Pom down under
Top 20
I wonder if you can buy a paper copy as I’m getting a new puppy very soon and it will need to be toilet trained
A good deal perhaps.
BRN Discussion Ongoing
- Thread starter TechGirl
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DingoBorat
Slim
Geisel Software — Robotics, AI/ML, & IOT Custom Software
Geisel Software – our expertise in robotics, AI/ML, and IoT transforms your challenges into success stories with performant & cost-efficient solutions.geisel.software
More importantly, the "right" kind of pies
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They seem to be a relatively small player though, just going on a less than half the LinkedIn following, we have..
Worcester's Geisel Software CEO wins SBA business person of year
Brian Geisel is the CEO of Geisel Software, a firm based at 67 Millbrook St. whose clients include iRobot, the U.S. Department of Veterans Affairs, Carbon Black and PharmAdva.
This is from 4 years ago, but shows they are a rapidly growing Company, well respected in their business community and definitely dealing with us, in my opinion.
Some relevant quotes from the article.
"Revenue has grown by a compounded annualized rate of 83% since 2017, according to the company" (to 2020, shows they know how to conduct business)
"Geisel Software specializes in customized software development, particularly in robotics but also in medical devices"
"Geisel has been quoted as an industry expert by Entrepreneur Magazine, Bloomberg Business, BBC, Forbes and others, the company said"
They are advertising Pico for us, but their interest, is most probably in TENNs?..
Or both me thinks. Narrow it down to to Brainchip products.Worcester's Geisel Software CEO wins SBA business person of year
Brian Geisel is the CEO of Geisel Software, a firm based at 67 Millbrook St. whose clients include iRobot, the U.S. Department of Veterans Affairs, Carbon Black and PharmAdva.www.wbjournal.com
This is from 4 years ago, but shows they are a rapidly growing Company, well respected in their business community and definitely dealing with us, in my opinion.
Some relevant quotes from the article.
"Revenue has grown by a compounded annualized rate of 83% since 2017, according to the company" (to 2020, shows they know how to conduct business)
"Geisel Software specializes in customized software development, particularly in robotics but also in medical devices"
"Geisel has been quoted as an industry expert by Entrepreneur Magazine, Bloomberg Business, BBC, Forbes and others, the company said"
They are advertising Pico for us, but their interest, is most probably in TENNs?..
DingoBorat
Slim
The CEO and Founder is switched on.
He was "also" at Edge A.I. Vision Alliance 2024, which is where he most probably met us (or it possibly happened earlier)
Only 28 subscribers, but his channel is worth going over..
Possible links to Apple? As he describes their AR headset, in one of his clips, or just general tech information?..
A focus on robotics.
The Geisel Software channel has ~5500 subscribers, still very small.
A space worth watching..
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Pom down under
Top 20
rgupta
Regular
The deal is not about $1.90 per week but how much money you will invest on those recommendations and feel trapped with all your investment money.
A good deal perhaps.
I used the deal a few years ago and still struck with 5gn, Eml, avh, bth, kgn, mp1, eos etc. a few of those companies sold at less than the recommended price of buy that includes Nearmap, limeade.
Nxl is the only recommended share which revert from 50 cents to $7 but still lower than recommended price 3 years ago.
So there is no better way than to research yourself. Even if you lose money, you will learn from mistakes.
Dyor
DingoBorat
Slim
Reminds me of the time my cat (since deceased
) was an adolescent and had diarrhea..He was trying in vain to "cover" the resultant splatter pack, inside his kitty litter tray.
(I apologise for any unpleasant mental images, this story may evoke).
BrainShit
Regular
@Diogenese HALP!
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LLM Optimization and Deployment on SiFive RISC-V Intelligence Products
LLM Optimization on SIFIve Intelligence Productswww.sifive.com
I can well imagine that in addition to the X280, the X390 can also contain Akida as an accelerator.
"The SiFive Intelligence X390 builds upon the success of its predecessor, the SiFive Intelligence X280, in combining AI and ML applications with hardware accelerators for mobile, infrastructure, and automotive applications."
SiFive CEO Patrick Little said in a statement, “The flexibility of SiFive’s RISC-V solutions allows companies to address the unique computing requirements of these segments and capitalize on the momentum around generative AI, where we have seen double-digit design wins, and for other cutting-edge applications.”
He said the company has 350 design wins and customers include Intel, Amazon, Qualcomm, Samsung, Google, NASA and more. SiFive started in the embedded market and moved up the food chain to high-performance cores.
SiFive unveils two new high-performance RISC-V processors
SiFive, a RISC-V processor design firm, unveiled two new chip designs aimed at bringing a high-performance computing solution.
Attachments
Still some very competent posters over there, put the downramping clowns on ignore.Don't even bother trying to talk logic to those doodle-heads @7für7. You'd have better luck communing with a rock IMO.
I personally wouldn't waste any of my precious kitty litter on them. Hehehe!
curdlednoodles over there posted the following research paper (dated Aug 2024) from:
Department of Mechanical and Aerospace Engineering, Missouri University of
Science and Technology, 400 W. 13th Street, Rolla, MO, USA, 65409
2 Department of Computer Science, Missouri University of Science and Technology,
500 W. 15th Street, Rolla, MO, USA, 65409
Called:
Few-Shot Transfer Learning for Individualized Braking Intent Detection on Neuromorphic Hardware
Nathan Lutes, Venkata Sriram Siddhardh Nadendla, K. Krishnamurthy
Objective: This work explores use of a few-shot transfer learning method to train and implement a convolutional spiking neural network (CSNN) on a BrainChip Akida AKD1000 neuromorphic system-on-chip for developing individual-level, instead of traditionally used group-level, models using electroencephalographic data. The efficacy of the method is studied on an advanced driver assist system related task of predicting braking intention. Main Results: Efficacy of the above methodology to develop individual specific braking intention predictive models by rapidly adapting the group-level model in as few as three training epochs while achieving at least 90% accuracy, true positive rate and true negative rate is presented. Further, results show an energy reduction of over 97% with only a 1.3x increase in latency when using the Akida AKD1000 processor for network inference compared to an Intel Xeon CPU. Similar results were obtained in a subsequent ablation study using a subset of five out of 19 channels. Significance: Especially relevant to real-time applications, this work presents an energy-efficient, few-shot transfer learning method that is implemented on a neuromorphic processor capable of training a CSNN as new data becomes available, operating conditions change, or to customize group-level models to yield personalized models unique to each individual.
Frangipani
Regular
EDGX displaying their work with Akida at the recent SPAICE conference
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Wouter Benoot on LinkedIn: #spaice #ai #spacetech #neuromorphiccomputing #aerospace
🌍 𝐖𝐡𝐞𝐫𝐞 𝐝𝐨 𝐀𝐈 𝐞𝐱𝐩𝐞𝐫𝐭𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐚𝐞𝐫𝐨𝐬𝐩𝐚𝐜𝐞 𝐢𝐧𝐝𝐮𝐬𝐭𝐫𝐲 𝐜𝐨𝐦𝐞 𝐭𝐨𝐠𝐞𝐭𝐡𝐞𝐫 𝐭𝐨 𝐞𝐱𝐜𝐡𝐚𝐧𝐠𝐞 𝐧𝐞𝐰 𝐢𝐝𝐞𝐚𝐬? Last…www.linkedin.com
Speaking of EDGX:
I am somewhat surprised no one has yet commented on the fact that EDGX no longer seems to be in an exclusive relationship with us as their neuromorphic partner:
Some posters will want to make you believe that as soon as a company / research institution / consultancy has discovered us, they will only have eyes for us, and that the competition can basically pack up and go home. It is a romantic notion for sure, but alas it is not the reality. The companies and institutions truly convinced of the benefits of neuromorphic technology will often be taking their time to explore different solutions and may end up doing business with / recommending (in the case of a consultancy) either
a) us
b) us and someone else or
c) someone else [as unimaginable that may seem to certain posters here].
While Accenture did praise Akida earlier this year, they continue to research Loihi (
https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-428774) and have also been evaluating SynSense’s ultra-low power offerings:
Or take ESA, for example: Laurent Hili didn’t restrict himself to visiting the BrainChip booth at the AI Hardware & Edge AI Summit in September: He and his colleague Luis Mansilla Garcia (who were both guests on Episode 31 of the BrainChip This is Our Mission podcast in March) also dropped by other AI chip companies’ booths such as that of Intel (-> Gaudi 3) and SpinnCloud Systems ( -> SpiNNaker 2), as evidenced by these recent screenshots I took of photos he posted resp. reposted on LinkedIn:
Another example:
We know the neuromorphic researchers from TCS to be BrainChip fans.
Yet, a month ago, in the comment section underneath one of his own posts, Sounak Dey from TCS expressed his regret of having missed the chance to meet up with Petrut Antoniu Bogdan from Innatera at Semicon India 2024 (Sept 11-13). No surprise, really, given that in recent months Sounak Dey has liked numerous posts by both BrainChip and Innatera.
Of course our competitors are in the same situation, with BrainChip showing up in unexpected places - so standing still is not an option, all those companies need to continually innovate, and BrainChip is doing just that. Having chosen to go the path of an IP company may pay out in the long run, but of course means leaving part of the addressable market to our competitors.
I’d be very cautious to quantify any lead in months or even years, like some posters have done and still do, despite having no insight whatsoever into the negotiations between any of the companies offering neuromorphic technology and their potential customers - in my opinion, such posts lull us into a false sense of security, which in turn could lead to further disappointment among already disappointed shareholders and provide more fodder for the downrampers should one of our competitors land a juicy contract first, especially in case it concerned one that BrainChip had also been vying for.
And in case you were wondering: No, I don’t have any insider information. I am just a keen observer (such as taking note of LinkedIn posts like the ones above or below), and prefer to draw my own conclusions rather than rely on contributions by anonymous shareholders wearing rose-coloured glasses or deliberately cherry-picking info or even twisting the truth to suit their narrative (be it negative or positive - this happens on both ends of the spectrum). And I encourage everyone to do the same (which admittedly is hard to do for many with very limited time to spare.)
Reading between the lines: We are also exploring other companies’ offerings and won’t make any promises.
Reading between the lines: We are also exploring other companies’ offerings and won’t make any promises.
No reading between the lines is necessary here, I’d say...
They just don’t spell it out with the words: “You’re in good company” or “Trusted by…”, but to me this is essentially saying the same thing, even though the folks at Innatera cannot pride themselves to already have had their tech publicly validated in an MB concept car.
Gerrit Ecke on LinkedIn: #neuromorphic #adas #ad
Mercedes-Benz invests in #Neuromorphic Computing! The technology is key to overcome the issue of increasing compute requirements on a tight energy budget of…
Eric Knappenberger on LinkedIn: #spacetech #neuromorphiccomputing #ai #spaceexploration #iac2024…
Hey Space network! Excited to see many familiar faces and meet many new ones, at IAC2024 in Milan this week. We will be presenting our work on the use of…
These businesses would be irresponsible if they did not look at other solutions. I guess that is why BRN has acquires competitors products and tests them against AKIDA. Also BRN had developed a cloud based program for potential clients to test our products in minutes.
Lots of competitors have developed solutions that are 'niche' based ie focus on say Vision or robotics.
BRN on the other hand does the lot, ie vision, robotics, auto, health, industrial and wearables etc.
We are very suited to huge companies like Tata who have fingers in many Edge use areas, eg Health, wearables, Industrials.
That is why Pico is so good. It can serve more than one purpose on one product. Eg tools- low power ans maintenance warnings and the list goes on.
BrainShit
Regular
Innatera and their T1 are indeed quite good. Their mission: to bring intelligence to a billion sensors by 2030.
Innatera's T1 operates using a proprietary analog-mixed signal computing architecture, rather than a fully digital one. In addition to the SNN accelerator, T1 also includes a CNN accelerator and a 32-bit RISCV core with 384 KB of memory for more conventional workloads.
Akida operates digitally. It is a fully digital, event-based neuromorphic processor.
The differences between digital processing and a proprietary analog-mixed signal computing architecture are as follows:
Digital Processing: Digital systems use discrete values (typically 0s and 1s) to represent information. They are highly resistant to noise, allow for efficient error detection and correction, and can be easily integrated with other digital systems.
Digital processing is deterministic, meaning each signal has a specific value at a given time.
Analog-Mixed Signal Architecture: This combines both analog and digital components to process signals. It captures the benefits of both worlds: the precision of analog signal processing and the flexibility of digital systems. Mixed-signal architectures are ideal for applications requiring the conversion between analog and digital signals, such as ADCs (Analog-to-Digital Converters) and DACs (Digital-to-Analog Converters). They are particularly useful in environments where both types of signals are present.
To sum up, digital processing offers robustness and integration ease, while mixed-signal architectures provide versatility in handling both analog and digital signals.
... but we got PICO, TENNs, features such as Vision Transformer acceleration and support for 8-bit weights, enabling larger and more complex models. We also target at a wider range of edge applications, including image processing and audio applications, while the T1 targets applications in battery-powered, power-limited and latency-critical devices.
Crossing my finger we'll win.
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