BRN Discussion Ongoing

[JDelekto]

It is really quite simple.

AKIDA is SNN. Prophesee produces spikes so they just plug in to each other and work.

When you travel to the UK from Australia and you want to recharge your laptop you need a converter which you plug into the wall socket then plug in your laptop. This allows you to then charge your laptop. The extra wires and bits and pieces in this converter adds time (latency)to how long the power takes to get from the wall socket to your lap top and also adds resistance which uses up some of the charge travelling from the socket to your laptop. Your laptop will still charge up and work.

Should add if you leave it on charging for a while you will notice the converter becomes warm so you are losing energy through heat.

So Prophesee if it is not connected to a natively spiking processor like AKIDA sends out its spikes just the same but to be used by Qualcomm it needs to convert the spikes into something else so it’s processor can understand and process the information in the original spikes.

In the process of conversion there is some loss of energy/information so the converted spikes produce suboptimal information for Qualcomm to process.

It still works but not as well as it might if it did not have to convert the spikes first before they were processed.

In the camera on your mobile for taking happy snaps this is probably not a particular issue however the extra power draw needed to convert the spikes so they can be processed and the extra power used by a neuromorphic processor that does not use SNN could be significant and reduce battery life to such an extent that the selfie generation might get annoyed an choose an iPhone.

There is also the question of extra heat and the actual cost of the electronics involved.

Where suboptimal performance of Prophesee’s vision sensor would not be acceptable would be in tracking hypersonic missiles and planes where you do not want to waste a single spike or milli second. Even counting pills if complete accuracy is required would necessitate every spike being accounted for.

Hope this helps.

My opinion only DYOR
FF

AKIDA BALLISTA

Are we sure that Qualcomm's latest Snapdragon doesn't provide an SNN?

This old article from 2013 suggests that Qualcomm's Zeroth platform was using an SNN and I wonder if that technology has made it into the newer processors.

 

[Tothemoon24]

This company is at the cutting edge in cancer detection.

Processing of data I can’t find atm , might be worth a closer look .

Sending much love to those who’s lives have been effected by this cruel monster .

Be great if the mighty Bchip played a part in kicking the f..ker in the arse

• Ibex Medical Analytics Enters Collaboration with AstraZeneca and Daiichi Sankyo to Develop AI-based HER2 Scoring Product

24 Jan, 2023
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Ibex’s AI Algorithm to Aid Pathologists with Accurate and Reproducible HER2 and HER2-low Assessment in Breast Cancer Diagnosis
Tel Aviv, Israel – January 24, 2023 – Ibex Medical Analytics (Ibex), the leader in AI-powered cancer diagnostics, today announced an agreement with AstraZeneca and Daiichi Sankyo, for the development, clinical validation and early adoption of an AI-powered product to aid pathologists with an accurate and reproducible assessment of HER2 immunohistochemistry (IHC) scoring in breast cancer patients.
Scoring of HER2 (human epidermal growth factor receptor 2) protein expression in breast cancer is used to identify patients who are likely to benefit from HER2-directed therapies. Currently, pathologists routinely score HER2 in tumor samples visually using a microscope, which can be challenging in cases of low HER2 expression as scoring is subjective and may lead to varied interpretations. Computational tools developed using Artificial Intelligence have the potential to support pathologists in accurate and objective scoring of HER2, which can help oncologists in selecting therapies that are approved for treating patients with HER2-positive or HER2-low breast cancer.
“Recognizing the vital role pathologists play in the diagnosis and treatment of cancer patients, we are thrilled to partner with AstraZeneca and Daiichi Sankyo to clinically validate our automated HER2 scoring product and offer it to laboratories around the world,” said Joseph Mossel, Co-founder and CEO of Ibex Medical Analytics. “As the most commonly diagnosed cancer in women, this collaboration will allow pathologists to utilize our technology to optimize breast cancer diagnosis and ultimately improve the identification of patients eligible for HER2-directed therapy.”
Ibex’s Galen™ Breast HER2 is an IHC scoring product that detects tumor areas and quantifies HER2 expression into four standard categories, 0, 1+, 2+ and 3+, based on the 2018 ASCO/CAP scoring guidelines1. As part of this collaboration, Ibex will work with AstraZeneca and Daiichi Sankyo to develop and clinically validate its HER2 IHC scoring product and generate evidence that further supports adoption of the technology.
A multi-site validation study on Galen Breast HER2 involved a cohort of 453 breast tumors of diverse subtypes. The study demonstrated that Galen’s AI algorithm provides an accurate and automated HER2 score for pathologists and was recently presented at the San Antonio Breast Cancer Symposium2.
Beyond this collaboration, Ibex supports pathologists with AI-based diagnostic solutions that help detect and grade different types of invasive and non-invasive breast cancer and other tumor types, and are used in everyday practice in laboratories, hospitals and health systems worldwide. Ibex’s Galen Breast solution demonstrated robust outcomes in detecting and grading multiple types of breast cancer and other clinically relevant features across clinical studies performed on numerous diagnostic workflows, one of which was recently published in Nature’s peer-reviewed npj Breast Cancer journal3,4.
In addition to HER2, Ibex is further expanding Galen Breast to include automated quantification of additional IHC-stained slides, such as ER, PR and Ki-67, intended to provide pathologists with a comprehensive set of tools for breast cancer diagnosis. With these expanded capabilities, Galen Breast may further enhance diagnostic efficiency and enable more accurate and objective scoring of breast biomarkers, improving treatment decisions and patient care.

Ibex's Galen™ Prostate Becomes First Standalone AI-Powered Cancer Diagnostics Solution to Obtain CE Mark Under the IVDR​

---

NEWS PROVIDED BY
Ibex Medical Analytics
Feb 09, 2023, 08:00 ET

---

Pathology Diagnostics Platform Meets Safety, Quality and Performance Criteria Under EU's New In Vitro Diagnostic Medical Devices Regulation.
TEL AVIV, Israel, Feb. 9, 2023 /PRNewswire/ -- Ibex Medical Analytics (Ibex), the leader in AI-powered cancer diagnostics, today announced that Galen™ Prostate is now CE marked under the In Vitro Diagnostic Medical Devices Regulation (IVDR) for supporting pathologists in primary diagnosis of prostate biopsies. Galen Prostate is the first standalone AI-based cancer diagnostics product of its kind certified under the IVDR.
IVDR is the new regulatory standard set by the European Union, replacing the previous In Vitro Diagnostic Medical Device Directive (IVDD). The new regulation sets a new bar for product performance and clinical validation, as well as post marketing surveillance. Galen Prostate received its IVDR CE certificate following a rigorous review demonstrating the quality of the product and its meticulous development process, safety, and performance. During 2023, Ibex plans to migrate additional products, including its Galen Breast and Galen Gastric solutions, under the IVDR certificate.
"Ibex continues to maintain the highest possible standards for its products, bringing cutting-edge computational solutions to improve outcomes of cancer care," said Dr. Yael Liebes-Peer, Head of Regulatory Affairs and Quality Assurance at Ibex Medical Analytics. "Dedicated to our mission of providing every patient with an accurate, timely and personalized cancer diagnosis, we are proud to provide the market's first IVDR-certified product, elevating the quality of diagnosis for patients, pathologists and laboratories."
To help improve the quality of cancer diagnosis, increase productivity and optimize pathology workflows, Galen Prostate uses AI to analyze biopsies ahead of pathologists' review, providing them with diagnostic insights to guide their diagnosis. Galen Prostate's algorithms were trained on large datasets from multiple pathology institutes around the world, enriched with rare prostatic malignancies. Galen helps pathologists diagnose cancer, provides additional insights, including a Gleason score, tumor size and associated morphologies for each cancer slide, and offers decision support tools to help accelerate diagnostic turnaround and reduce subjectivity.
Ibex offers the most widely deployed AI technology in pathology, supporting pathologists worldwide with augmented diagnostic capabilities during diagnosis of breast, prostate, and gastric biopsies. Improving dignostic accuracy, reducing turnaround time, boosting productivity and improving user experience for pathologists, Galen has demonstrated excellent outcomes across multiple clinical studies performed in different pathology labs and diagnostic workflows1,2,3,4,5.

 

[Zedjack33]

This company is at the cutting edge in cancer detection.

Processing of data I can’t find atm , might be worth a closer look .

Sending much love to those who’s lives have been effected by this cruel monster .

I just spent 3 weeks in the sticks with no contact. First contact was a message that my brother has cancer and radio starts asap. Would be great for Brn to fast forward. Will be too late for others unfortunately.

 

[Tothemoon24]

So sorry to read your unfortunate news Zedjack, wishing you & your brother the best of luck .

 

[Rise from the ashes]

Best of luck to your brother my thoughts and prayers are with him. @Zedjack33

 

[Diogenese]

Are we sure that Qualcomm's latest Snapdragon doesn't provide an SNN?

This old article from 2013 suggests that Qualcomm's Zeroth platform was using an SNN and I wonder if that technology has made it into the newer processors.

Hi JD,


A few days ago, @Stable Genius posted this diagram of Snapdragon 8.2 which has a pair of AI preprocessors:

In response, I posted this Qualcomm patent application which shows an arrangement with a pair of "split" accelerators:

• #48,708

US2020250545A1 SPLIT NETWORK ACCELERATION ARCHITECTURE

[0041] FIG. 3 is a block diagram illustrating a neural network acceleration architecture 300 , in accordance with aspects of the present disclosure. The neural network acceleration architecture 300 includes a first AI inference accelerator (e.g., first AIIA 330 ), a second AI inference accelerator (e.g., second AIIA 340 ), and a host processor 310 . In this configuration, the host processor 310 includes a host runtime block 312 to execute a host application 320 to operate a neural network. In this example, the neural network of the host application 320 exceeds a fixed amount of memory provided by a single AI inference accelerator (AIIA).

[0042] According to this aspect of the present disclosure, the neural network of the host application 320 is split across the first AIIA 330 and the second AIIA 340 .

Interestingly, the block diagram of the Snapdragon in the patent is virtually unchanged from the block diagram in the 2013 article.

 

[Jumpchooks]

Agreed @Steve10, that's what caught my eye when first reading it. The very first "Target Application" listed is:

• Image processing (blur, background elimination, etc).

So, what products would require this application?

Phobile Mones?

 

[MrRomper]

@Diogenese your assistance please with this Intel patent.
Are they trying to pole vault the moat and block Brainchip's future patents using external memory.

https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11593623

Thanks in advance.

 

[Frangipani]

@Zedjack33, sorry to hear that your family is going through this… All the best for your brother!
Hopefully mRNA technology will - again - prove to be a game changer with personalised therapeutic cancer vaccines in the near future. While the COVID-19 pandemic abruptly thrust mRNA technology into the limelight on a global stage and most people had probably never heard of it prior to 2020, oncological research in this field has actually been going on for two decades and recent trials have shown promising results.

 

[Slade]

Not sure if this has been shared but it’s great to see Global Foundries, GM, Renesas, Oculi and Brainchip mentioned in the same article.

I particularly liked this:
“GF is also championing the computing sector, namely with BrainChip's Akida neuromorphic chip built on 22 nm fully depleted silicon-on-insulator (FD-SOI)technology.”

https://www.allaboutcircuits.com/news/in-series-agreements-globalfoundries-buoys-chip-supply-from-home/

 

[Diogenese]

@Diogenese your assistance please with this Intel patent.
Are they trying to pole vault the moat and block Brainchip's future patents using external memory.

https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11593623

Thanks in advance.

Hi MrRomper,

That patent is no threat to Akida.

It has very inelegant architecture and uses processors during the inference operation. It also is synchronous.

All that interplay with external memories is an homage to John von Neumann.

The claims relate to a configuration which is alien to Akida:

1. A system for processing spiking neural network operations, the system comprising:
a plurality of neural processor clusters, each of the neural processor clusters to operate a plurality of neurons of a neural network, wherein each of the neural processor clusters comprises:
at least one neural processor to determine respective states of the plurality of neurons;
internal memory to maintain the respective states of the plurality of neurons;
an address generation unit to determine, based on a spike message received from a respective axon processor, a corresponding memory address for a particular postsynaptic neuron tracked in the internal memory; and
a control unit to:
retrieve neuron state data for the particular postsynaptic neuron from the internal memory, based on the corresponding memory address;
modify a potential of the particular postsynaptic neuron indicated in the neuron state data, based on the spike message received from the respective axon processor; and
write the neuron state data for the particular postsynaptic neuron back to the internal memory;
a plurality of axon processors, each of the axon processors to process synapse data of a plurality of synapses in the neural network, wherein the axon processors are coupled to respective banks of external memory, and wherein each of the axon processors comprises a control unit to:
retrieve synapse data of a subset of the plurality of synapses from a respective bank of the external memory;
evaluate the synapse data, based on a spike message received from a presynaptic neuron of a neural processor cluster; and
transmit, based on the evaluated synapse data, a weighted spike message to a postsynaptic neuron at a neural processor cluster.

This flow chart illustrates the use of the neuron processor (605) and the axon processor (610) as well as retrieving data from external memory (615) during operation.

 

[Deleted member 118]

Looks like today might be the day @DingoBorat or do I hold of a little bit longer with the overall SP still falling due to LDA cashing in.

 

[TechGirl]

Not sure if this has been shared but it’s great to see Global Foundries, GM, Renesas, Oculi and Brainchip mentioned in the same article.

I particularly liked this:
“GF is also championing the computing sector, namely with BrainChip's Akida neuromorphic chip built on 22 nm fully depleted silicon-on-insulator (FD-SOI)technology.”

https://www.allaboutcircuits.com/news/in-series-agreements-globalfoundries-buoys-chip-supply-from-home/

Bloody Brilliant article

Thanks Slade

 

[TopCat]

Has anyone here ever done any research on Dolphin Designs. Partners with Global Foundries and has designs with FD-SOI at 22nm and claims mW power consumption for sensors at the VERY edge! Clients now exceeding 500!

[Press release] Dolphin Design wins an Embedded Award for Tiny Raptor, its Energy-Efficient Neural Network AI Accelerator - Accelerate Energy Efficient SoC designs - Dolphin Design

Embedded World, Nuremberg, Germany, 21 June 2022. Dolphin Design, an advanced chip design company and leader in Edge Computing and AI platforms for the Internet of Things (IoT), receives the Embedded World Award 2022 in the start-up category for Tiny Raptor. This IP represents a breakthrough in...

www.dolphin-design.fr

Tiny RAPTOR is a complete Neural Processor solution to deploy AI at the very edge combining Software and Hardware approaches, resulting from more than three years of development, together with CEA-List in a joint laboratory.

CEA-Leti & Dolphin Design Report FD-SOI Breakthrough that Boosts Operating Frequency by 450% and Reduces Power Consumption by 30%

GRENOBLE, France – Feb. 22, 2021 – CEA-Leti and Dolphin Design have developed an adaptive back-biasing (ABB) architecture for FD-SOI chips that can be seamlessly integrated in the digital design flow with industrial-grade qualification, overcoming integration drawbacks of existing ABB techniques.

www.leti-cea.fr

CEA-Leti & Dolphin Design Report FD-SOI Breakthrough that Boosts Operating Frequency by 450% and Reduces Power Consumption by 30%​

The architecture enables reducing energy consumption of processors in 22nm FD-SOI technology by up to 30 percent and increasing the operating frequency up to 450 percent compared to a technique in which body biased technique is not used. It also improves the manufacturing yield.

About Dolphin Design

Headquartered in France, Dolphin Design, previously known as Dolphin Integration, is a semiconductor company employing 160 people, including 140 highly qualified engineers. They provide differentiating platform solutions built on state-of-the-art IPs and architectures, customized by unique system level utilities to deliver fast and secure ASICs, either designed by or for their clients. These platforms are available for various technological processes and optimized for Energy Efficient SoC Design. Alongside their clients, now exceeding 500 companies, they focus on human, inventive and long-term collaboration to enable them to bring products, powered by innovative and accessible integrated circuits that minimize environmental impact, to the hands of billions of people every day. In consumer markets including IoT, AI and 5G, and in high reliability markets, they unleash SoC designer creativity to deliver differentiation.

 

[Fact Finder]

Has anyone here ever done any research on Dolphin Designs. Partners with Global Foundries and has designs with FD-SOI at 22nm and claims mW power consumption for sensors at the VERY edge! Clients now exceeding 500!

[Press release] Dolphin Design wins an Embedded Award for Tiny Raptor, its Energy-Efficient Neural Network AI Accelerator - Accelerate Energy Efficient SoC designs - Dolphin Design

Embedded World, Nuremberg, Germany, 21 June 2022. Dolphin Design, an advanced chip design company and leader in Edge Computing and AI platforms for the Internet of Things (IoT), receives the Embedded World Award 2022 in the start-up category for Tiny Raptor. This IP represents a breakthrough in...

www.dolphin-design.fr

Tiny RAPTOR is a complete Neural Processor solution to deploy AI at the very edge combining Software and Hardware approaches, resulting from more than three years of development, together with CEA-List in a joint laboratory.

CEA-Leti & Dolphin Design Report FD-SOI Breakthrough that Boosts Operating Frequency by 450% and Reduces Power Consumption by 30%

GRENOBLE, France – Feb. 22, 2021 – CEA-Leti and Dolphin Design have developed an adaptive back-biasing (ABB) architecture for FD-SOI chips that can be seamlessly integrated in the digital design flow with industrial-grade qualification, overcoming integration drawbacks of existing ABB techniques.

www.leti-cea.fr

CEA-Leti & Dolphin Design Report FD-SOI Breakthrough that Boosts Operating Frequency by 450% and Reduces Power Consumption by 30%​

The architecture enables reducing energy consumption of processors in 22nm FD-SOI technology by up to 30 percent and increasing the operating frequency up to 450 percent compared to a technique in which body biased technique is not used. It also improves the manufacturing yield.

About Dolphin Design

Headquartered in France, Dolphin Design, previously known as Dolphin Integration, is a semiconductor company employing 160 people, including 140 highly qualified engineers. They provide differentiating platform solutions built on state-of-the-art IPs and architectures, customized by unique system level utilities to deliver fast and secure ASICs, either designed by or for their clients. These platforms are available for various technological processes and optimized for Energy Efficient SoC Design. Alongside their clients, now exceeding 500 companies, they focus on human, inventive and long-term collaboration to enable them to bring products, powered by innovative and accessible integrated circuits that minimize environmental impact, to the hands of billions of people every day. In consumer markets including IoT, AI and 5G, and in high reliability markets, they unleash SoC designer creativity to deliver differentiation.

View attachment 31236 View attachment 31235

Going back a bit in the old memory banks to when Mr. Dinardo was CEO someone asked about Raptor and the response from Peter van der Made was it is just an accelerator.

The reason I mention this was in the time of Mr. Dinardo he was hammering away to shareholders and the market that AKIDA was not an accelerator but a processor, a tiny Ai computer on a chip.

When he departed Rob Telson moved the language back towards describing AKIDA as an accelerator and I suggested at the time that this change in language may have been driven by customers inability to understand just what AKIDA was all about whereas they had some understanding of accelerators.

By describing AKIDA as an accelerator it was easier to get through the customers front door where they could then be educated as to what AKIDA was and why it should be chosen over a simple accelerator.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Steve10]

Another company to keep an eye on is SiTime which is owned by MegaChips.

SiTime | The Precision Timing Company | MEMS Timing, Oscillator, TCXO, OCXO, Silicon Oscillators, MEMS Resonator, Clock Timing

SiTime is a leader in MEMS timing solutions, having shipped billions of units. Learn about our silicon MEMS oscillators, TCXOs, OCXOs, MEMS resonators, clock generators, jitter cleaners, clock timing, timing clock, sitm stock, and much more.

www.sitime.com

SiTime Transforms Precision Timing Market for Edge Networks​

DATA CENTER AND CO-LOCATIONNEWS
By AIT News Desk On Mar 17, 2022

SiTime Corporation , a market leader in precision timing, introduced the Elite X Super-TCXO for edge networks such as data centers, 5G front haul, connected cars and industrial IoT. In these applications, Elite X solves critical timing problems and enables delivery of new services.

“Our Elite X Super-TCXO shines by delivering 2x better stability and 30x higher reliability than quartz. Consequently, we believe that Elite X will now be the precision timing device of choice in edge equipment,” said Piyush Sevalia, SiTime.

“Twenty-two million autonomous vehicles on the road by 2025, the rapid adoption of 5G, and the continued growth of data centers will require a large buildout in outdoor, decentralized edge networks,” said Piyush Sevalia, executive vice president of marketing at SiTime. “These new edge devices and their precision timing heartbeat must perform reliably in the presence of extreme temperatures, thermal shock, and vibration. Here, our Elite X Super-TCXO shines by delivering 2x better stability and 30x higher reliability than quartz. Consequently, we believe that Elite X will now be the precision timing device of choice in edge equipment.”

To enable new time-sensitive services such as ADAS, virtual reality, and smart manufacturing, edge devices will need to deliver faster speeds with lower latency. Precision timing plays a crucial role in their success. Legacy timing devices such as quartz TCXOs and mini-OCXOs have well-known weaknesses such as sensitivity to thermal shock and vibration, stability degradation at high temperatures, and shorter operating life. By using silicon MEMS technology that is inherently more robust and reliable, Elite X overcomes these problems and enables the next generation of time-sensitive services everywhere.

In edge networks, additional specifications such as aging, warm-up time, and power consumption are important for overall performance. Even here, SiTime Elite X outperforms legacy timing devices, simplifies system design, and offers dependable, consistent performance.

With Elite X (±10-20 ppb stability), Emerald (±5 ppb), and Elite (±50-500 ppb), SiTime offers a broad portfolio of best-in-class TCXOs and OCXOs that meet various application requirements in communications, networking, automotive, and industrial IoT.

SiT5501 Elite X Super-TCXO Features and Benefits

The SiT5501 Elite X Super-TCXO includes the following features and benefits:

• ±10 ppb frequency stability
• -40°C to +105°C operating temperature. More applications require 105°C operation.
• 110 mW typical power consumption
• Small package, 7.0 mm x 5.0 mm
• ±0.5 ppb/°C dF/dT (frequency slope), resistant to thermal shock and airflow
• ±0.5 ppb daily aging
• Any frequency from 1 to 60 MHz with up to 6 decimal places of accuracy

SiTime Transforms Precision Timing Market for Edge Networks

SiTime Corporation , a market leader in precision timing, today introduced the Elite X Super-TCXO for edge networks such as data centers,

aithority.com

Blog​

• Company
• News
• SiTime Blog
• Timing's Critical Role in the AI Revolution

JAN092018
Timing's Critical Role in the AI Revolution
Posted By: Mark Bajus
Small timing devices run a big part of our lives, and many times, we fail to realize it. I sat down with Aaron Partridge, the chief scientist at SiTime, to discuss his prognostications for the future of the electronics industry and the role that timing will play.

As you look ahead, what trends in electronics do you see?​

One giant trend that I see is the development of AI systems. Artificial intelligence will usher in the next wave of the industrial revolution. The first wave used steam power to mechanize production and travel in the 1780s and extended this with fossil fuel in the 1920s. The second used electronics and software to automate communications in the 1980s. Today, we need to process the data from our increasingly digitized world. AI organizes this data to augment our mental limits.
One can think of technology as extending our human limits. The first wave amplified our muscles, in that we can fly, drive, and move heavy objects. The second wave amplified our senses, in that we could hear people thousands of miles away or see minute objects. And the third wave is now amplifying our ability to think.

You use the present tense to talk about the next wave of the industrial revolution. Why is that?​

That’s the thing with technological revolutions. When we are in the midst of them, many of us don’t notice that change is happening. The technology slowly creeps into our lives. We won’t wake up one day and suddenly live in the world of the Jetsons. Right now, the personal assistants in our mobile devices, the self-driving car I just bought, they both use artificial intelligence.

What is timing’s role in AI?​

Timing will play a critical role in the communications infrastructure that AI leverages. When many people think about artificial intelligence, they think of robots, but it is about more than that. It’s also about processing massive amounts of data. So, AI relies on data centers to store information and on high-speed radio and fiber to transport the information – all of which relies on timing. Without high-performance oscillators, artificial intelligence systems wouldn’t be able to process the data reliably and without latency.

How do you see AI fitting into the evolution of timing?​

That’s a pretty big question. What did timing mean to the Romans? The Romans could precisely measure sunrise, midday, and sunset. Their sundials divided the day into 12 hours of daylight and 12 hours of nighttime, and the length of the hours depended on the length of the day. So, if Romans agreed to meet at 1:00, they were probably accurate to maybe 20 minutes.
Skip ahead a couple millennia to today. Our phones know what time it is to a microsecond. Our GPS receivers know the accurate time to within thirty billionths of a second. So, we’ve gone from 1,000 seconds to a millionth-of-a-second accuracy. That is a billion time more accurate.
And we are not done. The upcoming 5G phones will hold time at least 10x more accurately than 4G, and soon GPS receivers will keep track of time down to one billionth of a second. So, that is a trillion times more accurate than the Romans.

In addition to accuracy, what else will be needed for AI systems?​

People are now talking about “the internet of things.” All of those “things” will be networked, and networking requires timing. So, in that sense, we are dealing with the “internet of time-synchronized things.”

In a world of artificial intelligence and time-synchronized things, there will be a massive number of sensors everywhere, and they will need to be smaller, consume less power, and continue to perform reliably as they age. MEMS-based timing solutions, like the ones from SiTime, fit perfectly into that world.

Timing's Critical Role in the AI Revolution | SiTime

AI systems would not be possible without timing. Aaron Partridge, the chief scientist at SiTime, explains the role that timing will play.

www.sitime.com

 

[toasty]

Yep. You put used trays in it and when it's full it drives into the kitchen, dodging people, to be unloaded. Just couldn't resist taking a photo for the 1000 eyes!

There's one of these operating at Mugen House, a Japanese restaurant in Adelaide..................

 

[buena suerte :-)]

ANNOUNCEMENT


$$$$$$$ BrainChip Introduces Second-Generation Akida Platform $$$$$$$


• Drives extremely efficient and intelligent edge devices for Artificial Intelligence of Things (AIoT) solutions
• New generation of Akida allows designers and developers to incorporate features that were not possible before
• Adds capabilities that are critically needed in industrial, automotive, digital health, smart home and smart city applications

Sydney – 06 March 2023: BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low power, fully digital, neuromorphic AI IP, today announced the launch of the second generation of its Akida™
platform that drives extremely efficient and intelligent edge devices for the Artificial Intelligence of Things (AIoT) solutions and services market that is forecast to be worth US$1T+ by 2030 according to an industry report published by Fortune Business Insights. Sean Hehir, BrainChip CEO said, “Our customers wanted us to enable expanded predictive intelligence, target tracking, object detection, scene segmentation, and advanced vision capabilities.
This new generation of Akida allows designers and developers to do things that were not possible before on an Edge device. By inferring and learning from raw sensor data, we take a substantial step toward a cloudless Edge AI experience. With this launch, we have significantly extended our competitive advantage in neuromorphic AI.” This hyper-efficient, yet powerful neural processing system, architected for embedded Edge AI applications, now adds efficient 8-bit processing to go with advanced capabilities such as time domain convolutions and vision transformer acceleration, for an unprecedented level of performance in sub-watt devices, taking them from perception towards cognition. The second-generation of Akida now includes Temporal Event Based Neural Nets (TENN) spatial-temporal convolutions that supercharge the processing of raw time-continuous streaming data, such as video analytics, target tracking, audio classification, analysis of health monitoring data such as heart rate and respiratory rate for vital signs prediction, Page | 2 and time series analytics used in forecasting, and predictive production line maintenance.

These capabilities are critically needed in industrial, automotive, digital health, smart home and smart city applications. The TENNs allow for radically simpler implementations by consuming raw data directly from sensors - drastically reducing model size and operations performed, while maintaining very high accuracy. This can shrink design cycles and dramatically lower the cost of development. Mr Hehir added, “The development of the second generation of Akida was strongly influenced by our customers’ feedback and driven by our extensive market engagement. We have recently expanded our sales organisation to become truly global and we are focused on executing more IP licence agreements and generating revenue growth over coming years. Another addition to the second generation of Akida is Vision Transformers (ViT) acceleration, a leading-edge neural network that has been shown to perform extremely well on various computer vision tasks, such as image classification, object detection, and semantic segmentation.

The Akida IP platform has a unique ability to learn on the device for continuous improvement and data-less customization that improves security and privacy. This, combined with the efficiency and performance available, enable very differentiated solutions that until now have not been possible. These include secure, small battery powered devices like hearing aids and wearable electronic devices such as watches, medical devices for monitoring vital signs, and consume only microwatts of power. This can scale up to HD-resolution vision solutions delivered through high-value, batteryoperated or fan-less devices enabling a wide variety of applications from surveillance systems to factory management and augmented reality to scale effectively. Akida’s software and tooling further simplifies the development and deployment of solutions and services with these features: • An efficient runtime engine that autonomously manages model accelerations completely transparent to the developer • MetaTF™ software that developers can use with their preferred framework, like TensorFlow/Keras, or development platform, like Edge Impulse, to easily develop, tune, and deploy AI solutions. • Supports all types of Convolutional Neural Networks (CNN), Deep Learning Networks (DNN), Vision Transformer Networks (ViT) as well as Spiking Neural Networks (SNNs), future-proofing designs as the models get more advanced. Akida comes with a Models Zoo and a burgeoning ecosystem of software, tools, and model vendors, as well as IP, SoC, foundry and system integrator partners. Page | 3 General availability will follow in Q3’ 2023.

A formal platform launch press release will take place on 7 March at 1:00am AEDT, 6 March at 6:00am US PST. This announcement is authorised for release by the BRN Board of Directors About BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY) BrainChip is the worldwide leader in edge AI on-chip processing and learning. The company’s first-to-market, fully digital, event-based AI processor, AkidaTM, uses neuromorphic principles to mimic the human brain, analysing only essential sensor inputs at the point of acquisition, processing data with unparalleled efficiency, precision, and economy of energy. Akida uniquely enables edge learning local to the chip, independent of the cloud, dramatically reducing latency while improving privacy and data security.

Akida Neural processor IP, which can be integrated into SoCs on any process technology, has shown substantial benefits on today’s workloads and networks, and offers a platform for developers to create, tune and run their models using standard AI workflows like TensorFlow/Keras. In enabling effective edge compute to be universally deployable across real world applications such as connected cars, consumer electronics, and industrial IoT, BrainChip is proving that onchip AI, close to the sensor, is the future, for its customers’ products, as well as the planet. Explore the benefits of Essential AI at www.brainchip.com. Follow BrainChip on Twitter: https://www.twitter.com/BrainChip_inc Follow BrainChip on LinkedIn: https://www.linkedin.com/company/779200

 

[Fact Finder]

BrainChip Introduces Second-Generation Akida Platform • Drives extremely efficient and intelligent edge devices for Artificial Intelligence of Things (AIoT) solutions • New generation of Akida allows designers and developers to incorporate features that were not possible before • Adds capabilities that are critically needed in industrial, automotive, digital health, smart home and smart city applications Sydney – 06 March 2023: BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low power, fully digital, neuromorphic AI IP, today announced the launch of the second generation of its Akida™ platform that drives extremely efficient and intelligent edge devices for the Artificial Intelligence of Things (AIoT) solutions and services market that is forecast to be worth US$1T+ by 2030 according to an industry report published by Fortune Business Insights. Sean Hehir, BrainChip CEO said, “Our customers wanted us to enable expanded predictive intelligence, target tracking, object detection, scene segmentation, and advanced vision capabilities. This new generation of Akida allows designers and developers to do things that were not possible before on an Edge device. By inferring and learning from raw sensor data, we take a substantial step toward a cloudless Edge AI experience. With this launch, we have significantly extended our competitive advantage in neuromorphic AI.” This hyper-efficient, yet powerful neural processing system, architected for embedded Edge AI applications, now adds efficient 8-bit processing to go with advanced capabilities such as time domain convolutions and vision transformer acceleration, for an unprecedented level of performance in sub-watt devices, taking them from perception towards cognition. The second-generation of Akida now includes Temporal Event Based Neural Nets (TENN) spatial-temporal convolutions that supercharge the processing of raw time-continuous streaming data, such as video analytics, target tracking, audio classification, analysis of health monitoring data such as heart rate and respiratory rate for vital signs prediction, Page | 2 and time series analytics used in forecasting, and predictive production line maintenance. These capabilities are critically needed in industrial, automotive, digital health, smart home and smart city applications. The TENNs allow for radically simpler implementations by consuming raw data directly from sensors - drastically reducing model size and operations performed, while maintaining very high accuracy. This can shrink design cycles and dramatically lower the cost of development. Mr Hehir added, “The development of the second generation of Akida was strongly influenced by our customers’ feedback and driven by our extensive market engagement. We have recently expanded our sales organisation to become truly global and we are focused on executing more IP licence agreements and generating revenue growth over coming years. Another addition to the second generation of Akida is Vision Transformers (ViT) acceleration, a leading-edge neural network that has been shown to perform extremely well on various computer vision tasks, such as image classification, object detection, and semantic segmentation. The Akida IP platform has a unique ability to learn on the device for continuous improvement and data-less customization that improves security and privacy. This, combined with the efficiency and performance available, enable very differentiated solutions that until now have not been possible. These include secure, small battery powered devices like hearing aids and wearable electronic devices such as watches, medical devices for monitoring vital signs, and consume only microwatts of power. This can scale up to HD-resolution vision solutions delivered through high-value, batteryoperated or fan-less devices enabling a wide variety of applications from surveillance systems to factory management and augmented reality to scale effectively. Akida’s software and tooling further simplifies the development and deployment of solutions and services with these features: • An efficient runtime engine that autonomously manages model accelerations completely transparent to the developer • MetaTF™ software that developers can use with their preferred framework, like TensorFlow/Keras, or development platform, like Edge Impulse, to easily develop, tune, and deploy AI solutions. • Supports all types of Convolutional Neural Networks (CNN), Deep Learning Networks (DNN), Vision Transformer Networks (ViT) as well as Spiking Neural Networks (SNNs), future-proofing designs as the models get more advanced. Akida comes with a Models Zoo and a burgeoning ecosystem of software, tools, and model vendors, as well as IP, SoC, foundry and system integrator partners. Page | 3 General availability will follow in Q3’ 2023. A formal platform launch press release will take place on 7 March at 1:00am AEDT, 6 March at 6:00am US PST

 

[Diogenese]

New Akida design announced

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Bronze