Food4 thought
Regular
Linked in is pumping robots and A I like crazy this 1 half of the new financial year is going to be a cracker I think
Hopefully we see the fruit
Hopefully we see the fruit
BRN Discussion Ongoing
- Thread starter TechGirl
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DingoBorat
Slim
Good chance it's independent A.I. of the neuromorphic kind, the Cloud is too slow and prone to interruptions.
Teksun Inc on LinkedIn: #technology #teksun #forwardcollisionwarning #safetyfirst #smartdriving…
Introducing Teksun Inc's Forward Collision Warning system – your new co-pilot for safer journeys. Our advanced #technology detects potential collisions and…www.linkedin.com
Are we here ……….
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We're not the only kid on the block, but do have a partnership with Teksun..
(but they have a few, including Qualcomm)
Teksun Partner
As a proven global technology partnerships with vendors and solution providers, we let our customer develop the best of breed solutions for end users.
teksun.com
I'm betting it's us, but I think that's already obvious
..Thank you......got drilled by zeebot for being computer dumbImagine your IoT devices had the intelligence of a human brain. This isn't just futuristic; it's achievable through neuromorphic computing! Neuromorphic computing mimics the behavior of brain neurons, offering human-like adaptability and learning capabilities. Why is this beneficial for IoT (Internet of Things)?
Currently, IoT devices mainly use the Von Neumann architecture, which processes data and commands sequentially in the same memory space. This method can lead to data bottlenecks and high power consumption, problematic for often battery-operated IoT devices 🪫.
Neuromorphic computing offers revolutionary advantages: · Parallel processing: Unlike sequential processing, neuromorphic systems can perform many tasks simultaneously. · Lower power consumption: Ideal for energy-efficient IoT devices. · Real-time processing: Ensures quick responses and low latency. · On-device adaptive learning: IoT devices can adapt and learn without constantly relying on central servers.
In what other areas could neuromorphic computing be useful? Share your thoughts in the comments.
#neuromorphiccomputing #AI #InternetofThings #VodafoneBusiness
(Sources: The Digital Speaker 2023, The Financial Express 2024)
Thank you"Imagine if your IoT devices had the intelligence of a human brain. It may sound like a dream of the future, but neuromorphic computing makes it possible! Neuromorphic computing mimics the behaviour of brain neurons and therefore has human-like adaptation and learning capabilities. But why could this be beneficial for the IoT (Internet of Things)? Up to now, IoT devices have mostly used the Neumann architecture, in which data and commands are processed sequentially in the same memory space. However, this method also leads to data bottlenecks and high power consumption, which is problematic for IoT devices that are often battery-operated 🪫. Neuromorphic computing offers revolutionary advantages here: - Parallel processing: unlike sequential processing, neuromorphic systems can perform many tasks simultaneously. - Lower power consumption: Ideal for IoT devices that rely on energy efficiency - Real-time processing: Ensures fast responses and low latency. - On-site adaptive learning: IoT devices can adapt and learn without constantly relying on centralised servers. In what other areas could neuromorphic computing become useful? Share your opinion in the comments. #neuromorphiccomputing #ki #internetofthings #vodafonebusiness (Sources: The Digital Speaker 2023, The Financial Express 2024)"
Frangipani
Regular
Since the following article is branded content by WIRED Consulting and QinetiQ (a UK-based Defense and Space Manufacturing company), chances are QinetiQ researchers have already been experimenting with neuromorphic technology - both Loihi 2 and Akida are explicitly referred to.
Also take a look at the illustration.
Taking inspiration from the human brain to create next-gen chips
As AI becomes the tech world’s center of gravity, the virtues of neuroscience-inspired computing systems are turning heads. These are now seen as a critical enabler for a raft of new innovations, not only on Earth, but in space…www.wired.com
BRANDED CONTENT BY
Neuromorphic Chips Could Solve Some Of AI’s Problems
As AI becomes the tech world’s center of gravity, the virtues of neuroscience-inspired computing systems are turning heads. These are now seen as a critical enabler for a raft of new innovations, not only on Earth, but in space…
WHAT IF WE told you there was a computer that can analyze and respond almost instantaneously to data from any of its thousands of sensors. That it can also match patterns in that data, recognizing faces, objects, and spoken words, and put that information into context, swiftly learning from what’s happening around it to predict what may happen next. Now, what if we told you it could do all that on around 20 watts of power, less than the average lightbulb—would that sound like a stretch?
As it happens, there are around eight billion of these miraculous devices operating in the world today. They’re called human brains, and they’re inspiring the relatively recent science of neuromorphic computing, a completely new approach to computer design in which elements of the system are modeled on the complex network of neurons and synapses that allow us to think and function.
“At the very basic level, neuromorphic computing is throwing out everything we think we know about computers and processors and looking at how biological brains compute,” says Mike Davies, Director of the Neuromorphic Computing Lab at Intel. “The guiding light is not just to achieve the levels of biological intelligence that we see in brains, but also the incredible efficiency and speed that we’re still very far from attaining with conventional technology.”
Traditional computers are based upon the classic Von Neumann architecture, in which data is constantly shuttled between a processing unit and a memory unit. This can create a bottleneck when large volumes of data are being processed. As a result, conventional computers are now approaching their limits, while also using mind-boggling quantities of energy to operate at those extremes. That’s been thrown into relief by the rise of “large language models” in AI, which require vast amounts of data and compute. It’s estimated that as much as 15 percent of the world’s total energy is now spent on some form of data manipulation, such as transmission or processing, and this figure is only likely to rise with the predicted millions of sensors that are necessary to enable a fully-fledged Internet of Things (IoT).
The neuromorphic approach offers a solution. It covers a range of different ways of mimicking neuroscience principles, and can apply to both hardware and software.
In Intel’s case, the company’s second-generation neuromorphic chip, Loihi 2, physically emulates the way that the brain processes data. Right now, as you read this sentence, your neurons are exchanging information with each other in a rush of electronic pulses (or “spikes”). The chip works in a similar way. It contains tens of thousands of silicon artificial neurons that also communicate through spiking electronic signals. This arrangement is known as a “spiking neural network” (SNN).
Whereas traditional chips incorporate a clock and work on the basis of continuously reading a rigid, sequential set of instructions, the neurons on the Loihi 2 chip work in parallel in an asynchronous way, and without any prescribed order. Like the neurons in our brain, its artificial neurons are event-triggered, and process information only after the receipt of an incoming activation signal.
A major benefit of this approach is that, as opposed to the always-on Von Neumann model, a spiking neuron network is effectively in “off” mode most of the time. Once triggered, it can then perform a huge number of parallel interactions.
“It’s exactly the same as the way the brain doesn’t churn every single feature of its incoming data,” says Jason Eshraghian, Assistant Professor at the University of California at Santa Cruz. “Imagine if you were to film a video of the space around you. You could be filming a blank wall, but the camera is still capturing pixels, whereas, as far as the brain is concerned, that’s nothing, so why process it?”
Because neuromorphic computing emulates the brain in this way, it can perform tasks using a fraction of the time and power needed by traditional machines.
Neuromorphic systems are also highly adaptable, because the connections between neurons can change in response to new tasks, making them well suited to AI. Analysts have therefore described it as a critical enabler of new technologies that could reach early majority adoption within five years.
Half a decade ago, Intel established a community of researchers around the world to explore the potential applications of neuromorphic computing in specific business use cases, ranging from voice and gesture recognition to image retrieval and robotic navigation. The results so far have been impressive, showing energy efficiency improvements of up to 1,000 times and speed increases of up to 100 times compared to traditional computer processors.
The potential of the neuromorphic approach in enabling less compute-hungry large language models for AI was recently demonstrated by Eshraghian and others at University of California Santa Cruz. Their “SpikeGPT” model for language generation, a piece of software that simulates an SNN through its algorithmic structures, uses approximately 30 times less computation than a similar model using typical deep learning methods.
“Large scale language models rely on ridiculous amounts of compute power,” he says. “Using spikes is a much more efficient way to represent information.”
Taking it to the edge
One of the major potential future benefits that comes from neuromorphic computing’s greater efficiency and speed is the capability to bring low-power, rapid decision-making to the increasing proliferation of devices that enable the Internet of Things. Think of autonomous vehicles, for instance. A neuromorphic chip negates the need to send signals over an internet connection for remote processing by powerful computers in the cloud. Instead, the device can carry out on-the-spot, AI-based learning in isolation—an approach known as “edge” computing.
“The dimension of remote adaptability and personalization that neuromorphic brings opens the door for all kinds of new capabilities with AI,” adds Davies, who believes the area of smart robots carrying out chores in the home, in particular, is one that’s ripe for development.
The term AIoT has been coined to describe the combination of AI and IoT, and California-based company BrainChip is already commercializing the concept with those new capabilities in mind. Its first-to-market digital neuromorphic processor, called Akida, is billed as “a complete neural processing engine for edge applications”.
Companies currently exploring the use of BrainChip’s technology include a leading car manufacturer that’s using it to boost the efficiency of in-car voice recognition, and a waste company that’s developing “smart bins” that can automatically sort and recycle different types of waste through a combination of AI-powered sensors and robotics—and wants to do it in the most efficient and eco-friendly way.
“We’re also working with space agencies to bring Akida into space, to be able to autonomously control machines on Mars, for instance,” says BrainChip CEO Sean Hehir. “When you have to run on solar power, you have to be very efficient. It also has to be completely autonomous, because there is no fast connection back to Earth. And don't forget that low power means low thermal emission—in space, you can't have a fan to cool something, because there's no air.”
Decentralizing AI from the cloud to a device also creates a desirable side effect: Greater privacy. “If you’re not moving data all around the world, you’re much more secure,” says Hehir. “It’s that simple.”
The Defense and National Security Perspective
Jeremy Baxter | Principal Systems Engineer for UAVs & Autonomy and QinetiQ Fellow
Any technology that can offer very fast reaction times or the ability to minimize power consumption will have real military benefits.
When combined with event-based sensing—which minimizes processing delays by reporting significant changes as soon as they occur—neuromorphic computing could allow us to create platforms that match the reaction times of birds and insects at a fraction of the weight and power of today’s technologies. Imagine a tiny, uncrewed aerial vehicle, for example, able to fly through woodland at high speeds yet avoid collisions.
There are two other application areas that could prove to be especially interesting. The first is defensive aid suites. These are military aircraft systems that offer protection from surface-to-air missiles, air-to-air missiles and guided anti-aircraft artillery where fast reaction times are crucial for survival.
The other is covert surveillance. Small, lower power devices are easier to conceal and last longer, playing to the strengths of neuromorphic processing.
Explore the other emerging innovation trends in the series…
DOWNLOAD THE FULL REPORT
- Mechanical human augmentation. Whether it’s additional limbs or smart exoskeletons, machinery is helping humans upgrade their natural capabilities.
- Power beaming. Sending power wirelessly over long distances could transform everything from electric vehicles to offshore wind farms.
- Biohybrid robots. Combining artificial and organic parts, biohybrid robots offer advantages such as self-repair and agility.
- Gene-editing and enhancement. Advances in biotech are spurring scientists to explore how genomes can be tweaked to make ecosystems more sustainable.
- Hyperspectral imaging. Hyperspectral cameras don’t merely record what something looks like, they can tell you what that thing is made from and help you see what the human eye cannot.
To find out more about QinetiQ, click here
To find out more about WIRED Consulting, click here
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QinetiQ - Science and Technology Vision
SandT Science and Technology S&T Defence Innovationwww.qinetiq.com
Here is a link to QinetiQ’s full report on emerging innovation trends:
Another - much larger and better-known - European player in the aerospace, defense & security sector highly interested in neuromorphic technology (as for example evidenced by its recent bio-inspired sensing technology challenge, see below) is Leonardo S.p.A. (originally Finmeccanica), headquartered in Rome and partially owned by the Italian government (the company’s largest shareholder at just over 30%).
Leonardo (company) - Wikipedia
Leonardo - Le tue soluzioni per le innovazioni di Leonardo
solverswanted.leonardo.com
The two new Solvers Wanted 2024 projects on Bio-Inspired Sensor Technology are underway
01 July 2024In May 2024, the kick-off meeting of the two winning projects of the technological challenge "Bio-inspired sensor technology" took place. This is one of the five formats hosted within Solvers Wanted, Leonardo's technological scouting platform that identifies and promotes innovative solutions, in collaboration with universities, research centres, companies and start-ups on a global scale.
Solvers Wanted is our concept of transformation and evolution of Open Innovation as a tool to support the Group's technological development, with a demand-driven approach to identify solutions for specific needs, capable of accelerating the development of technological/strategic plans in line with the 2024-2028 Industrial Plan.
As Simone Ungaro, Leonardo's Chief Strategy and Innovation Officer, explains, “With Solvers Wanted, Leonardo starts from the industrial point of view to understand the needs, and then moves towards the system made up of companies, research centres, universities, to explore possible solutions."
The Bio-inspired sensor technology challenge, launched in October 2023, was aimed at finding solutions in the field of neuromorphic sensors to be used in Detection & Tracking applications. Neuromorphic sensors are electro-optical sensors that reproduces the functionality of the retina, similarly to the human eye. This category includes event-based sensors, which react to changes in light intensity rather than frame rates (sequences of frames) or artificial control signals, sensors that emulate the management of the dynamics of the human eye and sensors that apply neuromorphic processing.
The winners of the challenge, who were awarded a 12-month contract for direct collaboration with Leonardo, are:
The EYE-TECH start up from Carrara with the EYE2DRIVE - Building the digital EYE project, coordinated by Monica Vatteroni and Andrea Raggi.
EYE2DRIVE aims to provide a prototype system to be used for image acquisition tests in critical situations and highly variable and non-optimal lighting conditions. The system, based on a solution owned by EYE-TECH, will integrate the ET1080 sensor and a calculation and processing unit which will make it particularly versatile and suitable for marketing for different applications. The system will also include firmware/software and artificial intelligence algorithms that will be adapted to application needs.
The Department of Computer Science, Bioengineering, Robotics and Systems Engineering of the University of Genoa with the SENSE-NN - symbolic end-to-end neuromorphic sensing project, coordinated by Prof. Fulvio Mastrogiovanni.
SENSE-NN will explore the use of neuromorphic sensors within a system that uses them to acquire information about the environment in which it operates. SENSE-NN wants to overcome the current barriers that derive from the use of neuromorphic sensors managed by canonical algorithms that were not developed to exploit their peculiarities. The objective of the project is to develop a robust hybrid framework that will employ neuromorphic sensors within a Large Language Model (LLM) capable of making rapid decisions, because it will use the data coming from the sensors, avoiding canonical algorithmics.
The kick-off meeting of the projects was held at the Campi Bisenzio site (Florence, Italy) in the presence of Pierpaolo Gambini, Head of the Open Innovation Organisational Unit, Manuel Fuselli (Solvers Wanted, startups and spinoffs), Antonio Porta (CTO LoB Optronics) and Marco Morini (CTIO Innovation – Quantum & Optronics Key Enabling Technologies).
Click here to discover the 5 formats and challenges of Solvers Wanted
https://www.baselinemag.com/news/neuromorphic-engineering-and-urban-farming-advance-concurrently/
Extract :-
Neuromorphic engineering is steadily advancing, modeling itself after the intricacies of the human brain.5 BrainChip Holdings, an Australian company, specializes in this unique field with their standout product, Akida. This revolutionary System-on-Chip (SoC) mirrors the human brain’s processing mechanism.
Notably, Akida reduces power consumption, making it ideal for devices reliant on extended battery life. It also boasts adaptability, easily syncing with a range of machinery from self-driving vehicles to IoT devices. All the signs point to Akida reshaping how AI systems calculate and interact with the world, ultimately pushing cognitive computing forward.
Bioprinting, while a specialized technology in the healthcare domain, harnesses 3D printing to layer biological materials, creating products with a far-reaching potential to shift paradigms in medical treatment, drug development, and food production. With an estimated market value of $1.8 billion by 2027, the bioprinting field is only expanding. This growth boils down to a combination of an escalating need for organ transplants, advancements in 3D printing technology and the increasing prevalence of chronic diseases.
In the bioprinting market, Organovo has proven itself noteworthy, developing 3D human tissues that simulate the structure and function of organic tissues.
In contrast, Urban Farming Technology focuses on the practical application of urban spaces for farming. This innovative field changes the game for food production and consumption. By offering city residents easy access to home-grown vegetables, Urban Farming Technology can tackle the challenge of decreasing farmland while promoting sustainability.
Urban farming techniques such as Vertical and Hydroponic farming can yield a hundredfold increase in produce compared to conventional farming. Not only is the food organic and nutrient-dense, but the methodology also contributes to a healthier lifestyle, reduces waste, and promotes community involvement and local economies. It’s clear that Urban Farming Technology is not just a farming fad; it’s leading us toward a healthier and greener lifestyle.
Despite the lack of recognition, these sectors carry immense potential and live on the brink of ground-breaking innovation and disruption. These promising sectors are providing a rich playground for daring startups ready to tap into their potential.
Extract :-
Neuromorphic engineering and urban farming advance concurrently
- By Adam Campbell
- Last updated July 2, 2024
Neuromorphic engineering is steadily advancing, modeling itself after the intricacies of the human brain.5 BrainChip Holdings, an Australian company, specializes in this unique field with their standout product, Akida. This revolutionary System-on-Chip (SoC) mirrors the human brain’s processing mechanism.
Notably, Akida reduces power consumption, making it ideal for devices reliant on extended battery life. It also boasts adaptability, easily syncing with a range of machinery from self-driving vehicles to IoT devices. All the signs point to Akida reshaping how AI systems calculate and interact with the world, ultimately pushing cognitive computing forward.
Bioprinting, while a specialized technology in the healthcare domain, harnesses 3D printing to layer biological materials, creating products with a far-reaching potential to shift paradigms in medical treatment, drug development, and food production. With an estimated market value of $1.8 billion by 2027, the bioprinting field is only expanding. This growth boils down to a combination of an escalating need for organ transplants, advancements in 3D printing technology and the increasing prevalence of chronic diseases.
In the bioprinting market, Organovo has proven itself noteworthy, developing 3D human tissues that simulate the structure and function of organic tissues.
Neuromorphic engineering and urban farming’s concurrent progress
This ground-breaking work suggests a future rich with possibilities in bioprinting.In contrast, Urban Farming Technology focuses on the practical application of urban spaces for farming. This innovative field changes the game for food production and consumption. By offering city residents easy access to home-grown vegetables, Urban Farming Technology can tackle the challenge of decreasing farmland while promoting sustainability.
Urban farming techniques such as Vertical and Hydroponic farming can yield a hundredfold increase in produce compared to conventional farming. Not only is the food organic and nutrient-dense, but the methodology also contributes to a healthier lifestyle, reduces waste, and promotes community involvement and local economies. It’s clear that Urban Farming Technology is not just a farming fad; it’s leading us toward a healthier and greener lifestyle.
Despite the lack of recognition, these sectors carry immense potential and live on the brink of ground-breaking innovation and disruption. These promising sectors are providing a rich playground for daring startups ready to tap into their potential.
SharesForBrekky
Regular
Quite damning statistics in this article:
www.theguardian.com
"Google’s goal of reducing its climate footprint is in jeopardy as it relies on more and more energy-hungry data centres to power its new artificial intelligence products. The tech giant revealed Tuesday that its greenhouse gas emissions have climbed 48% over the past five years."
"AI will result in data centres using 4.5% of global energy generation by 2030, according to calculations by research firm SemiAnalysis."
"Water usage is another environmental factor in the AI boom, with one study estimating that AI could account for up to 6.6bn cubic metres of water use by 2027 – nearly two-thirds of England’s annual consumption."
Google’s emissions climb nearly 50% in five years due to AI energy demand
Tech giant’s goal of reducing climate footprint at risk as it grows increasingly reliant on energy-hungry data centres
"Google’s goal of reducing its climate footprint is in jeopardy as it relies on more and more energy-hungry data centres to power its new artificial intelligence products. The tech giant revealed Tuesday that its greenhouse gas emissions have climbed 48% over the past five years."
"AI will result in data centres using 4.5% of global energy generation by 2030, according to calculations by research firm SemiAnalysis."
"Water usage is another environmental factor in the AI boom, with one study estimating that AI could account for up to 6.6bn cubic metres of water use by 2027 – nearly two-thirds of England’s annual consumption."
I got also a warning… I don’t get it why
supersonic001
Regular
BrainChip on LinkedIn: #ai
Summer vacation (or winter weekends, depending on your location) is the perfect time to relax and catch up on your reading. BrainChip offers a wealth of…
MDhere
Regular
they are partnered with Renesas so there may be a tie with us there, but an IP licence is sounding pretty damn good, so I will run with your thoughts there especially after ready Tata Elxsi report with our mention in it.
supersonic001
Regular
Renesas Electronics on LinkedIn: #ai #software
Our new R-Car Open Access (RoX) development platform takes simulation and testing to the next level! Check out our latest demo from Amazon Web Services (AWS)…
Smoothsailing
Regular
Sean did say we should have a couple of deals this year in the bag at the AGM if I remember correctly
supersonic001
Regular
MosChip® on LinkedIn: #aum #future #highperformance #computing #collaboration #industry…
✨ Exciting News ✨ Centre for Development of Advanced Computing (C-DAC) Teams Up with MosChip® and Socionext Inc. to Develop Groundbreaking Arm-Based HPC…
Nice nice Anil ……
FiveBucks
Member
Fixed it
MosChip® on LinkedIn: #aum #future #highperformance #computing #collaboration #industry…
✨ Exciting News ✨ Centre for Development of Advanced Computing (C-DAC) Teams Up with MosChip® and Socionext Inc. to Develop Groundbreaking Arm-Based HPC…
Nice nice Anil ……
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supersonic001
Regular
John Deere on LinkedIn: In a blink of an eye
To put this into perspective, See & Spray™ technology detects weeds faster than a human eye can.
Are we on with these guys, can’t recall …
I can't remember that comment. He was excited and said the BOD wouldn't be happy if it took until 2026 but I can't recall a couple this year. Hope your right. Once we get 1 I think it could be a steady flow.
FiveBucks
Member
Hopefully (like last time) we can do a few deals in quick succession! If we don't see any, I'm afraid our share price will tank.
Smoothsailing
Regular
I don’t recall the Exact words ether however there was some reference to getting a couple of deals this year, he thought was possible .
I’ll have to rewatch
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