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Sirod69

bavarian girl ;-)

Arm and Baidu PaddlePaddle build an AI ecosystem together

Arm and Baidu PaddlePaddle, China's premier open-source deep learning platform, are working together to accelerate AI-based IoT development opportunities in a brand new ecosystem. This article was written in collaboration with the Arm China Strategic Alliance Team.


Baidu PaddlePaddle and Arm have a shared vision of a mobile hardware ecosystem, and therefore, the two parties have been in a long-term collaboration that has included Baidu PaddlePaddle joining the Arm AI Partner Program. Arm’s extensive AI ecosystem simplifies AI deployment on intelligent endpoint devices by providing best-in-class tools, algorithms and applications to businesses worldwide.

The partnership is clearly a pivotal moment in the evolution of AI development in China. After more than 6 years of development, Baidu PaddlePaddle now ranks first in the comprehensive share of open-source deep learning frameworks in China. Nearly 5 million developers have created 560,000 models based on the PaddlePaddle open-source deep learning platform, serving 180,000 enterprises and institutions. PaddlePaddle helps developers quickly realize AI ideas, innovate AI applications, and serve as a basic platform to support more and more industries to realize industrial intelligent upgrades.

Arm AI Partners such as Baidu PaddlePaddle are leading global AI software and hardware providers ready to help support your next AI project built on Arm. For more information, please visit the Arm AI Partner Program.


How to Deploy PaddlePaddle on Arm Cortex-M with Arm Virtual Hardware​

 
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stuart888

Regular
Long Range Wireless Network (LoRaWAN).



https://iot.eetimes.com/2022-wireless-networks-for-iot-part-2-non-cellular-options/

LPWANS FOR MASSIVE IOT APPLICATIONS​

As mentioned above, cellular IoT might not be the best option for many industrial, agricultural, and government applications.

The thousands of sensors in a farm, millions of smart meters, or the hundreds of waste bins in a city do not require those devices to be continuously connected and send data. In many of those applications, the amount of data transmitted is minimal, usually in regular bursts of data.

Many of those sensors and actuators will operate without human intervention for several years and, in many cases, with the same batteries.

What is essential for connecting those devices is having a network that operates in sub-GHz unlicensed spectrum, covers a vast area, and requires very little power from the device to send/receive data.

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cosors

👀
event-based vision on edge computing, SynSense and Prophesee (and Sony)

You will probably know this older article from over there, but I didn't. I find it quite good because of the overview. There has been a lot of speculation here recently about Prophesee and Sony.
Does the SNN processor Dynap-CNN from SynSense mentioned in the article mean that they are still working on it with Prophesee and we are left out in this matter or we were brought in as a better alternative? Or what does that mean for us?
Bear with me if you have already discussed this. I did a keyword search and there is so much info exchanged here that it may have passed me by. I would be very grateful for an (short) answer.

Neuromorphic pioneer recognised at Vision Stuttgart
6 October 2021
Prophesee has won the Vision Award at Vision Stuttgart for its neuromorphic approach to imaging. Greg Blackman speaks to Luca Verre, the firm’s CEO, about prospects for the technology
https://www.imveurope.com/analysis-opinion/neuromorphic-pioneer-recognised-vision-stuttgart

____
And one more question. I was trying to find out if Apple's M2 neuromorphic capabilities are a serious competitor or rival for us? There have often been nicely summarized posts of alternative neuromorphic chips and where they stand in comparison to us. Can anyone point me to such a post? I skimmed the Apple and neuromorph thread to the best of my ability but didn't get it, have little insight. Is there maybe even a specs comparison or an Akida spec thread I haven't found yet? Fullmoonfever had presented the chip and then it was hoped that FF would go for it. However, I could not find the answer. I mean no one really went into it but may not have found it either.Again, I would be very grateful.
 
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Is Akida capable of something like this?
 
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Vanman1100

Regular
This could be very important but we need a bit more information before I tell my wife and she insists we move to the house she found on realestate.com today.

My opinion only DYOR
FF

AKIDA BALLISTA
Haha. I have one of them as well! God bless her.
 
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stuart888

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FFS. Look at the first two comments on the video.
And wow, I dig Todd's set up. Interesting video
 
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Luppo71

Founding Member
These new products from Bosch look interesting.

 
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equanimous

Norse clairvoyant shapeshifter goddess
Program SolicitationOpen DateClose DateSelection Announcement Date
NASA STTR 2021 Phase II Proposal Period
only STTR 2021 Phase I awardees eligible to apply
May 06, 2022Due last day of Phase I contractSep 09, 2022*


---

New NASA STTRs coming out soon
H6.22Deep Neural Net and Neuromorphic Processors for In-Space Autonomy and Cognition
Lead Center: GRC

Participating Center(s): ARC

Solicitation Year: 2021

Scope Title:

Neuromorphic Capabilities​

Scope Description:
This subtopic specifically focuses on advances in signal and data processing. Neuromorphic processing will enable NASA to meet growing demands for applying artificial intelligence and machine learning algorithms onboard a spacecraft to optimize and automate operations. This includes enabling cognitive systems to improve mission communication and data-processing capabilities, enhance computing performance, and reduce memory requirements. Neuromorphic processors can enable a spacecraft to sense, adapt, act, and learn from its experiences and from the unknown environment without necessitating involvement from a mission operations team. Additionally, this processing architecture shows promise for addressing the power requirements that traditional computing architectures now struggle to meet in space applications.

The goal of this program is to develop neuromorphic processing software, hardware, algorithms, architectures, simulators, and techniques as enabling capability for autonomous space operations. Emerging memristor and other radiation-tolerant devices, which show potential for addressing the need for energy-efficient neuromorphic processors and improved signal processing capability, are of particular interest due to their resistance to the effects of radiation.

Additional areas of interest for research and/or technology development include: (a) spiking algorithms that learn from the environment and improve operations, (b) neuromorphic processing approaches to enhance data processing, computing performance, and memory conservation, and (c) new brain-inspired chips and breakthroughs in machine understanding/intelligence. Novel memristor approaches that show promise for space applications are also sought.

This subtopic seeks innovations focusing on low-size, -weight, and -power (-SWaP) applications suitable to lunar orbital or surface operations, thus enabling efficient onboard processing at lunar distances. Focusing on SWaP-constrained platforms opens up the potential for applying neuromorphic processors in spacecraft or robotic control situations traditionally reserved for power-hungry general-purpose processors. This technology will allow for increased speed, energy efficiency, and higher performance for computing in unknown and uncharacterized space environments including the Moon and Mars. Proposed innovations should justify their SWaP advantages and target metrics over the comparable relevant state of the art.
Expected TRL or TRL Range at completion of the Project: 4 to 6
Primary Technology Taxonomy: Level 1: TX 10 Autonomous Systems
Level 2: TX 10.1 Situational and Self Awareness
Desired Deliverables of Phase I and Phase II:

  • Prototype
  • Hardware
  • Software
Desired Deliverables Description:
Phase I will emphasize research aspects for technical feasibility and show a path toward a Phase II proposal. Phase I deliverables include concept of operations of the research topic, simulations, and preliminary results. Early development and delivery of prototype hardware/software is encouraged.

Phase II will emphasize hardware and/or software development with delivery of specific hardware and/or software products for NASA, targeting demonstration operations on a low-SWaP platform. Phase II deliverables include a working prototype of the proposed product and/or software, along with documentation and tools necessary for NASA to use the product and/or modify and use the software. In order to enable mission deployment, proposed prototypes should include a path, preferably demonstrated, for fault and mission tolerances. Phase II deliverables should include hardware/software necessary to show how the advances made in the development can be applied to a CubeSat, SmallSat, and rover flight demonstration.
State of the Art and Critical Gaps:
The current state of the art (SOA) for in-space processing is the High Performance Spaceflight Computing (HPSC) processor being developed by Boeing for NASA Goddard Space Flight Center (GSFC). The HPSC, called the Chiplet, contains 8 general purpose processing cores in a dual quad-core configuration. Delivery is expected by December 2022. In a submission to the Space Technology Mission Directorate (STMD) Game Changing Development (GCD) program, the highest computational capability required by a typical space mission is 35 to 70 GFLOPS (billion fast logical operations per second).

The current SOA does not address the capabilities required for artificial intelligence and machine learning applications in the space environment. These applications require significant amounts of multiply and accumulate operations, in addition to a substantial amount of memory to store data and retain intermediate states in a neural network computation. Terrestrially, these operations require general-purpose graphics processing units (GP-GPUs), which are capable of teraflops (TFLOPS) each—approximately 3 orders of magnitude above the anticipated capabilities of the HPSC.

Neuromorphic processing offers the potential to bridge this gap through a novel hardware approach. Existing research in the area shows neuromorphic processors to be up to 1,000 times more energy efficient than GP-GPUs in artificial intelligence applications. Obviously, the true performance depends on the application, but nevertheless the architecture has demonstrated characteristics that make it well-adapted to the space environment.
Relevance / Science Traceability:
The Cognitive Communications Project, through the Human Exploration and Operations Mission Directorate (HEOMD) Space Communications and Navigation (SCaN) Program, is one potential customer of work from this subtopic area. Neuromorphic processors are a key enabler to the cognitive radio and system architecture envisioned by this project. As communications become more complex, cognition and automation will play a larger role to mitigate complexity and reduce operations costs. Machine learning will choose radio configurations and adjust for impairments and failures. Neuromorphic processors will address the power requirements that traditional computing architectures now struggle to meet and are of relevance to Lunar return and Mars for autonomous operations, as well as of interest to HEOMD and Science Mission Directorate (SMD) for in situ avionics capabilities.
References:
Several reference papers that have been published at the Cognitive Communications for Aerospace Applications (CCAA) workshop are available at: http://ieee-ccaa.com.
 
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Zedjack33

Regular
In good company.

The co-located AI Hardware and Edge AI Summittakes place in two weeks at the Santa Clara Marriott, September 13-15.
 

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chapman89

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Kachoo

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stuart888

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stuart888

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Slymeat

Move on, nothing to see.
Talk about trust . I bought a small piece of the Berlin Wall at an Antique shop in Carbargo 30 years ago . I have since lost it but thinking back it could have been a bit of concrete from anywhere . It was off white with big flecks of grey broken stones mixed in with it . It was nice thinking I had a bit of history
I know someone who was present when the wall came down. He souveniered a small piece, along with a photo of him smashing at the wall, and hence that is the only piece I‘d ever believe to be authentic. Even as such, it did just appear to be a nondescript piece of concrete. One could easily get flogged off a fake.
 
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uiux

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Though we already know about the new patent, like to think Ann today given the formal notice of granting came out o/night.

Screenshot_2022-09-01-06-11-54-91_4641ebc0df1485bf6b47ebd018b5ee76.jpg
 
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With Akida it will be Smart and unbreakable

View attachment 15545
Hi @uiux

I have let Ken know and he has acknowledged and praised these Chinese researchers for their ethics and adventurous spirit. I have made up the bit about praise because I cannot use what he actually said here.

Leaving ethics aside, and they have, this is not a commercial product, and like any rabies ridden old dog you pick up from the pound, they can call it what they like, say Google for example.

The issue only arises when you try and commercialise it as a product and market it as Google.

I suspect that Brainchip will do no more than send a letter to the scientific journal advising that the name is in use and the researchers will be put on notice.

As for their research it echoes research sponsored by NASA that I posted here last year about spiking graph neural networks and also sent to Brainchip to loud silence.

There is something about what these researchers are engaged in which is best summed up in the old expression

‘Imitation is the sincerest form of flattery that mediocrity can pay to greatness.'

My opinion only DYOR
FF

AKIDA BALLISTA
 
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FJ-215

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FFS. Look at the first two comments on the video.
And wow, I dig Todd's set up. Interesting video
YouTube showing 2 comments made but can't view them. Assuming they weren't nice?
 
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YouTube showing 2 comments made but can't view them. Assuming they weren't nice?
One was for porn and the other was for onlyfans.
 
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