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Seems to be some customer traffic in California. Nice to see the required languages.
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This will be very boring it’s obvious they are only going to talk about AKIDA technology.An workshop coming up with Heinrich Gotzig from Valeo chairing
NeuroEng 2022 Workshop | EBCCSP'2022 Conference
NeuroEng Workshop First International Workshop on Event Sensing and Neuromorphic Engineering NeuroEng 2022 Technical focus The aim of the International Workshop on Event Sensors and Neuromorphic Engineering is to provide a platform for the research communities to exchange new ideas and research...ebccsp2022.org
Topics of interest include, but are not limited to:
- event-based sensing,
- event-based neuromorphic engineering,
- event-driven
- vision, event-driven audio,
- event-based olfactory systems,
- event-driven robot skin,
- event-based information processing,
- event-based motion detection and integration,
- spiking neural networks,
- edge computing,
- address-event representation,
- visual recognition,
- depth estimation,
- real-time algorithms,
- motion estimation,
- object tracking,
- sensor fusion.
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AKIDA BALLISTA
thelittleshort
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Expansion goes on.Seems to be some customer traffic in California. Nice to see the required languages.
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That is one full-on job!
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Interesting new article by Prof. Benosman, co-founder of Prophesee. As Brainchip isn't mentioned every word cries for Akida:
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Well it is a pity about all the other requirements because I recon I could fulfil this one in spades:
“A fun, positive, upbeat person who can get excited about the world of artificial intelligence, even if you have no idea how it works!”
Probably a few others could have applied too.
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AKIDA BALLISTA
I am very disappointed because I wanted to apply for the job. I read the criteria and although I don't meet most of the criteria there is one that I know I can match as good as anyone:
+ A fun, positive, upbeat person who can get excited about the world of artificial intelligence, even if you have no idea how it works!
We must have typed that at that same time. LolWell it is a pity about all the other requirements because I recon I could fulfil this one in spades:
“A fun, positive, upbeat person who can get excited about the world of artificial intelligence, even if you have no idea how it works!”
Probably a few others could have applied too.
My opinion only DYOR
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AKIDA BALLISTA
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Cool
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...
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A little while back i put up a demographic impact of the published article "A review of Current Neuromorphic Approaches for Vision, Auditory and Olfactory Sensors" Well i had a little bit of time to check it and well Mumbai was alot of hits (interesting Tata Office is in Mumbai) and Palo Alto, California got some (Home of Tesla, before move to Texas) Just saying....... 
co-incidence..maybe...
co-incidence..maybe... Attachments
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I think this statement needs a little more scrutiny.Has anyone heard of Imec? The technology sounds very similar to ours????
https://www.imec-int.com/en
/Imec Builds World’s First Spiking Neural Network-Based Chip for Radar Signal Processing
Press release
Imec Builds World’s First Spiking Neural Network-Based Chip for Radar Signal Processing
Flagship use-case includes the creation of a smart, low-power anti-collision radar system for drones that identifies approaching objects in a matter of milliseconds
LEUVEN (Belgium), April 28, 2020 — Imec, a world-leading research and innovation hub in nanoelectronics and digital technologies, today presents the world’s first chip that processes radar signals using a spiking recurrent neural network. Mimicking the way groups of biological neurons operate to recognize temporal patterns, imec’s chip consumes 100 times less power than traditional implementations while featuring a tenfold reduction in latency – enabling almost instantaneous decision-making. For example, micro-Doppler radar signatures can be classified using only 30 μW of power. While the chip’s architecture and algorithms can easily be tuned to process a variety of sensor data (including electrocardiogram, speech, sonar, radar and lidar streams), its first use-case will encompass the creation of a low-power, highly intelligent anti-collision radar system for drones that can react much more effectively to approaching objects.
Artificial neural networks (ANNs) have already proven their worth in a wide range of application domains. They are a key ingredient, for instance, of the radar-based anti-collision systems commonly used in the automotive industry. But ANNs come with their share of limitations. For one, they consume too much power to be integrated into increasingly constrained (sensor) devices. Additionally, ANNs’ underlying architecture and data formatting requires data to undertake a time-consuming journey from the sensor device to the AI inference algorithm before a decision can be made. Enter spiking neural networks (SNNs).
“Today, we present the world’s first chip that processes radar signals using a recurrent spiking neural network,” says Ilja Ocket, program manager of neuromorphic sensing at imec.
Imec’s novel chip was initially designed to support electrocardiogram (ECG) and speech processing in power-constrained devices. Yet thanks to its generic architecture that features a completely new digital hardware design, it can also easily be reconfigured to process a variety of other sensory inputs like sonar, radar and lidar data. Contrary to analog SNN implementations, imec’s event-driven digital design makes the chip behave exactly and repeatedly as predicted by the neural network simulation tools.
Use-case: a smarter, low-power anti-collision system for drones (and cars)
The drone industry – even more than the automotive sector – works with constrained devices (e.g. limited battery capacity) that need to react quickly to changes in their environment in order to appropriately react to approaching obstacles.
“Hence, a flagship use-case for our new chip includes the creation of a low-latency, low-power anti-collision system for drones. Doing its processing close to the radar sensor, our chip should enable the radar sensing system to distinguish much more quickly – and accurately – between approaching objects. In turn, this will allow drones to nearly instantaneously react to potentially dangerous situations,” says Ilja Ocket. “One scenario we are currently exploring features autonomous drones that depend on their on-board camera and radar sensor systems for in-warehouse navigation, keeping a safe distance from walls and shelves while performing complex tasks. This technology could be used in plenty of other use-cases as well – from robotics scenarios to the deployment of automatic guided vehicles (AGVs) and even health monitoring.”
“This chip meets the industry’s demand for extremely low-power neural networks that truly learn from data and enable personalized AI. For its creation, we rallied experts from various disciplines within imec – from the development of training algorithms and spiking neural network architectures that take neuroscience as a basis, to biomedical and radar signal processing and ultra-low power digital chip design. That is where imec really makes a difference,” Kathleen Philips, program director of IoT cognitive sensing at imec, concludes.
Imec Builds World’s First Spiking Neural Network-Based Chip for Radar Signal Processing | imec
Flagship use-case includes the creation of a smart, low-power anti-collision radar system for drones that identifies approaching objects in a matter of millisecondswww.imec-int.com
Imec’s novel chip was initially designed to support electrocardiogram (ECG) and speech processing in power-constrained devices. Yet thanks to its generic architecture that features a completely new digital hardware design, it can also easily be reconfigured to process a variety of other sensory inputs like sonar, radar and lidar data. Contrary to analog SNN implementations, imec’s event-driven digital design makes the chip behave exactly and repeatedly as predicted by the neural network simulation tools.
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Great pickup WH. Probably too soon for @Diogenese to access the new patent???
It is very suspicious that they have been able to engineer such a dramatic change without external assistance.
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AKIDA BALLISTA
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I had a quick look at this website and there is a lot of material there. I think they’re saying they’ve got their own SNN chip but not sure of the quality of it compared to Brainchip. I’m still wading through it so I can’t comment on it until I’ve read it properly and a bit tired to concentrate on it atm.
https://www.imec-int.com/en/reading-room?tags[]=Artificial+intelligence
Surprised Unknown Soldier or similar hadn’t thrown this in our face a year or so ago as competition as it looks to be around for a while so I’m guessing (and have a feeling/recollection) it has been looked at already:
Building a low-latency, low-power & accurate SNN chip | imec
Imec’s spiking neural network (SNN) chip combines low latency and energy consumption with high accuracy
Regardless I’m still confident of where we are heading. I’m sure if there was another commercial neuromorphic chip out there since 2020 it would have been brought to our attention a lot earlier!
Cheers.
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