BRN Discussion Ongoing

[JoMo68]

Happy birthday FF!

 

[hamilton66]

POWERED BY

VITICULTURE - FRUITS - AGRICULTURE​

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• https://www.visiovitis.de/landwirtschaft
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precision viticulture​

INTELLIGENT SENSORS FOR SMART VITICULTURE​

​

​

NEW! Thanks to "LoRa" technology, our sensors have a range of up to 6 kilometers* and can monitor areas of up to 10,000 hectares*. As a result, this technology is also the perfect solution for wine cooperatives.​

​

VineSense : The perfect solution for viticulture 4.0​

​

Sensors installed in the rows of vines measure the micro-climatic parameters of the vines.​

This data is transmitted wirelessly. The information is automatically forwarded to the Netsens data center in Florence every 5 minutes.​

The authenticated user can then access this data from any Internet-enabled device, worldwide.​

​

VineSense is a decision support system and provides reliable information on:​

​

• Development of pathogens: downy mildew, oidium, botrytis, grape moth .​

• Late frost alert , in real-time via email and SMS​

• Infection risk assessment compared to current phenological stage​

• Real-time mapping of microclimatic conditions​

​

Looking at the phenological phases observed in the field, the software models automatically adapt to the specific conditions of your vineyards.​

The agronomic models provide you with useful information about the stage of development and the risk of the most important pathogens. Here, innovative technology and (biodynamic) viticulture 4.0 go hand in hand.​

​

* dependent on geographic location​

Grapes have been mentioned by Brainchip. I have research papers where SNN's can be used to detect VOC's from mould, mildew and yeasts on plants/grape vines. If you have a vineyard with multiple sensors running 24 hours a day doing what is spoken off above at the cost of electricity you would not want them running at full power every second of every minute of every day and you would not want them sending masses of data continuously to the cloud. If you have just listened to Kristopher Carlson's presentation it is fresh in you mind how AKIDA powered sensors can overcome these issues and take cost away as a barrier to adoption.

My opinion only DYOR
FF

AKIDA BALLISTA

F/F, happy b/d mate. BRN should be talking to Penfolds, Costa group etc etc - the big players in the Oz market. That's just OZ, and 1 specific market. ! I love this stock for the possibilities. Is their an industry on big scale that Akida can't assist. It's mindblowing.
GLTA

 

[Deleted member 118]

Is this old

IBM Researchers Showcase Their Non-Von Neumann AI Hardware Breakthrough in Neuromorphic Computing That Can Help Create Machines To Recognize Objects Just Like Humans

This research summary article is based on the paper. 'Phase-change memtransistive synapses for mixed-plasticity neural computations' Human brains are exceptionally good at remembering and learning new information. This brain capacity is credited to how the data is stored and processed by the...

www.marktechpost.com

 

[Violin1]

I'm getting the impression that a lot of us are planning on attending the AGM this year.
Can anyone who has been to previous Brainchip AGM's give us an idea of how many people showed up?
Hope the venue will be large enough this year for us and our bonhomie.
Very much looking forward to greeting our distinguished management and meeting some of the 1000 eyes and perhaps having our appetites whipped up some more.
AKIDA BALLISTA
AKIDA EVERYWHERE
GLTAH

I confirmed with Tony that we don't need to register and he said no but maybe get there in good time as the venue isn't huge. Thankfully I will have just finished with Covid so when we are all standing like sardines I'll be ok!

 

[MDhere]

I'm getting the impression that a lot of us are planning on attending the AGM this year.
Can anyone who has been to previous Brainchip AGM's give us an idea of how many people showed up?
Hope the venue will be large enough this year for us and our bonhomie.
Very much looking forward to greeting our distinguished management and meeting some of the 1000 eyes and perhaps having our appetites whipped up some more.
AKIDA BALLISTA
AKIDA EVERYWHERE
GLTAH

ok i checked flights from Brisbane. i can grab a flight and arrive after 4pm on mon 23rd and can leave by 5pm tues 24th. Anyone want to catch up Monday evening? and does anyone have a spare room in the city

 

[Jumpchooks]

Enough is enough and so back to Brainchip. I just found the following article about Edge Impulse from 2020 which given they are now out of the closet and proudly stating they are partnered with Brainchip it makes interesting reading. If you want to understand the possibilities a must read:


elee
Follow
Jul 26, 2020
·
4 min read
·
Listen

Save

Edge Impulse

Introduction
There are over 250 Billion microcontrollers in the world, but before we dive into how these small little chips permeate all aspects of our lives lets understand what they are. Microcontrollers are essentially small computer processing units that condense a control unit onto a tiny chip that’s around the size of a thumbnail.
Edge Impulse has created technology that allows Machine Learning Models to be deployed on microcontroller embedded devices. As all parts of our world — from industry, enterprise to home — migrate to an IoT universe, the applications for Edge Impulse become almost endless.
Company Overview
EdgeImpulse provides a tinyML(tiny machine learning) platform for developers to collect data, build machine learning models, and deploy and modify the model in real-time. These models can also be run locally so that they remain ultra low power control systems. Thus, these microcontrollers can collect large amounts of data, train, and optimize control operations without having to continuously update or stream to the cloud. Its pipeline can be applied to a huge range of microcontrollers allowing developers in virtually any industry to use Edge Impulse’s Platform.

Photo Creds to Johan Stokking
Market Analysis
The global machine learning market size is expected to reach USD 96.7 billion by 2025, according to a new report by Grand View Research. Combined with the existing 250 Billion microcontrollers that exist today and the 38.2 Billion expected to be deployed by 2023, a fast-approaching merge of these two technologies has huge market potential.
We even see clear interest from the likes of industry giants such as Google, Facebook, Tesla, Qualcomm, Samsung, and Sony, who have invested large amounts into tinyML R&D and regularly attend tinyML summits. Apple recently acquired TinyML startup — Xnor.ai — while AWS launched open-source AutoGluon — an ML pipeline with neural net search functionality.

Photo Credit to Technavio
Concern
— GTM: Edge Impulse’s technology caters perfectly to large scale corporate partners. Navigating and acquiring these partnerships will be a huge part of the company’s success. Currently, the Edge is partnered with a number of microcontroller players including the main industry player, Arm, but Edge Impulse may have trouble approaching new collaborators who do not have a deep background in tinyML.
— Stage of Technology: TinyML has yet to go mainstream. R&D is still in its early stage, and although we see extensive action from industry players there is still a long way to go. The success of this technology hinges on strong partnerships between microcontroller manufacturers, direct support, cloud services, and tool management systems. We definitely see these coming together, but the fruits of this labor will likely emerge in the long haul rather than in the next 1–2 years.
Other Players
SensiML — Acquired by QuickLogic, the company provides a SensiML Analytics Toolkit. The end-to-end development platform consolidates spanning data collection, labeling, algorithm and firmware auto-generation, and testing. Like Edge Impulse, SensiML’s platform is compatible with a huge array of microcontroller cores.
Cartesiam — Based in France, the startup has created the NanoEdge™ AI Studio which allows users to embed a machine learning static library on any ARM Microcontroller.
Reality.ai
Final Evaluation
Microcontrollers will become the backbone of smart factories, farms, stores, and buildings. Edge Impulse is strategically positioned to be the platform that will power this innovation. Unlike its competitors, it provides local processing, a key feature that will allow microcontrollers to learn independently. The company is a team of engineers with killer experience, and Edge Impulse’s current CEO was previously VP of Development at Arm. With all of this considered, the potential is clear. Even though we may have to wait a little while, I’m excited to stick around and see what they do next

 

[Jumpchooks]

Enough is enough and so back to Brainchip. I just found the following article about Edge Impulse from 2020 which given they are now out of the closet and proudly stating they are partnered with Brainchip it makes interesting reading. If you want to understand the possibilities a must read:


elee
Follow
Jul 26, 2020
·
4 min read
·
Listen

Save

Edge Impulse

Introduction
There are over 250 Billion microcontrollers in the world, but before we dive into how these small little chips permeate all aspects of our lives lets understand what they are. Microcontrollers are essentially small computer processing units that condense a control unit onto a tiny chip that’s around the size of a thumbnail.
Edge Impulse has created technology that allows Machine Learning Models to be deployed on microcontroller embedded devices. As all parts of our world — from industry, enterprise to home — migrate to an IoT universe, the applications for Edge Impulse become almost endless.
Company Overview
EdgeImpulse provides a tinyML(tiny machine learning) platform for developers to collect data, build machine learning models, and deploy and modify the model in real-time. These models can also be run locally so that they remain ultra low power control systems. Thus, these microcontrollers can collect large amounts of data, train, and optimize control operations without having to continuously update or stream to the cloud. Its pipeline can be applied to a huge range of microcontrollers allowing developers in virtually any industry to use Edge Impulse’s Platform.

Photo Creds to Johan Stokking
Market Analysis
The global machine learning market size is expected to reach USD 96.7 billion by 2025, according to a new report by Grand View Research. Combined with the existing 250 Billion microcontrollers that exist today and the 38.2 Billion expected to be deployed by 2023, a fast-approaching merge of these two technologies has huge market potential.
We even see clear interest from the likes of industry giants such as Google, Facebook, Tesla, Qualcomm, Samsung, and Sony, who have invested large amounts into tinyML R&D and regularly attend tinyML summits. Apple recently acquired TinyML startup — Xnor.ai — while AWS launched open-source AutoGluon — an ML pipeline with neural net search functionality.

Photo Credit to Technavio
Concern
— GTM: Edge Impulse’s technology caters perfectly to large scale corporate partners. Navigating and acquiring these partnerships will be a huge part of the company’s success. Currently, the Edge is partnered with a number of microcontroller players including the main industry player, Arm, but Edge Impulse may have trouble approaching new collaborators who do not have a deep background in tinyML.
— Stage of Technology: TinyML has yet to go mainstream. R&D is still in its early stage, and although we see extensive action from industry players there is still a long way to go. The success of this technology hinges on strong partnerships between microcontroller manufacturers, direct support, cloud services, and tool management systems. We definitely see these coming together, but the fruits of this labor will likely emerge in the long haul rather than in the next 1–2 years.
Other Players
SensiML — Acquired by QuickLogic, the company provides a SensiML Analytics Toolkit. The end-to-end development platform consolidates spanning data collection, labeling, algorithm and firmware auto-generation, and testing. Like Edge Impulse, SensiML’s platform is compatible with a huge array of microcontroller cores.
Cartesiam — Based in France, the startup has created the NanoEdge™ AI Studio which allows users to embed a machine learning static library on any ARM Microcontroller.
Reality.ai
Final Evaluation
Microcontrollers will become the backbone of smart factories, farms, stores, and buildings. Edge Impulse is strategically positioned to be the platform that will power this innovation. Unlike its competitors, it provides local processing, a key feature that will allow microcontrollers to learn independently. The company is a team of engineers with killer experience, and Edge Impulse’s current CEO was previously VP of Development at Arm. With all of this considered, the potential is clear. Even though we may have to wait a little while, I’m excited to stick around and see what they do next

One day, in the not to distant future, I would dearly love to shake hands and shoot the breeze with you. Happy Birthday

 

[Esq.111]

Is this old

IBM Researchers Showcase Their Non-Von Neumann AI Hardware Breakthrough in Neuromorphic Computing That Can Help Create Machines To Recognize Objects Just Like Humans

This research summary article is based on the paper. 'Phase-change memtransistive synapses for mixed-plasticity neural computations' Human brains are exceptionally good at remembering and learning new information. This brain capacity is credited to how the data is stored and processed by the...

www.marktechpost.com

Evening Rocket577,

Cheers for sharing this article. Interesting , and no , myself atleast have not seen this before.

One for Diogenese, if he would be so kind to translate into English.

Thankyou in advance Diogenese.

Regards,
Esq.

 

[Jumpchooks]

I think Blind Freddy is too busy dancing

I am more than happy to work towards the "Brain Chip Boogee". My foot tappin , rythym, hippee shake is warming to the concept. Akida Ballista has a certain Latin Dance undertone too.

 

[Fact Finder]

Is this old

IBM Researchers Showcase Their Non-Von Neumann AI Hardware Breakthrough in Neuromorphic Computing That Can Help Create Machines To Recognize Objects Just Like Humans

This research summary article is based on the paper. 'Phase-change memtransistive synapses for mixed-plasticity neural computations' Human brains are exceptionally good at remembering and learning new information. This brain capacity is credited to how the data is stored and processed by the...

www.marktechpost.com

Interesting but a long way to go:

“The team’s findings are more exploratory than demonstrations at the system level. While they intend to develop this method further, they also feel that the current proof-of-concept results already reveal substantial scientific interest in the broader areas of neuromorphic engineering — in computing and a better understanding of the brain through more faithful emulations. The devices are straightforward to construct and operate and are based on well-researched technology. The at-scale implementation, which involves tying together all the computing primitives and other hardware pieces, is the researchers’ main problem. The current findings demonstrate the value of mixed-plasticity neural computations in neuromorphic engineering. This not only makes, for example, visual cognition more human-like, but it also saves money on costly training methods”

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Jumpchooks]

View attachment 6465 View attachment 6466
one sec getting the info
Its a Flexifinger pulse crop lifter and the are all over the world one sec im just checking it.
It appears drone related.. one sec
APPEARS TO HAVE BEEN TAKEN BY ROADRUNNER DRONEWORKS
TAKEN...WITH PHANTON 4!!! or with the Inspire 1. but still checking
for maybe agrinova quebec... still checking..

wait!!! Visiovitis!!! has the picture on their home page!

I agree with FF, it looks like some sort of plug in wall vaporizing gadget

 

[Baisyet]

Here is the interview with Valeo's Clemnet Naovel

AutoVision News on LinkedIn: #lidar #avnews #autosens #innovation #automotive

AutoVision News Live at AutoSens Detroit 2022 Welcome Clément Nouvel, LiDAR Technical Director at Valeo Group, leading supplier in the field of safety and…

www.linkedin.com

 

[equanimous]

 

[MDhere]

I agree with FF, it looks like some sort of plug in wall vaporizing gadget

lol yes well we have moved past the vap we now into the gadgets.

 

[Jumpchooks]

Thats a CLAAS header. Made in Germany.

The applications on a Harvester are many... most modern harvester are guided by GPS and have been for years.. including autosteer...

Places i could see AI

1. Autonavigation, use every inch of comb to reduce fuel costs and soil compaction
2. Object identification - Threat assessments inside crops ie Stumps and livestock (Combines cost about $500k)
3. Moisture content measurement - Grain can only be harvested with the right moisture content for efficient "sifting"
4. Service optimisation, Vibration analysis - hot bearings are the most common cause of fires because wheat dust is literally explosive.
5. Machine Optimisation - there are two machines in one body in a harvester. One that is separating and sorting grain while the other moves across the ground. The speed of both can be altered to optimise the "yield".
6. Real time Yield analysis, analysis and mapping of soil conditions so that different rates of pasture improvement can be utilised. Literally placing fertiliser during sowing to compensate for missing nutrients in the soil for that particular part of the paddock.
7. Machine matching, perfectly timed unloading into chaser bins.. the location of field bins varies with Yield.

I'm sure there are other applications i have missed. I watched the John Deere autonomous tractor reveal last year with much interest.

(As a side note, Unfortunately for some Russians at the moment, stolen equipment from Ukraine is turning up useless once landed as it appears John Deere is disabling machines via satelitte.)

Please don't forget GPS controls on Earth Moving Machinery , Civil Construction, especially in remote areas. Mine sites especially

 

[Andy38]

I’m drinking the cheapest and this is the cheapest at $75 a case here in Weipa

Was up there fishing last week…interesting place. Albatross went alright though. Enjoy

 

[Baisyet]

Here is the interview with Valeo's Clemnet Naovel

AutoVision News on LinkedIn: #lidar #avnews #autosens #innovation #automotive

AutoVision News Live at AutoSens Detroit 2022 Welcome Clément Nouvel, LiDAR Technical Director at Valeo Group, leading supplier in the field of safety and…

www.linkedin.com

Here is another one from Cerence

[Video] Cerence Inc. on LinkedIn: Cerence Embedded and Multi-Seat Technologies in MBUX

The latest version of #MBUX -- Mercedes-Benz User Experience -- powered by Cerence, features a hybrid approach that strikes the perfect balance between…

www.linkedin.com

 

[HopalongPetrovski]

ok i checked flights from Brisbane. i can grab a flight and arrive after 4pm on mon 23rd and can leave by 5pm tues 24th. Anyone want to catch up Monday evening? and does anyone have a spare room in the city

I'm not getting in till latish on Monday night and am staying in a hotel up the road. The rooms were only a $100 a night when I booked if you want to give them a try. It's the Great Southern Hotel in Haymarket. Seems pretty reasonable to me for a basic room in the city.

 

[cosors]

I continue to try to find out who the industrial leader in automation might be. The picture of a maybe KUKA is not enough for me.
It's an exciting journey all the way for exapmle to University of Waterloo and Chris Eliasmith. They, in turn, are a development partner of FESTO (control and automation technology group; 20,000 employees) for picking robots.
https://www.festo.com/us/en/e/about...-projects/flairop-research-project-id_948361/
They are very well known here, maybe someone knows the blue pneumatic hoses. I have not met a single factory hall where a system from them has not been installed. But I don't want to go into that, my search has no result yet and I continue joing the dots.

I just want to share with you some exciting development I found:


https://www.festo.com/de/de/e/ueber...t-id_326923/?siteUid=fox_de&siteName=Festo+DE




If they haven't heard of Akida through the University of Waterloo, it's high time they did. So, I have to keep looking for our automation leader. I'm heading back to the other side of the world to Japan. Our partners and some automation leaders are based there.

...but the development/evolution of robotics is exciting, isn't it?

https://jwpm.com.au/industrial-marketing-blog/brn-brainchip-neuromorphic

 

[Diogenese]

Evening Rocket577,

Cheers for sharing this article. Interesting , and no , myself atleast have not seen this before.

One for Diogenese, if he would be so kind to translate into English.

Thankyou in advance Diogenese.

Regards,
Esq.

Hi Esq,

I have a file on this from a month ago.

Researchers from IBM’s Zurich lab have argued that these recognition techniques could be improved by enhancing AI hardware. The goal is to use the well-known phase-change memory (PCM) technology to develop a new type of artificial synapse. The researchers employ a PCM memtransistive synapse, which combines memristors, a nonvolatile electronic memory element, and transistors into a single low-power device. This shows a non-Von Neumann in-memory computing architecture that offers various powerful cognitive frameworks for ML applications, such as short-term spike-timing-dependent plasticity and probabilistic Hopfield Neural Networks.

In-memory computing has become popular in the last year or two - an attempt to get around the von Neumann bottleneck on the bus from the memory to the processor as the processor attempts to retrieve data from the memory. Akida is similar in that the memory is distributed amongst its 80 NPUs (Neuromorphic Processing Units).

A phase change material is one whose resistance can be changed by applying a large voltage in one direction, and reversed by applying the voltage in the opposite direction. The change in resistance can be detected by sensing the size of the current when a lower voltage is applied.

IBM has been playing around with phase change-materials for over a decade.

US2010223220A1 ELECTRONIC SYNAPSE

They are familiar with STDP:

WO2010133399A1 ELECTRONIC LEARNING SYNAPSE WITH SPIKE-TIMING DEPENDENT PLASTICITY USING PHASE CHANGE MEMORY

They also claim unsupervised learning:

US11164080B2 Unsupervised, supervised and reinforced learning via spiking computation

Even when IBM did summon up the courage to dip their toes in the digital neuron pond, they still kept a lifeline firmly attached to the analog neuron anchor:

WO2014080300A1 NEURAL NETWORK
"0016] The term digital neuron as used herein represents an framework configured to simulate a biological neuron. An digital neuron creates connections between processing elements that are roughly functionally equivalent to neurons of a biological brain. As such, a neuromorphic and synaptronic computation comprising digital neurons, according to embodiments of the invention, may include various electronic circuits that are modeled on biological neurons. Further, a neuromorphic and synaptronic computation comprising digital neurons, according to embodiments of the invention, may include various processing elements (including computer simulations) that are modeled on biological neurons.

Although certain illustrative embodiments of the invention are described herein using digital neurons comprising digital circuits, the present invention is not limited to digital circuits. A neuromorphic and synaptronic computation, according to embodiments of the invention, can be implemented as a neuromorphic and synaptronic framework comprising circuitry and additionally as a computer simulation. Indeed, embodiments of the invention can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment containing both hardware and software elements."

Like most of the NNs that I've seen coming from Switzerland, with one exception, they all use analog neurons/synapses. The analog neuron is a closer replica of the human neuron, but, in silicon, it is difficult to reproduce the neurons with sufficient accuracy, so that the threshold voltage for the neurons with "identical" inputs can differ between neurons. Analog neurons add the voltage or current of the spikes, but the amplitude of the voltage/current is not consistent between neurons because of manufacturing variations. Given that neurons can have hundreds of inputs, the errors accumulate to give inconsistent performance with analog neurons. With Akida's digital neurons this is not a problem because the digital bits are ON or OFF (1 or zero), and it was PvdM's recognition of this that has put us where we are today.