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TheDrooben
Pretty Pretty Pretty Pretty Good
A little profile on Nikunj Kotecha.....our former Senior Solutions Architect until Nov 2023.......some little titbits in there on automotive and earables
www.bisinfotech.com
Nikunj Kotecha Redefining Technology for a Smarter Future
Nikunj Kotecha has emerged as a pioneering figure in AI, making significant contributions to advancements in ML and AI model computing.
www.bisinfotech.com
But, apart from:A little profile on Nikunj Kotecha.....our former Senior Solutions Architect until Nov 2023.......some little titbits in there on automotive and earables
Nikunj Kotecha Redefining Technology for a Smarter Future
Nikunj Kotecha has emerged as a pioneering figure in AI, making significant contributions to advancements in ML and AI model computing.
Akida,
TENNs.
AV models,
MetaTF,
benchmarking tools,
transformers,
Edge impulse,
Edge Box,
IP licensing,
strategic partnerships,
in cabin functionality,
model quantizing and fine tuning,
workshop leadership,
application notes,
what else has Nikunj done for Brainchip?
ForrestofHope
Regular
Interesting article: Did Nikunj just release a new partnership? Has Space Machines Company been mentioned before?A little profile on Nikunj Kotecha.....our former Senior Solutions Architect until Nov 2023.......some little titbits in there on automotive and earables
Nikunj Kotecha Redefining Technology for a Smarter Future
Nikunj Kotecha has emerged as a pioneering figure in AI, making significant contributions to advancements in ML and AI model computing.
“He also contributed to BrainChip’s partnership with Space Machines Company where he assisted with model quantization and fine-tuning of the model architecture for improved efficiency in harsh environments.”
Roadside Assistance in Space
Providing resilient, scalable and sustainable space operations.
Space Cadet
Regular
Think you'll find it is the Ant61 thing.Interesting article: Did Nikunj just release a new partnership? Has Space Machines Company been mentioned before?
“He also contributed to BrainChip’s partnership with Space Machines Company where he assisted with model quantization and fine-tuning of the model architecture for improved efficiency in harsh environments.”
Roadside Assistance in Space
Providing resilient, scalable and sustainable space operations.www.spacemachines.com
SC
TheDrooben
Pretty Pretty Pretty Pretty Good
Space Machines built the Optimus-1 spacecraft with ANT61 on board which had Akida integrated into itInteresting article: Did Nikunj just release a new partnership? Has Space Machines Company been mentioned before?
“He also contributed to BrainChip’s partnership with Space Machines Company where he assisted with model quantization and fine-tuning of the model architecture for improved efficiency in harsh environments.”
Roadside Assistance in Space
Providing resilient, scalable and sustainable space operations.
TheDrooben
Pretty Pretty Pretty Pretty Good
Space Cadet
Regular
TheDrooben
Pretty Pretty Pretty Pretty Good
7für7
Top 20
HE TOOK SOMEONES JOOOOB
Bravo
If ARM was an arm, BRN would be its biceps💪!
Our illustrious leader, Sean Hehir participated in a video session with the Industrial Technology Research Institute (ITRI).
Intriguingly there was an article published online about 16 hours ago which describes how the ITRI was at CES, showing off a new AI-driven trainer that uses image analysis and data inference to improve an athlete’s performance.
I wonder if Sean got to polish up on his badminton skills? But more importantly, I wonder if we're involved in this AI athlete training system in some way, shape or form?
US badminton Olympian Howard Shu plays with ITRI’s AI Badminton Trainer at CES 2025. [Photo: ITRI]
https://www.linkedin.com/shareArticle?mini=true&url=https://www.fastcompany.com/91258203/ai-taught-me-to-be-a-slightly-better-badminton-player-at-ces&media=AI+taught+me+to+be+a+(slightly)+better+badminton+player+at+CES
BY Chris Morris3 minute read
I am not what you would call a finely tuned athletic machine. I am, if anything, an outdated lawnmower engine held together by duct tape and rust. So when I was offered the opportunity to let AI help make me a better athlete at CES, I jumped at the opportunity.
The offer came from the Industrial Technology Research Institute (ITRI), a non-profit that uses applied research to drive industrial development. They were showing off a new AI-driven trainer that uses image analysis and data inference to improve an athlete’s performance. The sport that was the focus of this particular demonstration? Badminton.
The upside, I thought, would be that no one at CES would be especially good at badminton—so it wouldn’t be as humbling as it would if the system was tracking, say, my golf swing. Then Howard Shu strolled by.
Shu is a member of the U. S. Olympic badminton team and has been playing the sport for 26 years. He’s tall, in remarkable shape, and knows how to make a shuttlecock do pretty much whatever he wants. He is, in other words, the antithesis of me. We’ll get back to him in a moment, though.
[Photo: ITRI]
To get a sense of my abilities, the training tool used a series of cameras to track my stance, swing, and other movements over five volleys. The data was fed into a Generative AI system, which instantly offered recommendations. At the same time, information like the speed of my volleys, the height with which they cleared the net, and where they landed on the court was captured and factored in as well.
I thought I was doing okay, honestly. I whacked the shuttlecock at 52 miles per hour, cleared the net by two feet, and made my invisible opponent chase it around the court. Then I walked over to see what the AI had to say.
“Ah, my friend!,” it wrote. “It looks like we’ve got a bit of a situation here.”
Maybe I hadn’t done quite as well as I thought I had.
The AI (which called itself Bill) noted that I was standing too close to the shuttlecock, which limited my ability to reach for the shot. Also, I needed to work on my weight transfer and balance. My footwork was not exactly ideal either.
And while it had my attention, Bill noted that my grip on the racket “might not be ideal for controlling the shuttlecock effectively or generating power” with my shots. And my follow-through was “abrupt.”
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Basically, the machine told me, I suck.
That’s when Shu took a turn. His speeds were closer to 80 mph—and he tightly grouped the shots. (He later told me he felt the system’s speed detection needed some calibrating as he normally hits faster than that.)
I gave the system one more try, with Shu suggesting I stand in a different spot on the court—and while my shots weren’t as powerful, they were much more tightly grouped. I won’t be threatening Shu’s spot on the Olympic team anytime soon, but I could be more of a beast at the local recreation center.
[Photo: ITRI]
This training tool is already used by the Taiwan Olympic badminton team, an ITRI representative told me. Shu said it was the first time he had had an opportunity to try it—adding that he expects a growing number of athletes will begin to incorporate AI into their training.
“It’s able to pick up things you’re not able to pick up with the naked eye,” he said. “I can tell you my smash is fast, but I’m not going to be able to tell you the exact speed. You’re able to dial in exact numbers and get data driven results. As high performing athletes, we’re always trying to find that 1% advantage.”
Bill, I should note, remained unimpressed with my performance on the court.
Shu might be looking for a 1% advantage. I’d settle for the AI being a bit less judgmental.
Intriguingly there was an article published online about 16 hours ago which describes how the ITRI was at CES, showing off a new AI-driven trainer that uses image analysis and data inference to improve an athlete’s performance.
I wonder if Sean got to polish up on his badminton skills? But more importantly, I wonder if we're involved in this AI athlete training system in some way, shape or form?
AI taught me to be a (slightly) better badminton player at CES
The Industrial Technology Research Institute was in Las Vegas to show off a new AI-driven trainer that uses image analysis and data inference to improve an athlete’s performance. The sport that served as our demonstration? Badminton.
US badminton Olympian Howard Shu plays with ITRI’s AI Badminton Trainer at CES 2025. [Photo: ITRI]
https://www.linkedin.com/shareArticle?mini=true&url=https://www.fastcompany.com/91258203/ai-taught-me-to-be-a-slightly-better-badminton-player-at-ces&media=AI+taught+me+to+be+a+(slightly)+better+badminton+player+at+CES
BY Chris Morris3 minute read
I am not what you would call a finely tuned athletic machine. I am, if anything, an outdated lawnmower engine held together by duct tape and rust. So when I was offered the opportunity to let AI help make me a better athlete at CES, I jumped at the opportunity.
The offer came from the Industrial Technology Research Institute (ITRI), a non-profit that uses applied research to drive industrial development. They were showing off a new AI-driven trainer that uses image analysis and data inference to improve an athlete’s performance. The sport that was the focus of this particular demonstration? Badminton.
The upside, I thought, would be that no one at CES would be especially good at badminton—so it wouldn’t be as humbling as it would if the system was tracking, say, my golf swing. Then Howard Shu strolled by.
Shu is a member of the U. S. Olympic badminton team and has been playing the sport for 26 years. He’s tall, in remarkable shape, and knows how to make a shuttlecock do pretty much whatever he wants. He is, in other words, the antithesis of me. We’ll get back to him in a moment, though.
To get a sense of my abilities, the training tool used a series of cameras to track my stance, swing, and other movements over five volleys. The data was fed into a Generative AI system, which instantly offered recommendations. At the same time, information like the speed of my volleys, the height with which they cleared the net, and where they landed on the court was captured and factored in as well.
I thought I was doing okay, honestly. I whacked the shuttlecock at 52 miles per hour, cleared the net by two feet, and made my invisible opponent chase it around the court. Then I walked over to see what the AI had to say.
“Ah, my friend!,” it wrote. “It looks like we’ve got a bit of a situation here.”
Maybe I hadn’t done quite as well as I thought I had.
The AI (which called itself Bill) noted that I was standing too close to the shuttlecock, which limited my ability to reach for the shot. Also, I needed to work on my weight transfer and balance. My footwork was not exactly ideal either.
And while it had my attention, Bill noted that my grip on the racket “might not be ideal for controlling the shuttlecock effectively or generating power” with my shots. And my follow-through was “abrupt.”
advertisement
Basically, the machine told me, I suck.
That’s when Shu took a turn. His speeds were closer to 80 mph—and he tightly grouped the shots. (He later told me he felt the system’s speed detection needed some calibrating as he normally hits faster than that.)
I gave the system one more try, with Shu suggesting I stand in a different spot on the court—and while my shots weren’t as powerful, they were much more tightly grouped. I won’t be threatening Shu’s spot on the Olympic team anytime soon, but I could be more of a beast at the local recreation center.
This training tool is already used by the Taiwan Olympic badminton team, an ITRI representative told me. Shu said it was the first time he had had an opportunity to try it—adding that he expects a growing number of athletes will begin to incorporate AI into their training.
“It’s able to pick up things you’re not able to pick up with the naked eye,” he said. “I can tell you my smash is fast, but I’m not going to be able to tell you the exact speed. You’re able to dial in exact numbers and get data driven results. As high performing athletes, we’re always trying to find that 1% advantage.”
Bill, I should note, remained unimpressed with my performance on the court.
Shu might be looking for a 1% advantage. I’d settle for the AI being a bit less judgmental.
Fullmoonfever
Top 20
Bit of a loss that one....would have been great if he'd stayed imo.
Btw....was looking at the M.2 update and curious on your thoughts if you can oblige?
Do you think we have a stack of M.2s available from the first AKD1000 run as well as the PCIe and we just essentially haven't released it to mkt but now is the time for added flexibility / requests for users / researchers?
Reason is I was just reading an old article (late 2020) on Anils presso to an industry group back in 2020 and the article includes the below image of our AKD1000 M.2 board which implies we had it back in 2020?
Mobile computing – Silverton Consulting
Posts about Mobile computing written by Ray
silvertonconsulting.com
Hi FMF,Bit of a loss that one....would have been great if he'd stayed imo.
Btw....was looking at the M.2 update and curious on your thoughts if you can oblige?
Do you think we have a stack of M.2s available from the first AKD1000 run as well as the PCIe and we just essentially haven't released it to mkt but now is the time for added flexibility / requests for users / researchers?
Reason is I was just reading an old article (late 2020) on Anils presso to an industry group back in 2020 and the article includes the below image of our AKD1000 M.2 board which implies we had it back in 2020?
View attachment 75767
Mobile computing – Silverton Consulting
Posts about Mobile computing written by Ray
That's a 20 node Akida, so maybe a FPGA test chip. Certainly not the Akida 1000.
https://www.eejournal.com/article/brainchip-debuts-neuromorphic-chip/
...
Brainchip’s test chip benchmarking results are impressive – claiming 1,100 fps with the $10 chip on CIFAR-10 with 82% accuracy, using less than 0.2 Watts – about 6K fps/watt. The company says this compares with 83% at 6K fps/watt from IBM’s “True North” (at a cost of around $1K) and 80% from Xilinx ZC709 at 6K fps/watt (also around $1K).
...
Brainchip’s development environment is available in Q3 2018, and should be accessible to an FPGA-based acceleration board in advance of availability of the Akida chip in 2019.
I'm constantly amazed at hoe BRN keep producing Akida 1000's out of their hat. I don't know where the Unigen, BH, VVDN, etc., chips will come from.
Pretty sure the December 2020 date was overoptimistic.
Agree TECH, its taken a lot of time and patience but we are closing on deals and the Edge is getting closer to widespread adoption.
Ironically as we and the Edge are closing in on success cloud based NVIDIA is making record highs.
It just shows that big changes in IT move at tortoise pace. This is actually good for us as when we are 'flying' new tech will have to wait like we did while we are making record highs.
NVIDIA has 25 billion shares and we have 2 billion on issue. If NVIDIA had only 2 bill SOI then it would be trading at circa $US1735. Puts our LDA plans into perspective.
Fullmoonfever
Top 20
Unfortunately all chips look the same to me.
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