JK200SX
Regular
what? An automatic transmission for a bicycle?
BRN Discussion Ongoing
- Thread starter TechGirl
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JK200SX
Regular
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What's French for "deja vu"?
buena suerte :-)
BOB Bank of Brainchip
I believe Akida will be used for both Valeo’s LiDAR 3 and their driver monitoring system.
Can you please repeat the question, s'il vous plais?
supersonic001
Regular
When I see an RT like do we think / know, hey here’s another Co. we’re talking to in discussions with Eap et al ‘ ?
www.linkedin.com
Sang Won Lee on LinkedIn: #qeexo #apm2022 #tinyml #automl
What an honor! Big congrats to Qeexo team. #qeexo #APM2022 #tinyML #autoML
Fact Finder
Top 20
"Large scotch please" I think.
Bravo
If ARM was an arm, BRN would be its biceps💪!
Qeexo and BoschWhen I see an RT like do we think / know, hey here’s another Co. we’re talking to in discussions with Eap et al ‘ ?
Sang Won Lee on LinkedIn: #qeexo #apm2022 #tinyml #automl
What an honor! Big congrats to Qeexo team. #qeexo #APM2022 #tinyML #autoML
View attachment 19210
Qeexo, and Bosch Enable Developers to Quickly Build and Deploy Machine-Learning Algorithms to Bosch AI-Enabled Sensors
/PRNewswire-PRWeb/ -- Qeexo, developer of the Qeexo AutoML, and Bosch Sensortec GmbH, a technology leader in MEMS sensing solutions, today announced that...
It's like deja vu all over again!Not sure but it sounds familiar
If you don't have dreams, you can't have dreams come true!
GDJR69
Regular
A oui bit
Stable Genius
Regular
When I see an RT like do we think / know, hey here’s another Co. we’re talking to in discussions with Eap et al ‘ ?
Sang Won Lee on LinkedIn: #qeexo #apm2022 #tinyml #automl
What an honor! Big congrats to Qeexo team. #qeexo #APM2022 #tinyML #autoML
View attachment 19210
That is gold @supersonic001.
I had put a question down on paper earlier this morning but didn’t put it on the forum as I thought I was off base. This is essentially what I was trying to describe. Just replace Edge Impulse with Qeexo in my next lot of text. (I’ll apologise for the length of it but I’m not as eloquent as FF or as precise with my words).
https://qeexo.com/ml-platform/
I am spit-balling here as I am trying to understand the sales/tech environment with Tiny ML. Maybe what I am suggesting is already being undertaken by Renesas/Megachipsetc but I’m not seeing any evidence of that; hence this discussion.
I have preached having faith in the Management Team, and I do but I’m just wondering why we aren’t seeing Brainchip in solutions yet. Is it because we are mostly dealing with the large OEM’s?
Is it possible to address the smaller market’s as well with “Plug and play” devices?
I follow Edge Impulse on LinkedIn and there are numerous solutions shown daily and with 65,000 projects world-wide but I am yet to see a solution on a Brainchip device (that we know of). E.g. fire detection in forests, ML identifying pests in crops, safety sensor prediction in mines. If you go to Edge Impulse website and visit their solutions there are lots: Product (edgeimpulse.com)
The 65,000 solutions can also have an exponential effect, e.g. a safety device might be a “Project” but a company may have hundreds of the same device in service e.g. 100s of portable radiation sensors in Ukraine nuclear reactor regions could be handy right now. Or the fire detection sensor in forests would need to be deployed in numerous locations to work effectively.
I get that large OEM’s are creating their own solutions in cars etc and companies like Valeo, MB, have their own specialists. Obviously they will eventually have large regular volume sales which will be great; not complaining there. I understand why they were targeted with early access programs and glad they were!
As a non-techie it looks to me that we are missing out on the thousands of smaller “Solutions” that will eventually add up. Being used as the “Go to” devices will also bring about that uptake to become mainstream.
As a solution could Brainchip (through Mega-chips for example) provide “Plug and play” devices (or SOC) to make it easier for the business community to aquire AI to solve their problems. Have it all ready to go so all a consumer has to do it pick the relevant ready to go device with all the common hardware already combined, have a company like Edge impulse program it and then they deploy it in their environment.
For example: a Prophesee camera combined with Brainchipand a communication part, likely Bluetooth to send the relevant signal when the determined event occurs.
E.g. when person approaches door and is recognised as friend door unlocks and message is sent to owner’s mobile phone s/he has arrived.
The ready to go devices could include all five senses/sensors we know Akida is compatible with and also include gases, chemicals, temperature etc. Then, when a company wants a device for a purpose there is a something ready-made waiting for the fine tuning program to be implemented for that specific use case, e.g. as FF suggested; gas detection the burnt toast, turn off the toaster.
I get Brainchip doesn’t want to get bogged down in the daily device production for thousands of small customers. We don’t have the staff for that. But I thought if we had common ready to go hardware combination solutions to hand over to someone like Edge Impulse to finish off it could get us out there solving problems quicker.
I am only guessing here but could you even buy a combined hardware device at say JB Hi-Fi, (or order online via KOGANor similar) take it home, connect for example to edge impulses via an app, choose your detection types and inferences via icons or hyperlinks to download onto the device and then “Boom” you have your own AI sensor inference, smart device ready to go?
Does that make sense? Is it a logical solution to advance our deployment?
I won’t be offended if you pile on and tell me it’s a bad idea
I just want to see Brainchip part of Edge Impulses next 65,000 solutions and thought that was a way for it to occur!
Qeexo to the rescue. This is a Monty!
alwaysgreen
Top 20
QEEXO = Future builders OF OUR BANK ACCOUNTS!When I see an RT like do we think / know, hey here’s another Co. we’re talking to in discussions with Eap et al ‘ ?
Sang Won Lee on LinkedIn: #qeexo #apm2022 #tinyml #automl
What an honor! Big congrats to Qeexo team. #qeexo #APM2022 #tinyML #autoML
View attachment 19210
GingerRogers
Emerged
SenseCAP A1101 - LoRaWAN Vision AI Sensor, Open the Door to the TinyML world
SenseCAP A1101 - LoRaWAN Vision AI Sensor is a TinyML Edge AI enabled smart image sensor. It supports a variety of AI models such as image recognition, people counting, target detection, meter recoignition etc. It also supports training models with TensorFlow Lite.
www.seeedstudio.com
Can anyone tell me if this has AKIDA? Posted in Edge Impluses twitter. Cheers
JK200SX
Regular
That is gold @supersonic001.
I had put a question down on paper earlier this morning but didn’t put it on the forum as I thought I was off base. This is essentially what I was trying to describe. Just replace Edge Impulse with Qeexo in my next lot of text. (I’ll apologise for the length of it but I’m not as eloquent as FF or as precise with my words).
https://qeexo.com/ml-platform/
I am spit-balling here as I am trying to understand the sales/tech environment with Tiny ML. Maybe what I am suggesting is already being undertaken by Renesas/Megachipsetc but I’m not seeing any evidence of that; hence this discussion.
I have preached having faith in the Management Team, and I do but I’m just wondering why we aren’t seeing Brainchip in solutions yet. Is it because we are mostly dealing with the large OEM’s?
Is it possible to address the smaller market’s as well with “Plug and play” devices?
I follow Edge Impulse on LinkedIn and there are numerous solutions shown daily and with 65,000 projects world-wide but I am yet to see a solution on a Brainchip device (that we know of). E.g. fire detection in forests, ML identifying pests in crops, safety sensor prediction in mines. If you go to Edge Impulse website and visit their solutions there are lots: Product (edgeimpulse.com)
The 65,000 solutions can also have an exponential effect, e.g. a safety device might be a “Project” but a company may have hundreds of the same device in service e.g. 100s of portable radiation sensors in Ukraine nuclear reactor regions could be handy right now. Or the fire detection sensor in forests would need to be deployed in numerous locations to work effectively.
I get that large OEM’s are creating their own solutions in cars etc and companies like Valeo, MB, have their own specialists. Obviously they will eventually have large regular volume sales which will be great; not complaining there. I understand why they were targeted with early access programs and glad they were!
As a non-techie it looks to me that we are missing out on the thousands of smaller “Solutions” that will eventually add up. Being used as the “Go to” devices will also bring about that uptake to become mainstream.
As a solution could Brainchip (through Mega-chips for example) provide “Plug and play” devices (or SOC) to make it easier for the business community to aquire AI to solve their problems. Have it all ready to go so all a consumer has to do it pick the relevant ready to go device with all the common hardware already combined, have a company like Edge impulse program it and then they deploy it in their environment.
For example: a Prophesee camera combined with Brainchipand a communication part, likely Bluetooth to send the relevant signal when the determined event occurs.
E.g. when person approaches door and is recognised as friend door unlocks and message is sent to owner’s mobile phone s/he has arrived.
The ready to go devices could include all five senses/sensors we know Akida is compatible with and also include gases, chemicals, temperature etc. Then, when a company wants a device for a purpose there is a something ready-made waiting for the fine tuning program to be implemented for that specific use case, e.g. as FF suggested; gas detection the burnt toast, turn off the toaster.
I get Brainchip doesn’t want to get bogged down in the daily device production for thousands of small customers. We don’t have the staff for that. But I thought if we had common ready to go hardware combination solutions to hand over to someone like Edge Impulse to finish off it could get us out there solving problems quicker.
I am only guessing here but could you even buy a combined hardware device at say JB Hi-Fi, (or order online via KOGANor similar) take it home, connect for example to edge impulses via an app, choose your detection types and inferences via icons or hyperlinks to download onto the device and then “Boom” you have your own AI sensor inference, smart device ready to go?
Does that make sense? Is it a logical solution to advance our deployment?
I won’t be offended if you pile on and tell me it’s a bad idea
I just want to see Brainchip part of Edge Impulses next 65,000 solutions and thought that was a way for it to occur!
Qeexo to the rescue. This is a Monty!
Perhaps brainchip should have a page (similar to that of Edge Impulse) where inventors and novices can post their projects that include Akida?
JK200SX
Regular
SenseCAP A1101 - LoRaWAN Vision AI Sensor, Open the Door to the TinyML world
SenseCAP A1101 - LoRaWAN Vision AI Sensor is a TinyML Edge AI enabled smart image sensor. It supports a variety of AI models such as image recognition, people counting, target detection, meter recoignition etc. It also supports training models with TensorFlow Lite.
Can anyone tell me if this has AKIDA? Posted in Edge Impluses twitter. Cheers
Lets see what happens?
Stable Genius
Regular
That is gold @supersonic001.
I had put a question down on paper earlier this morning but didn’t put it on the forum as I thought I was off base. This is essentially what I was trying to describe. Just replace Edge Impulse with Qeexo in my next lot of text. (I’ll apologise for the length of it but I’m not as eloquent as FF or as precise with my words).
https://qeexo.com/ml-platform/
I am spit-balling here as I am trying to understand the sales/tech environment with Tiny ML. Maybe what I am suggesting is already being undertaken by Renesas/Megachipsetc but I’m not seeing any evidence of that; hence this discussion.
I have preached having faith in the Management Team, and I do but I’m just wondering why we aren’t seeing Brainchip in solutions yet. Is it because we are mostly dealing with the large OEM’s?
Is it possible to address the smaller market’s as well with “Plug and play” devices?
I follow Edge Impulse on LinkedIn and there are numerous solutions shown daily and with 65,000 projects world-wide but I am yet to see a solution on a Brainchip device (that we know of). E.g. fire detection in forests, ML identifying pests in crops, safety sensor prediction in mines. If you go to Edge Impulse website and visit their solutions there are lots: Product (edgeimpulse.com)
The 65,000 solutions can also have an exponential effect, e.g. a safety device might be a “Project” but a company may have hundreds of the same device in service e.g. 100s of portable radiation sensors in Ukraine nuclear reactor regions could be handy right now. Or the fire detection sensor in forests would need to be deployed in numerous locations to work effectively.
I get that large OEM’s are creating their own solutions in cars etc and companies like Valeo, MB, have their own specialists. Obviously they will eventually have large regular volume sales which will be great; not complaining there. I understand why they were targeted with early access programs and glad they were!
As a non-techie it looks to me that we are missing out on the thousands of smaller “Solutions” that will eventually add up. Being used as the “Go to” devices will also bring about that uptake to become mainstream.
As a solution could Brainchip (through Mega-chips for example) provide “Plug and play” devices (or SOC) to make it easier for the business community to aquire AI to solve their problems. Have it all ready to go so all a consumer has to do it pick the relevant ready to go device with all the common hardware already combined, have a company like Edge impulse program it and then they deploy it in their environment.
For example: a Prophesee camera combined with Brainchipand a communication part, likely Bluetooth to send the relevant signal when the determined event occurs.
E.g. when person approaches door and is recognised as friend door unlocks and message is sent to owner’s mobile phone s/he has arrived.
The ready to go devices could include all five senses/sensors we know Akida is compatible with and also include gases, chemicals, temperature etc. Then, when a company wants a device for a purpose there is a something ready-made waiting for the fine tuning program to be implemented for that specific use case, e.g. as FF suggested; gas detection the burnt toast, turn off the toaster.
I get Brainchip doesn’t want to get bogged down in the daily device production for thousands of small customers. We don’t have the staff for that. But I thought if we had common ready to go hardware combination solutions to hand over to someone like Edge Impulse to finish off it could get us out there solving problems quicker.
I am only guessing here but could you even buy a combined hardware device at say JB Hi-Fi, (or order online via KOGANor similar) take it home, connect for example to edge impulses via an app, choose your detection types and inferences via icons or hyperlinks to download onto the device and then “Boom” you have your own AI sensor inference, smart device ready to go?
Does that make sense? Is it a logical solution to advance our deployment?
I won’t be offended if you pile on and tell me it’s a bad idea
I just want to see Brainchip part of Edge Impulses next 65,000 solutions and thought that was a way for it to occur!
Qeexo to the rescue. This is a Monty!
To put into a pictorial of the steps I was trying to describe:
The only problem at the moment is there is no SNN: Hopefully that will change!
AusEire
Founding Member. It's ok to say No to Dot Joining
SenseCAP A1101 - LoRaWAN Vision AI Sensor, Open the Door to the TinyML world
SenseCAP A1101 - LoRaWAN Vision AI Sensor is a TinyML Edge AI enabled smart image sensor. It supports a variety of AI models such as image recognition, people counting, target detection, meter recoignition etc. It also supports training models with TensorFlow Lite.
Can anyone tell me if this has AKIDA? Posted in Edge Impluses twitter. Cheers
SenseCAP A1101 - LoRaWAN Vision AI Sensor is an image recognition AI sensor designed for developers. It will be your choice to open the door to the new TinyML world if you are:
- a machine learning developer who wants to develop edge AI and vision recognition applications and is finding a low-cost and reliable hardware platform to get started; or
- a software/hardware engineer who is keen to learn about TinyML, the model training process, and the algorism
"algorism" - isn't that an inconvenient truth?
Doesn't do 1-shot learning:
https://wiki.seeedstudio.com/Train-Deploy-AI-Model-A1101/
1. Train your own AI model with a public dataset¶
..."After you have enough images captured, click on the terminal window and press the following key combinations to stop the capturing process"
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