BRN Discussion Ongoing

[Bravo]

Actually, upon further inspection, it looks as though Qualcomm are only interested in promoting the VVDN and Teksun products which feature Qualcomm processors.

Qualcomm Empowers Indian Companies with Edge AI Solutions to Scale IoT Deployments​

Published on:
18 Oct 2024, 5:54 pm


Qualcomm Technologies, Inc. announced its support of Indian ODMs to help accelerate their deployment of new Edge AI applications with distributed computing from the edge to the cloud, including support for 5G.

The Qualcomm® Edge AI Box Solutions offer scalability, ease of use, and best-in-class performance to help meet the needs of demanding industrial and commercial IoT applications and enhance offerings across security and surveillance, factory safety, traffic flow management, energy resource management, video collaboration, real time data insights, retail, and more.
Key Benefits:
Cost optimized design- Add intelligence to existing legacy cameras and sensor installations with a Qualcomm Edge AI Box Solution. Maximize investments and avoid costly upgrades and installation costs. Test and deploy new edge AI applications easier and enable faster deployments.
High performance, power-efficient machine learning- Easily add machine learning models that run power efficiently including object detection and recognition, people detection and counting and more, with the ability to run simultaneous edge AI models across the same network.
Real-time analytics and insights - Deliver real-time insights with low latency to enable on-demand decisions by processing data on the device, reducing dependency on the cloud.
On-device data security and privacy - Build better privacy, security, and protection for data by processing at the edge to minimize the risk of unauthorized external access.
“Qualcomm Technologies is uniquely positioned to take the IoT ecosystem forward. Our edge AI solutions bring together the industry’s leading technologies across powerful computing, innovative edge AI processing, power efficiency, reduced latency, latest 5G and Wi-Fi connectivity, crystal-clear video and more to fuel the next-generation of resilient, high-performing IoT applications,” said Suri Maddhula, Qualcomm Technologies, Inc.
“The expansion of the IoT footprint in India is an important catalyst in India’s digital transformation journey and Qualcomm Technologies is committed to empowering the ecosystem with the solutions needed to help it grow,” said Khusdil Dahiya, Business Development, Qualcomm India Pvt. Ltd.
Expansive Ecosystem
In order for IoT to scale, a range of different solutions is needed to address the varying needs of industry applications. The Qualcomm Edge AI Box Solutions enable the ecosystem of hardware and software partners to quickly and efficiently develop connected solutions tailored to different use cases. Marking a significant milestone in India’s digital transformation and ‘Make in India’ journey, Qualcomm Technologies is engaged with a growing list of leading Indian hardware and software companies to develop scalable solution customized for specific use cases. Working with a wide-range of Original Design Manufacturers (ODMs), Independent Software Vendors (ISVs) and System Integrators (SIs), these solutions will enable their customers worldwide to quickly and efficiently deploy pre-designed solutions in a manner that is tailored for their needs.
Leading Indian manufacturers are showing ecosystem support for the use of Qualcomm Edge AI solutions:
VVDN
Sreejith, SVP Engineering, Vision BU, VVDN Technologies, said "The Qualcomm AI Edge Box Solutions, designed and developed by VVDN are based on the latest Qualcomm® SoCs, including QCS6490, QCM6490 and IQ-9100, represent a significant step forward in real-time video analytics and edge data processing. With applications across smart retail, security, surveillance, smart cities, and industrial sectors, this solution opens new global opportunities, delivering enhanced performance and driving innovation at the edge for our customers”.
Innominds
“Innominds has launched a series of edge AI devices developed using Qualcomm Technologies, which along with a comprehensive suite of middleware and software applications, provide solutions to the manufacturing, defense, construction and med tech verticals. Our devices are designed for running multi-channel AI workloads at the edge, providing seamless connectivity to public and private clouds via GigE/5G/Wi-Fi, and purpose built to solve complex deployment, security and maintenance challenges facing the industry”, said Raj Ganti, President of Innominds Software Inc. “Using Qualcomm Technologies’ cutting-edge silicon and software and Qualcomm® AI Hub, seamless orchestration of edge devices via the cloud (on premise and through hyperscalers) and our solutions landscape, Innominds is well-positioned to address growing de-carbonization efforts being pursued by our customers.”
Teksun Inc
"We are thrilled to announce our collaboration with Qualcomm Technologies to deliver next-generation Edge AI solutions. We are excited to unveil our latest product - Edge AI Box, designed to empower industries with advanced applications that enhance productivity, improve safety, and drive innovations. The Edge AI Box is supported by our extensive Telep AI Libraries, providing businesses with faster time-to-market and reliable, cutting-edge results," said Arjun Dedaniya, Head, Solutions Engineering, Teksun Inc
Tessolve
“EDGE Box is a global opportunity for Tessolve, it is going to solve problems and drive efficiencies. This solution helps enable powerful connections and reduce latency, along with dynamic triple ISPs and advanced edge AI and compute, delivering astonishing performance at low power and AI performance of up to 12 TOPS. The target applications include smart cameras, ruggedized handhelds and tablets, kiosks, industrial scanners, dash cameras, point-of-sale systems and human machine interface systems,” said Kirankumar Nagendra, Vice President, Embedded System, Tessolve

https://digitalterminal.in/enterprise/qualcomm-empowers-indian-companies-with-edge-ai-solution

 

[Bravo]

I missed this but I have a feeling that BrainChip is somehow involved. Need to check if indeed the report below is true.

Oticon Medical’s ears must be burning after parent company Demant struck a deal to divest the implant business in a sale to fellow hearing technology developer Cochlear.

Copenhagen-based Demant will sell off Oticon to the Australian buyer for 850 million Danish kroner, or about $120 million. Cochlear will shell out 700 million Danish kroner in upfront cash once the deal is finalized, then the remaining 150 million kroner within 18 months of its closing.

As part of the deal, Cochlear has promised to continue supporting the more than 75,000 people who have already received Oticon’s hearing implants. Moving forward, it will also take the newly acquired products into consideration for compatibility purposes as it develops future technologies.

https://www.fiercebiotech.com/medtech/music-cochlears-ears-demant-sells-oticon-hearing-implant-business-120m

Hi Slade,

This might be of interest in relation to your post back in July 2022. Unfortunately it's behind a paywall.

Demant CEO sees power consumption as crucial parameter in development of AI hearing aids

AI systems can significantly increase power consumption, requiring extra effort to keep consumption under control.

medwatch.com

 

[IloveLamp]

GR716B

Gaisler

www.gaisler.com

Ádria Barros de Oliveira on LinkedIn: #gr716b #grscrub #grlib

During my first year working at Frontgrade Gaisler I was entitled to develop the GRSCRUB IP. Now, five years later, the first ASICs featuring GRSCRUB are…

www.linkedin.com

 

[Mt09]

Actually, upon further inspection, it looks as though Qualcomm are only interested in promoting the VVDN and Teksun products which feature Qualcomm processors.

Qualcomm Empowers Indian Companies with Edge AI Solutions to Scale IoT Deployments​

Published on:
18 Oct 2024, 5:54 pm


Qualcomm Technologies, Inc. announced its support of Indian ODMs to help accelerate their deployment of new Edge AI applications with distributed computing from the edge to the cloud, including support for 5G.

The Qualcomm® Edge AI Box Solutions offer scalability, ease of use, and best-in-class performance to help meet the needs of demanding industrial and commercial IoT applications and enhance offerings across security and surveillance, factory safety, traffic flow management, energy resource management, video collaboration, real time data insights, retail, and more.
Key Benefits:
Cost optimized design- Add intelligence to existing legacy cameras and sensor installations with a Qualcomm Edge AI Box Solution. Maximize investments and avoid costly upgrades and installation costs. Test and deploy new edge AI applications easier and enable faster deployments.
High performance, power-efficient machine learning- Easily add machine learning models that run power efficiently including object detection and recognition, people detection and counting and more, with the ability to run simultaneous edge AI models across the same network.
Real-time analytics and insights - Deliver real-time insights with low latency to enable on-demand decisions by processing data on the device, reducing dependency on the cloud.
On-device data security and privacy - Build better privacy, security, and protection for data by processing at the edge to minimize the risk of unauthorized external access.
“Qualcomm Technologies is uniquely positioned to take the IoT ecosystem forward. Our edge AI solutions bring together the industry’s leading technologies across powerful computing, innovative edge AI processing, power efficiency, reduced latency, latest 5G and Wi-Fi connectivity, crystal-clear video and more to fuel the next-generation of resilient, high-performing IoT applications,” said Suri Maddhula, Qualcomm Technologies, Inc.
“The expansion of the IoT footprint in India is an important catalyst in India’s digital transformation journey and Qualcomm Technologies is committed to empowering the ecosystem with the solutions needed to help it grow,” said Khusdil Dahiya, Business Development, Qualcomm India Pvt. Ltd.
Expansive Ecosystem
In order for IoT to scale, a range of different solutions is needed to address the varying needs of industry applications. The Qualcomm Edge AI Box Solutions enable the ecosystem of hardware and software partners to quickly and efficiently develop connected solutions tailored to different use cases. Marking a significant milestone in India’s digital transformation and ‘Make in India’ journey, Qualcomm Technologies is engaged with a growing list of leading Indian hardware and software companies to develop scalable solution customized for specific use cases. Working with a wide-range of Original Design Manufacturers (ODMs), Independent Software Vendors (ISVs) and System Integrators (SIs), these solutions will enable their customers worldwide to quickly and efficiently deploy pre-designed solutions in a manner that is tailored for their needs.
Leading Indian manufacturers are showing ecosystem support for the use of Qualcomm Edge AI solutions:
VVDN
Sreejith, SVP Engineering, Vision BU, VVDN Technologies, said "The Qualcomm AI Edge Box Solutions, designed and developed by VVDN are based on the latest Qualcomm® SoCs, including QCS6490, QCM6490 and IQ-9100, represent a significant step forward in real-time video analytics and edge data processing. With applications across smart retail, security, surveillance, smart cities, and industrial sectors, this solution opens new global opportunities, delivering enhanced performance and driving innovation at the edge for our customers”.
Innominds
“Innominds has launched a series of edge AI devices developed using Qualcomm Technologies, which along with a comprehensive suite of middleware and software applications, provide solutions to the manufacturing, defense, construction and med tech verticals. Our devices are designed for running multi-channel AI workloads at the edge, providing seamless connectivity to public and private clouds via GigE/5G/Wi-Fi, and purpose built to solve complex deployment, security and maintenance challenges facing the industry”, said Raj Ganti, President of Innominds Software Inc. “Using Qualcomm Technologies’ cutting-edge silicon and software and Qualcomm® AI Hub, seamless orchestration of edge devices via the cloud (on premise and through hyperscalers) and our solutions landscape, Innominds is well-positioned to address growing de-carbonization efforts being pursued by our customers.”
Teksun Inc
"We are thrilled to announce our collaboration with Qualcomm Technologies to deliver next-generation Edge AI solutions. We are excited to unveil our latest product - Edge AI Box, designed to empower industries with advanced applications that enhance productivity, improve safety, and drive innovations. The Edge AI Box is supported by our extensive Telep AI Libraries, providing businesses with faster time-to-market and reliable, cutting-edge results," said Arjun Dedaniya, Head, Solutions Engineering, Teksun Inc
Tessolve
“EDGE Box is a global opportunity for Tessolve, it is going to solve problems and drive efficiencies. This solution helps enable powerful connections and reduce latency, along with dynamic triple ISPs and advanced edge AI and compute, delivering astonishing performance at low power and AI performance of up to 12 TOPS. The target applications include smart cameras, ruggedized handhelds and tablets, kiosks, industrial scanners, dash cameras, point-of-sale systems and human machine interface systems,” said Kirankumar Nagendra, Vice President, Embedded System, Tessolve

https://digitalterminal.in/enterprise/qualcomm-empowers-indian-companies-with-edge-ai-solution

Perhaps not dissimilar to Merc/Intel the other day, companies like to be associated with big names. Would a layman exec buy a Qualcomm edge box or a Brainchip edge box?

 

[Guzzi62]

GR716B

Gaisler

www.gaisler.com

Ádria Barros de Oliveira on LinkedIn: #gr716b #grscrub #grlib

During my first year working at Frontgrade Gaisler I was entitled to develop the GRSCRUB IP. Now, five years later, the first ASICs featuring GRSCRUB are…

www.linkedin.com

View attachment 71420

Thanks, that very interesting what she wrote:

5 years later, huh!

It just shows how long time these developments can take from idea to product.

It was said by someone in the know that software is much quicker getting to the market, which even a layman like me can understand.

Our first and (so far) 2 IP deals must be getting closer to commercialization.

 

[7für7]

Actually, upon further inspection, it looks as though Qualcomm are only interested in promoting the VVDN and Teksun products which feature Qualcomm processors.

Qualcomm Empowers Indian Companies with Edge AI Solutions to Scale IoT Deployments​

Published on:
18 Oct 2024, 5:54 pm


Qualcomm Technologies, Inc. announced its support of Indian ODMs to help accelerate their deployment of new Edge AI applications with distributed computing from the edge to the cloud, including support for 5G.

The Qualcomm® Edge AI Box Solutions offer scalability, ease of use, and best-in-class performance to help meet the needs of demanding industrial and commercial IoT applications and enhance offerings across security and surveillance, factory safety, traffic flow management, energy resource management, video collaboration, real time data insights, retail, and more.
Key Benefits:
Cost optimized design- Add intelligence to existing legacy cameras and sensor installations with a Qualcomm Edge AI Box Solution. Maximize investments and avoid costly upgrades and installation costs. Test and deploy new edge AI applications easier and enable faster deployments.
High performance, power-efficient machine learning- Easily add machine learning models that run power efficiently including object detection and recognition, people detection and counting and more, with the ability to run simultaneous edge AI models across the same network.
Real-time analytics and insights - Deliver real-time insights with low latency to enable on-demand decisions by processing data on the device, reducing dependency on the cloud.
On-device data security and privacy - Build better privacy, security, and protection for data by processing at the edge to minimize the risk of unauthorized external access.
“Qualcomm Technologies is uniquely positioned to take the IoT ecosystem forward. Our edge AI solutions bring together the industry’s leading technologies across powerful computing, innovative edge AI processing, power efficiency, reduced latency, latest 5G and Wi-Fi connectivity, crystal-clear video and more to fuel the next-generation of resilient, high-performing IoT applications,” said Suri Maddhula, Qualcomm Technologies, Inc.
“The expansion of the IoT footprint in India is an important catalyst in India’s digital transformation journey and Qualcomm Technologies is committed to empowering the ecosystem with the solutions needed to help it grow,” said Khusdil Dahiya, Business Development, Qualcomm India Pvt. Ltd.
Expansive Ecosystem
In order for IoT to scale, a range of different solutions is needed to address the varying needs of industry applications. The Qualcomm Edge AI Box Solutions enable the ecosystem of hardware and software partners to quickly and efficiently develop connected solutions tailored to different use cases. Marking a significant milestone in India’s digital transformation and ‘Make in India’ journey, Qualcomm Technologies is engaged with a growing list of leading Indian hardware and software companies to develop scalable solution customized for specific use cases. Working with a wide-range of Original Design Manufacturers (ODMs), Independent Software Vendors (ISVs) and System Integrators (SIs), these solutions will enable their customers worldwide to quickly and efficiently deploy pre-designed solutions in a manner that is tailored for their needs.
Leading Indian manufacturers are showing ecosystem support for the use of Qualcomm Edge AI solutions:
VVDN
Sreejith, SVP Engineering, Vision BU, VVDN Technologies, said "The Qualcomm AI Edge Box Solutions, designed and developed by VVDN are based on the latest Qualcomm® SoCs, including QCS6490, QCM6490 and IQ-9100, represent a significant step forward in real-time video analytics and edge data processing. With applications across smart retail, security, surveillance, smart cities, and industrial sectors, this solution opens new global opportunities, delivering enhanced performance and driving innovation at the edge for our customers”.
Innominds
“Innominds has launched a series of edge AI devices developed using Qualcomm Technologies, which along with a comprehensive suite of middleware and software applications, provide solutions to the manufacturing, defense, construction and med tech verticals. Our devices are designed for running multi-channel AI workloads at the edge, providing seamless connectivity to public and private clouds via GigE/5G/Wi-Fi, and purpose built to solve complex deployment, security and maintenance challenges facing the industry”, said Raj Ganti, President of Innominds Software Inc. “Using Qualcomm Technologies’ cutting-edge silicon and software and Qualcomm® AI Hub, seamless orchestration of edge devices via the cloud (on premise and through hyperscalers) and our solutions landscape, Innominds is well-positioned to address growing de-carbonization efforts being pursued by our customers.”
Teksun Inc
"We are thrilled to announce our collaboration with Qualcomm Technologies to deliver next-generation Edge AI solutions. We are excited to unveil our latest product - Edge AI Box, designed to empower industries with advanced applications that enhance productivity, improve safety, and drive innovations. The Edge AI Box is supported by our extensive Telep AI Libraries, providing businesses with faster time-to-market and reliable, cutting-edge results," said Arjun Dedaniya, Head, Solutions Engineering, Teksun Inc
Tessolve
“EDGE Box is a global opportunity for Tessolve, it is going to solve problems and drive efficiencies. This solution helps enable powerful connections and reduce latency, along with dynamic triple ISPs and advanced edge AI and compute, delivering astonishing performance at low power and AI performance of up to 12 TOPS. The target applications include smart cameras, ruggedized handhelds and tablets, kiosks, industrial scanners, dash cameras, point-of-sale systems and human machine interface systems,” said Kirankumar Nagendra, Vice President, Embedded System, Tessolve

https://digitalterminal.in/enterprise/qualcomm-empowers-indian-companies-with-edge-ai-solution

DONT CRY FOR ME EDGE-AKIDAAAAAA….

 

[IloveLamp]

Lucky Munemo on LinkedIn: #machinelearning

Are you harnessing the full potential of your Edge Data Centre? If integration of #MachineLearning models and minimizing power consumption are causing you a…

www.linkedin.com

Sigma Technology Group | Engineering the digital revolution

We are Sigma Technology Group, a global company with family spirit. Software and Embedded systems development │ IT Infrastructure & DevOps │ Cloud services │ Product information │ Digital transformation.

sigmatechnology.com

 

[TECH]

Lucky Munemo on LinkedIn: #machinelearning

Are you harnessing the full potential of your Edge Data Centre? If integration of #MachineLearning models and minimizing power consumption are causing you a…

www.linkedin.com

Sigma Technology Group | Engineering the digital revolution

We are Sigma Technology Group, a global company with family spirit. Software and Embedded systems development │ IT Infrastructure & DevOps │ Cloud services │ Product information │ Digital transformation.

sigmatechnology.com

View attachment 71423 View attachment 71424 View attachment 71425

There's our old mate AKIDA 1000......still shining brightly....there is certainly a lot of narrowness in that brilliant piece of architecture
Don't ever doubt yourself Peter, your 1st generation chip was a piece of pure masterclass.

You, Anil, Kris and the original team that put in the hard yards....take a well deserved bow. AKIDA 1 1.5 2 and 3 ?

Tech (Perth)

 

[Pom down under]

Perhaps not dissimilar to Merc/Intel the other day, companies like to be associated with big names. Would a layman exec buy a Qualcomm edge box or a Brainchip edge box?

Qualcomm all day long at this stage unfortunately

 

[Smoothsailing]

Asking ChatGpt

**Conclusion**

In summary, Megachip utilizes Brainchip's Akida technology primarily to enhance its product offerings across various sectors including smart cameras, IoT devices, automotive applications, consumer electronics, and healthcare technologies. The focus is on improving efficiency through real-time data processing while minimizing power consumption.

Probability that the answer is correct: 95%

 

[Tothemoon24]

SDV platforms combine high-performance computing and high-speed interfaces with support for real-time updates.

Several major trends are driving automotive innovation, including the evolution of vehicle automation from partial to full driving assistance, and the ability to implement security, in-vehicle infotainment (IVI) and vehicle performance features through complex software. These capabilities rely on a centralized, high-performance computing (HPC) architecture tailored to the automotive environment and delivered through a software-defined vehicle (SDV) platform.
The equivalent of a mobile data center, SDV platforms accept new software so automobiles can support a growing variety of revenue-generating features and capabilities while steadily progressing through the six levels of autonomy defined by the Society of Automotive Engineers (SAE).

State of automation​

Most vehicle manufacturers currently implement Level 1 of the SAE’s six automation levels. This partial-automation level consists of discrete features delivered through an advanced driver-assistance system (ADAS), while Level 2 offers more sophisticated ADAS capabilities by combining features, such as adaptive cruise control and lane centering, that are more valuable to the driver and increase revenue margins for the automotive OEM.
At Level 1 and 2 of the SAE definitions, drivers are still considered to be driving the vehicle and retain responsibility for the safety of the passenger and vehicle. OEMs are now planning the transition to Level 3 (in which the driver conditionally relinquishes responsibility for controlling the vehicle to the ADAS system) and even Level 4 (in which these hand-over conditions are further reduced).
These are substantial steps. An example of a Level 3 capability is the “traffic-jam chauffeur” in which the vehicle drives itself but the driver must be prepared to take control. With Level 4, the conditions may be eliminated and all control is given to the vehicle. Figure 1 shows how the SAE levels are defined and implemented.

Figure 1: SAE’s six levels of driving automation define hands-on/-off features and requirements. They are enabled through technologies ranging from cameras and sensors and associated data to data logging and cloud connectivity. (Source: Microchip Technology)
Moving from Level 2 to Level 3 or 4 requires that the vehicle be given adequate sensory perception as well as algorithmic processing capabilities or even artificial intelligence so that it can autonomously navigate its route. The vehicle must also be able to identify who or what is responsible for driving the vehicle at any given moment and under the given conditions, then operate accordingly.
In addition to protecting the safety of the car and passenger at all levels of the SAE automation evolution, vehicle manufacturers must continue to create a great IVI experience that, increasingly, is delivered to the vehicle much like smartphone apps are. The number of apps and high-value content-streaming services for the vehicle is growing alongside the steady evolution of driver automation.
Other capabilities are also being delivered through sophisticated software, including security updates and a variety of vehicle-handling, acceleration and emissions enhancements. Facilitating these software additions through the SDV concept ensures that vehicles can be upgraded throughout their lifetime, but this cannot be accomplished with the majority of today’s Level 1 and 2 in-vehicle ADAS systems, which use dedicated, function-specific hardware modules.
Without a software-definable platform that can accept enhanced software, ADAS systems can perform only the functions for which they were designed, and there is little or no ability to upgrade features. Today’s SDV platforms offer the additional benefit of replacing today’s extremely complex and power-hungry architecture for supporting what can be up to 100 electronic control units (ECUs) and their collective 100 million lines of software code or more.

A better way to manage ECUs while enabling the SDV​

Transforming vehicles into data centers on wheels not only supports the SDV concept but also provides a better way to manage the growing variety of ECUs used for engine, transmission, traction, anti-lock braking and airbag control, as well as those for climate control, windows and seat controls, among others.
This rapid expansion of ECUs has been driven by growing demand for vehicle performance and feature innovations, but it generates an astounding increase in software code—as much as 7× that of a commercial airliner—that needs to be distributed throughout the vehicle. The architecture that has been used to accomplish this is not particularly energy-efficient, nor is it compute-efficient, as most ECUs perform a single task and cannot be upgraded.
The SDV’s HPC architecture includes a variety of powerful CPU capabilities for general-purpose computing applications as well as specialized functions, such as video processing (Figure 2).

Figure 2: The SDV architecture combines HPC, high-speed interfaces for edge sensor connection, cloud connectivity and support for real-time updates. (Source: Microchip Technology)
SDV computing functions can be added at any point in the life of the vehicle, which will have a significant impact on traditional vehicle depreciation rates. Older vehicles can be updated to include features otherwise available only on newer vehicles, as long as both cars have compatible HPC clusters.
Adding to the attractiveness of the SDR approach, the data feed from a modern vehicle’s radar, vision cameras, LiDAR, accelerometers, GPS and other sensors that provide information about its surroundings can enable many safety, performance or entertainment tasks. New features that are added to the vehicle can also leverage this data and reside in the HPC alongside existing ADAS and infotainment features.

When to expect HPC clusters​

It is likely that HPC cluster implementation will coincide with the arrival of Level 3 and Level 4 automation, which requires a step-function increase in compute performance. But the earliest form of HPC implementation may arrive as a Level 2 ADAS feature (sometimes referred to as Level 2+) so that ADAS system upgrades can be offered after the sale of a vehicle. It is logical to include the processing of infotainment data within the HPC cluster, as it is already largely a compute function with speakers, microphones, displays and other specific edge peripherals.
Some argue against in-vehicle HPC over concerns that it will increase complexity/risk and system cost, but these issues have already been resolved in data centers and other applications. Server ODMs have ready access to hardware design services and many automotive Tier 1 suppliers are already supporting emerging OEM needs for HPC system capabilities. OEMs and system integrators can focus on ADAS application software development and application delivery using existing hardware architectures, with the option to reduce their development burden by taking advantage of the software that ADAS component suppliers offer with their compute system-on-chips (SoCs) and network switches. This allows them to focus on system integration and policy rather than processing algorithms or low-level drivers.
Meanwhile, the industry is developing optimized hardware with superior cost structures at many levels of the supply chain, across a range of both existing Level 2 systems and projected Level 3 systems. Component hardware optimized for automotive, which supports HPC architectures, includes high-performance image-processing SoCs originally developed for wireless devices and AI applications, PCIe interconnects from data centers for high-bandwidth, low-latency data sharing, and connectivity to the Ethernet in-vehicle network, now in use by almost all automotive OEMs.
Supporting standardized and common software within an HPC architecture reduces OEM development costs and enables scalability across vehicle platforms. Common software reduces recall risks by eliminating the software bugs caused by unique software stacks that are developed for a single vehicle feature set or platform.

Realizing SDV benefits​

The advent of the SDV will bring an additional factor to an automotive OEM’s cost-benefit equation, which was traditionally predicated on the car manufacturer’s one-time financial transaction with customers with no opportunity for post-sale revenue other than through service and repair centers. Now, OEMs will be able to demonstrate how their solutions can generate additional after-sale revenue for the car manufacturer, as well as the extent to which this revenue is material to its financial results. And while initial revenue streams from upgrades or subscriptions may be small compared with vehicle revenue, the profitability is large and could have an outsize effect on bottom-line results.
With the ability to access a standard feature interface within an SDV’s HPC system, there is also the opportunity to create an “app store” model for developers and consumers that is similar to what exists in the mobile phone segment. This app store can contain a broad range of add-on vehicle applications that generate revenue from consumers with specific interests or tastes. As in the mobile phone segment, this approach leverages a vast number of software developers, each of whom may serve a small consumer segment but together deliver a huge number of offerings to an even larger user base.
A hypothetical example of this type of upgrade is a predictive-maintenance capability that enables servicing to be scheduled on a wear-and-tear basis rather than the traditional time- or mileage-based approaches. Vehicles with the necessary sensors could collect data from the suspension system, for instance, which could then be used to track and analyze system part conditions using advanced anomaly-detection algorithms and recommend when servicing should be scheduled. It may even be possible to make immediate adjustments to one or more operating parameters through a real-time software patch.
Rather than returning a car to the garage or certified service center for updates to these and other capabilities via a data cable or, in some cases, through USB ports, it will be possible to implement them over the air (OTA) as standard practice. The same approach can be used for safety, emissions or performance recalls, with the potential to substantially reduce OEM costs.
The arrival of SDV platforms that easily incorporate new OTA software features will enable cars to evolve from products whose key attributes are handling, power, speed and looking to data centers on wheels that deliver an increasingly personalized overall in-cabin experience. The ability to deliver this experience through featured upgrades and third-party apps will redefine the automobile manufacturer business model that until now was based on a one-time sales event. Instead, it will be possible to realize long-term returns on hardware investments, especially as SDVs with connectivity to OEM servers via the cloud create opportunities to introduce subscription-based and application-download business models.

 

[TheUnfairAdvantage]

Starkey AI. Interesting podcast. From 14:45 there is a definition of the ai they use on chip. On chip learning. Low power. @Diogenese have you deep dived into their Ip?

I like what they are doing with hearing aids. Brainchip have mentioned some work in this area. Be great if we were involved. Suspect not because Starkey have been doing this work for a while now and it would have to show up in the financials . On chip learning and low power. I thought we had a lead in this field and therefore hoping it is us.


https://m.youtube.com/watch?v=G8GP4Fv1lxw

 

[Smoothsailing]

Posted recently with SNN

Starkey AI. Interesting podcast. From 14:45 there is a definition of the ai they use on chip. On chip learning. Low power. @Diogenese have you deep dived into their Ip?

I like what they are doing with hearing aids. Brainchip have mentioned some work in this area. Be great if we were involved. Suspect not because Starkey have been doing this work for a while now and it would have to show up in the financials . On chip learning and low power. I thought we had a lead in this field and therefore hoping it is us.

posted recently with SNN

 

[Tothemoon24]

 

[SharesForBrekky]

This major healthcare innovation conference is about to happen, and maybe something to keep an eye out for. Plenty of talk about the impact of how AI will have on the healthcare sector.

HLTH Event 2024 | Las Vegas, NV | October 19-22, 2025 - HLTH

HLTH USA 2025 is healthcare's #1 must-attend healthcare innovation event covering AI & Emerging Tech, Care Delivery, Health Policy, Investment Strategy, and more. Taking place October 19-22, 2025. Learn more!

www.hlth.com

The Venetian Expo Center, Las Vegas | October 20 – 23, 2024

 

[Diogenese]

Still no licence announcements.

However, it needs to be borne in mind that some of our well known EAP engagements are joint developments.

In the normal course of events, revenue from JDs follows sales, so there would not normally be up front licence fees.

And, of course, the ASX disclosure rules prevent BRN from foreshadowing any upcoming revenue without disclosure of the details, which would entail a breach of NDAs, a situation with which BRN, among others, is unhappily familiar.

So, while I believe that Valeo and Mercedes are more than likely using TENNS/Akida2 software in their upcoming releases (Scala 3, CLA (?)), and Sean has disclosed our commercial algorithm product, we may need to wait for sales of these products before we see revenue, and this will be at the end of a specified accounting period, so hopefully there will be some announcement beforehand, such as on release of the product.


https://www.msn.com/en-us/autos/aut...-details-all-the-changes-for-2025/ar-AA1soRTA

Mercedes-Benz Details All The Changes For 2025​

Story by Evan Williams
...
Merc(d)edes-Benz has added the latest (2024) MBUX version to the C-Class sedan.

It is also worth keeping in mind that of late both Mercedes and Valeo have stressed the ability to readily update software for SDVs, allowing for functional software upgrades.

While I continually remind myself of these circumstances, I just wish things were moving faster.

 

[TheUnfairAdvantage]

Still no licence announcements.

However, it needs to be borne in mind that some of our well known EAP engagements are joint developments.

In the normal course of events, revenue from JDs follows sales, so there would not normally be up front licence fees.

And, of course, the ASX disclosure rules prevent BRN from foreshadowing any upcoming revenue without disclosure of the details, which would entail a breach of NDAs, a situation with which BRN, among others, is unhappily familiar.

So, while I believe that Valeo and Mercedes are more than likely using TENNS/Akida2 software in their upcoming releases (Scala 3, CLA (?)), and Sean has disclosed our commercial algorithm product, we may need to wait for sales of these products before we see revenue, and this will be at the end of a specified accounting period, so hopefully there will be some announcement beforehand, such as on release of the product.


https://www.msn.com/en-us/autos/aut...-details-all-the-changes-for-2025/ar-AA1soRTA

Mercedes-Benz Details All The Changes For 2025​

Story by Evan Williams
...
Merc(d)edes-Benz has added the latest (2024) MBUX version to the C-Class sedan.

It is also worth keeping in mind that of late both Mercedes and Valeo have stressed the ability to readily update software for SDVs, allowing for functional software upgrades.

While I continually remind myself of these circumstances, I just wish things were moving faster.

So we’re not ruling out a joint development with Starkey as well?

 

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[Smoothsailing]

Chatgpt. question


Companies Using Renesas with Brainchip Inside

Renesas Electronics Corporation has partnered with BrainChip to integrate their Akida neuromorphic processor technology into various applications, particularly in the automotive and IoT sectors. One notable company that utilizes Renesas’ technology alongside BrainChip’s Akida is Nissan Motor Co., Ltd. Nissan has adopted Renesas’ innovative automotive technology for its ProPILOT 2.0 system, which features advanced driver assistance capabilities. This system relies on Renesas’ R-Car automotive system-on-chip (SoC) and RH850 automotive control microcontroller (MCU), which can potentially incorporate BrainChip’s Akida IP for enhanced AI processing.

Additionally, other companies in the industrial and consumer IoT sectors are likely to leverage the combination of Renesas’ SoCs and BrainChip’s Akida technology due to its low power consumption and high performance for edge AI applications. However, specific names of these companies may not be explicitly mentioned in the available information.

In summary, Nissan Motor Co., Ltd. is a prominent example of a company using Renesas technology that could integrate BrainChip’s solutions within its systems.

 

[Smoothsailing]

ChatGpt …when will we see Brainchip in a product​

​

Conclusion​

In summary, while specific product names have not yet been disclosed publicly by BrainChip or its partners, it is anticipated that we will see the first commercial products utilizing BrainChip’s Akida technology in late 2024 across various sectors including automotive and consumer electronics.

Probability of Correctness: 90%