GStocks123
Regular
This recently published article is worth the read. Quite a few experiments completed with Akida, Loihi 2 & DynappCNN. Akida appears to outperform on most.
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
Bravo
If ARM was an arm, BRN would be its biceps💪!
Quantum Corporation as opposed to Quantum Ventura.
1.)
2)
3)
www.quantum.com
1.)
2)
3)
Quantum® Unveils Enhanced Partner Portal and Program, Receives Channel Recognition from CRN
Quantum Corporation (NASDAQ: QMCO), the pioneer in end-to-end data management solutions designed for the AI era, demonstrates its commitment to the ch
www.businesswire.com
Technology Partners
Quantum works closely with our Technology Partners to deliver proven joint solutions based on our award-winning scale-out storage, archive, and data protection portfolio. Create rock-solid solutions for today's most demanding environments by becoming a technology partner.
Justchilln
Regular
That was for one of brainchips earliest failures “studio”Quantum Corporation as opposed to Quantum Ventura.
1.)
View attachment 69622
2)
View attachment 69621
3)
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Quantum® Unveils Enhanced Partner Portal and Program, Receives Channel Recognition from CRN
Quantum Corporation (NASDAQ: QMCO), the pioneer in end-to-end data management solutions designed for the AI era, demonstrates its commitment to the chwww.businesswire.comTechnology Partners
Quantum works closely with our Technology Partners to deliver proven joint solutions based on our award-winning scale-out storage, archive, and data protection portfolio. Create rock-solid solutions for today's most demanding environments by becoming a technology partner.
Bravo
If ARM was an arm, BRN would be its biceps💪!
Then why is BrainChip listed on their website CURRENTLY as a partner?
Christmas past or Marley
Christmas Past or Marley's ghost?Quantum Corporation as opposed to Quantum Ventura.
1.)
View attachment 69622
2)
View attachment 69621
3)
View attachment 69620
Quantum® Unveils Enhanced Partner Portal and Program, Receives Channel Recognition from CRN
Quantum Corporation (NASDAQ: QMCO), the pioneer in end-to-end data management solutions designed for the AI era, demonstrates its commitment to the chwww.businesswire.comTechnology Partners
Quantum works closely with our Technology Partners to deliver proven joint solutions based on our award-winning scale-out storage, archive, and data protection portfolio. Create rock-solid solutions for today's most demanding environments by becoming a technology partner.
Food4 thought
Regular
The AI Innovator
open menu
For the rest of the series, click here.
AI’s on-screen iterations, including the use of generative AI in chatbots, have been grabbing the majority of the world’s attention since the debut of ChatGPT in late 2022. For its next act, AI will move out of the cloud to devices at the edge − with the future of AI being off-screen and in the physical world.
This move will supercharge robotics and IoT, and the technology driving it all will be compound semiconductors, including the material gallium nitride (GaN). Compound semiconductors, or computer chips made from two or more elements as opposed to single-element silicon, are becoming increasingly important in areas where higher performance is required.
AI’s future at the edge cannot happen without compound semiconductor materials that outperform silicon in three key ways. First, they operate very efficiently at RF frequencies. Second, they are effective emitters and detectors of light over a broad spectrum. Third, they are very efficient, particularly in harsh environments for such things as power conversion.
This is a realm pioneered by compound semiconductor lasers and detectors that employ gallium arsenide (GaAs) and indium phosphide (InP), and improved versions of these devices will be necessary for AI progression. Furthermore, it is not only physically sensing things in three dimensions that will be important; wearable health monitors use compound semiconductor materials for biological sensing, an area poised to be revolutionized by off-screen AI.
Finally, the next version of AI will require ultra-fast, ultra-reliable, low latency connectivity even with things at the edge, and the excellent RF properties of compound semiconductors, particularly GaAs and GaN, will be exploited to enable this capability.
While much of the compute is expected to move to the edge for the next iteration of AI, the energy requirements will remain high; energy usage will scale regardless of whether the compute is occurring in the cloud or at the edge. This makes compound semiconductor materials a necessity for AI to progress.
In addition, the compound semiconductor material GaN is very robust, making it ideal for edge devices such as robotics that operate in harsh environments with elevated temperatures, higher humidities, and the like.
It is easy to see how this will benefit industrial robotics at the edge, but GaN’s capability could take things further, even as far as outer space. MIT researchers recently demonstrated that GaN was able to tolerate exposure to more than 900°F for 48 hours, making it a promising candidate for space exploration.
In this next ‘off-screen’ phase of AI, different bottlenecks for the technology will be encountered. The limitations will move to the devices at the edge. The sense and connect demands on edge devices will become extreme, as the next version of AI will require devices to operate on real time data in ways never seen before.
This, in turn, will make these devices more power hungry. To address these new requirements, compound semiconductor materials will be required, and materials such as GaN will become indispensable.
open menu
AI MODELS/TOOLS
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SEPTEMBER 19, 2024
Google's AI research assistant rolls out a new capability: It can turn your documents into a realistic-sounding podcast featuring two 'people' who even banter. - OpenAI’s AI Models that Can Reason: How Good Are They?
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OpenAI's latest family of models can reason - they stop and think before answering a prompt. A Wharton professor took it for a test. - UCLA Study: AI Beats Doctors in Prostate Cancer Analysis
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UCLA researchers found that AI is 45 times more accurate at mapping the spread of prostate cancer than doctors. - Meta’s Open Source Llama Nearing 350 Million Downloads
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This breakthrough suggests that synthetic materials can develop a rudimentary form of 'memory' to enhance capabilities.
Featured Videos: MIT Course on Deep Learning
Part 1: Introduction to Deep LearningPart 2: Recurrent Neural Networks, Transformers and Attention
Part 3: Deep Computer Vision / Convolutional Neural Networks
For the rest of the series, click here.
Why the Future of AI Depends on Compound Semiconductors
BY RODNEY PELZEL ON SEPTEMBER 18, 2024AI’s on-screen iterations, including the use of generative AI in chatbots, have been grabbing the majority of the world’s attention since the debut of ChatGPT in late 2022. For its next act, AI will move out of the cloud to devices at the edge − with the future of AI being off-screen and in the physical world.
This move will supercharge robotics and IoT, and the technology driving it all will be compound semiconductors, including the material gallium nitride (GaN). Compound semiconductors, or computer chips made from two or more elements as opposed to single-element silicon, are becoming increasingly important in areas where higher performance is required.
AI’s future at the edge cannot happen without compound semiconductor materials that outperform silicon in three key ways. First, they operate very efficiently at RF frequencies. Second, they are effective emitters and detectors of light over a broad spectrum. Third, they are very efficient, particularly in harsh environments for such things as power conversion.
Increased functionality of devices at the edge
The transition of AI off-screen into the realm of IoT means that the devices at the edge will need to get more capable. For example, they will be required to ‘sense’ their environment in ultra-high resolution − meaning that 3D recognition and LiDAR systems like those employed in mobile handsets will become essential for all sorts of devices where this capability is not needed today.This is a realm pioneered by compound semiconductor lasers and detectors that employ gallium arsenide (GaAs) and indium phosphide (InP), and improved versions of these devices will be necessary for AI progression. Furthermore, it is not only physically sensing things in three dimensions that will be important; wearable health monitors use compound semiconductor materials for biological sensing, an area poised to be revolutionized by off-screen AI.
Finally, the next version of AI will require ultra-fast, ultra-reliable, low latency connectivity even with things at the edge, and the excellent RF properties of compound semiconductors, particularly GaAs and GaN, will be exploited to enable this capability.
Increasing efficiency, reducing power demands
When it comes to AI, much of the world’s attention is currently focused on the energy needs of data centers, and rightly so – and if all data centers around the world were converted from silicon to GaN by the end of the decade, it is estimated that energy loss would be reduced by 30% to 40%. To put that into perspective, the conversion would save more than 100 terawatt hours and avoid 125 megatons of carbon dioxide emissions.While much of the compute is expected to move to the edge for the next iteration of AI, the energy requirements will remain high; energy usage will scale regardless of whether the compute is occurring in the cloud or at the edge. This makes compound semiconductor materials a necessity for AI to progress.
In addition, the compound semiconductor material GaN is very robust, making it ideal for edge devices such as robotics that operate in harsh environments with elevated temperatures, higher humidities, and the like.
It is easy to see how this will benefit industrial robotics at the edge, but GaN’s capability could take things further, even as far as outer space. MIT researchers recently demonstrated that GaN was able to tolerate exposure to more than 900°F for 48 hours, making it a promising candidate for space exploration.
What’s next for AI
While the conversation around AI has certainly intensified over the last year and a half, one important thing to remember about this technology is that we are really at the beginning. Right now, generative AI applications are operating on massive amounts of data, pulling information from LLMs and incorporating clever algorithms to deliver a response.In this next ‘off-screen’ phase of AI, different bottlenecks for the technology will be encountered. The limitations will move to the devices at the edge. The sense and connect demands on edge devices will become extreme, as the next version of AI will require devices to operate on real time data in ways never seen before.
This, in turn, will make these devices more power hungry. To address these new requirements, compound semiconductor materials will be required, and materials such as GaN will become indispensable.
Author
-
Rodney Pelzel
Rodney Pelzel is the CTO of IQE plc, a global supplier of advanced wafer products and material solutions to the semiconductor industry. He has deep expertise in semiconductor materials engineering and the epitaxial growth of compound semiconductors. His work has been widely published and he is the co-inventor of over 30 patents.
DingoBorat
Slim
I remember reading somewhere (thought it might be in the original CTO announcement, but it's not) that Tony has a strong commercialisation focus (especially for a CTO, who are known to like to "tinker")..
Whether it was actually said or it's just a figment of my imagination, it's clearly evidenced, by his statement, that he definitely is commercialisation focused!
rgupta
Regular
Not sure he is commercialisation focused or not but definately he is out spoken and wants to do something than to defend himself. To me he is an aggressor and will not stop from challenging himself and his competitors.
He is definately on a mission.
Bravo
If ARM was an arm, BRN would be its biceps💪!
‘We’ve Fused Signal Processing and AI’: NVIDIA CEO Outlines Future of Telecom at T-Mobile’s Capital Markets Day
Jensen Huang joined T-Mobile CEO Mike Sievert in a surprise fireside chat on how the companies are advancing telecommunications with AI.September 19, 2024 by Brian Caulfield
Share
In a surprise appearance at T-Mobile’s Capital Markets Day, NVIDIA founder and CEO Jensen Huang shared a bold vision for the future of telecommunications.
“We’ve fused signal processing and AI,” Huang declared during a fireside chat with T-Mobile CEO Mike Sievert, speaking to an audience of press, analysts and investors. “This is going to be a great new growth opportunity for the telecommunications industry.”
Huang’s remarks came alongside NVIDIA’s announcement of its groundbreaking AI Aerial platform, which promises to reshape wireless networks by integrating AI and radio access networks, AI-RAN.
The platform is designed to optimize network performance, efficiency and new revenue potential, such as AI-computing-as-a-service during periods when network infrastructure is underutilized, maximizing the return on assets.
During the conversation, Huang emphasized the importance of AI in shaping the future of telecommunications, particularly highlighting the role of AI-RAN in optimizing and scaling network performance.
Fusing radio computing and AI computing into one architecture allows companies to apply AI models to optimize signal quality across diverse environments, Huang explained.
He emphasized that this fusion would lead to improved network efficiency and new growth opportunities for the telecommunications industry,
“We could teach these AI models how to optimize signal quality in hundreds of thousands of virtual cities,” Huang said.
AI-RAN aligns with NVIDIA’s broader vision to make AI an integral part of network infrastructure, enabling telecommunications providers to unlock new revenue streams and deliver enhanced experiences through generative AI, robotics and autonomous technologies.
Huang underscored the synergies between NVIDIA and T-Mobile, particularly their collaboration on the newly announced AI-RAN Innovation Center, as co-authors of transformation. The AI-RAN Innovation Center, developed with T-Mobile, Ericsson and Nokia, is set to accelerate the commercialization of AI-RAN technologies.
Every radio operates in a unique and constantly changing world environment. This is where deep reinforcement learning algorithms embedded into radio signal processing make complex computations simpler with AI to help deliver a customer-centric network experience.
Sievert emphasized how virtualizing RAN into the cloud will create new business opportunities. He explained that AI workloads will increasingly require compute power located close to the customer, leveraging underutilized network resources.
Huang also highlighted the crucial role AI will play in making networks more energy-efficient, emphasizing the need for sustainable technology as the demand for data and connectivity grows.
“We have to use AI to reduce energy consumption,” Huang said. “Everything that we accelerate, everything that we teach an AI model to do [we] will do a lot more energy efficiently.”
As Huang explained, by simulating AI models in virtual environments with accurate physics and then emulating them in the real world, NVIDIA maximizes energy efficiency. This approach underpins the NVIDIA AI Aerial suite of platforms for designing, training and deploying AI-driven cellular networks for AI.
With NVIDIA AI Aerial now supporting a growing ecosystem of partners this collaboration marks a milestone in the telecom industry’s journey toward a future powered by AI.
‘We’ve Fused Signal Processing and AI’: NVIDIA CEO Outlines Future of Telecom at T-Mobile’s Capital Markets Day
At T-Mobile’s Capital Markets Day, NVIDIA founder and CEO Jensen Huang shared a bold vision for the future of telecommunications
blogs.nvidia.com
Does this
have something to do with that
?
Last edited:
rgupta
Regular
I remember Sean used to say they are working with a big communication company, that was approx 18 months ago and since then there was no talk on that. May be it was T mobile and then chose to go with Nvidia later on. But definately that will mean Sean's claim we have not lost a customer will be wrong.‘We’ve Fused Signal Processing and AI’: NVIDIA CEO Outlines Future of Telecom at T-Mobile’s Capital Markets Day
Jensen Huang joined T-Mobile CEO Mike Sievert in a surprise fireside chat on how the companies are advancing telecommunications with AI.
September 19, 2024 by Brian Caulfield
Share
In a surprise appearance at T-Mobile’s Capital Markets Day, NVIDIA founder and CEO Jensen Huang shared a bold vision for the future of telecommunications.
“We’ve fused signal processing and AI,” Huang declared during a fireside chat with T-Mobile CEO Mike Sievert, speaking to an audience of press, analysts and investors. “This is going to be a great new growth opportunity for the telecommunications industry.”
Huang’s remarks came alongside NVIDIA’s announcement of its groundbreaking AI Aerial platform, which promises to reshape wireless networks by integrating AI and radio access networks, AI-RAN.
The platform is designed to optimize network performance, efficiency and new revenue potential, such as AI-computing-as-a-service during periods when network infrastructure is underutilized, maximizing the return on assets.
During the conversation, Huang emphasized the importance of AI in shaping the future of telecommunications, particularly highlighting the role of AI-RAN in optimizing and scaling network performance.
Fusing radio computing and AI computing into one architecture allows companies to apply AI models to optimize signal quality across diverse environments, Huang explained.
He emphasized that this fusion would lead to improved network efficiency and new growth opportunities for the telecommunications industry,
“We could teach these AI models how to optimize signal quality in hundreds of thousands of virtual cities,” Huang said.
AI-RAN aligns with NVIDIA’s broader vision to make AI an integral part of network infrastructure, enabling telecommunications providers to unlock new revenue streams and deliver enhanced experiences through generative AI, robotics and autonomous technologies.
Huang underscored the synergies between NVIDIA and T-Mobile, particularly their collaboration on the newly announced AI-RAN Innovation Center, as co-authors of transformation. The AI-RAN Innovation Center, developed with T-Mobile, Ericsson and Nokia, is set to accelerate the commercialization of AI-RAN technologies.
Every radio operates in a unique and constantly changing world environment. This is where deep reinforcement learning algorithms embedded into radio signal processing make complex computations simpler with AI to help deliver a customer-centric network experience.
Sievert emphasized how virtualizing RAN into the cloud will create new business opportunities. He explained that AI workloads will increasingly require compute power located close to the customer, leveraging underutilized network resources.
Huang also highlighted the crucial role AI will play in making networks more energy-efficient, emphasizing the need for sustainable technology as the demand for data and connectivity grows.
“We have to use AI to reduce energy consumption,” Huang said. “Everything that we accelerate, everything that we teach an AI model to do [we] will do a lot more energy efficiently.”
As Huang explained, by simulating AI models in virtual environments with accurate physics and then emulating them in the real world, NVIDIA maximizes energy efficiency. This approach underpins the NVIDIA AI Aerial suite of platforms for designing, training and deploying AI-driven cellular networks for AI.
With NVIDIA AI Aerial now supporting a growing ecosystem of partners this collaboration marks a milestone in the telecom industry’s journey toward a future powered by AI.
‘We’ve Fused Signal Processing and AI’: NVIDIA CEO Outlines Future of Telecom at T-Mobile’s Capital Markets Day
At T-Mobile’s Capital Markets Day, NVIDIA founder and CEO Jensen Huang shared a bold vision for the future of telecommunicationsblogs.nvidia.com
Does this
View attachment 69633
View attachment 69632
Anyway the things are so much wired that more you try to solve them, more entangled them become.
Let us wait and watch and look at financials.
Dyor
Pom down under
Top 20
2024 is quickly coming to an end. It's probably time for Sean to come out and say 2025 is our year!
Pom down under
Top 20
Hot off the press:‘We’ve Fused Signal Processing and AI’: NVIDIA CEO Outlines Future of Telecom at T-Mobile’s Capital Markets Day
Jensen Huang joined T-Mobile CEO Mike Sievert in a surprise fireside chat on how the companies are advancing telecommunications with AI.
September 19, 2024 by Brian Caulfield
Share
In a surprise appearance at T-Mobile’s Capital Markets Day, NVIDIA founder and CEO Jensen Huang shared a bold vision for the future of telecommunications.
“We’ve fused signal processing and AI,” Huang declared during a fireside chat with T-Mobile CEO Mike Sievert, speaking to an audience of press, analysts and investors. “This is going to be a great new growth opportunity for the telecommunications industry.”
Huang’s remarks came alongside NVIDIA’s announcement of its groundbreaking AI Aerial platform, which promises to reshape wireless networks by integrating AI and radio access networks, AI-RAN.
The platform is designed to optimize network performance, efficiency and new revenue potential, such as AI-computing-as-a-service during periods when network infrastructure is underutilized, maximizing the return on assets.
During the conversation, Huang emphasized the importance of AI in shaping the future of telecommunications, particularly highlighting the role of AI-RAN in optimizing and scaling network performance.
Fusing radio computing and AI computing into one architecture allows companies to apply AI models to optimize signal quality across diverse environments, Huang explained.
He emphasized that this fusion would lead to improved network efficiency and new growth opportunities for the telecommunications industry,
“We could teach these AI models how to optimize signal quality in hundreds of thousands of virtual cities,” Huang said.
AI-RAN aligns with NVIDIA’s broader vision to make AI an integral part of network infrastructure, enabling telecommunications providers to unlock new revenue streams and deliver enhanced experiences through generative AI, robotics and autonomous technologies.
Huang underscored the synergies between NVIDIA and T-Mobile, particularly their collaboration on the newly announced AI-RAN Innovation Center, as co-authors of transformation. The AI-RAN Innovation Center, developed with T-Mobile, Ericsson and Nokia, is set to accelerate the commercialization of AI-RAN technologies.
Every radio operates in a unique and constantly changing world environment. This is where deep reinforcement learning algorithms embedded into radio signal processing make complex computations simpler with AI to help deliver a customer-centric network experience.
Sievert emphasized how virtualizing RAN into the cloud will create new business opportunities. He explained that AI workloads will increasingly require compute power located close to the customer, leveraging underutilized network resources.
Huang also highlighted the crucial role AI will play in making networks more energy-efficient, emphasizing the need for sustainable technology as the demand for data and connectivity grows.
“We have to use AI to reduce energy consumption,” Huang said. “Everything that we accelerate, everything that we teach an AI model to do [we] will do a lot more energy efficiently.”
As Huang explained, by simulating AI models in virtual environments with accurate physics and then emulating them in the real world, NVIDIA maximizes energy efficiency. This approach underpins the NVIDIA AI Aerial suite of platforms for designing, training and deploying AI-driven cellular networks for AI.
With NVIDIA AI Aerial now supporting a growing ecosystem of partners this collaboration marks a milestone in the telecom industry’s journey toward a future powered by AI.
‘We’ve Fused Signal Processing and AI’: NVIDIA CEO Outlines Future of Telecom at T-Mobile’s Capital Markets Day
At T-Mobile’s Capital Markets Day, NVIDIA founder and CEO Jensen Huang shared a bold vision for the future of telecommunicationsblogs.nvidia.com
Does this
View attachment 69633
View attachment 69632
This is Nvidia's recently published NN patent:
WO2024183052A1 FEDERATED LEARNING TECHNIQUE 20230309; pub 20240912
= US2024303504A1 FEDERATED LEARNING TECHNIQUE
Apparatuses, systems, and techniques to train/use one or more neural networks. In at least one embodiment, a processor comprises one or more circuits to cause neural network training information to be aggregated based, at least in part, on contribution of the neural network training data and one or more performance metrics of the neural network.
It's a massive document 263 pages including 56 pages of drawings.
It's about federated learning using cloud-based processors to download, eg, NNs and maps to cars (Fig 9D). Fig 9C shows the vehicle's sensor/processor configuration. sensor fusion would be part of this.
Terroni2105
Founding Member
What are you saying Dio?
Jensen was banging on about sensor fusion shortly after this patent was published, so it's within the realms of possibility that this patent is related to sensor fusion (in the car) among other things like federated learning (in the cloud).
As I recall, previous Nvidia patents do not get down to the details of the NN hardware, and I haven't read this one yet, but I don't think it gets down to that level of detail. Let's hope their AI engineers have been smart enough to make the right choice.
TheUnfairAdvantage
Regular
What are you saying Dio?
From what I was told soon after it became common knowledge that Tony was continuing on in Peters role as our new CTO,
that he was a go getter, the type of individual who went for it, no messing around.
Peter and he share a number of things in common with regards to the future direction of this ground breaking research, agreeing
on the future direction to keep driving us forward and leading the way. mutual respect from both men is clearly evident.
8 months until the next AGM....gee how time fly's....sorry I just couldn't help myself.
that he was a go getter, the type of individual who went for it, no messing around.
Peter and he share a number of things in common with regards to the future direction of this ground breaking research, agreeing
on the future direction to keep driving us forward and leading the way. mutual respect from both men is clearly evident.
8 months until the next AGM....gee how time fly's....sorry I just couldn't help myself.
rgupta
Regular
Hi TechFrom what I was told soon after it became common knowledge that Tony was continuing on in Peters role as our new CTO,
that he was a go getter, the type of individual who went for it, no messing around.
Peter and he share a number of things in common with regards to the future direction of this ground breaking research, agreeing
on the future direction to keep driving us forward and leading the way. mutual respect from both men is clearly evident.
8 months until the next AGM....gee how time fly's....sorry I just couldn't help myself.
We definitely need revenue before the next AGM otherwise the same is going to be very explosive.
Regarding Tony I feel he is in category of PVDM and Anil
Intelligent, humble down to earth, helping person. I like his involvements and understanding about share holders concerns better than brainchip management.
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