BRN Discussion Ongoing

[Esq.111]

Morning Chippers,

America , defence budget , set for a top up....... business as usual.

Congress passes $886 billion defense policy bill, Biden to sign into law

The bill includes a four-month extension of Section 702, a controversial surveillance authority, giving lawmakers more time to either reform or keep the program.

www.cnbc.com

Regards,
Esq.

 

[IloveLamp]

Super proud of the team, well done all. | Mohammed Umar Dogar

Super proud of the team, well done all. Looking forward to 2024 with many more exciting things to come..

www.linkedin.com

 

[IloveLamp]

Pat Gelsinger on LinkedIn: #itstartswithintel | 10 comments

The arrival of the AI PC with Intel Core Ultra represents an inflection point in the PC industry. Computers infused with AI capabilities are permanently… | 10 comments on LinkedIn

www.linkedin.com

 

[Getupthere]

Tokay Lite no-code Edge AI camera with night vision and TensorFlow Lite support and more

A new multifunctional Edge AI camera offering nightvision, motion detection, TensorFlow Lite support, no-code set up and open source design

www.geeky-gadgets.com

Tokay Lite no-code Edge AI camera with night vision and TensorFlow Lite support and more​

10:39 am December 14, 2023 By Julian Horsey

​

A new multifunctional Edge AI camera offering night vision, motion detection, TensorFlow Lite support, no-code set up and open source design is now available to purchase from just $89 from the Crowd Supply website. Watch the video below for a quick overview of what you can expect from this tiny and affordable Edge AI camera. The Tokay Lite, is an advanced AI camera platform and ESP32-based development board. This sophisticated piece of hardware is not just a camera, but a versatile tool with a myriad of applications that stretch from security to wildlife monitoring, and even agricultural use.
At the heart of the Tokay Lite lies its onboard Edge AI Processing capability. This feature allows real-time image analysis and decision-making without the need for an external computer. It is a testament to the power of edge computing, where data is processed on the device itself, thus reducing latency and increasing speed. Whether it’s detecting an intruder in a security setup or identifying a rare bird species in a wildlife monitoring scenario, the Tokay Lite can process and analyze data in real-time, right at the source.

Tokay Lite no-code Edge AI camera​

The Tokay Lite is powered by open-source firmware, and its no-code web interface makes it user-friendly even for those not versed in programming. This interface allows users to configure settings according to their specific needs. Moreover, the device can be seamlessly integrated with major IoT and AI platforms like AWS, ThingsBoard, and Home Assistant, further enhancing its versatility.



Watch this video on YouTube.

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• ROVAOM 4K color night vision camera from $249
• Samsung Galaxy Enhance-X AI camera app

One of the standout features of the Tokay Lite is its facial recognition and detection capabilities. The device comes pre-loaded with a facial recognition model, but users can also reprogram it with their own AI models. This feature can be particularly useful in security applications, where recognizing and identifying individuals is paramount.
Beyond its use in security, the Tokay Lite also finds application in robotics. It can serve as a sensor and decision-making unit, providing real-time visual data and performing visual recognition tasks. This capability can be instrumental in developing robots that can navigate their environment and interact with objects and individuals.
The Tokay Lite is designed for plug-and-play integration, featuring an AI-capable chip with 8 MB FLASH and 8 MB of external RAM. Its adaptable power modes and night vision feature make it suitable for use in various environmental conditions. The device is also equipped with light and motion sensors for environmental monitoring.

The open-source nature of the Tokay Lite extends to its SDK, providing developers with the freedom to customize and enhance the device’s capabilities. The device comes with numerous examples, serving as a valuable resource for developers looking to explore its potential.
Technical specifications of the Tokay Lite include an onboard MCU: ESP32-S3, sensor interface: DVP, stock camera sensor: OV2640, image capabilities: 0.3 MP / 2 MP / 3 MP with RGB and JPEG support, frame rate: up to 15 FPS, night vision, sensors: light sensor and passive IR (motion detection), connectivity: Wi-Fi and BLE, memory: 8 MB Flash, 512 kB + 8 MB RAM, software: TF-Lite Micro, esp-dl, interfaces: SPI, UART, battery connector: JST-PH (2 mm pitch), and customizable power features: programmable external RTC.
The Tokay Lite is now available to purchase from Crowd Supply priced at $89 with shipping expected to take place sometime around May 2024. Its versatility, advanced capabilities, and user-friendly design make it a valuable tool in various fields, from security to robotics. As AI continues to evolve, devices like the Tokay Lite serve as a reminder of the exciting possibilities that lie ahead.

Tokay Lite camera features​

• Designed for Plug-and-Play: Ready for integration with a hassle-free setup.
• Powerful AI-Capable Chip: Packed with an 8 MB FLASH and 8 MB of external RAM for AI tasks.
• Adaptable Power Modes: Switch between low power and high-performance modes to match your power needs.
• Night Vision: Equipped with night vision and onboard IR LED illumination for all-environment use.
• Environmental Monitoring: Features light and motion sensors for comprehensive environmental awareness.
• No-Code UI: Easily set up projects and fine-tune sensors without coding.
• Seamless Integrations: Effortlessly connects to major IoT and AI platforms like AWS IoT, Edge Impulse, and ThingsBoard.
• Open Source: Explore the possibilities with an open-source SDK and numerous examples.

Specifications​

• Onboard MCU: ESP32-S3
• Sensor Interface: DVP
• Stock Camera Sensor: OV2640
• Image Capabilities: 0.3 MP / 2 MP / 3 MP with RGB and JPEG support
• Frame Rate: Up to 15 FPS
• Night Vision: Yes
• Sensors: Includes Light Sensor and Passive IR (Motion Detection)
• Connectivity: Wi-Fi and BLE
• Memory: 8 MB Flash, 512 kB + 8 MB RAM
• Software: TF-Lite Micro, esp-dl
• Interfaces: SPI, UART
• Battery Connector: JST-PH (2 mm pitch)

 

[Xray1]

BrainChip Previews Industry’s First Edge Box Powered by Neuromorphic AI IP​

BrainChip Previews Industry’s First Edge Box Powered by Neuromorphic AI IP

BrainChip Previews Industry’s First Edge Box Powered by Neuromorphic AI IP LAGUNA HILLS, Calif.--(BUSINESS WIRE)-- BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low p

crweworld.com

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, neuromorphic AI IP, today released previews of the industry’s first Edge box based on neuromorphic technology built in collaboration with VVDN Technologies, a premier electronics and manufacturing company.

The Akida™ Edge Box—expected to begin pre-sales on January 15th, 2024—powers AI applications in challenging environments where performance and efficiency are essential. The device will be demonstrated for the first time at CES 2024, January 9-12 in Las Vegas.

Designed for vision-based AI workloads, the compact Akida Edge box is intended for video analytics, facial recognition, and object detection, and can extend intelligent processing capabilities that integrate inputs from various other sensors. This device is compact, powerful, and enables cost-effective, scalable AI solutions at the Edge.

BrainChip’s event-based neural processing, which closely mimics the learning ability of the human brain, delivers essential performance within an energy-efficient, portable form factor, while offering cost-effectiveness surpassing market standards for edge AI computing appliances. BrainChip’s Akida neuromorphic processors are capable of on-chip learning that enables customization and personalization on device without support from the cloud, enhancing privacy and security while also reducing training overhead, which is a growing cost for AI services.

“BrainChip’s neuromorphic technology gives the Akida Edge box the ‘edge’ in demanding markets such as industrial, manufacturing, warehouse, high-volume retail, and medical care,” said Sean Hehir, CEO of BrainChip. “We are excited to partner with an industry leader like VVDN technologies to bring groundbreaking technology to the market.”

“There is a strong demand for cost-effective, flexible edge AI computation across many industries,” said Puneet Agarwal, Co-Founder and CEO, VVDN Technologies. “VVDN is excited to offer OEMs its experience and expertise in bringing the advanced, transformative technology integrations that meet market needs and eventually help them with faster time to market.”

BrainChip’s Akida Edge Box is suitable for environments that require cost-effective and low-latency AI processing. In security and surveillance, it can automatically detect and report intrusion, identify individuals in restricted areas, and perform behavior analysis to recognize suspicious behaviors or potential threats.

In retail and warehousing, it can assist in inventory management and loss prevention by identifying when shelves are empty, when restocking is needed, and when merchandise is removed without authorization. Behavior analysis capabilities can also help retailers understand how customers interact with products and store layouts to maximize profitability.

The Akida Edge Box brings AI to industrial settings for visual detection applications such as quality inspection, identifying defects or irregularities in products, and integration with factory robotic systems for precise object manipulation. It can be used to enhance plant and worker safety, identify whether workers are using proper safety gear, following protocols and proper workflows, and identify malfunctions in assembly lines.

Healthcare applications include patient monitoring, such as noting a patient’s physical movements to ensure safety and provide alerts for falls or unusual behavior. In rehabilitation facilities it can track and analyze patient movements to aid in physical therapy. In elder care settings it can be used to detect falls or other situations that require staff assistance or intervention.

I wonder for how much it will be sold for and how those sale funds will be finally distributed between BRN & VVDN.

 

[Xray1]

Do people here think now, is perhaps the Time, to strongly recommend those we know and love, to invest a decent sum in BrainChip?

Perhaps from their Super?

$17500 will buy you 100000 shares in this Company and on the basis, that it could be lost, or profoundly change their future, could be a good "bet"?...

Many here have already recommended strongly over the years, with good intentions, but ill effect.

I personally encouraged my Brother to buy 50000 shares at 95 cents last year and now he won't listen to me about averaging down ..


Disclosure - I am very heavily invested in BrainChip and bought another 10000 shares yesterday..

I sleep like a baby at night, but if BrainChip doesn't "make it" my future will seriously look a bit like this..

View attachment 52053

Provided someone will be kind enough to let me park this beauty on their property ..



However, I will probably still look at it like this..

View attachment 52054

I personally would wait and see what actually eventuates between now and the AGM

 

[KiKi]

I wonder for how much it will be sold for and how those sale funds will be finally distributed between BRN & VVDN.

I might be completely mistaken, but I think I read something like 9,900 Dollar somewhere. Or was it 990?
O.k. I am not sure.

 

[IloveLamp]

Redirecting

 

[Bravo]

https://www.eetimes.com/podcasts/perceiving-touch-with-event-based-neuromorphic-computing/

Extract


I highlighted this section because according to Nandan Nayampally at CVPR 2023 Workshop on Event-based Vision IniVation is a "Partner".

 

[Bravo]

AI & Big Data Expo: Unlocking the potential of AI on edge devices​

About the Author​

By Ryan Daws | December 15, 2023
Categories: Artificial Intelligence, Development, Enterprise, Healthcare, Industries, Machine Learning,
Ryan is a senior editor at TechForge Media with over a decade of experience covering the latest technology and interviewing leading industry figures. He can often be sighted at tech conferences with a strong coffee in one hand and a laptop in the other. If it's geeky, he’s probably into it. Find him on Twitter (@Gadget_Ry) or Mastodon (@gadgetry@techhub.social)



In an interview at AI & Big Data Expo, Alessandro Grande, Head of Product at Edge Impulse, discussed issues around developing machine learning models for resource-constrained edge devices and how to overcome them.
During the discussion, Grande provided insightful perspectives on the current challenges, how Edge Impulse is helping address these struggles, and the tremendous promise of on-device AI.

Key hurdles with edge AI adoption​

Grande highlighted three primary pain points companies face when attempting to productise edge machine learning models, including difficulties determining optimal data collection strategies, scarce AI expertise, and cross-disciplinary communication barriers between hardware, firmware, and data science teams.
“A lot of the companies building edge devices are not very familiar with machine learning,” says Grande. “Bringing those two worlds together is the third challenge, really, around having teams communicate with each other and being able to share knowledge and work towards the same goals.”

Strategies for lean and efficient models​

When asked how to optimise for edge environments, Grande emphasised first minimising required sensor data.
“We are seeing a lot of companies struggle with the dataset. What data is enough, what data should they collect, what data from which sensors should they collect the data from. And that’s a big struggle,” explains Grande.
Selecting efficient neural network architectures helps, as does compression techniques like quantisation to reduce precision without substantially impacting accuracy. Always balance sensor and hardware constraints against functionality, connectivity needs, and software requirements.
Edge Impulse aims to enable engineers to validate and verify models themselves pre-deployment using common ML evaluation metrics, ensuring reliability while accelerating time-to-value. The end-to-end development platform seamlessly integrates with all major cloud and ML platforms.

Transformative potential of on-device intelligence​

Grande highlighted innovative products already leveraging edge intelligence to provide personalised health insights without reliance on the cloud, such as sleep tracking with Oura Ring.
“It’s sold over a billion pieces, and it’s something that everybody can experience and everybody can get a sense of really the power of edge AI,” explains Grande.
Other exciting opportunities exist around preventative industrial maintenance via anomaly detection on production lines.
Ultimately, Grande sees massive potential for on-device AI to greatly enhance utility and usability in daily life. Rather than just raw data, edge devices can interpret sensor inputs to provide actionable suggestions and responsive experiences not previously possible—heralding more useful technology and improved quality of life.
Unlocking the potential of AI on edge devices hinges on overcoming current obstacles inhibiting adoption. Grande and other leading experts provided deep insights at this year’s AI & Big Data Expo on how to break down the barriers and unleash the full possibilities of edge AI.
“I’d love to see a world where the devices that we were dealing with were actually more useful to us,” concludes Grande.

 

[Getupthere]

I can’t say I have seen Sean sell his shares to pay his taxes as yet?

Last year he sold 2 to 3 days after receiving them.

 

[Kachoo]

I can’t say I have seen Sean sell his shares to pay his taxes as yet?

Why would he sell at this price. Likely he could have found other financial ways to pay.

I'm surprised how many people are shocked he has not sold.

He was given 2 million part of his package at 20 cents so say half is tax then he needs to come up with 200 k

He is not a stupid man he I will say that. So say the SP at the AGM is 60 cents will that be a win for him absolutely. And he is genuinely in the belief the SP is bellow real value. I don't want to argue about SP that's dictated by the market be it this or that.

But last year he got shares at 80 cents paid tax selling it would have cost him 800 k to keep all. If you go with the theory at that time the sp may have still been high then no kidding he sold his tax portion.

Today he gets them at 20 cents 4 times cheaper so if say the value of the company IP is somewhere between 20 and 80 lets say 50 cents what would you do finance the tax and keep the shares.

Sean is putting his money in the game I'm surprised many don't see this while your all looking at the flaws and looking to hang a person he quietly put skinning the game. Yes that's putting skin in the game.

My opinion and personal view is do as smart money not as what agenda driven unknown posters vent when mad or are trying to block validated clear news that is interested.

Forget the old past look to the future.

Sean did buy yes at a discount part of his payment but likely he put quite a bit of his money now in the form of tax to me that's confidence that SP is below what the guy that knows all that is happening at BRN.

 

[Frank Zappa]

Tech, as you have stated:

" still not expecting any cash receipts/revenue in this closing quarter or next, sorry, but that's my opinion....it's hard to swallow, but that's just how I see things....give it to me if I'm wrong !"

I am also of the opinion, that if there are also no new IP agreements nor increased / meaningful revenue levels entered into by the time the AGM is held, then who know's what the Co's position and outcome will be, given that a "Strike 2" action might / may still be pending.

I would be very careful before going down a second strike course of action . Looking at the graph of TAH share price after successfully striking out at their directors has not led to a $ 1.00 share price hot tub gathering.

 

[Diogenese]

Why would he sell at this price. Likely he could have found other financial ways to pay.

I'm surprised how many people are shocked he has not sold.

He was given 2 million part of his package at 20 cents so say half is tax then he needs to come up with 200 k

He is not a stupid man he I will say that. So say the SP at the AGM is 60 cents will that be a win for him absolutely. And he is genuinely in the belief the SP is bellow real value. I don't want to argue about SP that's dictated by the market be it this or that.

But last year he got shares at 80 cents paid tax selling it would have cost him 800 k to keep all. If you go with the theory at that time the sp may have still been high then no kidding he sold his tax portion.

Today he gets them at 20 cents 4 times cheaper so if say the value of the company IP is somewhere between 20 and 80 lets say 50 cents what would you do finance the tax and keep the shares.

Sean is putting his money in the game I'm surprised many don't see this while your all looking at the flaws and looking to hang a person he quietly put skinning the game. Yes that's putting skin in the game.

My opinion and personal view is do as smart money not as what agenda driven unknown posters vent when mad or are trying to block validated clear news that is interested.

Forget the old past look to the future.

Sean did buy yes at a discount part of his payment but likely he put quite a bit of his money now in the form of tax to me that's confidence that SP is below what the guy that knows all that is happening at BRN.

What's the penalty for insider non-trading?

 

[Kachoo]

What's the penalty for insider non-trading?

Getting to keep his shares lol!

 

[Fullmoonfever]

I wonder for how much it will be sold for and how those sale funds will be finally distributed between BRN & VVDN.

Not entirely sure myself that it will be a profit split as such.

The original Ann was that we "engaged" VVDN, "a premier electronics engineering and manufacturing company, to deliver the industry’s first Edge box based on neuromorphic technology."

Implies to me still that we possibly paid for the service and manufacturing and will go to market.

In the latest Ann, VVDN said it "is excited to offer OEMs its experience and expertise in bringing the advanced, transformative technology integrations that meet market needs and eventually help them with faster time to market."

They are offering the OEM their experience and expertise.

Maybe, if VVDN are selling it through their channel to mkt they may get a %. Will be interesting to see how it comes out in the wash though so to speak.

 

[Diogenese]

Not entirely sure myself that it will be a profit split as such.

The original Ann was that we "engaged" VVDN, "a premier electronics engineering and manufacturing company, to deliver the industry’s first Edge box based on neuromorphic technology."

Implies to me still that we possibly paid for the service and manufacturing and will go to market.

In the latest Ann, VVDN said it "is excited to offer OEMs its experience and expertise in bringing the advanced, transformative technology integrations that meet market needs and eventually help them with faster time to market."

They are offering the OEM their experience and expertise.

Maybe, if VVDN are selling it through their channel to mkt they may get a %. Will be interesting to see how it comes out in the wash though so to speak.

VVDN already provide an Edge Box with Nvidia so they will have unique knowledge and experience of EBs in use. They will know what input ports are required as well as the types of models to identify different inputs.

 

[Fullmoonfever]

VVDN already provide an Edge Box with Nvidia so they will have unique knowledge and experience of EBs in use. They will know what input ports are required as well as the types of models to identify different inputs.

No doubt, as they state that sort of experience in their offering and make sense to engage them.

Just not sure how BRN are going to structure up the path to mkt yet.

Themselves, with VVDN as well or other resellers that's all.

 

[Diogenese]

No doubt, as they state that sort of experience in their offering and make sense to engage them.

Just not sure how BRN are going to structure up the path to mkt yet.

Themselves, with VVDN as well or other resellers that's all.

The first announcement said both would sell it.

 

[David holland]

Does anybody know of Brainchip's expectations with such a box,
Or is it another way of getting Brainchip's brand out there in the marketplace?