brainchip.com
Hi Bravo,Look at this! I think we could be onto a goer here! Or at the very least it's definitely something we should keep an eye on from a competition point of view IMO.
Background:
- Sonova acquired Sennheisser in 2021.
- VALEO and Sennheisser have been working together combining their technologies on for an immersive sound system in a demo car which was showcased at CES 2024.
Sonova's new hearing aids:
- Will be available 2025
- Incorporate real-time artificial intelligence
- Can learn from the user
- Can reduce and cancel unwanted noise
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Sonova to expand AI-powered hearing aids
To Arnd Kaldowski, CEO of Switzerland-based multinational hearing solutions provider Sonova, visiting China "at least three times a year" is important, quoting one of his former bosses to explain, "if you are not in China, you are not global".www.chinadaily.com.cn
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Maybe he is just being polite?How does it fit to Anil's reaction?
View attachment 70984
As I mentioned in a recent post [https://lnkd.in/eUkymQEq], we have more news on our research into neuromorphic computing. We have signed a Memorandum of Understanding with the University of… | Markus Schäfer | 24 comments
As I mentioned in a recent post [https://lnkd.in/eUkymQEq], we have more news on our research into neuromorphic computing. We have signed a Memorandum of Understanding with the University of Waterloo in Ontario, Canada to collaborate on research in this important field. The focus is on the...www.linkedin.com
Morning Chippers ,Look at this! I think we could be onto a goer here! Or at the very least it's definitely something we should keep an eye on from a competition point of view IMO.
Background:
- Sonova acquired Sennheisser in 2021.
- VALEO and Sennheisser have been working together combining their technologies on for an immersive sound system in a demo car which was showcased at CES 2024.
Sonova's new hearing aids:
- Will be available 2025
- Incorporate real-time artificial intelligence
- Can learn from the user
- Can reduce and cancel unwanted noise
View attachment 70997
View attachment 71002
Sonova to expand AI-powered hearing aids
To Arnd Kaldowski, CEO of Switzerland-based multinational hearing solutions provider Sonova, visiting China "at least three times a year" is important, quoting one of his former bosses to explain, "if you are not in China, you are not global".
View attachment 71004
View attachment 71003
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| Name | Audeara Limited |
| ACN | 604 368 443 |
| Chairman | David Trimboli |
| MD | Dr James Alexander Fielding |
| Address | 35 Brookes St Bowen Hills, QLD 4006 |
| Phone | -- |
| Fax | -- |
| Website | www.audeara.com |
| Dividend Reinvestment | No |
| DRP Status | None |
| Dividend Reinvestment Features-- | |
| Shareholder Discount | -- |
| Investor Relations Phone-- | |
| Investor Relations Name | Henry Jordan |
| Principal Registry | Computershare Investor Services Pty Ltd |
| Address | Yarra Falls, 452 Johnston St Abbotsford, VIC 3067 |
| Postal Address | GPO Box 3224 Melbourne,VIC,3001 |
| Phone | +61 3 9415 4000 |
| Fax | +61 3 9473 2500 |
| Investor Enquiries | +61 3 9415 4000 |
| Toll Free | 1300 787 272 |
| Website | Click to view |
| enquiry@computershare.com.au |
There are situations, where the question is mostly the answer!
You are in witness protection??
why
View attachment 70974 View attachment 70975 View attachment 70976#neuromorphic #adas #ad | Gerrit Ecke
Mercedes-Benz invests in #Neuromorphic Computing! The technology is key to overcome the issue of increasing compute requirements on a tight energy budget of Advanced Driver Assistance Systems #ADAS and Autonomous Driving #AD systems. Stay tuned! :)
View attachment 71033
Neuromorphic computing has considerable potential for us across many areas.
By mimicking the functionality of the human brain, it can make next-generation AI computation considerably faster and more energy efficient.
One current research project is NAOMI4Radar funded by the German Federal Ministry for Economic Affairs and Climate Action. As consortium leader, we are working with partners to assess how neuromorphic computing can be used to optimise the processing chain for radar data in automated driving systems.
Current Mercedes-Benz models use frontal radar to see 200 metres in front of them. For instance, our DRIVE PILOT system uses radar data as one of its many sources for enabling conditionally automated driving.
The aim of the NAOMI4Radar project is to demonstrate that neuromorphic computing can bring fundamental benefits to future generations of automated and autonomous driving systems.
But as I said, this is just one current research. More on that soon.
View attachment 71034
Loihi 2 - smoke screen or smoked
Over 12 months ago Mercedes served this up fingers crossed our time has arrived
View attachment 71035
My new “In the Loop” series kicks off with #Neuromorphic Computing – the clear winner of my poll a few weeks ago.
For those unfamiliar, this highly significant field of computing strives to emulate the multi-tasking of the human brain. Traditional microprocessors function sequentially. However, as the complexity and scale of calculations sores, this way of doing things is rapidly running out of road.
The idea is not new, but trying to “put a brain on a chip” is a mammoth task. To put it into figures: the human brain has 86-100 billion neurons operating on around 20 watts. Current neural chips from leading developers such as BrainChip and Intel Corporation contain around 1 million neurons and consume roughly 1 watt of power.
So, you see, despite impressive advances, there is still a very long way to go. Neuromorphic computing goes well beyond chip design and includes a specific kind of artificial neural network called #spikingneuralnetworks (SNN). They consume far less energy because the neurons are silent most of the time, only firing (or spiking) when needed for events.
Together with intense parallel execution on neuromorphic chips, the new processing principles require us to go beyond the application of existing #AI frameworks to neuromorphic chips. We have to fundamentally rethink the algorithms that ultimately enable future AI functions in our cars, gathering joint inspiration from machine learning, chip design and neuroscience. Our experts are working closely with our partners to examine their potential in new applications.
The thing is, even a tiny fraction of the thinking capacity of the human brain can go a long way in several fields that are extremely relevant to automotive applications. Examples include advanced driving assistance systems #ADAS as well as the on-board analysis of speech and video data, which can unlock major advances in how we communicate with our cars.
We already made some interesting findings here with our VISION EQXX, where we applied neuromorphic principles to the “Hey Mercedes” hot-word detection. That alone made it five to ten times more energy efficient than conventional voice control. As AI and machine learning take on an increasingly important role in the software-defined vehicle, the energy this consumes is likely to become a critical factor.
I’ll touch on our latest findings in an upcoming “In the Loop” and tell you my thoughts on where this is taking us.
In the meantime, for those of you interested in reading up on neuromorphic computing, check out the slider for my recommended sources. I’ve graded them to ensure there’s something for everyone, from absolute beginner to true geeks.
Correct ! As I stated in my post
Lohi ?View attachment 71033
Neuromorphic computing has considerable potential for us across many areas.
By mimicking the functionality of the human brain, it can make next-generation AI computation considerably faster and more energy efficient.
One current research project is NAOMI4Radar funded by the German Federal Ministry for Economic Affairs and Climate Action. As consortium leader, we are working with partners to assess how neuromorphic computing can be used to optimise the processing chain for radar data in automated driving systems.
Current Mercedes-Benz models use frontal radar to see 200 metres in front of them. For instance, our DRIVE PILOT system uses radar data as one of its many sources for enabling conditionally automated driving.
The aim of the NAOMI4Radar project is to demonstrate that neuromorphic computing can bring fundamental benefits to future generations of automated and autonomous driving systems.
But as I said, this is just one current research. More on that soon.
View attachment 71034
Loihi 2 - smoke screen or smoked
Over 12 months ago Mercedes served this up fingers crossed our time has arrived
View attachment 71035
My new “In the Loop” series kicks off with #Neuromorphic Computing – the clear winner of my poll a few weeks ago.
For those unfamiliar, this highly significant field of computing strives to emulate the multi-tasking of the human brain. Traditional microprocessors function sequentially. However, as the complexity and scale of calculations sores, this way of doing things is rapidly running out of road.
The idea is not new, but trying to “put a brain on a chip” is a mammoth task. To put it into figures: the human brain has 86-100 billion neurons operating on around 20 watts. Current neural chips from leading developers such as BrainChip and Intel Corporation contain around 1 million neurons and consume roughly 1 watt of power.
So, you see, despite impressive advances, there is still a very long way to go. Neuromorphic computing goes well beyond chip design and includes a specific kind of artificial neural network called #spikingneuralnetworks (SNN). They consume far less energy because the neurons are silent most of the time, only firing (or spiking) when needed for events.
Together with intense parallel execution on neuromorphic chips, the new processing principles require us to go beyond the application of existing #AI frameworks to neuromorphic chips. We have to fundamentally rethink the algorithms that ultimately enable future AI functions in our cars, gathering joint inspiration from machine learning, chip design and neuroscience. Our experts are working closely with our partners to examine their potential in new applications.
The thing is, even a tiny fraction of the thinking capacity of the human brain can go a long way in several fields that are extremely relevant to automotive applications. Examples include advanced driving assistance systems #ADAS as well as the on-board analysis of speech and video data, which can unlock major advances in how we communicate with our cars.
We already made some interesting findings here with our VISION EQXX, where we applied neuromorphic principles to the “Hey Mercedes” hot-word detection. That alone made it five to ten times more energy efficient than conventional voice control. As AI and machine learning take on an increasingly important role in the software-defined vehicle, the energy this consumes is likely to become a critical factor.
I’ll touch on our latest findings in an upcoming “In the Loop” and tell you my thoughts on where this is taking us.
In the meantime, for those of you interested in reading up on neuromorphic computing, check out the slider for my recommended sources. I’ve graded them to ensure there’s something for everyone, from absolute beginner to true geeks.
hmmmThat's a research chip that Loihi2 from Intel.
View attachment 71033
Neuromorphic computing has considerable potential for us across many areas.
By mimicking the functionality of the human brain, it can make next-generation AI computation considerably faster and more energy efficient.
One current research project is NAOMI4Radar funded by the German Federal Ministry for Economic Affairs and Climate Action. As consortium leader, we are working with partners to assess how neuromorphic computing can be used to optimise the processing chain for radar data in automated driving systems.
Current Mercedes-Benz models use frontal radar to see 200 metres in front of them. For instance, our DRIVE PILOT system uses radar data as one of its many sources for enabling conditionally automated driving.
The aim of the NAOMI4Radar project is to demonstrate that neuromorphic computing can bring fundamental benefits to future generations of automated and autonomous driving systems.
But as I said, this is just one current research. More on that soon.
View attachment 71034
Loihi 2 - smoke screen or smoked
Over 12 months ago Mercedes served this up fingers crossed our time has arrived
View attachment 71035
My new “In the Loop” series kicks off with #Neuromorphic Computing – the clear winner of my poll a few weeks ago.
For those unfamiliar, this highly significant field of computing strives to emulate the multi-tasking of the human brain. Traditional microprocessors function sequentially. However, as the complexity and scale of calculations sores, this way of doing things is rapidly running out of road.
The idea is not new, but trying to “put a brain on a chip” is a mammoth task. To put it into figures: the human brain has 86-100 billion neurons operating on around 20 watts. Current neural chips from leading developers such as BrainChip and Intel Corporation contain around 1 million neurons and consume roughly 1 watt of power.
So, you see, despite impressive advances, there is still a very long way to go. Neuromorphic computing goes well beyond chip design and includes a specific kind of artificial neural network called #spikingneuralnetworks (SNN). They consume far less energy because the neurons are silent most of the time, only firing (or spiking) when needed for events.
Together with intense parallel execution on neuromorphic chips, the new processing principles require us to go beyond the application of existing #AI frameworks to neuromorphic chips. We have to fundamentally rethink the algorithms that ultimately enable future AI functions in our cars, gathering joint inspiration from machine learning, chip design and neuroscience. Our experts are working closely with our partners to examine their potential in new applications.
The thing is, even a tiny fraction of the thinking capacity of the human brain can go a long way in several fields that are extremely relevant to automotive applications. Examples include advanced driving assistance systems #ADAS as well as the on-board analysis of speech and video data, which can unlock major advances in how we communicate with our cars.
We already made some interesting findings here with our VISION EQXX, where we applied neuromorphic principles to the “Hey Mercedes” hot-word detection. That alone made it five to ten times more energy efficient than conventional voice control. As AI and machine learning take on an increasingly important role in the software-defined vehicle, the energy this consumes is likely to become a critical factor.
I’ll touch on our latest findings in an upcoming “In the Loop” and tell you my thoughts on where this is taking us.
In the meantime, for those of you interested in reading up on neuromorphic computing, check out the slider for my recommended sources. I’ve graded them to ensure there’s something for everyone, from absolute beginner to true geeks.
