www.nviso.ai
This reminds me of the story of Archer Materials (AXE). They have figured out a way of doing quantum computing at room temperature and like BRN Mr Shainline may not be aware of this?If you want to stop worrying about competitors and whether Brainchip is moving fast enough I suggest reading the following article:
Toward Optoelectronic Chips That Mimic the Human Brain
Mon, 18 Apr 2022 19:00:01 +0000
The human brain, which is made up of some 86 billion neuronsconnected in a neural network, can perform remarkable feats of computing. Yet it consumes just a dozen or so watts. How does it do it?
IEEE Spectrum recently spoke with Jeffrey Shainline, a physicist at the National Institute of Standards and Technology in Boulder, Colo., whose work may shine some light on this question. Shainline is pursuing an approach to computing that can power advanced forms of artificial intelligence—so-called spiking neural networks, which more closely mimic the way the brain works compared with the kind of artificial neural networks that are widely deployed now. Today, the dominant paradigm uses software running on digital computers to create artificial neural networks that have multiple layers of neurons. These “deep” artificial neural networks have proved immensely successful, but they require enormous computing resources and energy to run. And those energy requirements are growing quickly: in particular, the calculations involved in training deep neural networks are becoming unsustainable.
Researchers have long been tantalized by the prospect of creating artificial neural networks that more closely reflect what goes on in networks of biological neurons, where, as one neuron accepts signals from multiple other neurons, it may reach a threshold level of activation that causes it to “fire,” meaning that it produces an output signal spike that is sent to other neurons, perhaps inducing some of them to fire as well.
“Compared with semiconductors, you can fit many more neurons and synapses on a wafer because you can stack in the third dimension. You can have maybe 10 layers, and that’s a big advantage.”
—Jeffrey Shainline, NIST
A few companies have produced chips for implementing electronic spiking neural networks. Shainline’s research focuses on using superconducting optoelectronic elements in such networks. His work has recently advanced from investigating theoretical possibilities to performing hardware experiments. He tells Spectrumabout these latest developments in his lab.
I’ve heard for years about neuromorphic processing chips from IBM and elsewhere, but I don’t get a sense that they have gained traction in the practical world. Am I wrong?
Jeffrey Shainline: Good question: Spiking neural networks—what are they good for?
IBM’s True North chip from 2014 made a big splash because it was new and different and exciting. More recently, Intel has been doing great things with its Loihi chip. Intel now has its second generation of that. But whether these chips will solve real problems remains a big question.
We know that biological brains can do things that are unmatched by digital computers. Yet these spiking neuromorphic chips don’t immediately knock our socks off. Why not? I don’t think that’s an easy question to answer.
One thing that I’ll point out is that one of these chips doesn’t have 10 billion neurons (roughly the number of neurons in a person’s brain). Even a fruit-fly brain has about 150,000 neurons. Intel’s most recent Loihi chip doesn’t even have that.
Knowing that they are struggling with what they’re going to do with this chip, the folks at Intel have done something clever: They’re giving academics and startups cheap access to their chip—for free in a lot of cases. They’re crowdsourcing creativity in hopes that somebody will find a killer app.
What would you guess the first killer app will be?
Shainline: Maybe a smart speaker, a speaker needs to be always on waiting for you to say some keyword or phrase. That normally requires a lot of power. But studies have shown that a very simple spiking neural algorithm running in one simple chip can do this while using almost no power.
Tell me about the optoelectronic devices that you and your NIST colleagues are working on and how they might improve spiking neural networks.
Shainline: First, you need to understand that light is going to be the best way that you can communicate between neurons in a spiking neural system. That’s because nothing can go faster than light. So using light for communication will allow you to have the biggest spiking neural network possible.
But it’s not enough to just send signals fast. You also need to do it in an energy-efficient manner. So once you’ve chosen to send signals in the form of light, the best energy efficiency you can achieve is if you send just one photon from a neuron to each of its synaptic connections. You can’t make an amount of light any less.
And the superconducting detectorswe are investigating are the best there is when it comes to detecting single photons of light—best in terms of how much energy they dissipate and how fast they can operate.
You could also build a spiking neural network that uses room-temperature semiconductors to send and receive optical signals, though. And right now, it isn’t obvious which strategy is best. But because I’m biased, let me share some reasons to pursue the superconducting approach.
Admittedly, using superconducting elements imposes a lot of overhead—you have to build everything in a cryogenic environment so that your devices remain cold enough to superconduct. But once you’ve done that, you can easily add another crucial element: something called a Josephson junction.
Josephson junctions are the key building block for superconducting computing hardware, whether they’re for superconducting qubits in a quantum computer, superconducting digital logic gates, or superconducting neurons.
Once you’ve decided to use light for communication and superconducting single-photon detectors to sense that light, you will have to build your computer in a cryogenic environment. So without further overhead, you now have Josephson junctions at your disposal.
And this brings a benefit that’s not obvious: It turns out that it is easier to integrate Josephson junctions in three dimensions than it is to integrate [MOSFETs—metal oxide semiconductor field-effect transistors] in three dimensions. That’s because with semiconductors, you fabricate MOSFETs on the lower plane of a silicon wafer. Then you put all your wiring layers up on top. And it becomes essentially impossible to put another layer of MOSFETs on top of that with standard processing techniques.
In contrast, it’s not hard to fabricate Josephson junctions on multiple planes. Two different research groups have demonstrated that. The same is true for the single-photon detectors that we’ve been talking about.
This is a key benefit when you consider what will be needed to allow these networks to scale into something resembling a brain in complexity. Compared with semiconductors, you can fit many more neurons and synapses on a wafer because you can stack in the third dimension. You can have maybe 10 layers, and that’s a big advantage.
The theoretical implications of this approach to computing are impressive. But what kind of hardware have you and your colleagues actually built?
Shainline: One of our most exciting recent results is the demonstration of the integration of superconducting single-photon detectors with Josephson junctions. What that allows us to do is receive single photons of light and use that to switch a Josephson junction and produce an electrical signal and then integrate the signals from many photon pulses.
We’ve recently demonstrated that technology here in our lab. We have also fabricated on a chip light sources that work at low temperatures. And we’ve spent a lot of time on the waveguides needed to carry light signals around on a chip, too.
I mentioned the 3D-integration—the stacking—that’s possible with this kind of computing technology. But if you’re going to have each neuron communicate to a few thousand other neurons, you would also need some way for optical signals to transition without loss from a waveguide in one layer to a waveguide in another layer. We’ve demonstrated that with as many as three stacked planes of these waveguides and believe we could extend that to 10 or so layers.
When you say “integration,” do you just mean that you’ve wired these components together, or do you have everything working on one chip?
Shainline: We have indeed combined superconducting single-photon detectors with Josephson junctions on one chip. That chip gets mounted on a little printed circuit board that we put inside a cryostat to keep it cold enough to remain superconducting. And we use fiber optics for communication from room temperature to low temperature.
Why are you so keen to pursue this approach, and why aren’t others doing the same?
Shainline: There are some pretty strong theoretical arguments as to why this approach to neuromorphic computing could be quite a game changer. But it requires interdisciplinary thinking and collaboration, and right now, we’re really the only group doing specifically this.
I would love it if more people got into the mix. My goal as a researcher is not to be the one that does all this stuff first. I'd be very pleased if researchers from different backgrounds contributed to the development of this technology”
My opinion only DYOR
FF
AKIDA BALLISTA
SMART WEALTH how appropriate is that beneficial use for all visionary Brainchip investors. I mostly hate marketing spin but I must say this is one for a T Shirt.involved in Smart Health, Smart Mobility, Smart Wealth
Human Behaviour Artificial Intelligence | NVISO
NVISO is a global leader in human behaviour artificial intelligence (AI) software serving manufacturers of user-centric products and services worldwide.www.nviso.ai
This is one to read closely as it is asking shareholders to approve a brand new Constitution not just amend the old one.AGM notice listed on the ASX. Details how to log in remotely and vote etc.
98 pages of info to devour.
www.zf.com
www.seeingmachines.com
www.nviso.ai
nviso.ai
www.nviso.ai
Such a shame this isn't (or can't be) announced on the ASX.Nviso collaboration is a good one.
Plenty of doors to unlock thru this partnership.
Definitely a player
Nviso + Cetera Financial
Cetera launches Decipher at Connect19 National Conference in Colorado, USA - NVISO
Cetera has successfully promoted Decipher during their 2019 Annual Connect19 National Conference hosted from July 22nd to July 25th 2019 at the Colorado Convention Center in Denver. Connect19 boasts more than 4,000 attendees and it is one of the industry’s largest and most prominent gatherings...
Nviso + Seeing Machines
NVISO and Seeing Machines to Bring Human Behaviour AI to Automotive World
NVISO and Seeing Machines to demonstrate Advanced Driver Monitoring System for detecting Driver Emotion at AI Expo 2020 in Tokyo, Japan
Nviso + Panasonic
NVISO and PANASONIC sign license agreement to embed Human Behaviour AI in companion robots - NVISO
NVISO signs a multi-year license agreement with PANASONIC for deployment of its Human Behavioural Analytics AI software solution in the PANASONIC Companion Robot NICOBO Lausanne, Switzerland – March 15, 2022 – nViso SA (NVISO), the leading Human Behavioural Analytics AI company, is pleased to...
Nviso + Paincheck
PainChek and NVISO are Redefining Pain Assessment - NVISO
NVISO’s client, PainChek™, uses video analysis, powered by NVISO’s AI-based visual intelligence technology, to detect facial expressions and characteristics most consistent with acute and chronic pain. A new video introducing the technology behind their present and future applications has been...
Nviso + Tobii DMS
Nviso + BNZ ( Bank of New Zealand )
BNZ uses facial recognition software to uncover New Zealanders' financial feelings - Retail Banker International
Bank of New Zealand (BNZ) has adopted facial recognition software for its website to help customers understand how they feel about their money.www.retailbankerinternational.com
Nviso + F&P Robotics
Investor Fact Sheet | NVISO
NVISO are leading experts in artificial intelligence and deep learning to accurately detect and predict human behaviors using visual intelligence.www.ir.nviso.ai
Hi @Dhm
A great resource generously shared. Many thanks @Taproot it has already been copied and sent off to my network. LOL FFNviso collaboration is a good one.
Plenty of doors to unlock thru this partnership.
Definitely a player
Nviso + Cetera Financial
Cetera launches Decipher at Connect19 National Conference in Colorado, USA - NVISO
Cetera has successfully promoted Decipher during their 2019 Annual Connect19 National Conference hosted from July 22nd to July 25th 2019 at the Colorado Convention Center in Denver. Connect19 boasts more than 4,000 attendees and it is one of the industry’s largest and most prominent gatherings...
Nviso + Seeing Machines
NVISO and Seeing Machines to Bring Human Behaviour AI to Automotive World
NVISO and Seeing Machines to demonstrate Advanced Driver Monitoring System for detecting Driver Emotion at AI Expo 2020 in Tokyo, Japan
Nviso + Panasonic
NVISO and PANASONIC sign license agreement to embed Human Behaviour AI in companion robots - NVISO
NVISO signs a multi-year license agreement with PANASONIC for deployment of its Human Behavioural Analytics AI software solution in the PANASONIC Companion Robot NICOBO Lausanne, Switzerland – March 15, 2022 – nViso SA (NVISO), the leading Human Behavioural Analytics AI company, is pleased to...
Nviso + Paincheck
PainChek and NVISO are Redefining Pain Assessment - NVISO
NVISO’s client, PainChek™, uses video analysis, powered by NVISO’s AI-based visual intelligence technology, to detect facial expressions and characteristics most consistent with acute and chronic pain. A new video introducing the technology behind their present and future applications has been...
Nviso + Tobii DMS
Nviso + BNZ ( Bank of New Zealand )
BNZ uses facial recognition software to uncover New Zealanders' financial feelings - Retail Banker International
Bank of New Zealand (BNZ) has adopted facial recognition software for its website to help customers understand how they feel about their money.
Nviso + F&P Robotics
Investor Fact Sheet | NVISO
NVISO are leading experts in artificial intelligence and deep learning to accurately detect and predict human behaviors using visual intelligence.
Loved the quote "we want a Mercedes to constantly learn..."It says there are 73 people waiting to watch this link. I wonder how many of them are us?
Two companies that I've been following have been ZF and Seeing machines, and now I've discovered they are customers of NVISO.
ZF:
I remember seeing this post from a colleague on Linkedin a few months ago:
View attachment 4590
and upon searching the ZF ProAI Supercomputer, I found:
ZF ProAI Supercomputer: The Source of Vehicle Intelligence - ZF
The intelligence of future vehicles will be controlled by a few extremely powerful central computers like the new ZF ProAI. It is the most flexible, scalable and powerful automotive-grade supercomputer on the market.ZF ProAI: The Source of Vehicle Intelligence
The intelligence of future vehicles will be controlled by a few extremely powerful central computers like the new ZF ProAI. It is the most flexible, scalable and powerful automotive-grade supercomputer on the market.
Modern vehicles feature increasingly more software functions. When software combines the intelligence of sensor information with the control of smart actuators, new powerful functions like driver assist systems emerge, which provide more comfort, more safety, or even more range when driving electrically. This is only possible with smart software algorithms. In traditional vehicle architectures, the bits and bytes act mainly in decentralized electronic control units (ECUs). In new and future vehicle platforms, the electric and electronic architecture (E/E architecture) will change dramatically. The computing power and the main software functions will be bundled in a few domain or zone controllers.
At Auto Shanghai 2021, the ZF Group presented the next generation of its automotive-grade supercomputer ZF ProAI for the first time. This central computer perfectly meets the manufacturers' requirements for the software-defined vehicles and their new E/E-architectures. It can serve as domain, zone or central controller.
“The ZF ProAI is currently the most flexible, scalable, and powerful automotive-grade supercomputer in the world,” said Oliver Briemle, Head of L4 Feature Development, Domain Control and V2X at ZF.
It is suitable for any vehicle type and for all levels of automated and autonomous driving: from Level 2 to Level 5.
Standardization meets scalability
Customized high-performance solutions for vehicle intelligence, suitable to any vehicle platform, but based on a single product – that’s the new ZF ProAI.
“When developing the new ZF ProAI, we paid particular attention to two things: standardization and scalability. Because this simplifies the choice immensely when selecting ZF ProAI as the central computer for a vehicle: No matter what the application needs are – ZF has the ideal solution,” said Briemle.
Standardization and flexibility are also key for the processor and the connectors: The supercomputer’s modular set-up means it can be equipped with System-on-Chip (SoC) variants from different manufacturers – depending on the planned application and the computing power required. The connectors are compatible with all common plugs on the market. Also, ZF has relied on the highest level of flexibility regarding software. In addition to in-house solutions, the supercomputer also runs programs and operating systems of the OEMs or third-party developers. Depending on the desired performance, three cooling options are available: passive cooling, air cooling and liquid cooling. Nevertheless, the installation dimensions remain the same: The new ZF ProAI has a uniform and compact housing size of only 240 x 138 x 49 millimeters. This is significantly smaller than its previous models and thus gives more freedom in the choice of installation options in the vehicle.
“When developing the new ZF ProAI, we paid particular attention to two things: standardization and scalability.”
Oliver Briemle, Head of L4 Feature Development, Domain Control and V2X at ZF
More performance, less power consumption
The new ZF ProAI also comes with more performance than ever before. Depending on the desired application from Level 2 to Level 5 and the corresponding computing power required, ZF ProAI can execute between 20 trillion and one quadrillion computing steps – per second. With a performance of up to 250 TOPS per unit, that’s an increase of 66 percent compared to the previous model, the ZF ProAI RoboThink.
And while performance increases, power consumption drops even more: With 1 watt of power, the ProAI achieves a performance of approximately 3 TOPS. That's up to 70 percent less power consumption than before. And, as an automotive grade product, its high-tech interior is resilient and reliable even under harsh conditions. It also offers an ASIL-D computing performance with state-of-the-art protection against cyber threats.
Enabling new vehicle functions and tapping their full potential: The AI-capabilities of ZF ProAI are optimized for deep learning processes, further enhancing its ability to deliver advanced safety features. The board offers a 360° GPU-driven fusion of all available sensor data, including environmental measurement data from radars, LiDARs, cameras and audio patterns.
ZF also provides a measurement data interface (MDI) for ProAI to forward the collected sensor data unaltered to a central storage system for development and testing purposes. This makes it much easier for developers to train artificial intelligence for autonomous driving.
Given such possibilities, it is not surprising that orders are already being placed with ZF. The first volume production for the latest version of the ZF ProAI will start in 2024.
SEEINGMACHINES:
Seeing Machines | Technology to get everyone home safe
Seeing Machines' industry leading driver and occupant monitoring system technology is enhancing safety by reducing transport fatalities.
They are based in Canberra, are a customer of NVISO, and are also working with XILINX (mentioned previously in these threads) on their FOVIO automotive chip.
People are getting confused. Some of us were hoping Hey Mercedes infotainment only being released with Akida in new models not the full package with Nvidia to be released in 2024. Looking likely Mercedes will wait until 2024 before using Akida in any commercial model with Akida incorporated right throughout the car.
