BRN Discussion Ongoing
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Taproot
Regular
Like Dio said, the VVDN / BRN Edge Box will be equipped with Akida 1000.Author just on hackster hedging bets either Gen 1 or even possibly Gen 2
BrainChip Partners with VVDN, Teases an Industrial "Akida Edge Box" for On-Device ML and AI
Compact edge AI compute device will be demonstrated live during the Consumer Electronics Show (CES) 2024, BrainChip promises.www.hackster.io
BrainChip Partners with VVDN, Teases an Industrial "Akida Edge Box" for On-Device ML and AI
Compact edge AI compute device will be demonstrated live during the Consumer Electronics Show (CES) 2024, BrainChip promises.
https://www.hackster.io/ghalfacree
ghalfacree
1 minute ago • Machine Learning & AI
BrainChip, which offers neuromorphic processing technology for high-efficiency machine learning and artificial intelligence (ML and AI) at the edge, has announced that it will be opening pre-sales for its Akida Edge Box — the "industry's first edge box powered by neuromorphic AI IP" — in January next year, following a demonstration at the Consumer Electronics Show (CES) 2024.
“BrainChip's neuromorphic technology gives the Akida Edge box the 'edge' in demanding markets such as industrial, manufacturing, warehouse, high-volume retail, and medical care," claims BrianChip's chief executive officer Sean Hehir of the company's impending launch. "We are excited to partner with an industry leader like VVDN technologies to bring groundbreaking technology to the market."
BrainChip has teased an upcoming "Akida Edge Box" device for its neuromorphic processing technology, due to be unveiled at CES in January 2024. (
: BrainChip)
"There is a strong demand for cost-effective, flexible edge AI computation across many industries," adds VVDN Technologies co-founder and chief executive officer Puneet Agarwal, whose company partnered with BrainChip to bring the Akida Edge Box to life. "VVDN is excited to offer OEMs [Original Equipment Manufacturers] its experience and expertise in bringing the advanced, transformative technology integrations that meet market needs and eventually help them with faster time to market.”
BrainChip showed off the original brain-inspired Akida neuromorphic processing concept at the Linley Fall Processor Conference back in 2019, refining the ecosystem over the next two years before the public launch of development kits built around compact Intel and Raspberry Pi computing systems.
In January last year the company announced full commercialization followed by a partnership with Edge Impulse to make Akida more accessible, and in October this year placed Akida 2.0 in "early access" as what Hehir claimed was a "significant step in BrainChip’s vision to bring unprecedented AI processing power to edge devices, untethered from the cloud."
The company has not yet shown off the Akida Edge Box, but had already launched development kits built around compact PCs and SBCs. (
: BrainChip)
Technical details of the Akida Edge Box have not yet been disclosed, but the device is likely to take the form of a small form factor or single-board computer coupled with one or more of the company's Akida or Akida 2.0 neuromorphic processing units. This, the company says, will offer support for "cost-effective and low-latency" on-device artificial intelligence workloads like visual detection, patient monitoring, security and surveillance, and manufacturing.
BrainChip and VVDN Technologies plan to formally unveil the Akida Edge Box at the Consumer Electronics Show 2024 in Las Vegas between January 9-12 2024 with a live demo, after which it will go up for pre-order ahead of an unspecified launch date. More information on the company's technology is available on the BrainChip website.
Products – Akida Neural Processor SoC
Learn more about the Akida Neural Proccesor System-on-Chip!
brainchip.com
At this stage in BRN development, I really think the most important thing to be doing is to benchmark this box against the other better name brand edge boxes like Nvidia and Qualcomm. There need to be comparisons made between the different edge boxes in like for like situations.
So that clear benchmarking can be defined, which can be turned into marketing gold. Less Power, smaller more compact device, with less components ie ( fans )., making the device instantly " greener " and more environmentally friendly. Then technical and performance benchmarks in like for like comparisons. We need to show that BRN / Neuromorphic / Akida is a better option / choice, and we need to clearly define why this is so. Unless Brainchip can show on paper and in real life demonstrations why this product can outperform the competition in clearly defined and understandable benchmarks, then consumers will continue to purchase the name brands every time. Lets hope that VVDN and Brainchip have a great presentation lined up for Jan 12 +
Fullmoonfever
Top 20
@DingoBorat @Taproot
Most likely correct hence my thinking emoji in my post.
However we know Gen 2 available to early adopters Q3, VVDN Ann was beginning of Sept and no doubt we would have been working with them prior you'd think in developing the EB.
Personally I'd like it to be the Gen 2 as what better way to showcase our latest tech with ViT, TENNS at the premier tech event in CES with essentially our first commercially available off the shelf consumer / business product.
Wishful thinking maybe though.
Most likely correct hence my thinking emoji in my post.
However we know Gen 2 available to early adopters Q3, VVDN Ann was beginning of Sept and no doubt we would have been working with them prior you'd think in developing the EB.
Personally I'd like it to be the Gen 2 as what better way to showcase our latest tech with ViT, TENNS at the premier tech event in CES with essentially our first commercially available off the shelf consumer / business product.
Wishful thinking maybe though.
JDelekto
Regular
I think that as Akida 2.0 was announced in March and the IP was made available as early access in October, they would most likely be using Akida 2.0 in their design.
The announcement claims that the Akida Edge Box was designed for vision-based AI workloads, so BrainChip would want to show off its TENN feature and vision transformers.
Putting this new device on display at CES is a chance to market the latest Akida technology, so I would bet that 2.0 would be at play here, possibly even with the hardware using the IP possibly being manufactured at Intel's Global Foundries.
If the Edge boxes were using the Akida 1.0 IP and could stand against the competitors in performance and power requirements, imagine how much more compelling it would make the Akida 2.0 IP for those still on the fence.
Mt09
Regular
Can’t remember at what time point but Sean specifically says the edge box contains akd1000, the chip we had made and have stock of. At this point there’s no akd2000 reference chip ie “hardware” no doubt that will come in the future.
Good morning back in Aussie,
I think an important point to remember with regards VVDN is this: they already make Edge Box's for both of our potential competitors,
namely Nvidia and Qualcomm, adding us to the mix sends a very strong message before a single confirmed sale has even been registered.
Can the others really compete, we shall all find out as CES unfolds, benchmarking is about to be ramped up a number of notches in my
opinion, the more product/s to hit the market will confirm our dominance at the edge, both Nvidia and Qualcomm representatives will be
keenly observing this launch at CES, the new kid on the block has finally arrived....
Akida.
Tech.
I think an important point to remember with regards VVDN is this: they already make Edge Box's for both of our potential competitors,
namely Nvidia and Qualcomm, adding us to the mix sends a very strong message before a single confirmed sale has even been registered.
Can the others really compete, we shall all find out as CES unfolds, benchmarking is about to be ramped up a number of notches in my
opinion, the more product/s to hit the market will confirm our dominance at the edge, both Nvidia and Qualcomm representatives will be
keenly observing this launch at CES, the new kid on the block has finally arrived....
Akida.Tech.
DingoBorat
Slim
AKIDA 2.0 is available, but there hasn't been an announcement of a physical AKD2000 reference chip being produced..
Not sure exactly when the AKD1000 chips were originally made, but there was the engineering samples and then the reference chips, which were greatly improved.
Must be getting close to two years though and they are going into Edge Boxes now and will be State of the Art!
To do that today, in these times of rapid technological development, just goes to show, how far AKIDA is ahead of the curve.
They could also use AKD1500 chips, if they needed to?..
We really have no idea, how many AKD1000 chips were produced, or what percentage of the run were "good".
There's always a non viable percentage and we don't know what the device yield is, when producing AKIDA chips, but I'm guessing, with the engineering samples coming out practically perfect first time (a huge credit to Anil Mankar, as was stated by Louis DiNardo, who had rarely seen that) that it is pretty high, by industry standards.
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Fullmoonfever
Top 20
Thanks for confirming that MT.
Makes sense seeing we got stock sitting around, just a shame then it wasn't our current flagship product at the flagship Tech event of the year.
No doubt Gen 2 will be on display anyway and big bonus if someone else is using it too.
Intel Foundry All Set to Mass-Produce 20A "2nm" Chips In 2024, Ramping Up Competition
Intel is all set to initiate production of its 20A (2nm process) next year, as revealed in an interview by the company's SVP.
Qualcomm website just got a facelift......
www.qualcomm.com
Qualcomm AI Products | Intuitive AI Technology | Qualcomm
Discover how Qualcomm AI technology transforms both LLMs, AI Agents, and computing in mobile, PCs, automotive, and IoT.
DingoBorat
Slim
Intel Foundry All Set to Mass-Produce 20A "2nm" Chips In 2024, Ramping Up Competition
Intel is all set to initiate production of its 20A (2nm process) next year, as revealed in an interview by the company's SVP.wccftech-com.cdn.ampproject.org
Samsung’s 3nm chip manufacturing yield may have surpassed TSMC’s 3nm yield
Over the past few years, Samsung Foundry lost several chip clients to TSMC due to its lower chip manufacturing yields ...
This article was updated in July this year.
"According to the report, Samsung Foundry's yield for its 3nm chip manufacturing process is 60%. In comparison, TSMC's 3nm chip yield is around 55%. It means Samsung finally has the upper hand over TSMC in ultra-advanced chip manufacturing technology. Since TSMC is behind Samsung Foundry in the 3nm segment, it is possible that Samsung could win back the clients it lost to TSMC for 4nm and 5nm processes"
Such low yields still in the 3nm process (4nm is 75 to 80% from the article) and they are going to 2nm next year??
..Moore's law for Von Neumann architecture is dead, when will they realise that?..
MDhere
Top 20
Qualcomm website just got a facelift......
Qualcomm AI Products | Intuitive AI Technology | Qualcomm
Discover how Qualcomm AI technology transforms both LLMs, AI Agents, and computing in mobile, PCs, automotive, and IoT.
View attachment 52145
Well well well once again you have made my
Sunday @IloveLamp ❤ I know I saw this exact same picture somewhere before and here it is -
This is now no coincidence my opinion. And wait what's the catchy words - sense, think, act.
Thankyou Nokia i have no further questionsfor more ❤
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Nokia a given with us imo agreed @MDhere . NOKIA and GOOGLE also involved with the aus gov in satellites/ space etc etc
DingoBorat
Slim
Nokia uses Qualcomm processors, so that's no surprise.
I want to see a rock solid connection, between us and them
Like Dio said, the VVDN / BRN Edge Box will be equipped with Akida 1000.
Products – Akida Neural Processor SoC
Learn more about the Akida Neural Proccesor System-on-Chip!
At this stage in BRN development, I really think the most important thing to be doing is to benchmark this box against the other better name brand edge boxes like Nvidia and Qualcomm. There need to be comparisons made between the different edge boxes in like for like situations.
So that clear benchmarking can be defined, which can be turned into marketing gold. Less Power, smaller more compact device, with less components ie ( fans )., making the device instantly " greener " and more environmentally friendly. Then technical and performance benchmarks in like for like comparisons. We need to show that BRN / Neuromorphic / Akida is a better option / choice, and we need to clearly define why this is so. Unless Brainchip can show on paper and in real life demonstrations why this product can outperform the competition in clearly defined and understandable benchmarks, then consumers will continue to purchase the name brands every time. Lets hope that VVDN and Brainchip have a great presentation lined up for Jan 12 +
Looks, very impressive to me, the uninitiated " clever dick - sometimes " learner, one.
Dodgy Ness. It's a good time now for you to put some thoughts together, to explain what this edgybox ( The Akida Ballista one ) is, i.e. so that I, and other " not so techy understandy " individuals can grasp this Technology in more detail. It appears to be a capable device, I think !! Perhaps you could explain why and how it is, and it's significance in terms of it's usage and it's current and future applications.
At this time, my head is a bit hurty trying to understand, " what's going on ( pretty similar to the the " Black box " ( that in actual fact is orange in colour in my understanding ) invention some years ago now ), here in Australia. Still not sure what and how that device works. Will this " edgebox " be a game changer at all, now and into the future, and could it improve/replace the " black box " in any way ?.
These questions/thoughts are open to all on this forum, so that I/others can become aware of what this device " edgebox " is designed to achieve, to enable us all to understand it's usefulness, moving forward.
And what could sales of this device bring realistically. I have other questions in regard to this, but they can wait until I've got my head around this edgebox device first.
TIA......
Akida Ballista ( Still, I'm Sure )....
hotty...
Fullmoonfever
Top 20
Nice to see Sony stepping up to neuromorphic as well.
Be great to have a formal link / overlap with Sony / Prophesee / Akida.
Yes, I know we partnered with Prophesee but yet to see where that's truly at yet.
ch.linkedin.com
Sony Europe Schlieren, Zurich, Switzerland
Apply
We look for the risk-takers, the collaborators, the inspired and the inspirational. We want the people who are brave enough to work at the cutting edge and create solutions that will enrich and improve the lives of people across the globe. So, if you want to make the world say wow, let's talk. The conversation starts here. If this role matches your ambitions and skillset, let's get started with your application.
The Stuttgart Laboratory 1 (SL1), which is part of the Sony Corporate Research and Development Center, conducts research in the areas of "Computational Imaging, Perception Systems, RF Communications, Artificial Intelligence and Speech & Sound Processing". SL1 is mainly located at the Stuttgart Technology Center (STC) in Germany, but also includes an office in Zürich, Switzerland. We want to accelerate the redefinition of computer vision based on the distinct characteristics of the novel Event-based Vision Sensor. Therefore, we are looking for a talented, motivated and software affine.
Neuromorphic Computing Research Intern (m/f)
to conduct basic algorithm development, work on demonstration prototypes with sensing and processing hardware and help to build a strong research portfolio from bottom up. This is an Internship or Master Thesis position at SL1 in Zürich, to start preferably in April, 1st 2024.
Your Responsibilities Will Be
Be great to have a formal link / overlap with Sony / Prophesee / Akida.
Yes, I know we partnered with Prophesee but yet to see where that's truly at yet.
Sony Europe sucht Neuromorphic Computing Research Intern in Schlieren, Zürich, Schweiz | LinkedIn
10:04:04 gepostet. We look for the risk-takers, the collaborators, the inspired and the inspirational. We want the…. Sehen Sie sich dieses und weitere Jobangebote auf LinkedIn an.
Neuromorphic Computing Research Intern
Sony Europe Schlieren, Zurich, Switzerland
1 week ago 156 applicants
See who Sony Europe has hired for this role
ApplyWe look for the risk-takers, the collaborators, the inspired and the inspirational. We want the people who are brave enough to work at the cutting edge and create solutions that will enrich and improve the lives of people across the globe. So, if you want to make the world say wow, let's talk. The conversation starts here. If this role matches your ambitions and skillset, let's get started with your application.
The Stuttgart Laboratory 1 (SL1), which is part of the Sony Corporate Research and Development Center, conducts research in the areas of "Computational Imaging, Perception Systems, RF Communications, Artificial Intelligence and Speech & Sound Processing". SL1 is mainly located at the Stuttgart Technology Center (STC) in Germany, but also includes an office in Zürich, Switzerland. We want to accelerate the redefinition of computer vision based on the distinct characteristics of the novel Event-based Vision Sensor. Therefore, we are looking for a talented, motivated and software affine.
Neuromorphic Computing Research Intern (m/f)
to conduct basic algorithm development, work on demonstration prototypes with sensing and processing hardware and help to build a strong research portfolio from bottom up. This is an Internship or Master Thesis position at SL1 in Zürich, to start preferably in April, 1st 2024.
Your Responsibilities Will Be
- Basic algorithm research with event-based vision sensor technology
- Development and implementation of neuromorphic computing algorithms for off-line training and on-line inference of spiking neural networks on neuromorphic hardware
- Benchmarking and comparison of performance (accuracy, latency and energy-efficiency) with conventional computer vision approaches
- Support establishment of a R&D infrastructure which facilitates teamwork for research & development
- Currently pursuing an MSc degree or equivalent in artificial intelligence, computer science or engineering (robotics, mechanical, electrical, or similar)
- Interested in inter-disciplinary research with a brain-inspired computing approach
- Experience with computer vision principles and related linear algebra and machine learning theory
- Experience with event-based cameras, robotics or autonomous vehicles is a plus
- We expect passion for good software with strong skills in Python and related machine learning frameworks (PyTorch). Additionally, knowledge of version control (git) is a plus
- We hope for good communication skills and willingness to work in an agile team
- Excellent oral and written English
TheDrooben
Pretty Pretty Pretty Pretty Good
Interesting comments from Pat Gelsinger......
Running AI applications from far away data centers is too costly for the likes of Microsoft (MSFT.O) and will have to be run on local PCs, Gelsinger said.
"There isn't any possible way that they can have a billion Windows devices hitting Azure to be running these workloads in real time," Gelsinger said
Happy as Larry
Running AI applications from far away data centers is too costly for the likes of Microsoft (MSFT.O) and will have to be run on local PCs, Gelsinger said.
"There isn't any possible way that they can have a billion Windows devices hitting Azure to be running these workloads in real time," Gelsinger said
Happy as Larry
DingoBorat
Slim
Tothemoon24
Top 20
Nokia Announces Speech-Based AI Network Management Tools
Nokia unveiled its cutting-edge AI solutions amid its plans to scale up networks for the industrial metaverse6
MIXED REALITYLATEST NEWS
Published: November 1, 2023
Demond Cureton
Nokia Bell Labs announced on Wednesday a novel natural language processing (NLP) solution for configuring networks using artificial intelligence (AI) and machine learning (ML).
Developed by Nokia Bell Labs’ UNEXT research initiative, the company’s Natural-Language Network is completely transforming how networks operate. This is crucial as the Espoo, Finland-based firm scales up its network infrastructure amid the rise of the industrial metaverse.
The company revealed the new digital tools at the Brooklyn 6G Summit in New York, NY, which took place from 31 Oct to 2 November.
At the event, it stated the new NLP solution can configure networks using prompts and speech. It will also understand user intentions and operate autonomously using its AI neural networking.
Nokia AI Researchers Develops NLP for the Telecom
Using Natural-Language Networks, Nokia can streamline network management with AI, moving away from complex setups to more agile, responsive systems to serve the end user.Artificial intelligence will power the networks, allowing service providers to maintain operations with rapid configuration capabilities. These intelligent systems will also monitor and learn from previous prompts, responses, and other data to optimise networks after each successful request, the company explained.
As the networking tool builds its neural networks across the infrastructure, it can operate without human intervention.
Csaba Vulkan, Network Systems Automation Research Leader, Nokia Bell Labs, said in a statement,
Thank You, Who’s UNEXT?
Nokia Bell Labs created the UNEXT research initiative to support the company’s efforts to innovate its network infrastructure. This has become a key focus of the company as it focuses on the industrial metaverse, which is currently digitally transforming global enterprises with massive results.According to the company, UNEXT draws inspiration from UNIX, the groundbreaking operating system (OS) Bell Labs invented in the 1960s with the Massachusetts Institute of Technology (MIT) and General Electric (GE).
The firm said in a press release that “UNEXT will redefine network software and systems the same way UNIX reshaped computing.”
It aims to achieve this by integrating a host of processes in the telecoms network, effectively evolving the network into an operating system.
Azimeh Sefidcon, Head of Network Systems and Security Research, Nokia Bell Labs, added,
AI to Become Central to Next-Gen Networks
The announcement comes at a critical time when Nokia aims to scale-up its network capacities amid a massive surge in network demand. Many of the world’s tech innovations are now forcing telecoms to rethink their strategies in infrastructural development and solutions, as the former puts exponential pressure on 4G and 5G networks.Unprecedented demand for telecoms bandwidth, speed, and reliability have not only come from consumers and their handheld devices like smartphones and tablets, but also from a growing need for low-latency, high-bandwidth, and high-speed networks to facilitate immersive tools.
Recent global innovations in virtual, augmented, and mixed reality at the consumer, enterprise, and industry are expected to place enormous pressure on telecoms infrastructure leading up to 2030 and beyond.
Thomas Hainzel, Head of Digital Industries Evolution & Partnerships, Nokia, explained to XR Today the challenges that Nokia faces amid the rise of multiple network-intensive metaverses in Industry 4.0.
Nokia is currently developing tools across the technology stack like the Internet of Things, AI, and cloud and edge computing, to secure network integrity and meet sustainability pledges amid future environmental challenges.
World Leaders Focus on AI Safety
However, as companies innovate their offerings with AI, governments are developing their roles in ensuring the safety of their respective citizens, at the national and global level.Nokia’s solution comes just days after United States President Joe Biden signed the Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence.
Hi Hotty,
Akida has 2 basic functions:
A. Classification/Inference;
B. Machine learning.
Using images/video as an example, classification is the identification of an object by comparison of similarity with classes of images in a model library. This is basically a guesstimate (probability).
Machine learning is the addition of new objects to the model library for future comparison.
The old CNN software running on CPU/GPU uses lots of Watts preforming MACs (Multiply Accumulate operations) which are maths heavy calculations. Akida operates on spikes indicating events (changes) which were initially represented by a single digital bit (now up to 4 bits in Akida 1 for increased accuracy). In a digital image, if adjacent pixels have the same illumination, then no event is registered, so no current is drawn by the associated transistors which is why Prophesee is a natural fit for Akida. On the other hand, in old style CNN, each pixel, which may be 16 bits is processed in a MAC processing matrix which involves 16*16 mathematical operations switching one or more transistors.
The new features of TeNNs and ViT are used for classification comparisons.
As we know Akida can be used with any sensor - camera, microphone, chemical sensor, vibration detector, ...
The EB can be used where signals from a number of sensors need to be classified.
This could be in a supermarket processing video images from all the checkouts to determine the price from a model and for stocktake purposes.
It can be used in a factory with many machines to determine if vibration indicates a need for maintenance.
https://brainchip.com/brainchip-previews-industrys-first-edge-box-powered-by-neuromorphic-ai-ip/
Designed for vision-based AI workloads, the compact Akida Edge box is intended for video analytics, facial recognition, and object detection, and can extend intelligent processing capabilities that integrate inputs from various other sensors. This device is compact, powerful, and enables cost-effective, scalable AI solutions at the Edge.
BrainChip’s event-based neural processing, which closely mimics the learning ability of the human brain, delivers essential performance within an energy-efficient, portable form factor, while offering cost-effectiveness surpassing market standards for edge AI computing appliances. BrainChip’s Akida neuromorphic processors are capable of on-chip learning that enables customization and personalization on device without support from the cloud, enhancing privacy and security while also reducing training overhead, which is a growing cost for AI services.
“BrainChip’s neuromorphic technology gives the Akida Edge box the ‘edge’ in demanding markets such as industrial, manufacturing, warehouse, high-volume retail, and medical care,” said Sean Hehir, CEO of BrainChip. “We are excited to partner with an industry leader like VVDN technologies to bring groundbreaking technology to the market.”
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