D
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Come along way since this presentation from 2019
BRN Discussion Ongoing
- Thread starter TechGirl
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SERA2g
Founding Member
You’ve come out of no where, spread negativity but won’t provide responses to questions?
Happy for you to be bearish but please parlay. Don’t just throw mud and walk away.
D
Deleted member 118
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Check out this link:BrainChip mention by Toshiba director
View attachment 34860
View attachment 34861
While NVIDIA is the current leader in specialized AI hardware with their Tensor Cores optimized for matrix multiplication used in deep learning, don’t overlook IBM, Intel, BrainChip, and others. | Jason Vu
While NVIDIA is the current leader in specialized AI hardware with their Tensor Cores optimized for matrix multiplication used in deep learning, don’t overlook IBM, Intel, BrainChip, and others. IBM’s neurosynaptic chips and Intel’s Loihi chip are neck to neck in neuromorphic computing...www.linkedin.com
Next-Level Neuromorphic Computing: Intel Lab's Loihi 2 Chip
Intel Lab’s Loihi 2 chip delivers outstanding performance & new features, including an open-source, community-driven neuromorphic computing framework.
It's nice to get a mention here but it's interesting how IBM's chip and Intel's Loihi 2 get kudos over AKIDA (I recall posters suspecting that Intel was perhaps deferring to AKIDA as the superior chip). Do we actually have a 3 year lead because it raises the old fear that one of the big companies will run over us with neuromorphic technology.
Is it possible that potential customers are waiting until the last minute to see which horse to back in the neuromorphic race?
Intel is also mentioned: 'We now have access to Intel Neuromorphic Research Consortium and are using it for other projects'. This after mentioning early access to Brainchip's AKIDA.I just stumbled across this which has mention to brainchip and it ties up nicely with nasa and its good to see they choose brainchip ahead of Loihi
You’ll need to download the full pdf
Robust Classification of Contraband Substances using Longwave Hyperspectral Imaging and Full Precision and Neuromorphic Convolutional Neural Networks
Several agencies such as the US Department of Homeland Security (DHS) seek to improve the detection of illegal threats and materials passing through P…pdf.sciencedirectassets.com
This research was conducted prior to AKIDA1500 release with transformers so perhaps this would leave Loihi in the dust.
Fullmoonfever
Top 20
So....we have a release not long ago confirming partnership with BRE on tactical edge products for the military.
There is a US defence & commercial sensing conference coming up.
Conference 12538
One of the presentations caught my eye...not to say is about Akida but is in the realm of what BRE and BRN are working in.
The other fun fact ...the presenter is obviously military but currently pursuing his PhD in Computer Science and Machine Learning Operations at Carnegie Mellon University.
Would expect will have some exposure to Akida?
spie.org
Paper 12538-28
Commanders must remain agile and adaptive in the future Artificial Intelligence (AI)-enabled multi-domain battlespace, where critical decisions are made at the tactical edge. Over-reliance on static, cloud-centric approaches to Machine Learning Operations (MLOps) compromises such agility and adaptability. These systems must operate in a dynamic threat environment, and learn to detect novel threats during operation. They must be able to perform this learning through the execution of tactical MLOps under austere and degraded conditions, especially limited wireless network bandwidth. In response to these requirements, this paper describes Hawk, a system that leverages edge proximity for rapid and iterative execution of the Observe stage of the Observe-Orient-Decide-Act loop. Central to this architecture is the use of tactical cloudlets. These mini data centers provide cloud-like computing resources without the communication latency to exascale data centers. Hawk enables a human to guide MLOps at low cognitive load, thus enabling an operational objective to be achieved at speed and scale while remaining usable and explainable.
Carnegie Mellon Univ. (United States)
MAJ Eric Sturzinger is a Network Systems Engineer (FA26A) who has served as a platoon leader and company executive officer before becoming the systems engineer for both a tactical signal brigade and expeditionary signal battalion. From 2017-2020, MAJ Sturzinger served as an Instructor and Assistant Professor in the Department of Electrical Engineering and Computer Science at the United States Military Academy. His most recent assignment was to the Artificial Intelligence Integration center (AI2C) in Pittsburgh, PA as a Senior Data Engineer and is currently pursuing his PhD in Computer Science and Machine Learning Operations at Carnegie Mellon University. His research interests include Future Internet Architectures, Edge Computing, Machine Learning Operations, Reinforcement Learning, Artificial Intelligence, and Geopolitics.
There is a US defence & commercial sensing conference coming up.
Conference 12538
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V
1 - 4 May 2023 | Tampa 2Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V, Conference Details
View program details for SPIE Defense + Commercial Sensing conference on Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V
spie.org
One of the presentations caught my eye...not to say is about Akida but is in the realm of what BRE and BRN are working in.
The other fun fact ...the presenter is obviously military but currently pursuing his PhD in Computer Science and Machine Learning Operations at Carnegie Mellon University.
Would expect will have some exposure to Akida?
Tactical agility for AI-enabled multi-domain operations
Commanders must remain agile and adaptive in the future Artificial Intelligence (AI)-enabled multi-domain battlespace, where critical decisions are made at the tactical edge. Over-reliance on static, cloud-centric approaches to Machine Learning Operations (MLOps) compromises such agility and...
Paper 12538-28
Tactical agility for AI-enabled multi-domain operations
2 May 2023 • 3:10 PM - 3:30 PM EDT | Tampa 2Commanders must remain agile and adaptive in the future Artificial Intelligence (AI)-enabled multi-domain battlespace, where critical decisions are made at the tactical edge. Over-reliance on static, cloud-centric approaches to Machine Learning Operations (MLOps) compromises such agility and adaptability. These systems must operate in a dynamic threat environment, and learn to detect novel threats during operation. They must be able to perform this learning through the execution of tactical MLOps under austere and degraded conditions, especially limited wireless network bandwidth. In response to these requirements, this paper describes Hawk, a system that leverages edge proximity for rapid and iterative execution of the Observe stage of the Observe-Orient-Decide-Act loop. Central to this architecture is the use of tactical cloudlets. These mini data centers provide cloud-like computing resources without the communication latency to exascale data centers. Hawk enables a human to guide MLOps at low cognitive load, thus enabling an operational objective to be achieved at speed and scale while remaining usable and explainable.
Presenter
Eric M. SturzingerCarnegie Mellon Univ. (United States)
MAJ Eric Sturzinger is a Network Systems Engineer (FA26A) who has served as a platoon leader and company executive officer before becoming the systems engineer for both a tactical signal brigade and expeditionary signal battalion. From 2017-2020, MAJ Sturzinger served as an Instructor and Assistant Professor in the Department of Electrical Engineering and Computer Science at the United States Military Academy. His most recent assignment was to the Artificial Intelligence Integration center (AI2C) in Pittsburgh, PA as a Senior Data Engineer and is currently pursuing his PhD in Computer Science and Machine Learning Operations at Carnegie Mellon University. His research interests include Future Internet Architectures, Edge Computing, Machine Learning Operations, Reinforcement Learning, Artificial Intelligence, and Geopolitics.
Everyone else missed it by ... "That much !!"
Damo4
Regular
Don't forget what Z said, it only takes 3-5 people to judge a post. If you have an account with good standing, we can report anything breaking the rules.
No point arguing with the uneducated, you have better things to do lads. They'll have the egg on the face soon enough and then you can reply to their messages
No point arguing with the uneducated, you have better things to do lads. They'll have the egg on the face soon enough and then you can reply to their messages
D
Deleted member 118
Guest
Yes it’s weird how so many posts were reported after a certain person joined the site, or just maybe coincidenceDon't forget what Z said, it only takes 3-5 people to judge a post. If you have an account with good standing, we can report anything breaking the rules.
No point arguing with the uneducated, you have better things to do lads. They'll have the egg on the face soon enough and then you can reply to their messages
View attachment 34866
EDIT: link doesn’t copy here without Financial Times subscription 
Article was about ARM producing their own chip.
https://www.ft.com/content/72897dde-2d84-48b1-8bd7-390e66049d40
The company will team up with manufacturing partners to develop the new chip, according to people briefed on the move who describe it as the most advanced chipmaking effort the Cambridge-headquartered group has ever embarked upon.
However, multiple industry executives told the FT that its newest chip — on which it started work in the past six months — is “more advanced’ than ever before. Arm has also formed a bigger team that will execute the effort and is targeting the product at chip manufacturers more than software developers, they said. The company has built a new “solutions engineering” team that will lead the development of these prototype chips for mobile devices, laptops and other electronics, according to people briefed on the move.
Article was about ARM producing their own chip.
https://www.ft.com/content/72897dde-2d84-48b1-8bd7-390e66049d40
The company will team up with manufacturing partners to develop the new chip, according to people briefed on the move who describe it as the most advanced chipmaking effort the Cambridge-headquartered group has ever embarked upon.
However, multiple industry executives told the FT that its newest chip — on which it started work in the past six months — is “more advanced’ than ever before. Arm has also formed a bigger team that will execute the effort and is targeting the product at chip manufacturers more than software developers, they said. The company has built a new “solutions engineering” team that will lead the development of these prototype chips for mobile devices, laptops and other electronics, according to people briefed on the move.
Tothemoon24
Top 20
Chip designer Arm makes its own advanced prototype semiconductor
Company to build test chip with factory partners, stoking fears it could in future compete with its biggest customersin London 6 HOURS AGO 41 Arm Ltd news. Arm is developing its own chip to showcase the capabilities of its designs, as the SoftBank-owned group seeks to attract new customers and fuel growth following a blockbuster IPO later this year. The company will team up with manufacturing partners to develop the new chip, according to people briefed on the move who describe it as the most advanced chipmaking effort the Cambridge-headquartered group has ever embarked upon. The effort comes just as SoftBank seeks to drive up Arm’s profits and attract investors to a planned listing on New York’s Nasdaq exchange. The company traditionally sells its blueprint designs to chip manufacturers, rather than getting involved directly in the development and production of semiconductors itself. The hope is that the prototype will allow it to demonstrate the power and capabilities of its designs to the wider market. Arm has previously built some test chips with partners including Samsung and Taiwan Semiconductor Manufacturing Co, largely aimed at enabling software developers to gain familiarity with new products. However, multiple industry executives told the FT that its newest chip — on which it started work in the past six months — is “more advanced’ than ever before. Arm has also formed a bigger team that will execute the effort and is targeting the product at chip manufacturers more than software developers, they said. The company has built a new “solutions engineering” team that will lead the development of these prototype chips for mobile devices, laptops and other electronics, according to people briefed on the move. The solutions engineering arm is led by chip industry veteran Kevork Kechichian, who joined Arm’s top executive team in February. He has held previous roles at chipmakers NXP Semiconductors and Qualcomm, overseeing the development of the San Diego-based company’s flagship Snapdragon chip. The team will also expand on Arm’s existing efforts to enhance the performance and security of designs, as well as bolster developer access to its products. Rumblings about Arm’s chipmaking moves have stoked fears in the semiconductor industry that if it makes a good enough chip, it could seek to sell it in the future and thereby become a competitor to some of its biggest customers, such as MediaTek or Qualcomm. People close to Arm insist there are no plans to sell or license the product and that it is only working on a prototype. Arm declined to comment. Any move to build chips for wider commercial sale would undermine Arm’s position as the “Switzerland” of the semiconductor industry, selling designs to almost all mobile device chipmakers while not directly competing with them. Its neutral model has led to its products being found in more than 95 per cent of smartphones, with customers including Qualcomm, MediaTek and Apple. “Working on intellectual property is one thing but really designing and working with production partners to turn those efforts into physical chips is a totally different arena. It’s more capital intensive,” a former Arm executive with knowledge of the effort told the FT. “At some point in the future [Arm] will definitely need returns to justify that massive investment.” SoftBank’s push for growth has led Arm to seek out changes to its commercial practices. The chip designer has sought to increase prices and overhaul its business model by charging royalties to device-makers rather than some of its chipmaker customers, the FT reported last month. Recommended Arm Ltd SoftBank’s Masayoshi Son set to sign off on Nasdaq listing for Arm Arm acknowledged in its annual report published last week that a principal risk to its business was the “significant concentration” in its customer base. Arm’s top 20 customers accounted for 86 per cent of revenues last year, so “the loss of a small number of key customers could significantly impact the group’s growth”. That warning came with Arm currently embroiled in a bitter legal dispute with Qualcomm, one of its largest customers, after it accused the chipmaker of using some of its designs without having procured the necessary licence. There are also widespread concerns in the industry that in-house chips developed by Apple, Arm’s largest customer, are outperforming those made by competitors such as Qualcomm and MediaTek. “Google thought it could demonstrate the world’s best Android OS so it built the Pixel phone. Microsoft thought it was the master of Windows so it built Surface laptops. So, naturally, Arm thinks it can build best-in-class Arm-based chips, better than chip developers out there,” said Brady Wang, a semiconductor analyst with Counterpoint Research. But making chips is even more challenging than building devices, Wang said. “It will need generation after generation of development efforts.” Additional reporting by Christian Davies in Seoul Copyright.
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So....we have a release not long ago confirming partnership with BRE on tactical edge products for the military.
There is a US defence & commercial sensing conference coming up.
Conference 12538
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V
1 - 4 May 2023 | Tampa 2
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V, Conference Details
View program details for SPIE Defense + Commercial Sensing conference on Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications Vspie.org
One of the presentations caught my eye...not to say is about Akida but is in the realm of what BRE and BRN are working in.
The other fun fact ...the presenter is obviously military but currently pursuing his PhD in Computer Science and Machine Learning Operations at Carnegie Mellon University.
Would expect will have some exposure to Akida?
Tactical agility for AI-enabled multi-domain operations
Commanders must remain agile and adaptive in the future Artificial Intelligence (AI)-enabled multi-domain battlespace, where critical decisions are made at the tactical edge. Over-reliance on static, cloud-centric approaches to Machine Learning Operations (MLOps) compromises such agility and...
Paper 12538-28
Tactical agility for AI-enabled multi-domain operations
2 May 2023 • 3:10 PM - 3:30 PM EDT | Tampa 2
Commanders must remain agile and adaptive in the future Artificial Intelligence (AI)-enabled multi-domain battlespace, where critical decisions are made at the tactical edge. Over-reliance on static, cloud-centric approaches to Machine Learning Operations (MLOps) compromises such agility and adaptability. These systems must operate in a dynamic threat environment, and learn to detect novel threats during operation. They must be able to perform this learning through the execution of tactical MLOps under austere and degraded conditions, especially limited wireless network bandwidth. In response to these requirements, this paper describes Hawk, a system that leverages edge proximity for rapid and iterative execution of the Observe stage of the Observe-Orient-Decide-Act loop. Central to this architecture is the use of tactical cloudlets. These mini data centers provide cloud-like computing resources without the communication latency to exascale data centers. Hawk enables a human to guide MLOps at low cognitive load, thus enabling an operational objective to be achieved at speed and scale while remaining usable and explainable.
Presenter
Eric M. Sturzinger
Carnegie Mellon Univ. (United States)
MAJ Eric Sturzinger is a Network Systems Engineer (FA26A) who has served as a platoon leader and company executive officer before becoming the systems engineer for both a tactical signal brigade and expeditionary signal battalion. From 2017-2020, MAJ Sturzinger served as an Instructor and Assistant Professor in the Department of Electrical Engineering and Computer Science at the United States Military Academy. His most recent assignment was to the Artificial Intelligence Integration center (AI2C) in Pittsburgh, PA as a Senior Data Engineer and is currently pursuing his PhD in Computer Science and Machine Learning Operations at Carnegie Mellon University. His research interests include Future Internet Architectures, Edge Computing, Machine Learning Operations, Reinforcement Learning, Artificial Intelligence, and Geopolitics.
The other fun fact ...the presenter is obviously military but currently pursuing his PhD in Computer Science and Machine Learning Operations at Carnegie Mellon University.
Would expect will have some exposure to Akida?
Very much the chicken and egg question ...
As far as AI goes, Helium is very light weight compared to Akida.EDIT: link doesn’t copy here without Financial Times subscription
Article was about ARM producing their own chip.
https://www.ft.com/content/72897dde-2d84-48b1-8bd7-390e66049d40
The company will team up with manufacturing partners to develop the new chip, according to people briefed on the move who describe it as the most advanced chipmaking effort the Cambridge-headquartered group has ever embarked upon.
However, multiple industry executives told the FT that its newest chip — on which it started work in the past six months — is “more advanced’ than ever before. Arm has also formed a bigger team that will execute the effort and is targeting the product at chip manufacturers more than software developers, they said. The company has built a new “solutions engineering” team that will lead the development of these prototype chips for mobile devices, laptops and other electronics, according to people briefed on the move.
Arm has previously built some test chips with partners including Samsung and Taiwan Semiconductor Manufacturing Co, largely aimed at enabling software developers to gain familiarity with new products. However, multiple industry executives told the FT that its newest chip — on which it started work in the past six months — is “more advanced’ than ever before.
Akida is "more advanced" than Helium.
BrainChip joined ARM's Partner Program 11 months ago, so they have been sitting on their hands for 5 months.
Rumblings about Arm’s chipmaking moves have stoked fears in the semiconductor industry that if it makes a good enough chip, it could seek to sell it in the future and thereby become a competitor to some of its biggest customers, such as MediaTek or Qualcomm. People close to Arm insist there are no plans to sell or license the product and that it is only working on a prototype. Arm declined to comment. Any move to build chips for wider commercial sale would undermine Arm’s position as the “Switzerland” of the semiconductor industry, selling designs to almost all mobile device chipmakers while not directly competing with them. Its neutral model has led to its products being found in more than 95 per cent of smartphones, with customers including Qualcomm, MediaTek and Apple. “Working on intellectual property is one thing but really designing and working with production partners to turn those efforts into physical chips is a totally different arena. It’s more capital intensive,” a former Arm executive with knowledge of the effort told the FT. “At some point in the future [Arm] will definitely need returns to justify that massive investment.”
... and where are all the "former ARM executive(s)" working?
Fullmoonfever
Top 20
Very true.
wilzy123
Founding Member
This is a great analysis
First there was SiFive and Akida (April 2022).
Then BrainChip joined the ARM Partners program (May 2022).
Then we had the announcement that Akida was compatible with the whole ARM range.
Then there is the upcoming ARM/Akida presentation in a month ...
Now ARM is producing a "more advanced" SoC, presumably because its performance is like science fiction which customers will not believe until they see it working.
... and, @Bravo , there's poor old Qualcomm stuck with their in-house AI.
Tothemoon24
Top 20
What happens next Dio ?
Sorry, I've run out of shilling pieces for the meter on my crystal ball.
Frangipani
Top 20
Mmmh, I wonder why, of all animals, iniVation would pick an image of a kangaroo to illustrate the key features of their all-new Aeveon sensor technology…
For a company based in Switzerland, obvious choices would have been a dairy cow, an Alpine ibex, a chamois, an Alpine marmot or a golden eagle.
Of course it could be mere coincidence or even a red herring. But how probable is that?
Edit: Right after hitting the send button, it occurred to me that this might be a wallaby rather than a roo… Sorry!
Technology
Technology Pioneers in neuromorphic vision The founders of iniVation invented the field of neuromorphic vision, which mimics key features of the human visual system. Our patented Dynamic Vision Sensor (DVS) transmits binary pixel-level change events, at microsecond time resolution. This...
inivation.com
Pioneers in neuromorphic vision
The founders of iniVation invented the field of neuromorphic vision, which mimics key features of the human visual system. Our patented Dynamic Vision Sensor (DVS) transmits binary pixel-level change events, at microsecond time resolution. This approach is equivalent to a high-speed camera at thousands of frames per second – but with far less data. The advantages include:
High speed (equivalent 10k+ fps) and very low latency (< 1 ms)
High dynamic range (over 120 dB)
Longer battery life
Reduced data rate
Aeveon™ – Redefining vision sensing
With our all-new Aeveon™technology, we are changing the game again. A new Adaptive Event Vision™ unified pixel architecture enables every pixel to generate multiple types of events:
Binary change events as with the legacy DVS
Multi-bit change events
Full frame readout
Region events
A state-of-the-art stacked sensor design with massively parallel Adaptive Event Cores produces a rich, highly compressed output stream. It combines the speed advantages of legacy DVS with the high fidelity of frame-based sensors.
Key Features
Lossless image reconstruction using adaptive multi-bit events.
Multiple dynamic regions of interest (ROIs) enable valuable bandwidth to be focused on the most critical regions of the scene, and updated on-the-fly.
On-sensor fast lossless compression, based on regions and motion information, saving up to 80% data.
Self-adapting smart pixels provide native high-dynamic range (HDR) output and minimize noise, particularly in low light.
Real world integration features
Anti Flicker
Remove artefacts caused by illumination variation
Improve quality for consumer imaging and automotive
Small pixel size enables high resolution
Stacked design enables pixels down to 1.5 µm or less
Full 1:1 events or frames from every pixel
Flexible architecture
Can be used directly with custom pixels (infrared, automotive, etc.)
Software compatibility
Works with all existing frame-based and event-based vision software
Protect your software investment
Aeveon application benefits
Automotive
Low-latency HDR vision
In-cabin observation
AR/VR
Low-latency fast scene camera
Fast, low-power eye tracking
SLAM
Mobile
HDR imaging, anti-blur
Ultra-high-speed video
Mobile robotics
Low-latency HDR vision
Fast SLAM, tracking
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