BRN Discussion Ongoing

[Frangipani]

A paper showing AKIDA 1000 being integrated into an on-board processor to help detect fugitive methane emissions from ageing oil and gas infrastructures facilitating operators to locate and mitigate these leaks, to order to help address the global climate crisis. The processor works in conjunction with NASA’s core Flight System (cFS).
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EXTRACT FROM PAGE 6

.1 BrainSat neuromorphic processor for CubeSats
One of the objectives of our work was to propose an al-
gorithm that could be executed on the novel neuromorphic
on-board processor (OBP) developed by BrainSat [12],
demonstrating its capability to serve small satellite mis-
sion needs and showing the potential of AI-based edge
computing. The OBP was specifically designed accord-
ing to mission requirements established for the monitoring
of point-source methane emissions with a 6U CubeSat, as
detailed in [13].
The designed OBP includes two PC104 modules, con-
nected through a mezzanine connector. It integrates both
CPU and FPGA capabilities and can cater for on board
computer functions, payload data processing and down-
link management. The OBP is equipped with the Akida
1000 neuromorphic processor, selected for its design ma-
turity, real-time processing capabilities and flight heritage.
The chip is tailored for event-based processing, featuring
80 Neuromorphic Processing Units (NPUs) with 100 KB
of SRAM each, supporting up to 1.2 million virtual neu-
rons and 10 billion virtual synapses with up to 8-bit pre-
cision, ideal for inference-heavy tasks. An FPGA pro-
vides glue logic to implement necessary data protocols
and serve as a soft CPU for OBC functions. Additionally,
a 12GB flight-proven Micron Solid State Device (SSD) is
included to provide non-volatile on-board memory. This
sub-system is constrained to a 0.5 U volume and is esti-
mated to consume a low power of less than 4 W.
The processor’s software architecture was designed to
minimize resource consumption. It is equipped with Real-
Time Executive for Multiprocessor Systems (RTEMS) as
its Real Time Operating System (RTOS), on top of which
NASA’s core Flight System (cFS) is used. cFS provides a
flight proven product on which OBP functions are built us-
ing open-source applications. For more information about
the BrainSat architecture, refer to our co-published pro-
ceeding [12]

https://www.researchgate.net/profile/Andrew_Karim/publication/385084411_Spiking_Neural_Network_Design_for_on-board_detection_of_methane_emissions_through_Neuromorphic_Computing/links/6714c30f035917754c104e47/Spiking-Neural-Network-Design-for-on-board-detection-of-methane-emissions-through-Neuromorphic-Computing.pdf

To save those of you some time who would like to find out more about the above mentioned co-publication on the BrainSat hardware architecture by seven other SGAC Small Satellite Group members the authors collaborated with - you can just click on the three posts of mine I referred back to in below post

https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-439236

as I had already covered both papers a month ago:

 

[Mt09]

To save those of you some time who would like to find out more about the above mentioned co-publication on the BrainSat hardware architecture by seven other SGAC Small Satellite Group members the authors collaborated with - you can just click on the three posts of mine I referred back to in below post

https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-439236

as I had already covered both papers a month ago:

View attachment 72943
View attachment 72944
View attachment 72945

Congrats.

 

[Earlyrelease]

Perth crew.
Yip its is that time of the year again for the obligatory xmas drinks.
Wednesday 11 December is booked for the 4pm-4.30pm start, I need numbers as they now take my credit card and charge $500 if I don't get the numbers (and not wing it like normal), so just PM if you are interest. Let us pray that because of the big break between drinks we can do as we did for the $1 dollar party and on the day (19 Jan2022) it was a $2 party.

 

[Frangipani]

Narendhiran Saravanane (https://naren200.github.io) - whose name didn’t pop up when I searched for it here on TSE - was a summer intern with BrainChip last year (from May to August 2023), while enrolled for a Master’s program at Arizona State University, which has been part of our company’s University AI Accelerator Program since its inauguration in September 2022.

After graduating in April of this year with an “MS in Robotics and Autonomous Systems (Honors)”, he worked for a company called Padma AgRobotics for six months - so until very recently (his CV is not quite as up-to-date as his LinkedIn and GitHub profiles in that respect).

Padma AgRobotics is a five-year old startup based in Chandler, AZ and very much intertwined with Arizona State University (ASU): Not only is its founder, Raghu Nandivada, an ASU alumni, but equally robotics engineer Cole Brauer, who had joined the then one-month old company in January 2020 and only left the start-up in July of this year and is now self-employed.

In May 2020, Padma AgRobotics won US$15,000 for their invention of weed-killing robots in the ASU-backed Sarsam Family Venture Challenge, and earlier this year Raghu Nandivada was featured in a fireside chat with Cultivate PHX, an AgriFood Tech Incubator within the J. Orin Edson Entrepreneurship + Innovation Institute at Arizona State University, that is “set to award an impressive $300,000 in seed grant funding to ventures demonstrating technological innovation and delivering benefits to the broader Phoenix area. Funding opportunities are available for ventures addressing key areas within the full lifecycle of food and advanced ventures seeking to pilot new technology.”

Cultivate PHX - Virtual Fireside Chat - J. Orin Edson Entrepreneurship + Innovation Institute

entrepreneurship.asu.edu

https://entrepreneurship.asu.edu/programs/cultivate-phx-agrifood-tech-incubator/ (where Raghu Nandivada gets quoted)

As you can see, Padma AgRobotics has lots of connections to Arizona State University.

“Gimme an R!”

ASU entrepreneurs pitch via video for online Demo Day competition | ASU News

Sometimes even a small amount of money makes a huge difference. An Arizona State University student took the $4,000 that she won in a Demo Day competition a year ago and created a company in her native Ghana to help feed children.

news.asu.edu

Could Padma AgRobotics possibly be engaged with us?

Remember the AkidaNet model published in a November 2022 paper by Vi Nguyen Thanh Le, Kevin, Tsiknos, Kristofor Carlson (all BrainChip) and Selam Ahderom (Edith Cowan University), first referred to in posts by @thelittleshort and @Fullmoonfever?

https://www.researchgate.net/publication/369268509_An_energy-efficient_AkidaNet_for_morphologically_similar_weeds_and_crops_recognition_at_the_Edge

Don’t think anyone has gone down this rabbit hole yet? I looked into the DSTG Women in STEM Award - specifically what her paper was about

I couldn’t actually find the paper that the won the award - An energy-efficient AkidaNet for morphologically similar weeds and crops recognition at the Edge' (co-authors Kevin Tsiknos, Kristofor Carlson, Selam Ahder, but another one that lead to the outputs below

Just googling for dots and this presso / paper I posted about back in Jan popped up.

Couldn't find it back then but it's HERE if anyone wanted a read.

@Diogenese thoughts whenever if you have time or anything of interest in it?

TIA

While I couldn’t find any specific mention of neuromorphic technology anywhere on their website or in either of their two SBIR grant applications for another precision agriculture project, namely “an autonomous harvester for cilantro with bunching and tying capability” (SBIR I phase was from 24 April 2023 to 29 February 2024 > US$181,500; the ongoing SBIR II phase is from 1 September 2024 to 31 August 2026 > US$ 650,000), the multiple ASU connections as well as the fact that a 2023 BrainChip summer intern verifiably worked with them for six months earlier this year, in combination with recalling a July 2023 interview with Nandan Nayampally made me wonder whether Padma AgRobotics could be a valid dot-join.

In said interview (watch from around 18 min), which I believe was first posted here on TSE by @TECH https://thestockexchange.com.au/threads/brn-discussion-ongoing.1/post-323887), Nandan referred to the long-term benefits of scaling your business offerings to a broader clientele by giving the example of preferably employing a consumer-friendly-priced service model for compact lawnmowers with weed-killing capabilities utilising Akida technology (hypothetical example only?) rather than trying to sell units of (already existing) premium lawnmowers with very expensive and bulky weed-control systems. (“Today, the economy is moving from a device economy to a service economy.”).

Now guess what the current business model of Padma AgRobotics looks like?

[To be continued in another post due to the upload limit of 10 files…]

 

[Frangipani]

While all of this sounded really promising (although it didn’t exactly evoke massive revenue ), I found out there is another company - Atlanta-based R2 Labs - involved that helped to develop the AI-powered agricultural robot for Padma AgRobotics and built their solution using the Arduino Pro Portenta H7 platform:

Case Studies - R2 Labs

www.arduino.cc

Now here comes the question for the more tech-savvy: Would it still hypothetically be possible that we are involved?

I did find two references online that Portenta X8 now has support for the Akida PCIe module (one by YouTuber Chris Méndez from the Dominican Republic, who works for Arduino and has uploaded several videos featuring the Akida), but couldn’t find anything regarding Portenta H7…

https://docs.arduino.cc/tutorials/portenta-x8/x8-firmware-release-notes/

And since I’m in the mood of maxing out my file uploads again, here are Padma AgRobotics’ SBIR phase I and II applications, in case anyone would like to use these to fuel or end this speculation (note that they refer to a cilantro harvester, though, not to the weed-control AI-powered agricultural robot featured on their website and in the January 2023 video):

 

[Bravo]

Texas Instruments integrating an NPU as an edge AI accelerator.

TI Integrates Edge AI and Real-Time Control in New Mission-Critical MCUs​

8 hours ago by Duane Benson

Today, TI unveiled new members of the C2000 processor family—one with hardware-accelerated AI and the other with a 64-bit core for real-time control.​

Today at Electronica 2024, Texas Instruments (TI) announced its new TMS320F28P55x series of C2000 MCUs. TI calls the series the industry’s first real-time microcontrollers with an integrated neural processing unit (NPU). Along with that announcement, TI also revealed the new 64-bit F29H85x series of MCUs built around its C29 digital signal processing (DSP) core. The C29 MCUs target automotive applications that require fault-tolerant, low-latency operations and predictive decision-making. Both sets of new MCUs can serve mission-critical applications that require low-latency, real-time detection, calculation, and response.

A Brief Introduction to the Two New MCU Series​

The 40+ variants of the TMS320F28P55x series (datasheet linked) come with an integrated hardware NPU and on-chip Flash memory of up to 1.1 MB. This series also features 24 pulse width modulation (PWM) channels and 39 analog-to-digital (ADC) channels.

TMS320F28P55x and F29H85x MCUs. Image (modified) used courtesy of Texas Instruments​

​

The second series of MCUs in this announcement, the F29H85x, provides motor and power control with two to three times the signal chain performance of its predecessors. TI also claims these devices have a five times faster fast Fourier transform (FFT) performance in diagnostics, tuning, and arc detection. Real-time interrupts run four times faster, and the MCUs are reportedly two to three times higher performing for general-purpose code execution. It includes an isolated hardware security module as well.

The TMS320F28P55x Series: Aided by a Powerful NPU​

For over 25 years, TI's C2000 family has provided real-time control in industrial and automotive applications. The newest additions to the family, the TMS320F28P55x series, integrate an NPU as an edge AI hardware accelerator. The NPU enables the MCU to offload AI processing from the primary core to dramatically increase real-time performance. The NPU offers advanced AI-based decision-making without loading down the primary processing core.

Functional block diagram of the TMS320F28P55x. Image used courtesy of Texas Instruments​

​

Conventional microcontrollers use simple logic to make real-time decisions. They use combinations of “if-then” or state machines to evaluate conditions and essentially make Boolean logic decisions based on given sets of input conditions. When sensor input is obvious and accurate, this type of system can work quite well. However, with more sensors providing input and with fast-changing conditions, ambiguity or sensor lag can lead to invalid input conditions or improper results. With today’s stringent safety and efficiency requirements, Boolean logic is insufficient for many requirements. That’s where edge AI can deliver significant improvements.

​

Adding NPU-based AI enables greater one-chip functionality with improved accuracy. Image used courtesy of Texas Instruments​

​

TI notes that NPU capabilities will benefit applications like arc fault detection in solar and energy storage systems and motor-bearing fault detection for predictive maintenance. In both cases, conventional MCU code can misconstrue such faults, misidentifying them or not identifying them soon enough. The NPU allows the MCU to perform more advanced AI-style interpretation of sensor inputs in real time.
The TMS320F28P55x's NPU can also be trained to adapt to different environments with different sensor inputs, greatly increasing detection accuracy. It can run convolution neural network models to learn complex patterns from sensor data. The NPU will offload these calculations from the main CPU core and use AI to detect complex fault conditions, which can result in a five to 10x decrease in latency for detection operations.

The F29H85x Series: Leveraging 64-bit DSP and Real-Time Control​

The F29H85x MCU uses TI’s new C29 DSP core to deliver more than double the real-time performance of its predecessor, the C28. The new F29H85x processor series with the C29 DSP core boasts TI’s very long instruction word (VLIW) architecture, which supports the execution of up to eight instructions per cycle. The MCUs offer cyber security features as well, including a fully isolated hardware security module to protect the system. Further, the hardware safety and security unit uses context-aware memory protection to extend hardware isolation to CPU tasks without interference. The architecture provides security without a performance penalty added to the rest of the MCU.

Improved C29 DSP core response receives, processes, and responds more than twice as fast. Image used courtesy of Texas Instruments​

​

The 64-bit DSP with complex math ability can speed the signal chain performance for motor and power control by two to three times over the C28. It has five times the fast Fourier transform (FFT) performance. (FFT is used for systems diagnostics, tuning, and arc detection.) Interrupt response is four times faster than the C28 and general-purpose processing code can be executed two to three times faster.
TI engineered the chips to comply with the International Organization for Standardization (ISO) 26262 and International Electrotechnical Commission (IEC) 61508 automotive and industrial safety standards.

C2000 real-time MCU F28P55x development kit in TI LaunchPad form factor. Image used courtesy of Texas Instruments​

​

The F29 processors are automotive safety integrity level (ASIL) D and safety integrity level (SIL) 3 certified. ASIL D is the highest of four automotive safety risk management levels. SIL 3 is an industrial standard for risk mitigation used in a number of industry standards. SIL has three levels, with three being the highest. Visit TI at its Electronica booth C4-158.

Here's a video on the above Texas Instruments edge-based AI solution with realtime fault prediction. All inference work is performed off-line. All of the neural network computation is off-loaded to the hardware accelerator.

This is a very interesting discussion!

 

[Bravo]

Thanks to @chapman89 for finding this earlier this morning!

Here's a Texas Instruments white paper that looks to have been published only very recently on the 7th November.

Check out what is says on page 3!

https://www.ti.com/lit/wp/spry349/spry349.pdf?ts=1731799955761&ref_url=https%253A%252F%252Fwww.google.com%252F

 

[rgupta]

Here's a video on the above Texas Instruments edge-based AI solution with realtime fault prediction. All inference work is performed off-line. All of the neural network computation is off-loaded to the hardware accelerator.

This is a very interesting discussion!

View attachment 72971

This one have a merit of akida in it.
If no akida here either that will mean ??
Dyor

 

[Bravo]

I'm keeping an eye on Microchip. I beleive it's only a matter of time before our technology will be integrated in some way with PolarFire as I've mentioned in previous posts.

Remembering that Akida has already been integrated with Microchip's 32-bit processor.

Microchip to Accelerate Real-time Edge AI with NVIDIA Holoscan

Combining our flexible FPGA fabric with NVIDIA's advanced AI platform and multi-protocol support is empowering developers to create innovative solutions...

www.globenewswire.com

Microchip to Accelerate Real-time Edge AI with NVIDIA Holoscan​

PolarFire® FPGA Ethernet Sensor Bridge provides low-power multi-sensor bridging to NVIDIA edge AI platforms​

November 14, 2024 08:03 ET| Source: Microchip Technology Inc.Follow

---

Share


CHANDLER, Ariz., Nov. 14, 2024 (GLOBE NEWSWIRE) -- To enable developers building artificial intelligence (AI)-driven sensor processing systems, Microchip Technology (Nasdaq: MCHP) has released its PolarFire® FPGA Ethernet Sensor Bridge that works with the NVIDIA Holoscan sensor processing platform.
PolarFire FPGAs enable multi-protocol support, and this first solution to be released as part of Microchip’s platform is compatible with MIPI® CSI-2®-based sensors and the MIPI D-PHY℠ physical layer. Future solutions will support a wide range of sensors with different interfaces, including SLVS-EC™ 2.0, 12G SDI, CoaXPress® 2.0 and JESD204B. The platform allows designers to leverage the power of the NVIDIA Holoscan ecosystem while taking advantage of the PolarFire FPGA’s power-efficient technology with low-latency communication and multi-protocol sensor support.
NVIDIA Holoscan helps streamline the development and deployment of AI and high-performance computing (HPC) applications at the edge for real-time insights. It brings into a single platform the necessary hardware and software systems for low-latency sensor streaming and network connectivity. The platform includes optimized libraries for data processing, sample AI models for jump-starting AI inference pipeline development, template applications to facilitate rapid prototyping and core microservices to run streaming, imaging and other applications.
With its ability to bridge real-time sensor data to NVIDIA Holoscan and the NVIDIA IGX and NVIDIA Jetson platforms for edge AI and robotics, the PolarFire FPGA Ethernet Sensor Bridge unlocks new edge-to-cloud applications, enables AI/ML inferencing and facilitates the adoption of AI in the medical, industrial and automotive markets.
“The Ethernet sensor bridge is based on Microchip's highly power-efficient, secure and reliable PolarFire FPGA platform,” said Bruce Weyer, vice president of Microchip’s FPGA business unit. “By combining our flexible FPGA fabric with NVIDIA's advanced AI platform and multi-protocol support, we're empowering developers to create innovative, real-time solutions that will revolutionize sensor interfaces across a wide range of powerful AI-driven edge applications.”
By utilizing the low power consumption of Microchip’s PolarFire FPGA technology, the NVIDIA Holoscan Sensor Bridge efficiently manages high-bandwidth data from diverse sensors over Ethernet, enabling real-time, high-performance edge AI processing on NVIDIA AI platforms. The power-efficient design is also conducive for small-footprint and energy- or cost-sensitive applications.
PolarFire FPGAs address security concerns in sensor applications by providing embedded security and safety features to help protect against potential cyber threats and provide physical, device, design and data integrity. They are additionally designed with single event upset (SEU) immunity, making them highly reliable in environments subject to radiation, such as space or high-altitude applications and medical environments. The SEU immunity also helps reduce the risk of data corruption and system failures.
To learn more about how Microchip’s development tool supports NVIDIA Holoscan and other applications, visit the PolarFire FPGA Ethernet Sensor Bridge web page.

About Microchip Technology:
Microchip Technology Inc. is a leading provider of smart, connected and secure embedded control and processing solutions. Its easy-to-use development tools and comprehensive product portfolio enable customers to create optimal designs which reduce risk while lowering total system cost and time to market. The company’s solutions serve approximately 123,000 customers across the industrial, automotive, consumer, aerospace and defense, communications and computing markets. Headquartered in Chandler, Arizona, Microchip offers outstanding technical support along with dependable delivery and quality. For more information, visit the Microchip website at www.microchip.com.

 

[Bravo]

I'm keeping an eye on Microchip. I beleive it's only a matter of time before our technology will be integrated in some way with PolarFire as I've mentioned in previous posts.

Remembering that Akida has already been integrated with Microchip's 32-bit processor.

View attachment 72974

Microchip to Accelerate Real-time Edge AI with NVIDIA Holoscan

Combining our flexible FPGA fabric with NVIDIA's advanced AI platform and multi-protocol support is empowering developers to create innovative solutions...

www.globenewswire.com

Microchip to Accelerate Real-time Edge AI with NVIDIA Holoscan​

PolarFire® FPGA Ethernet Sensor Bridge provides low-power multi-sensor bridging to NVIDIA edge AI platforms​

November 14, 2024 08:03 ET| Source: Microchip Technology Inc.Follow

---

Share


CHANDLER, Ariz., Nov. 14, 2024 (GLOBE NEWSWIRE) -- To enable developers building artificial intelligence (AI)-driven sensor processing systems, Microchip Technology (Nasdaq: MCHP) has released its PolarFire® FPGA Ethernet Sensor Bridge that works with the NVIDIA Holoscan sensor processing platform.
PolarFire FPGAs enable multi-protocol support, and this first solution to be released as part of Microchip’s platform is compatible with MIPI® CSI-2®-based sensors and the MIPI D-PHY℠ physical layer. Future solutions will support a wide range of sensors with different interfaces, including SLVS-EC™ 2.0, 12G SDI, CoaXPress® 2.0 and JESD204B. The platform allows designers to leverage the power of the NVIDIA Holoscan ecosystem while taking advantage of the PolarFire FPGA’s power-efficient technology with low-latency communication and multi-protocol sensor support.
NVIDIA Holoscan helps streamline the development and deployment of AI and high-performance computing (HPC) applications at the edge for real-time insights. It brings into a single platform the necessary hardware and software systems for low-latency sensor streaming and network connectivity. The platform includes optimized libraries for data processing, sample AI models for jump-starting AI inference pipeline development, template applications to facilitate rapid prototyping and core microservices to run streaming, imaging and other applications.
With its ability to bridge real-time sensor data to NVIDIA Holoscan and the NVIDIA IGX and NVIDIA Jetson platforms for edge AI and robotics, the PolarFire FPGA Ethernet Sensor Bridge unlocks new edge-to-cloud applications, enables AI/ML inferencing and facilitates the adoption of AI in the medical, industrial and automotive markets.
“The Ethernet sensor bridge is based on Microchip's highly power-efficient, secure and reliable PolarFire FPGA platform,” said Bruce Weyer, vice president of Microchip’s FPGA business unit. “By combining our flexible FPGA fabric with NVIDIA's advanced AI platform and multi-protocol support, we're empowering developers to create innovative, real-time solutions that will revolutionize sensor interfaces across a wide range of powerful AI-driven edge applications.”
By utilizing the low power consumption of Microchip’s PolarFire FPGA technology, the NVIDIA Holoscan Sensor Bridge efficiently manages high-bandwidth data from diverse sensors over Ethernet, enabling real-time, high-performance edge AI processing on NVIDIA AI platforms. The power-efficient design is also conducive for small-footprint and energy- or cost-sensitive applications.
PolarFire FPGAs address security concerns in sensor applications by providing embedded security and safety features to help protect against potential cyber threats and provide physical, device, design and data integrity. They are additionally designed with single event upset (SEU) immunity, making them highly reliable in environments subject to radiation, such as space or high-altitude applications and medical environments. The SEU immunity also helps reduce the risk of data corruption and system failures.
To learn more about how Microchip’s development tool supports NVIDIA Holoscan and other applications, visit the PolarFire FPGA Ethernet Sensor Bridge web page.

About Microchip Technology:
Microchip Technology Inc. is a leading provider of smart, connected and secure embedded control and processing solutions. Its easy-to-use development tools and comprehensive product portfolio enable customers to create optimal designs which reduce risk while lowering total system cost and time to market. The company’s solutions serve approximately 123,000 customers across the industrial, automotive, consumer, aerospace and defense, communications and computing markets. Headquartered in Chandler, Arizona, Microchip offers outstanding technical support along with dependable delivery and quality. For more information, visit the Microchip website at www.microchip.com.

Speaking of NVIDIA's Holoscan, Advantech has integrated their AI video system with NVIDIA Holoscan for real-time surgical navigation.

Advantech is an Edge Impulse ecosystem partner, as is BrainChip.

Transforming Healthcare with Real-Time AI Image Analytic​

---

News provided by​

Advantech
Nov 14, 2024, 05:37 ET

Share this article​

https://thestockexchange.com.au/javascript:;

---

Join us to discover how NVIDIA IGX and SDVoE enable seamless ultra-low latency solutions
TAIPEI, Nov. 14, 2024 /PRNewswire/ -- Advantech announces enhanced AI detection for endoscopy surgical systems with the integration of its MIC-735M-IO, powered by NVIDIA IGX™, and the VEGA series ultra-low-latency SDVoE solution. Utilizing NVIDIA Holoscan AI software, this solution enables real-time AI surgical detection, transforming endoscopy. To explore these advancements, join Advantech's upcoming webinar, "Transforming Endoscopy with Real-Time AI Detection," covering the MIC-735M-IO and VEGA series in AI-powered visualization and ultra-low latency transmission, shaping the future of digital operating rooms.



Register Link

Look deep into our solution:
Advantech IGX System: Advancing Medical AI with NVIDIA Holoscan for Superior Real-Time Image Analytics
The Advantech MIC-735M-IO is a compact, medical-grade edge AI system (192 x 376.7 x 338.5 mm) equipped with NVIDIA IGX Orin™. It includes a PCIe x16 slot for the NVIDIA RTX™ A6000 GPU or the newly supported NVIDIA RTX 6000 Ada Generation GPU, delivering AI performance up to 1705 TOPS. Built on the NVIDIA IGX platform, the MIC-735M-IO seamlessly integrates with NVIDIA Holoscan, enabling real-time AI processing and supporting the MONAI framework for training deep learning models optimized for medical AI workflows. Using NVIDIA Holoscan, the MIC-735M-IO enhances visualization and automatic anomaly detection, enabling doctors to perform surgery on Endoscopy Surgical Systems more effectively and with ultra-low latency. Additionally, the MIC-735M-IO comes with documentation for medical certifications (IEC 60601, 62304) to ensure compatibility with existing medical equipment.
The Advantech VEGA Series: Delivering Ultra-Low Latency and High-Quality Video for Real-Time Surgical Navigation
Advantech has developed a range of video-over-IP products using SDVoE technology, including the VEGA 1000 series UHD video converter systems and the VEGA-3003 UHD SDVoE video capture card, specifically designed for remote video transmission. The VEGA-1200 and VEGA-1100 are essential for processing 4K video clips in digital OR systems, transmitting via 10G Ethernet using SDVoE technology. Additionally, the VEGA-3003 decodes video sources, ensuring ultra-low latency and high-quality video composition. These VEGA SDVoE solutions integrate seamlessly within the OR, ensuring reliable video reception and maintaining top-quality standards, enabling surgeons to make precise, real-time decisions based on AI-processed data.
With this advancement, healthcare centers can significantly advance their endoscopy surgical system technology by leveraging Advantech's AI platform, NVIDIA Holoscan, and SDVoE video over IP technologies. This integration accelerates AI model deployment, improves surgical accuracy, and achieves high-precision image analysis with ultra-low latency video transmission. For more information about this project, please contact your local sales team.
About Advantech: Advantech's corporate vision is to enable an intelligent planet. The company is a global leader in the fields of IoT intelligent systems and embedded platforms. To embrace the trends of IoT, big data, and artificial intelligence, Advantech promotes IoT hardware and software solutions with the Edge Intelligence WISE-PaaS core to assist business partners and clients in connecting their industrial chains. Advantech is also working with business partners to co-create business ecosystems that accelerate the goal of industrial intelligence. (www.advantech.com)
SOURCE Advantech

Transforming Healthcare with Real-Time AI Image Analytic

/PRNewswire/ -- Advantech announces enhanced AI detection for endoscopy surgical systems with the integration of its MIC-735M-IO, powered by NVIDIA IGX™, and...

www.prnewswire.com

 

[Bravo]

Published 7 Nov 2024

Can Nvidia’s ‘Hyper Moore’s Law’ Spark An AI Revolution?

Jensen Huang, the CEO of Nvidia discussed on the No Priors AI-focused podcast the concept of "Hyper Moore’s Law."

www.forbes.com

EXTRACT

 

[Pom down under]

Poxy jet lag

 

[Pom down under]

Old video but don’t think it’s been posted, nor have I watched it

 

[Pom down under]

Not sure if posted plus a video in it with Anil

Neuromorphic NPU Sips Power to Handle Edge Machine-Learning Models

BrainChip’s Akida Pico neural processing unit, which leverages spiking neural networks, targets low-power IoT and edge-computing devices.

www.electronicdesign.com

 

[FiveBucks]

Not sure if posted plus a video in it with Anil

Neuromorphic NPU Sips Power to Handle Edge Machine-Learning Models

BrainChip’s Akida Pico neural processing unit, which leverages spiking neural networks, targets low-power IoT and edge-computing devices.

www.electronicdesign.com

A video with anil in it..... NSFW?

 

[Smoothsailing]

Old video but don’t think it’s been posted, nor have I watched it

ARM mention NN at 25.30

 

[Townyj]

Poxy jet lag

Not sure what it is about this Ipxchange fella.. but he is an awkward interviewer.

 

[Dallas]

Coca-Cola hat seinen ikonischen Weihnachts-Spot mit generativem KI umgesetzt https://the-decoder.de/coca-cola-hat-seinen-ikonischen-weihnachts-spot-mit-generativer-ki-umgesetzt/

 

[manny100]

If you have had a look over on the crapper you will understand why the Government is planning to ban access to social media for the under 16's.
They are digging for dumb over there.

 

[Frangipani]

A random Google search came up with this to-be-launched-soon product on a Taiwanese website:

Coming soon

Coming soon - Manual and Semi-Auto wafer level probe station, prober repair/upgrade, power device parameter analyzer, secondhand probe stations/measuring equipment sales, measure DC (IV/CV), WAT probe cards, IC touch. - Product List - Zhi-Hsin Technology 稚欣科技

www.zhi-hsin.com.tw

Pure coincidence (since other names of products on that Zhi-Hsin Technology website - both by Apollowave and SJD Technology - are also made up of a letters/number combination) or could there be more to it?

Company | APOLLO WAVE

www.apollowave.co.jp