, and automatically generate 3D models. The AI or machine-learning systems described herein may include technologies enabled by adaptive predictive power and that exhibit at least some degree of autonomous learning to automate and/or enhance pattern detection (for example, recognizing irregularities or regularities in data), customization (for example, generating or modifying rules to optimize record matching), and/or the like. The systems may be trained and re-trained using feedback from one or more prior analyses of the data, ensemble data, and/or other such data. Based on this feedback, the systems may be trained by adjusting one or more parameters, weights, rules, criteria, or the like, used in the analysis of the same. This process can be performed using the data and ensemble data instead of training data, and may be repeated many times to repeatedly improve the determination and location of various structures within scan data. The training minimizes conflicts and interference by performing an iterative training algorithm, in which the systems are retrained with an updated set of data (for example, data received before, during, and/or after each flight of aircraft) and based on the feedback examined prior to the most recent training of the systems. This provides a robust analysis model that can better determine locations, features, structures, and/or the like in a cost effective and efficient manner.


This patent post-dates TENNs by many months. It uses lidar to monitor the distance between the planes and controls the petrol hose accordingly. It also uses ML, so it is an ideal application for Akida TENNs.

This one monitors turbulence to predictively correct flight path, very useful in refueling (think spitting the dummy).

US2025138194A1 Aircraft Acceleration Prediction Using Lidar Trained Artificial Intelligence 20231027

An air vehicle management system comprising a controller for an air vehicle. The controller is configured to determine a prediction of an acceleration using an air vehicle model system and backscatter data. The air vehicle model system is trained to predict the acceleration using the backscatter data and is generated using backscatter light detected from emitting a laser beam in an atmosphere in a direction ahead of the air vehicle. The controller is configured to determine an adjustment to a number of flight control settings for the air vehicle that reduces a stress on the air vehicle using the prediction of the acceleration. The controller is configured to adjust the number of flight control settings using the adjustment.

 

[Labsy]

I'm feeling like I don't think I could handle any explosive news after such a long wait. I reckon I'll break down and cry like a baby if and when it happens.... Getting butterflies in my bellie and teary in the eyes...c'mon chippers! Get ready to party like its 1999... Let goooooooooo!!!

 

[FJ-215]

Hey !

just to clarify …my original question was more general (and to be honest, a bit on the light-hearted side) because his statement felt rather vague. And I wasn’t saying Ceva or LLVision already bought a BrainChip license.

And than..after your reply..my point was different..if Ceva, a US company, can openly power AR glasses developed by a Chinese firm (LLVision) and those products are set for global launch, then clearly it’s not some universal “forbidden zone” where no Western tech/IP can be used in China.

Sure, BrainChip doesn’t have a license there yet, but that’s not the same as saying it can’t happen. The Ceva example shows the door is not completely shut. Export restrictions hit certain categories (high-end GPUs, supercomputing, military tech), but they don’t block everything across the board.

So the whole “China is totally off-limits for BrainChip” argument doesn’t really hold up.

Hi @7für7

I'm with you. I wish our board is doing everything possible to enter every market on earth. Given their level of courage when it comes to dealing with the ASX, China might just be a bridge to far.

Anyway, If you look at my original post, I was taking aim at the muppets who keep spamming businesses on LinkedIn that we most likely have nothing to do with.

To my eyes, it's the equivalent of the cryto clowns that show up here.

 

[Pom down under]

I'm feeling like I don't think I could handle any explosive news after such a long wait. I reckon I'll break down and cry like a baby if and when it happens.... Getting butterflies in my bellie and teary in the eyes...c'mon chippers! Get ready to party like its 1999... Let goooooooooo!!!