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CHIPS
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7 Semiconductor Startups Revolutionizing EdgeAI - techovedas
Discover the cutting-edge landscape of EdgeAI with these 7 dynamic semiconductor startups.
techovedas.com
CHIPS
Regular
I don't recall having seen this in February ...
www.eenewseurope.com
Extract:
The heterogeneous architecture sees the DRP as an accelerator working with a microcontroller core. Renesas produced a prototype of an embedded AI-MPU with these technologies and confirmed its high-speed and low-power-consumption operation. A test chip achieved 130TOPS of performance and power consumption of 23.9 TOPS/W with a 0.8 V supply without needing a heatsink.
Significantly reducing heat generation will contribute to the spread of automation into various industries, such as the robotics and smart technology markets. These technologies will be applied to the Renesas RZ/V series of ARM A55-based microcontrollers for vision AI applications.
This is one of several edge AI technologies that Renesas is developing for edge AI in embedded chips for different end markets. It also has a deal with Brainchip for higher performance edge AI IP.
The severe restrictions on heat generation, particularly for embedded devices, are driving higher performance and lower power consumption are required in AI chips.
Renesas optimized the DRP-based AI accelerator (DRP-AI) for pruning, which can omit calculations that do not significantly affect recognition accuracy. However, it is common that calculations that do not affect recognition accuracy randomly exist in AI models. This causes a difference between the parallelism of hardware processing and the randomness of pruning, which makes processing inefficient.
By analyzing how pruning pattern characteristics and a pruning method are related to recognition accuracy in typical image recognition AI models (CNN models), we identified the hardware structure of an AI accelerator that can achieve both high recognition accuracy and an efficient pruning rate, and applied it to the DRP-AI design.
Software was also developed to reduce the weight of AI models optimized for this DRP-AI. This converts the random pruning model configuration into highly efficient parallel computing, resulting in higher-speed AI processing.
This flexible N:M pruning technology can dynamically change the number of cycles in response to changes in the local pruning rate in AI models, allows for fine control of the pruning rate according to the power consumption, operating speed, and recognition accuracy required by users.
This reduces the number of AI model processing cycles to as little as one-sixteenth of pruning incompatible models and consumes less than one-eighth of the power.
Robot applications require advanced vision AI processing for recognition of the surrounding environment while motion judgment and control require detailed condition programming in response to changes in the surrounding environment where CPU-based software processing is more suitable than AI-based processing.
The DRP runs an application while dynamically changing the circuit connection configuration between the arithmetic units inside the chip for each operation clock according to the processing details. Since only the necessary arithmetic circuits operate even for complex processing, lower power consumption and higher speeds are possible.
For example, SLAM (Simultaneously Localization and Mapping), one of the typical robot applications, is a complex configuration that requires multiple programming processes for robot position recognition in parallel with environment recognition by vision AI processing.
Renesas demonstrated operating this SLAM through instantaneous program switching with the DRP and parallel operation of the AI accelerator and CPU, resulting in about 17 times faster operation speeds and about 12 times higher operating power efficiency than the embedded CPU alone.
www.renesas.com
Low power edge AI core for robotics kills the heatsink
Renesas Electronics has developed embedded accelerator technology for low power edge AI without the need for a heatsink.
www.eenewseurope.com
Extract:
Renesas Electronics has developed embedded accelerator technology for low power edge AI without the need for a heatsink.
The dynamically reconfigurable processor (DRP-AI) developed by Renesas was shown at the ISSCC conference in the US this week for processing lightweight edge AI models for vision-based robotic application.The heterogeneous architecture sees the DRP as an accelerator working with a microcontroller core. Renesas produced a prototype of an embedded AI-MPU with these technologies and confirmed its high-speed and low-power-consumption operation. A test chip achieved 130TOPS of performance and power consumption of 23.9 TOPS/W with a 0.8 V supply without needing a heatsink.
Significantly reducing heat generation will contribute to the spread of automation into various industries, such as the robotics and smart technology markets. These technologies will be applied to the Renesas RZ/V series of ARM A55-based microcontrollers for vision AI applications.
This is one of several edge AI technologies that Renesas is developing for edge AI in embedded chips for different end markets. It also has a deal with Brainchip for higher performance edge AI IP.
The severe restrictions on heat generation, particularly for embedded devices, are driving higher performance and lower power consumption are required in AI chips.
Renesas optimized the DRP-based AI accelerator (DRP-AI) for pruning, which can omit calculations that do not significantly affect recognition accuracy. However, it is common that calculations that do not affect recognition accuracy randomly exist in AI models. This causes a difference between the parallelism of hardware processing and the randomness of pruning, which makes processing inefficient.
By analyzing how pruning pattern characteristics and a pruning method are related to recognition accuracy in typical image recognition AI models (CNN models), we identified the hardware structure of an AI accelerator that can achieve both high recognition accuracy and an efficient pruning rate, and applied it to the DRP-AI design.
Software was also developed to reduce the weight of AI models optimized for this DRP-AI. This converts the random pruning model configuration into highly efficient parallel computing, resulting in higher-speed AI processing.
This flexible N:M pruning technology can dynamically change the number of cycles in response to changes in the local pruning rate in AI models, allows for fine control of the pruning rate according to the power consumption, operating speed, and recognition accuracy required by users.
This reduces the number of AI model processing cycles to as little as one-sixteenth of pruning incompatible models and consumes less than one-eighth of the power.
Robot applications require advanced vision AI processing for recognition of the surrounding environment while motion judgment and control require detailed condition programming in response to changes in the surrounding environment where CPU-based software processing is more suitable than AI-based processing.
- Renesas ships its ARM Cortex-M85 microcontroller
- MCU to boost embedded-AI imaging for smart appliances
The DRP runs an application while dynamically changing the circuit connection configuration between the arithmetic units inside the chip for each operation clock according to the processing details. Since only the necessary arithmetic circuits operate even for complex processing, lower power consumption and higher speeds are possible.
For example, SLAM (Simultaneously Localization and Mapping), one of the typical robot applications, is a complex configuration that requires multiple programming processes for robot position recognition in parallel with environment recognition by vision AI processing.
Renesas demonstrated operating this SLAM through instantaneous program switching with the DRP and parallel operation of the AI accelerator and CPU, resulting in about 17 times faster operation speeds and about 12 times higher operating power efficiency than the embedded CPU alone.
www.renesas.com
CHIPS
Regular
Innatera raises €15m for neuromorphic edge AI
Dutch chip startup up Innatera has raised €15m for its neuromorphic spiking neural network (SNN) edge AI technology
www.eenewseurope.com
Sirod69
bavarian girl ;-)
BrainChip's innovative technology is inspired by the complex neural pathways of the human brain. As applications and use-case solutions continue to evolve, new realms of innovation are unlocking and expanding. Join us in shaping the future of Hashtag#AI. https://lnkd.in/gUGhvCvb Hashtag#EdgeAI Hashtag#neuromphic
www.linkedin.com
#ai #edgeai #neuromphic | BrainChip
BrainChip's innovative technology is inspired by the complex neural pathways of the human brain. As applications and use-case solutions continue to evolve, new realms of innovation are unlocking and expanding. Join us in shaping the future of #AI. https://lnkd.in/gUGhvCvb #EdgeAI #neuromphic
CrabmansFriend
Regular
Although a potential „rival“ to Brainchip, I already got curious when I was checking Innatera the last time they where mentioned as MiG capital also where early investors of BioNTech. So I just see this as further confirmation of neuromorphic computing at the edge getting ready for prime time and getting considered of value throughout a lot of different type of fields and also investing entities.Innatera raises €15m for neuromorphic edge AI
Dutch chip startup up Innatera has raised €15m for its neuromorphic spiking neural network (SNN) edge AI technology
View attachment 59720
Hi Iseki,
Maybe you could share how you came to get Sean's email address ?
One persons view or definition of progress or success can vary widely once you have a room full of different personalities.
I personally see great progress, year on year, is that reflected in the here and now, possibly not to many and that all leads back to
that great rebalance in ones life......personal choice, you make personal choices daily, as does the Board.
Akida
TechLooks like we have a massive fan over at GOOGLE and interestingly liked an nvidia blackwell post in-between a bunch of brn posts...........
www.linkedin.com
Lucern Ma - University of California, Los Angeles - Taipei, Taipei City, Taiwan | LinkedIn
APAC Regional Cloud Transformation Technical Lead · SUMMARY<br><br>• 9+ years in People Management & Employee Skills Development/Coaching in multinational companies<br>• 10+ years in customer-facing technical leadership roles in Semiconductor and Cloud Computing industries<br>• Experienced in...
Looks like we have a massive fan over at GOOGLE and interestingly liked an nvidia blackwell post in-between a bunch of brn posts...........
Lucern Ma - University of California, Los Angeles - Taipei, Taipei City, Taiwan | LinkedIn
APAC Regional Cloud Transformation Technical Lead · SUMMARY<br><br>• 9+ years in People Management & Employee Skills Development/Coaching in multinational companies<br>• 10+ years in customer-facing technical leadership roles in Semiconductor and Cloud Computing industries<br>• Experienced in...
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Smoothsailing
Regular
I took the liberty to send Tony an email last week myself asking him toward to Sean at his convenience which was from a much more respectful angle letting Sean know we all love him down under and very much appreciate the master piece he is laying out for the foundations for a successful BRN.
I also let Tony know we are aware of how the pests are stinking up social media which we are fumigating on a daily basis.
Hi @CHIPS ,Hi Iseki,
Maybe you could share how you came to get Sean's email address ?
One persons view or definition of progress or success can vary widely once you have a room full of different personalities.
I personally see great progress, year on year, is that reflected in the here and now, possibly not to many and that all leads back to
that great rebalance in ones life......personal choice, you make personal choices daily, as does the Board.
Akida
Clearly my post is just for fun. But it points out the obvious. That the direction of the company which is to tell OEM's who want to use Akida based sensor systems to go to Renesas who also will sell you their own proprietary chip that can do the job, is suicide. Let's make a batch ourselves to show it can be done.
If, as a shareholder, you want to see our technology flourish, then we need to get it out there and not just have it available as IP that you can go off and build yourself.
Do you want to be selling Corolas or Morgans?
Your post is basically saying that the board should be making personal choices, and that we shareholders have only the personal choice of investing or not. But this is not the case. This is wrong on every level. Mostly on the level that says we should all, board members and shareholders alike be enlightened about the progress of our company.
Don't spray near the baby!
RobjHunt
Regular
Who the bloody hell are you implying is "We"?. It seems blatantly obvious your email was drafted by "You" as your first line of you post states "My letter to Sean" Therefore the only one that would have the inclination to draft and sent this email is "You"
Never assume "You" speak for the "We" ole mate, well certainly not for "Me!!" You know what happens when you assume.
Put more Pantene on your upcoming shopping list Possum.
Smoothsailing
Regular
totally inappropriate
Our CEO, Mitch Stevison Ph.D., is at University of Pennsylvania’s Wharton Aerospace 2024 today where he’ll be talking about how technology can enable and drive an organization’s strategic agility… | Frontgrade Technologies
Our CEO, Mitch Stevison Ph.D., is at University of Pennsylvania’s Wharton Aerospace 2024 today where he’ll be talking about how technology can enable and drive an organization’s strategic agility. Mitch is sharing the stage with industry leaders Bob Smith, former CEO of Blue Origin; Scott Stapp...
We, the disaffected shareholders.
Haven't you heard of Luther?
cosors
👀
Rskiff
Regular
not tempted to clink to support those fwitsView attachment 59750
How to invest in a meme stock.
to be filled here:
waiting for reponse
View attachment 59749
...our top five are here:
Get Access to The Motley Fool's Latest Stock Picks
KiKi
Regular
Considering his position I am pretty sure he is just an investor like us and maybe the google lady as well.
cosors
👀
Ok, I'll delete it. I'm used to it.)
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