Quatrojos
Regular
I started a new thread. It's like, 'BRN/Vorago, Telstar, KT, Mercedes Benz, BRN' on repeat...
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
Ah no offence intended but methinks it depends entirely on the duration of the flight and the urgency at which one requires a top-up, what....
Fox151
Regular
If it's qantas and free... you don't muck around.
D
Deleted member 118
Guest
Morning FF
Thought you might like a Sunday read.
Thought you might like a Sunday read.
Me too!!!Have just seen and corrected its JoMo68 who has organised a table for 20 for the Melbourne chapter at Harlow in Richmond at 6.30 pm on 15 March coming up.
Sorry for mangling your nom de plume Jo.
Will be there with bells on
Dang Son
Regular
Hi FF
From my perspective I would like to see our company progress in the publication of claimed accuracies
I remember covid19 has since been said to be ^98% accurate but I haven't yet seen the peer review that was threatened about 2 yrs ago.
Imo More Published Accuracies would provide the market with greater confidence in AKIDA without breaching any NDA.
Fact Finder
Top 20
If you are referring to peer reviewed published papers then they would have to breach NDAs as they have to provide a full and complete description of what they did and what they used so that someone else can repeat the experiment and obtain the same results.
The fact that the peer reviewed papers have not yet been published means they are still working with the NDA protected companies.
The Mercedes partnership has potentially a range of peer reviewed papers that Brainchip could publish but this will only be possible when Mercedes says go for it.
The day that Brainchip has complete freedom to publish peer reviewed papers is some distance in the future in my opinion but I look forward to that day along with yourself and all other shareholders.
My opinion only DYOR
FF
AKIDA BALLISTA
Learning
Learning to the Top 🕵♂️
Fact Finder
Top 20
Hi Rocket
Nice read.
There are three takeaways for me:
1. The speed of change is going to require flexibility. The authors see that flexibility being a driver of software solutions as hardware cannot be easily updated or retrained. The authors clearly have not heard of AKIDA technology and it’s on chip learning. (The audience goes quiet absorbing the enormity of this technology breakthrough then thunderous applause.)
2. The following extract regarding ARM opens up the prospects for some very close relationship with Brainchip. In what form is the billions and billions of dollars question???
“Arm Will be Forced to Change Its Business Model to Sustain Innovation
It was announced over a year ago that an agreement had been reached for NVIDIA to acquire Arm for US$40 billion, despite the takeover still needing approval from the European Union (EU) and several regulators around the world, as well as from Arm’s IP licensees. However, this development has uncovered numerous concerns about Arm’s future, and chief among them is the lack of synergy needed to transform itself and grow beyond just licensing its IP. Arm is in crucial need of expanding its engineering resources, while revamping its business model and technology offerings, if it wants to cope effectively with the phenomenal demand for technology innovation required to sustain the mobile and the computing ecosystems, and to become a key solution provider for the markets it serves.
With or without the NVIDIA acquisition, if Arm’s Research and Development (R&D) and engineering resources do not evolve in line with market demand for innovation, then the entire industry will be slowed because it is Arm’s Instruction Set Architectures (ISAs) and micro-architectures that are the foundation platforms for innovation in the mobile computing markets. Therefore, it will be incumbent on the industry to inject billions of dollars to expand Arm’s R&D and sustain innovation because the company cannot achieve this objective under the current status quo. If this is not addressed, then Arm will not be able to execute on its ambitious plans with the resources it has currently, which could become a major issue that will affect the entire industry.”
3. Further evidence that Brainchip is in the right place ahead of all the world with its COTs AKD1000 chip, IP and product pipeline and ongoing planned AKD2000, AKD500, AKD1500, AKD3000, AKD4000, AKD5000.
“The Proliferation of TinyML
TinyML is already showing massive potential and will be on the path to becoming the largest segment of the edge Machine Learning (ML) market by shipment volume. ABI Research forecasts total shipments of 1.2 billion devices with TinyML chipsets in 2022. This means more devices will be shipped with TinyML chipsets, as compared to those with edge ML chipsets. In addition, the proliferation of ultra-low-power ML applications means more brownfield devices will also be equipped with ML models for on-device anomaly detection, condition monitoring, and predictive maintenance.
The Commercialization of the Neuromorphic Chipset
With the recent release of Intel’s Loihi 2 neuromorphic chip, research in neuromorphic and Spiking Neural Networks (SNNs) will increasingly involve the industry and provide a hint about the sort of commercial Artificial Intelligence (AI) applications in which these networks can integrated. Other neuromorphic chipset vendors to take note of are BrainChip and GrAI Matter Labs. Neuromorphic chips can implement the currently popular Deep Neural Networks (DNNs) as well. However, the use of SNNs will provide the most significant benefits in the long term, with superior performance in latency response and energy efficiency.”
My opinion only DYOR
FF
AKIDA BALLISTA
Dang Son
Regular
Thanks FF, for your Professional View , correcting my lay opinion.
I guess I was wrong in hoping that publishing accuracies might be a legitimate avenue for the company to validate sensor accuracy claims to the market and potentially prevent some of the share price slippage that we have experience lately.
Kind Regards
Fact Finder
Top 20
Hi Deng
This should not be seen as a problem. The failure to publish is a product of a highly ethical company building trusted relationships with its customers and the scientific community generally.
The papers that have been published in respect of AERO using the ADE to identify the 20 gas data set WITH A STATE OF THE ART PERFORMANCE has never been questioned.
I can guarantee that academics and competitors would have been secretly running the experiment again and again to find a flaw so they could publish that the science was flawed. It was published in 2019 and not a single negative response.
The same thing would be taking place with the more recent paper regarding Malt. To date nothing negative.
Peer reviewed scientific publications are incredibly important and cannot be fudged in anyway otherwise the scientists involved can have their reputations and credibility destroyed.
Brainchip is releasing information all the time. When Peter van der Made presented in November 2020 at BIC that AKD1000 engineering sample was 178 times more power efficient than Loihi that was a very brave statement to make.
It is now 2022 and there has never been any question from Intel that this statement was wrong or flawed in some fashion.
The science is there for the market to see and the validation is also there with the companies who are early adopters Mercedes, Valeo, NASA, Vorago and licensees Renesas and MegaChips.
The share price is what it is and is nothing to do with anything at the moment other than world wide economic and political tensions and some activist shorting.
My opinion only DYOR
FF
AKIDA BALLISTA
Dang Son
Regular
Is GrAI Matter Labs a competitor Chip?
GrAI Matter Labs | Fastest Edge AI Processor
GrAI Matter Labs has created the fastest edge AI processor for machine vision in robotics, AR/VR, drones and more. It achieves ultra-low latency at low power by leveraging sparsity.
www.graimatterlabs.ai
D
Deleted member 118
Guest
D
Deleted member 118
Guest
Another mention of BRN and the 2nd link more of a Sunday read and also mentions BRN
ARTIFICIAL INTELLIGENCE: ITS EVOLVING NATURE AND FUTURE PROSPECTS
ARTIFICIAL INTELLIGENCE: ITS EVOLVING NATURE AND FUTURE PROSPECTS
thelittleshort
Top Bloke
Hey @Fact Finder
Should probably know this but what differentiates the subsequent iterations of the Akida suite vs AKD1000 ie AKD2000, AKD500, AKD1500, AKD3000, AKD4000, AKD5000 - size, capabilities etc?
I’m relatively late to the Brainchip party and am furiously playing catch up
Cheers
TLS
Dhm
Regular
I have mentioned Chris Ciovacco before , and probably will continue to do so. He puts out a weekly video that speaks to probabilities of continuing bullishness in US equity markets. He is rock solid. This weeks video is no different. If you choose to watch it, it may help to put the playback speed to 1.5 or 1.75 in the settings icon.
Fact Finder
Top 20
Hi tls
The best person to speak to this would be Peter van der Made however we have the second best in Dio so I will leave it to him to deal with in detail. He has addressed this issue before and has kept the slide put out by Brainchip with the plan for these devices.
I can say in a purely non technical sense that AKD500 was a cheaper smaller version of AKD1000 aimed at white goods like fridges. AKD1500 quoting Dio was AKD1000 with a little bit of LSTM added. AKD2000 has the full blown LSTM on board a must for ADAS and AV allowing for prediction from given events ie; ball rolling out from between parked cars could be followed by child, stroller coming out from parked cars, drunk staggering around at edge of the road could fall into path of vehicle type of things.
AKD3000 is the biggie as it is looking to implement a cortical column for advanced thinking on chip so that the current cochlear implant for example could produce real sounds for the wearer or it could be used as the foundation for a bionic eye that restores vision. I believe AKD4000 and AKD5000 are approaching true artificial general intelligence and will replace Fact Finder on here.
Seriously though Dio is the best one to give you the story.
My opinion only DYOR
FF
AKIDA BALLISTA
I
Ilovepie
Guest
This is a bit out of context. I mentioned BRN to some friends. I am not really technically so I tried my best to explain the technology. So far so on. They thought it was a ridiculous technology and they called me stupid for not understanding the tech 100%. So the guys i showed BRN stock they end up buying the stock and they are saying they didn't buy it because of me and they are not telling me anything about how much they invested or anything they just kept everything a secret, they didn't even say thanks and took all the credit. Wow this was really a stab to my soul haha "Friends"... 
Fact Finder
Top 20
Every producer of semiconductors is a competitor to Brainchip.Is GrAI Matter Labs a competitor Chip?
GrAI Matter Labs | Fastest Edge AI Processor
GrAI Matter Labs has created the fastest edge AI processor for machine vision in robotics, AR/VR, drones and more. It achieves ultra-low latency at low power by leveraging sparsity.
The better question to ask is can GrAi compete with Brainchip. The answer to which is no not at present.
GrAi are doing a simple SNN chip. Brainchip is doing an SCNN chip. Brainchip does one shot and incremental learning and CNN to SNN conversion on chip. AKIDA can as a result learn and adapt and be taught new information after commencing operation.
On GrAi's site it refers to the advantages of using SNN in a camera door bell from a power perspective. GrAi using SNN saves power on your door bell by only processing relevant events and is told at the factory what the relevant events are that it needs to process. Great idea. Saves power.
Brainchip's AKIDA on the other hand uses SNN and saves power however as Brainchip's Anil Mankar and others have stated it can be shown the images (or the real persons) who live at the address or who are permitted access and it will then only react to those persons who are not entitled to be there and ring the bell. If after some months Christmas arrives and guests come to stay you can add their images for the duration of their stay. If you sell the property the system might be considered a fixture and need to be left. You could cancel all the existing images and the new owners can then add themselves.
On top of this GrAi appears to only be capable of processing one sense at a time whereas Brainchip makes the point that it can process all five senses plus Lidar, Radar, Sonar etc on AKD1000.
So as I said at the beginning the question is not are they a competitor but can they compete.
The other thing to consider is something which over on HC the trolls used to attack Brainchip on was the low cost of the AKD1000 at $US10 to $US15. The thing about this is that by being so cheap and even much, much cheaper if you take only a couple of nodes via the IP sales model you can get all these features for a ridiculously low price so that even if a company like GrAi is tendering along side Brainchip their more powerful self learning one shot training chip will be the better choice.
If you go into a car dealer and they say this is the base model but you can have the AMG version with all the upgrades for exactly the same price I would suggest on 99 out of 100 occasions you are going to take the AMG version.
My opinion only DYOR
FF
AKIDA BALLISTA
Fact Finder
Top 20
Hi Rocket
The first paper has been posted before might even have been by me. LOL Good read and of course gives Brainchip a rap.
The second report is written by someone who does not know what Ai actually is or that AKIDA is digital technology and not affected by Analog issues but the Brainchip name is getting out there:
3.4 AI Hardware Compared to the intensive innovative effort observed for each of the three algorithm-oriented domains, Hardware is a niche domain with only approximately 2000 inventions published in 2008-2017 (Exhibit 8). As observed, long-existing graphics processing units (GPUs), central processing units (CPUs) and field-programmable gate arrays (FPGAs) account for about 50% of the innovation activity in this domain and are considered to be the current state of the art in providing computing power to AI platforms. The significantly lower innovation focus in this domain suggests that current hardware is sufficient for most of the present AI applications. Though CPUs, GPUs, and FPGAs are already well-established, advancements in semiconductor technology have been made to develop more powerful, faster CPUs and GPUs capable of handling large amount of data and complex algorithms. FPGAs are also gaining traction as an important tool to research new AI algorithms, to train AI systems and enable low-volume deployment. Interestingly, 99% of inventions relating to CPUs also involve either GPUs or FPGAs, suggesting that a combinational use of them may be the optimal solution to power an AI system. The commercial availability of CPUs, GPUs and FPGAs present them as convenient options for market adoption. However, AI-specific processors are also being developed for specific AI uses. Neuromorphic chips, accounting for 3% of the inventions in hardware, promises to handle larger, more complex datasets with less energy and power consumption, making them useful for AI applications at the edged . An example is Brainchip’s Akida NSoC, suitable for advanced driver assistance systems (ADAS), autonomous vehicles, drones, vision-guided robotics, surveillance and machine vision systems [12] . However, neuromorphic chips face a key obstacle to mass deployment in AI platforms in the precise control of the analog signalling intensity [12] [13]. This has been an area of research interest for many players in the neuromorphic chip space. As AI-systems get increasingly sophisticated with burgeoning needs to handle larger, more complex data, the demands on computing power will increase. It would be a matter of time that the computing power of GPUs, FPGAs and CPUs will not meet the demands of AI, calling for a need to research and develop new processing units.
My opinion only DYOR
FF
AKIDA BALLISTA
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