BRN Discussion Ongoing

[DingoBorat]

They make a NPU Neural Processing Unit, but aren't touting neuromorphic?.. I think there's a difference @Diogenese?

Kneron Unveils the KL730 AI Chip, Propelling Low-Energy GPT Solutions at Scale | Kneron – Full Stack Edge AI

●Tackling the largest bottleneck in AI adoption - energy costs - the KL730 yields a 3 to 4 times leap in energy efficiency compared to previous Kneron models and versus peers●The KL730 offers base-level compute power starting from 0.35 to 4 effective tera operations per second, supporting the mos...

www.kneron.com

A lot of talk about use for Chat GPT models, so like in your article Esq, they definitely are trying to "ride" the A.I. wave..
They know where the attention is and they're going for it.

I don't think what they've got is a technical threat to us, but they are competition.

Neural Processor - WikiChip

A neural processor, a neural processing unit (NPU), or simply an AI Accelerator is a specialized circuit that implements all the necessary control and arithmetic logic necessary to execute machine learning algorithms, typically by operating on predictive models such as artificial neural networks...

en.wikichip.org

A neural processor, a neural processing unit (NPU), or simply an AI Accelerator is a specialized circuit that implements all the necessary control and arithmetic logic necessary to execute machine learning algorithms, typically by operating on predictive models such as artificial neural networks (ANNs) or random forests (RFs).

Nothing special, an accelerator..

 

[Stable Genius]

Hi all,

If you’re on this forum you probably already understand the content of this article but it educates on the differences between edge, far edge, cloud etc quite well. BRN not mentioned but it describes the landscape and where the technology is going.

Network-On-Chips Enabling Artificial Intelligence/Machine Learning Everywhere​

7Shares

What goes on between the sensor and the data center.
SEPTEMBER 28TH, 2023 - BY: FRANK SCHIRRMEISTER

Recently, I attended the AI HW Summit in Santa Clara and Autosens in Brussels. Artificial intelligence and machine learning (AI/ML) were critical themes for both events, albeit from different angles. While AI/ML as a buzzword is very popular these days in all its good and bad ways, in discussions with customers and prospects, it became clear that we need to be precise in defining what type of AI/ML we are talking about when discussion requirements of networks-on-chips (NoCs).

Where is AI/ML happening?​

To discuss where the actual processing is happening, I found it helpful to use a chart that shows what is going on between sensors that create the data, the devices we all love and use, the networks transmitting the data, and the data centers where a lot of the “heavy” computing takes place.

From sensors to data centers – AI/ML happens everywhere.
Sensors are the starting point of the AI/ML pipeline, and they collect raw data from the environment, which can be anything from temperature readings to images. At Autosens, in the context of automotive, this was all about RGB and thermal cameras, radar, and lidar. On-chip AI processing within sensors is a burgeoning concept where basic data preprocessing happens. For instance, IoT sensors utilize lightweight ML models to filter or process data, reducing the load and the amount of raw data to be transmitted. This local processing helps mitigate latency and preserve bandwidth. As discussed in some panels at Autosens, the automotive design chain needs to make some tough decisions about where computing happens and how to distribute it between zones and central computing as EE architectures evolve.
Edge devices are typically mobile phones, tablets, or other portable gadgets closer to the data source. In my view, cars are yet another device, albeit pretty complex, with its own “sensor to data center on wheels” computing distribution. The execution of AI/ML models on edge devices is crucial for applications that require real-time processing and low latency, like augmented reality (AR) and autonomous vehicles that cannot rely on “always on” connections. These devices deploy models optimized for on-device execution, allowing for quicker responses and enhanced privacy, as data doesn’t always have to reach a central server.
Edge computing is an area where AI/ML may happen without the end user realizing it. The far edge is the infrastructure most distant from the cloud data center and closest to the users. It is suitable for applications requiring more computing resources and power than edge devices but also needs lower latency than cloud solutions. Examples might include advanced analytics models or inference models that are heavy for edge devices but are latency-sensitive, the industry seems to adopt the term “Edge AI” for the computing going on here. Notable examples include facial recognition and real-time traffic updates on semi-autonomous vehicles, connected devices, and smartphones.
Data centers and the cloud are the hubs of computing resources, providing unparalleled processing power and storage. They are ideal for training complex, resource-intensive AI/ML models and managing vast datasets. High-performance computing clusters in data centers can handle intricate tasks like training deep neural networks or running extensive simulations, which are not feasible on edge devices due to resource constraints. Generative AI originally resided here, often requiring unique acceleration, but we already see it moving to the device edge as “On-Device Generative AI,” as shown by Qualcomm.
When considering a comprehensive AI/ML ecosystem, layers of AI/ML are intricately connected, creating a seamless workflow. For example, sensors might collect data and perform initial processing before sending it to edge devices for real-time inference. More detailed analysis takes place at far or near edge computing resources for more detailed analysis, before the data reaches data centers for deep insights and model (re-)training.

How are NoCs an enabler?​

As outlined above, AI/ML is happening everywhere, literally. However, as described, the resource requirements vary widely. NoCs play in three main areas here: (1) connecting the often very regular AI/ML subsystems, (2) de-risking the integration of all the various blocks on chips, and (3) connecting various silicon dies in a chiplet scenario (D2D) or various chips in a chip-to-chip (C2C) environment.

Networks-on-Chips (NoCs) as a critical enabler of AI/ML.
The first aspect – connecting AI/ML subsystems – is all about fast data movement, and for that, broad bit width, the ability to broadcast, and virtual channel functionality are critical. Some application domains are unique, as outlined in “Automotive AI Hardware: A New Breed.” In addition, the general bit-width requirements vary significantly between sensors, devices, and edges.
To enable the second aspect, connecting all the bits and pieces on a chip, it is all about the support of the various protocols – I discussed them last month in “Design Complexity In The Golden Age Of Semiconductors.” Tenstorrent’s Jim Kellerdescribed the customer concern regarding de-risking best in a recent joint press releaseregarding Arteris’ FlexNoC and Ncore technology: “The Arteris team and IP solved our on-chip network problems so we can focus on building our next-generation AI and RISC-V CPU products.”
Finally, the industry controversially discusses the connections between chiplets across all application domains. The physical interfaces with competing PHYs (XSR, BOW, OHBI, AIB, and UCIe) and their digital controllers are at the forefront of discussion. In the background, NoCs and “SuperNoCs” across multiple chiplets/chips must support the appropriate protocols. We are currently discussing Arm’s CHI C2C and other proposals. It will require the proverbial village of various companies to make the desired open chiplet ecosystem a reality.

Where are we heading from here?​

AI/ML’s large universe of resource requirements makes it an ideal fuel for what we experience as a semiconductor renaissance today. NoCs will be a crucial enabler within the AI/ML clusters, connecting building blocks on-chip and connecting chiplets carrying AI/ML subsystems. Brave new future, here we come!

Network-on-Chips Enabling Artificial Intelligence/Machine Learning Everywhere

What goes on between the sensor and the data center.

semiengineering.com

Happy Day Light Savings!

 

[TheFunkMachine]

Undoubtedly trying times for us shareholders. A number of posters have already replied to you reassuringly, expressing their (and also my) belief that the steep downward slide of the share price is multifactorial, but has nothing to do with our company’s sound fundamentals and its future growth potential at the extreme edge, just like you said yourself. The free fall of the share price in inverse correlation to Brainchip’s verifiable progress reminded me of a picture that I had posted in another (BRN-unrelated) thread a couple of months ago and that I’d like to share with you now.

While both my photo and comment happen to be about black and white swans, please note they do not relate to Nassim Nicholas Taleb’s theory of black swan events. And it’s sad that I have to explicitly state this, but with so many online trolls around, twisting one’s words, I’d better clarify upfront that the black/white dichotomy is of course not meant to carry any racist undertones whatsoever, along the lines of someone with a lighter skin colour being superior to someone with a darker complexion.

I would also like to apologise in advance to all waterfowl of the species Cygnus atratus that I personally do not perceive to be any less graceful than their majestic white cousins. As well as to to all residents or natives of WA, who - I am sure - dearly love their state bird emblem. And last but not least I’d kindly ask you to ignore the fact that besides their dark plumage black swans may have a slightly different silhouette as opposed to mute swans.

So without further ado, here is said picture and what I had posted at the time (totally unrelated to the BRN share price):


View attachment 45726


“(…) here is a sunset picture I took a couple weeks ago. What kind of swans do you see? Black ones or white ones? Well, at first sight they may APPEAR to be black due to the backlighting effect (especially if you live in Down Under and are used to seeing black swans all the time), but if you zoom in closer, you will actually be able to make out the white feathers of the swan standing. Why am I posting this picture? To demonstrate that sometimes things are not what they seem to be at first sight.”

Shockingly many stock market participants are mistaking BRN for a black swan - they take a glance at our company and think they’ve seen enough, dismissing it as just another small cash-burning start-up, that has failed miserably in commercialising their professed revolutionary tech, even though AI (they mean Generative AI) is on everyone’s lips these days; they see a sea of red flags such as the plummeting share price, no substantial revenue, no new signing of IP licenses, the company’s head of sales seemingly leaving for greener pastures (some would even go as far as saying leaving a sinking ship), they interpret NDAs as an excuse to hide lack of customer interest and consider BRN’s removal from the ASX 200 as yet another sign of failure. Countless shareholders have been losing faith over time (or were forced to sell to pay their bills), and the shorters and manipulators have been making heaps of money on the way down.

However, things are not always what they seem to be at first sight.

Until the sun rises, the majority of these Brainchip bears will not realise or want to believe that what we have here is an altogether different species of swan. They will be in for a big surprise.

At the same time, others can’t be fooled as for what kind of beast this really is. They can tell, even in the dark.


No financial advice. DYOR.

Thank you! What a stunning Photo and beautiful analogy. It's true, just like how darkness looms right before the break of dawn, difficult times often precede moments of growth, change, and new opportunities. It's a comforting reminder that even in the midst of darkness, there is always the potential for a brighter future.

 

[TheFunkMachine]

Al Martin and Rob Telson discuss Brainchip and Edge at 28min35sec

Al: "Who is your biggest competitor?"

Rob Telson: "There are a lot of great companies that are designing and have developed applications and devices to support AI in the future. I think that when you look at the company that has really seen some success incorporating AI into active working products it’s the big guy that’s developed GPU’S and that is NVIDIA. But what they’re doing doesn’t support the edge devices of the future, and that’s where we strongly believe two things. Number one we don’t see companies like that as a competitor. We actually see them as a partner where we can complement what they have started and what they're doing, and our technology can work side by side in those environments or it can work independent in those environments."

im sure this has been posted before but just to keep the dream alive I will post it again.

Nvidia moves towards neuromorphic technology


https://www.linkedin.com/posts/clif...8-Ox61?utm_source=share&utm_medium=member_ios

 

[Diogenese]

Neural Processor - WikiChip

A neural processor, a neural processing unit (NPU), or simply an AI Accelerator is a specialized circuit that implements all the necessary control and arithmetic logic necessary to execute machine learning algorithms, typically by operating on predictive models such as artificial neural networks...

en.wikichip.org

A neural processor, a neural processing unit (NPU), or simply an AI Accelerator is a specialized circuit that implements all the necessary control and arithmetic logic necessary to execute machine learning algorithms, typically by operating on predictive models such as artificial neural networks (ANNs) or random forests (RFs).

Nothing special, an accelerator..

As you say, nothing special.
A very modest improvement in power consumption, some of which may be attributed to:

US2023223402A1 Three-dimensional Integrated Circuit

A 3D integrated circuit includes a substrate, a first layer on top of the substrate, and a second layer on top of the first layer. The first layer includes a first chip, and a first network bridge formed at a first side of the first chip. The second layer includes a second chip, and a second network bridge formed at a first side of the second chip. The first chip and the first network bridge are coupled to the substrate through bumps. The second chip is coupled to the first chip and the first network bridge through bumps. The second network bridge is coupled to the first network bridge through bumps. The first network bridge and the second network bridge each include a network switch for controlling data transfer and/or power distribution.

Presumably the 3D system increases speed and reduces power. (Sony were early users of 3D IC.)

 

[Boab]

Great short video.

Renesas Electronics | LinkedIn

Renesas Electronics | 270,813 followers on LinkedIn. We're a world's leading semiconductor manufacturer. Our mission is to make our lives easier and a world that's safer, healthier, greener, and smarter.

www.linkedin.com

 

[Boab]

This is the one but as i said the other day I'm effed if I know how to tranfer it from LinkedIn to here

 

[buena suerte :-)]

Shiiiit who thought anyone would be cheering for .20c this time 12 months ago.

Some awful quiet posters now. Just going through old TSEX and HC posts for some people because the Singa’s are telling me to - you know who you are and where you at??

Exactly...20c!!!!!!! I think we will all be cheering on every 5c+ jump!! ... Our days of $1++ will return soooooon!?

Cheers

 

[Glen]

What do you not trust about Gmail?

I got this info from Bard AI.

 

[Neuromorphia]

This is the one but as i said the other day I'm effed if I know how to tranfer it from LinkedIn to here
View attachment 46003

ok found it for ya

[Video] Sailesh Chittipeddi on LinkedIn: How AI is Reinventing the Semiconductor Industry

How AI is Reinventing the Semiconductor Industry

www.linkedin.com

hi boab... i clicked on share down the bottom, then selected copy link. then pasted it on post.

 

[Xray1]

I’m in agreement with you Rob.. Surely there’ll be a atleast 1-2 new IP deals before the years out as Chapman eluded to, and that should ward off the wolves atleast for the next AGM..

I hope that if we do have say 1 -2 additional IP contracts with
" Revenue Flows " attached to same by the next AGM ... that the person or Insto' that voted some ~174 Million votes against the last remuneration report may revise their vote this time round or maybe that person or Insto' has their own agenda to oust/change the current Board of Directors .......... time will tell ............ but I do beleive that the Board of Directors knows exactly the identity of who this person / insto' is from the AGM voting records and will take decisive proactive action to have this issue resolved in a most favourable manner ........ otherwise some could be removed from the board with a strike 2 action following them around which will not imo be an impressive notation in their future resume's.

 

[Boab]

ok found it for ya

[Video] Sailesh Chittipeddi on LinkedIn: How AI is Reinventing the Semiconductor Industry

How AI is Reinventing the Semiconductor Industry

www.linkedin.com

View attachment 46004
hi boab... i clicked on share down the bottom, then selected copy link. then pasted it on post.

Lesson learned. Mercy buccups

 

[DingoBorat]

I hope that if we do have say 1 -2 additional IP contracts with
" Revenue Flows " attached to same by the next AGM ... that the person or Insto' that voted some ~174 Million votes against the last remuneration report may revise their vote this time round or maybe that person or Insto' has their own agenda to oust/change the current Board of Directors .......... time will tell ............ but I do beleive that the Board of Directors knows exactly the identity of who this person / insto' is from the AGM voting records and will take decisive proactive action to have this issue resolved in a most favourable manner ........ otherwise some could be removed from the board with a strike 2 action following them around which will not imo be an impressive notation in their future resume's.

It will be impossible to have any revenue guidance, on any new IP deals, just as it has been on the last 2 with Renesas and MegaChips (Not including the 3 or 4 IP licences through MegaChips)..

I don't think we will be "able" to have revenue guidance, for maybe 3 or 4 years...
We are (obviously) still too early in our commercialisation period.

Giving revenue guidance, is something a more mature company gives and the nature of our business model, doesn't really allow for it..

That's why Sean said to "watch the financials" even though, even he thought that we would see more sooner..
That's going to be the only way really, for a while, to judge how things are going financially..


The strength of investor confidence and therefore appreciation in the share price, will be in the "Blue Sky" potential, of any new IP deals named.

That doesn't mean the share price won't be built on something "solid".

Remember the value or price of something, is based on things like supply and demand, perceived value etc..

NVIDIA is currently the darling of A.I..

Some investors have described the stock as priced for perfection. Looking at the last 12 months of company earnings, Nvidia has a price-to-earnings ratio of 220, which is stunningly rich even compared with notoriously high-valued tech companies. Amazon's P/E ratio is at 110, and Tesla's is at 70, according to FactSet. 11 Aug 2023

The price to earnings ratios of tech companies, can be very high, if their stock is in demand.

 

[DingoBorat]

It will be impossible to have any revenue guidance, on any new IP deals, just as it has been on the last 2 with Renesas and MegaChips (Not including the 3 or 4 IP licences through MegaChips)..

I don't think we will be "able" to have revenue guidance, for maybe 3 or 4 years...
We are (obviously) still too early in our commercialisation period.

Giving revenue guidance, is something a more mature company gives and the nature of our business model, doesn't really allow for it..

That's why Sean said to "watch the financials" even though, even he thought that we would see more sooner..
That's going to be the only way really, for a while, to judge how things are going financially..


The strength of investor confidence and therefore appreciation in the share price, will be in the "Blue Sky" potential, of any new IP deals named.

That doesn't mean the share price won't be built on something "solid".

Remember the value or price of something, is based on things like supply and demand, perceived value etc..

NVIDIA is currently the darling of A.I..

Some investors have described the stock as priced for perfection. Looking at the last 12 months of company earnings, Nvidia has a price-to-earnings ratio of 220, which is stunningly rich even compared with notoriously high-valued tech companies. Amazon's P/E ratio is at 110, and Tesla's is at 70, according to FactSet. 11 Aug 2023

The price to earnings ratios of tech companies, can be very high, if their stock is in demand.

Of course we are too young a company to use price to earnings ratios anyway..
Just trying to show, that even mature companies, can have a fair bit of Blue Sky "built" into the share price.

This is a good article on valuing startups, if you're interested..

How to Value a Startup Company With No Revenue - MassChallenge

Pre-revenue startup valuation can be a tricky endeavor. There are many things to take into consideration, from the management team and market trends to the demand for the product and the marketing risks involved. And here’s the thing: After evaluating … Read More

masschallenge.org

I know we do have "some" revenue..
And bear in mind, that this article is about startups, that are literally "just" starting up.. Ala BrainChip 2016..

 

[Mt09]

I got this info from Bard AI.

Your link was an add for G mail, that’s all I could see. But yes anything from Bard/chat gpt should be taken with a grain of salt.

 

[Quatrojos]

New partnership: IAR and Edge Impulse to provide IAR customers worldwide with integrated AI and ML capabilities

IAR, the world leader in software and services for embedded development, today announced a commercial partnership with Edge Impulse, the leading edge

www.businesswire.com

 

[Schnitzel lover]

It will be impossible to have any revenue guidance, on any new IP deals, just as it has been on the last 2 with Renesas and MegaChips (Not including the 3 or 4 IP licences through MegaChips)..

I don't think we will be "able" to have revenue guidance, for maybe 3 or 4 years...
We are (obviously) still too early in our commercialisation period.

Giving revenue guidance, is something a more mature company gives and the nature of our business model, doesn't really allow for it..

That's why Sean said to "watch the financials" even though, even he thought that we would see more sooner..
That's going to be the only way really, for a while, to judge how things are going financially..


The strength of investor confidence and therefore appreciation in the share price, will be in the "Blue Sky" potential, of any new IP deals named.

That doesn't mean the share price won't be built on something "solid".

Remember the value or price of something, is based on things like supply and demand, perceived value etc..

NVIDIA is currently the darling of A.I..

Some investors have described the stock as priced for perfection. Looking at the last 12 months of company earnings, Nvidia has a price-to-earnings ratio of 220, which is stunningly rich even compared with notoriously high-valued tech companies. Amazon's P/E ratio is at 110, and Tesla's is at 70, according to FactSet. 11 Aug 2023

The price to earnings ratios of tech companies, can be very high, if their stock is in demand.

I do remember the shock at seeing nearly $5mill revenue through Megachips sub-licencees..

Next opportunity would more likely be royalty revenues in the Dec Qtrly or the H2 report in March 2024 courtesy of Renesas.

Thinking is if there were receipts in the Dec Qtrly that could be exciting from a time frame perspective where potentially first royalties came early in H2- which could provide upside surprise the the H2 financials..

If indeed there were a few new IP deals as well, that would go off like a firecracker!

 

[Tothemoon24]

Elnfochips looks like a company that Brainchip could complement, don’t think l’v read any dots about them so I’m probably wrong as usual

Redirecting

www-einfochips-com.cdn.ampproject.org

Low power ARM Cortex-M/A processors are ideal for the smaller devices because of their small form factor and minimal power requirements. Complex portable devices that require graphical user interface and wireless connectivity require powerful processors like Qualcomm Snapdragon. These portable devices need to be compact; this is achieved by packing multiple components in small space. However, hardware design also needs consider sink design to dissipate waste heat.

Operating System (OS)​

Android and Linux OS have been the preferred choice for most of the portable medical devices due to their highly customizable and advanced features for compute, performance and power. However, to ensure power and memory optimization, the OS must be optimized with a small memory footprint. Most real-time operating systems will provide some form of power management techniques that need to be implemented as per the device requirement.

Device Connectivity​

RELATED BLOG
Understanding the Working of Embedded IoT Medical Devices

Following the latest IOT trends, we are also seeing a shift in how medical devices are connected. Earlier, the connectivity was expected to be intermittent wired or wireless. Now, it is possible to provide global connectivity – either directly to the Internet (the “Internet of Things”), or to a local intermediary device, such as a medical device paired to the user’s smartphone, which eventually provides a path to the Internet.

The true future of wearable medical devices is highly dependent on this wireless connectivity. This spans from Near Field Radio, Bluetooth/BLE, Wi-Fi, up through mobile cellular networks. This is an area where technology, protocols, and options are changing rapidly.

eInfochips has hands-on engineering experience in FDA Class 2 and Class 3 medical devices for monitoring, diagnostics & imaging, wearable health and telemedicine. Through in-depth medical domain and process (IEC 60601 – 1/2/6, IEC 62304, 510K, ISO 13485) expertise along with strong expertise on compact, high-speed and multi-processor hardware, eInfochips has developed multiple portable medical devicesfor diagnostics, home care, and remote monitoring based on latest NXP i.MX, TI and Qualcomm Snapdragon processors. Some of our work includes:

• ISO-13485 complaint design multi-sensor portable health monitoring device
• Wearable heart rate monitoring fevice
• Class II telehealth device with 8MP camera; 2.4 inch touch screen
• Mobile enablement for ultrasound imaging solution

eInfochips Recognized for Engineering Excellence at Nasscom Spotlight Awards

eInfochips, a leading provider of product engineering and digital transformation services, has won twin honors at the inaugural Spotlight Awards ceremony hosted

www.cxotoday.com

https://www.eetindia.co.in/einfochips-launches-rdp-based-on-nxps-i-mx-93/

Current and Emerging Trends in Point-of-Care Testing (POCT) Devices​

In today’s rapidly evolving healthcare landscape, Point-of-Care Testing (POCT) devices play a crucial role in delivering timely and accurate diagnostic information. These devices provide healthcare professionals with the ability to perform tests and obtain results at or near the patient’s location, significantly improving patient care and treatment outcomes. Furthermore, advancements in biosensors, nanotechnology, smartphone-based platforms, integration with EHR, and applications in personalized medicine are paving the way for the future.

Image Source: ResearchGate

Current Trends in Point-of-Care Testing Devices​

● Miniaturization and Portability​

Advances in technology have facilitated the miniaturization and higher portability of Point-of-Care Testing (POCT) devices. These compact devices allow for on-the-spot testing, eliminating the need for sending samples to centralized laboratories. Healthcare professionals can now perform tests quickly and efficiently at the patient’s bedside, in emergency rooms, ambulances, or remote locations, resulting in faster diagnosis and treatment decisions.

● Integration of Advanced Technologies​

To increase their effectiveness and accuracy, POCT devices are increasingly using contemporary technologies like the Internet of Things (IoT), artificial intelligence (AI), and machine learning. IoT-enabled devices enable seamless connection, enabling real-time data transmission and analysis. AI and machine learning algorithms help in interpreting test results, providing accurate diagnoses. These advancements enhance the effectiveness and precision of POCT devices, thereby improving patient management.

● Expanded Test Menus and Multiplexing Capabilities​

Modern POCT devices offer expanded test menus, allowing healthcare professionals to perform a wide range of tests on a single device. This capability eliminates the need for multiple devices and reduces turnaround time for obtaining test results. Furthermore, multiplexing capabilities enable simultaneous testing of multiple analytes, enhancing the efficiency and cost-effectiveness of POCT.

● Enhanced Connectivity and Data Management Features​

POCT devices now come equipped with enhanced connectivity options, enabling seamless integration with electronic health records (EHR) systems. This connectivity facilitates real-time data sharing between the device and the healthcare provider, allowing for improved monitoring, tracking, and follow-up care. Data management features also aid in generating comprehensive reports and analytics, contributing to evidence-based decision-making.

● Adoption of Disposable and Single-Use Devices​

The adoption of disposable and single-use POCT devices is increasing rapidly. These devices eliminate the requirement of lengthy and expensive sterilization processes, diminishing the chance of cross-contamination and boosting infection control initiatives. Disposable devices also enhance convenience and workflow efficiency, making them ideal for rapid and point-of-care testing.

Emerging Trends in Point-of-Care Testing Devices​

● Advancements in Biosensors and Bioanalytical Techniques​

The development of novel biosensors and bioanalytical techniques holds great promise for the future of POCT devices. These advancements enable highly sensitive and specific detection of analytes, leading to improved accuracy and reliability of test results. Biosensors based on electrochemical, optical, and nanomaterial-based technologies offer great potential for rapid and point-of-care diagnostics.

● Development of Smartphone-Based Point-of-Care Testing Devices​

Smartphone-based POCT devices are emerging as a disruptive technology in the healthcare industry. By utilizing the existing capabilities of smartphones, such as built-in cameras, processors, and connectivity, these devices transform smartphones into powerful diagnostic tools. Smartphone-based POCT devices offer simplicity, accessibility, and affordability, making them ideal for resource-limited settings and remote patient monitoring.

● Integration of POCT Devices with Electronic Health Records (EHR)​

The integration of POCT devices with EHR systems allows for seamless data exchange, enhancing the continuity of care. Real-time transmission of test results from the POCT device to the patient’s EHR enables healthcare professionals to access comprehensive patient information, make informed decisions, and provide personalized care. This integration streamlines workflow, reduces errors, and improves patient outcomes.

● Application of POCT Devices in Personalized Medicine and Remote Monitoring​

POCT devices are increasingly being utilized in personalized medicine and remote monitoring. These devices enable healthcare professionals to tailor treatments based on individual patient characteristics, optimizing therapy outcomes. In remote monitoring scenarios, patients can perform tests using POCT devices in the comfort of their homes, with the results transmitted to healthcare providers. This approach improves patient engagement, reduces hospital visits, and enhances disease management.

Benefits and Implications of Current and Emerging Trends​

Image Source: ACS publications

● Enhancing Patient Care and Treatment Results​

The newest POCT device trends help patients receive better care and achieve better results from their treatments. Faster diagnosis, timely intervention, and personalized treatment options result in better disease management, reduced complications, and improved patient satisfaction. POCT tools let medical personnel make quick, educated decisions that improve patient safety and care quality.

● Improved Efficiency and Cost-Effectiveness in Healthcare Delivery​

POCT devices accelerate diagnostic procedures by obviating the requirement for sample transportation and cutting down on turnaround times. This efficiency leads to faster decision-making, decreased patient wait times, and optimized resource utilization. Moreover, by enabling point-of-care testing, these devices reduce the burden on centralized laboratories and associated costs, making healthcare delivery more cost-effective.

● Expansion of Point-of-Care Testing Applications Beyond Traditional Settings​

The current and emerging trends in POCT devices are expanding their applications beyond traditional healthcare settings. These devices find utility in remote or resource-limited areas, disaster response scenarios, ambulatory care, home healthcare, and even non-medical settings such as sports medicine and veterinary care. The versatility of POCT devices broadens access to healthcare, ensuring timely and accurate diagnoses for diverse populations.

● Empowerment of Healthcare Professionals and Patients with Real-Time Data​

POCT devices empower healthcare professionals and patients by providing real-time data. Healthcare professionals can make informed decisions quickly, leading to improved patient management. Real-time data access also supports telemedicine initiatives, enabling remote consultations and guidance based on immediate test results.

Challenges and Future Directions​

● Regulatory Considerations and Standardization​

The implementation of current and emerging trends in POCT devices requires robust regulatory frameworks and standardized guidelines. Standardization efforts ensure consistent performance, reliability, and safety, fostering trust in POCT technology.

● Privacy and Security Concerns in Data Transmission and Storage​

With the increasing connectivity and integration of POCT devices with electronic systems, ensuring data privacy and security becomes crucial. Patient information must be adequately safeguarded during data transfer and storage. Protecting sensitive healthcare data requires encryption, authentication, and compliance with data protection laws.

● Integration of Point-of-Care Testing Devices into Existing Healthcare Systems​

The seamless integration of POCT devices into existing healthcare systems poses technical and logistical challenges. Collaboration between device manufacturers, software developers, and healthcare providers is essential for interoperability with EHR systems, laboratory information systems, and other healthcare platforms. Integration should focus on user-friendly interfaces, data standardization, and interoperability to realize the full potential of POCT devices.

● Continued Research and Development for Innovation in Point-of-Care Testing Technology​

Investment in novel biosensing technologies, nanomaterials, smartphone-based platforms, and AI algorithms will drive innovation and improve the performance of POCT devices. Collaboration between industry, academia, and healthcare providers is essential for pushing the boundaries of POCT technology and addressing unmet clinical needs.

Bottomline​

The current and emerging trends in POCT devices are revolutionizing the way diagnostic information is obtained and utilized in healthcare settings. Miniaturization, integration of advanced technologies, expanded test menus, enhanced connectivity, and the adoption of disposable devices are shaping the present landscape. These trends have significant implications for patient care, efficiency, and access to healthcare. However, addressing challenges related to regulation, privacy, integration, and continuous innovation is critical for realizing the full potential of POCT devices and ensuring their seamless incorporation into existing healthcare systems. Healthcare organizations can improve patient outcomes and the effectiveness and efficiency of healthcare delivery by staying on the cutting edge of these trends.

 

[Tothemoon24]

Revolutionising neuromorphic sensory devices

RMIT researchers have unveiled a device that possesses the ability to ‘see’ and create memories, akin to the way humans do.

pacetoday.com.au

The neuromorphic device can be deployed in various sectors of manufacturing in Australia and beyond, such as precision manufacturing and can be used for automation and decision-making on the go. Imagine self-monitoring production lines that can instantly detect flaws and defects, autonomous robots that navigate intricate environments, and supply chain systems that optimise routes and resource allocation on the fly. The possibilities are as vast as they are transformative.

Recently, Professor Walia and his team received funding from the Australian Research Council under the National Intelligence and Security Discovery Research Grants 2023, for a defence project that will take their technology further. The expected outcome of the project is an autonomous vision device that highlights changes in the scene using visible and infrared wavelengths.

 

[Tothemoon24]

@Diogenese when you have time could you provide your opinion on this paper

Dated 9th September 2023
Linked below
Cheers

https://dl.acm.org/doi/full/10.1145/3609101

SoCs equipped with neuromorphic hardware are available, but they rarely consider the integration of non-neuromorphic hardware accelerators. For instance, Akida [6] is an SoC containing an Arm processor that controls the neuromorphic hardware, but does not support the on-chip integration of other hardware accelerators. Similarly, the Loihi SoC [13] consists of a neuromorphic processor and an Intel x86 processor, which merely manages the neuromorphic processor. Loihi is typically deployed as part of a Nahuku expansion board [21, 22], which contains up to 32 interconnected Loihi chips that all interface with the same on-board Arria 10 FPGA. This FPGA is used to interact with the surroundings, notably via sensors and actuators. Additionally, the FPGA is controlled by an off-chip processor (distinct from the aforementioned x86 processor) from which the high-level software application is executed, such as compiling the neuromorphic model and visualizing results.