BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
TechGirl
Founding Member
Good article about ARMs M85
No mention of brainchip but in the article they mention accelerators, ML etc and they mention Renesas’s working silicon as an example.
“Arm’s partners have endorsed Cortex-M85 and already announced their plans to bring their M85-based devices to the market in the next year. For example, Renesas announced that it will demonstrate the first working silicon based on Cortex-M85.”
community.arm.com
Dimos Rossidis
March 8, 2023
7 minute read time.
Released in 2022, Arm Cortex-M85 has been the highest performing CPU in the Cortex-M portfolio. With scalar performance of more than 6 CoreMark/MHz and 3 DMIPS/MHz, Cortex-M85 has been an excellent fit for high-performance IoT, industrial control and automotive applications. At the same time, due to the implementation of the Arm Helium Technology, Cortex-M85 demonstrates significantly higher machine learning (ML) and digital signal processing (DSP) capabilities than Cortex-M7. These benefits make Cortex-M85 a very powerful core for microcontroller (MCU) applications where compute performance is key.
The deterministic operation (due to the Tightly Coupled Memories – TCMs) combined with the high compute capabilities make Cortex-M85 an ideal CPU choice for applications where intelligence is being increasingly pushed to the edge. The processor can enable endpoint devices to not only sense and collect data, but also perform a significant amount of computation, and even execute sophisticated ML algorithms on the CPU within a predictable time frame.
There is also a rising demand for this high performance to address new workloads, and be deployed in safety critical applications where the IP needs to be capable of managing and detecting any faults.
This is why we are delighted to announce that at the end of 2022, Arm released Cortex-M85 revision 1. Cortex-M85 r1 introduces the following:
In the automotive industry, Cortex-M85 can be used for diverse applications with varying safety needs. Some applications demand ASIL D for the highest safety integrity levels. One example are the high torque traction motors, where the significant growth in vehicle electrification has led to demand for more actuation across the vehicle. Other applications demand a lower safety integrity level, such as ASIL B. This is the case for vehicle cockpit displays incorporating cluster information.
Safety Ready logo
Cortex-M85 r1 is equipped with multiple safety features to address these varying safety needs. To meet the demands of ASIL D single point fault detection, Cortex-M85 can be implemented as a Dual Core Lockstep (DCLS) pair of processors, with one copy of the logic used to detect faults in the other. Although a DCLS configured Cortex-M85 can be deployed to achieve the diagnostic coverage needed for lower safety levels, the processor also supports mechanisms where this can be achieved with greater power and area efficiency. This is done through a combination of self-test functions and the ability of the Cortex-M85 r1 to detect Transient Faults. Self-testing through the use of Arm Software Test Libraries (STLs) can be used to detect permanent faults in the logic by periodically and flexibly executing the STLs on the processor. The flops in the design can be protected with the Transient Fault Protection (TFP) feature, which is able to identify a single bit fault in groups of flops. The cache memories are protected against faults with Error Correcting Code (ECC) providing Single Error Correction Double Error Detection (SECDED). In combination, these mechanisms can help deliver a more efficient solution for applications with ASIL B requirements.
Furthermore, Cortex-M85 r1 provides hardware which enables the in-field and on-line testing of the internal processor memories with Memory Built-in Self-Test (MBIST). A software Programmable MBIST Controller (PMC) can be integrated into the design to access, exercise, and test these memories while the processor continues to execute. Protection is also offered to transactions into and out of the processor by using interface protection. This is an extension to Arm’s Advanced Microcontroller Bus Architecture (AMBA) protocol and guards the transactions with parity protection against undetected corruption in the transaction between the core and the receiving interface, like the interconnect.
Arm has performed safety assessments on many of our Cortex-M processors using independent third-party assessors that issue certificates for the IP. Cortex-M85 will follow this same path. It has a safety package which provides information and evidence for partners to use in the development of products with safety requirements. For Cortex-M85, this planned assessment will evaluate both its systematic development and diagnostic capabilities for ASIL D and ASIL B.
The continuous need for higher processing capabilities results in the implementation of high performing processors, like Cortex-M85. At the same time, this raises the need for custom hardware accelerators, and the necessity for easy integration to the existing CPU. Accelerators are treated as memory-mapped IPs, through an internal coprocessor interface. Legacy Cortex-M CPUs, like Cortex-M33, implement such an interface, allowing the hardware accelerators to be closely integrated to the processor, and reducing the latency in data and instruction transfers. However, some applications require the execution of specialized data processing functions on the CPU, so that they can operate directly on general-purpose registers.
This need is addressed through Arm Custom Instructions (ACI), with Cortex-M85 – alongside Cortex-M55 – also implementing this feature. ACI allows chip designers to include custom defined data processing instructions directly on the Cortex-M processor, and enables the users to implement their own instructions by using the existing Cortex-M85 hardware.
Diagram showing how ACI combines with Cortex-M85 to meet the requirements for acceleration
Moreover, with ACI on Cortex-M85, the user does not have to turn to alternative architectures to implement a desired instruction encoding. Instead, this can now be done on CPUs that are based on the Arm architecture, with Cortex-M85 being the first high-performing microcontroller to provide this option. Through ACI, the user is given the power to innovate within the proven Arm architecture, while maintaining the ecosystem advantages of the Cortex-M CPUs.
All of the above makes ACI a powerful feature, as it provides a performance boost for low-latency instructions, easy integration with an existing software ecosystem and scalability across Cortex-M processors. ACI is the perfect fit for applications using specialized bit field processing, trigonometric functions, and image pixel manipulations. It can also be applied to accelerate frequently used data processing functions.
Through Cortex-M85 r1, Arm partners can now use all the enhanced features for improved performance and safety, and apply them in the IoT, automotive and industrial markets through their next-generation MCU products.
For more information, visit the Cortex-M85 page below.
No mention of brainchip but in the article they mention accelerators, ML etc and they mention Renesas’s working silicon as an example.
“Arm’s partners have endorsed Cortex-M85 and already announced their plans to bring their M85-based devices to the market in the next year. For example, Renesas announced that it will demonstrate the first working silicon based on Cortex-M85.”
Cortex-M85: Safety and performance updates
This blog outlines new updates to the Arm Cortex-M85 CPU to improve safety, flexibility and performance for IoT and automotive markets.
community.arm.com
Cortex-M85: Enabling safety and boosting flexibility and performance even higher
Dimos Rossidis
March 8, 2023
7 minute read time.
Released in 2022, Arm Cortex-M85 has been the highest performing CPU in the Cortex-M portfolio. With scalar performance of more than 6 CoreMark/MHz and 3 DMIPS/MHz, Cortex-M85 has been an excellent fit for high-performance IoT, industrial control and automotive applications. At the same time, due to the implementation of the Arm Helium Technology, Cortex-M85 demonstrates significantly higher machine learning (ML) and digital signal processing (DSP) capabilities than Cortex-M7. These benefits make Cortex-M85 a very powerful core for microcontroller (MCU) applications where compute performance is key.
The deterministic operation (due to the Tightly Coupled Memories – TCMs) combined with the high compute capabilities make Cortex-M85 an ideal CPU choice for applications where intelligence is being increasingly pushed to the edge. The processor can enable endpoint devices to not only sense and collect data, but also perform a significant amount of computation, and even execute sophisticated ML algorithms on the CPU within a predictable time frame.
There is also a rising demand for this high performance to address new workloads, and be deployed in safety critical applications where the IP needs to be capable of managing and detecting any faults.
This is why we are delighted to announce that at the end of 2022, Arm released Cortex-M85 revision 1. Cortex-M85 r1 introduces the following:
- Important functional safety features. The functional safety support helps in achieving both ASIL D/SIL 3 and, with lower hardware overhead, ASIL B/SIL2 safety requirements.
- The implementation of Arm Custom Instructions (ACI). ACI is a key feature that increases software flexibility by allowing user-defined instructions, and can also boost performance even higher by enabling accelerators that are tightly coupled with the datapath of the processor.
- Improved streaming performance, which is very important for workloads making increased memory accesses.
Cortex-M85: The first safety ready high-performing Cortex-M
Automotive and industrial control products rely on safety standards, which ensure that each individual electrical or electronic component integrated into the product meet functional safety requirements. Arm’s Safety Readyportfolio is based on the ISO 26262 (for automotive) / IEC 61508 (for industrial) safety standards. ISO 26262 / IEC 61508 are risk-based standards that aim to address potential hazards caused by the malfunction of these systems. They provide frameworks and guidelines that should be followed during the development of a system and determine Automotive Safety Integrity Level (ASIL) / Safety Integrity Level (SIL) based on a risk assessment analysis.In the automotive industry, Cortex-M85 can be used for diverse applications with varying safety needs. Some applications demand ASIL D for the highest safety integrity levels. One example are the high torque traction motors, where the significant growth in vehicle electrification has led to demand for more actuation across the vehicle. Other applications demand a lower safety integrity level, such as ASIL B. This is the case for vehicle cockpit displays incorporating cluster information.
Safety Ready logo
Cortex-M85 r1 is equipped with multiple safety features to address these varying safety needs. To meet the demands of ASIL D single point fault detection, Cortex-M85 can be implemented as a Dual Core Lockstep (DCLS) pair of processors, with one copy of the logic used to detect faults in the other. Although a DCLS configured Cortex-M85 can be deployed to achieve the diagnostic coverage needed for lower safety levels, the processor also supports mechanisms where this can be achieved with greater power and area efficiency. This is done through a combination of self-test functions and the ability of the Cortex-M85 r1 to detect Transient Faults. Self-testing through the use of Arm Software Test Libraries (STLs) can be used to detect permanent faults in the logic by periodically and flexibly executing the STLs on the processor. The flops in the design can be protected with the Transient Fault Protection (TFP) feature, which is able to identify a single bit fault in groups of flops. The cache memories are protected against faults with Error Correcting Code (ECC) providing Single Error Correction Double Error Detection (SECDED). In combination, these mechanisms can help deliver a more efficient solution for applications with ASIL B requirements.
Furthermore, Cortex-M85 r1 provides hardware which enables the in-field and on-line testing of the internal processor memories with Memory Built-in Self-Test (MBIST). A software Programmable MBIST Controller (PMC) can be integrated into the design to access, exercise, and test these memories while the processor continues to execute. Protection is also offered to transactions into and out of the processor by using interface protection. This is an extension to Arm’s Advanced Microcontroller Bus Architecture (AMBA) protocol and guards the transactions with parity protection against undetected corruption in the transaction between the core and the receiving interface, like the interconnect.
Arm has performed safety assessments on many of our Cortex-M processors using independent third-party assessors that issue certificates for the IP. Cortex-M85 will follow this same path. It has a safety package which provides information and evidence for partners to use in the development of products with safety requirements. For Cortex-M85, this planned assessment will evaluate both its systematic development and diagnostic capabilities for ASIL D and ASIL B.
Boosting flexibility and performance with Arm Custom Instructions
The compute and processing requirements in recent embedded systems have increased significantly. This is especially true in the IoT space where the market is pushing the compute requirements to the endpoint devices (such as smart sensors/cameras, agricultural drones, etc.) of the IoT system.The continuous need for higher processing capabilities results in the implementation of high performing processors, like Cortex-M85. At the same time, this raises the need for custom hardware accelerators, and the necessity for easy integration to the existing CPU. Accelerators are treated as memory-mapped IPs, through an internal coprocessor interface. Legacy Cortex-M CPUs, like Cortex-M33, implement such an interface, allowing the hardware accelerators to be closely integrated to the processor, and reducing the latency in data and instruction transfers. However, some applications require the execution of specialized data processing functions on the CPU, so that they can operate directly on general-purpose registers.
This need is addressed through Arm Custom Instructions (ACI), with Cortex-M85 – alongside Cortex-M55 – also implementing this feature. ACI allows chip designers to include custom defined data processing instructions directly on the Cortex-M processor, and enables the users to implement their own instructions by using the existing Cortex-M85 hardware.
Diagram showing how ACI combines with Cortex-M85 to meet the requirements for acceleration
Moreover, with ACI on Cortex-M85, the user does not have to turn to alternative architectures to implement a desired instruction encoding. Instead, this can now be done on CPUs that are based on the Arm architecture, with Cortex-M85 being the first high-performing microcontroller to provide this option. Through ACI, the user is given the power to innovate within the proven Arm architecture, while maintaining the ecosystem advantages of the Cortex-M CPUs.
All of the above makes ACI a powerful feature, as it provides a performance boost for low-latency instructions, easy integration with an existing software ecosystem and scalability across Cortex-M processors. ACI is the perfect fit for applications using specialized bit field processing, trigonometric functions, and image pixel manipulations. It can also be applied to accelerate frequently used data processing functions.
Upgraded streaming performance
Cortex-M85 r1 has an enhanced datapath to deliver significantly higher streaming performance compared to the legacy Cortex-M processors. Specifically, Cortex-M85 r1 delivers about 2x higher streaming performance than Cortex-M55 and Cortex-M7 using LMbench. This enhancement is very important for any workload that requires continuous memory access across the AXI interface. For example, large footprint code that requires external memory access.Cortex-M85 based products to be brought in the market soon
Arm’s partners have endorsed Cortex-M85 and already announced their plans to bring their M85-based devices to the market in the next year. For example, Renesas announced that it will demonstrate the first working silicon based on Cortex-M85.Through Cortex-M85 r1, Arm partners can now use all the enhanced features for improved performance and safety, and apply them in the IoT, automotive and industrial markets through their next-generation MCU products.
For more information, visit the Cortex-M85 page below.
What pisses me off most is that they never admit they missed their target... tbh given this an extremely advanced technology in a new field and given they got so much things done (joining eco systems & forming partnerships, etc.), it's totally understandable that they didnt meet the timeline or revenue target...but they need to acknowledge what has happened and move on and provide a new target... I am so worried that it may repeat brain studio, accelerator, etc. back in 2015
D
Deleted member 118
Guest
I for one and probably the only 1, am more than happy with the timeline for revenue not expecting until late 23 early 24 as I was unable to add to my holdings until recently and will accumulate like mad now.
D
Deleted member 1270
Guest
Well said. As a competition to all on this site.. humour me and try and find the presentation that Sean gave a couple of days ago.
D
Deleted member 1270
Guest
So you're really saying that we shouldn't believe anything management state regarding the timeline to revenue and we should take comfort that you are happy to wait until 2024 for revenue?
Stable Genius
Regular
It’s been posted 4 times now; and is on the previous page. Wiltzy posted it last.
D
Deleted member 1270
Guest
Link to the companies website please. Then you get the prize!
The point I am trying to make is why should I have to go and search the internet for a company presentation? I should be able to easily locate it shouldn't I?
p.s. I have the presentation as I listened to it live.
Stable Genius
Regular
I don’t think Brainchip can be responsible for what employees of other companies are putting on the internet.
D
Deleted member 1270
Guest
Don't you feel though that we should expect honest and timely information about the company we own, from management?
Even though it is a speccy it is clear that the flow of information from the company is disappointing to say the least.
D
Deleted member 1270
Guest
The guy works for Brainchip.
Kachoo
Regular
I don't know what you do for a living but nobody admits to short falls in industry.
But you do have the right to be upset.
Being the studio? Well if you invested then what kind of media coverage and activity did you see out side of BRN about Studio? I was not a share holder so I don't know.
Putting new targets can be tricky on having new contracts. You can forecast current contracts but new ones are really unknown. This will lead to more issues best leave it out. Zacks put revenue to be 11 million for 2023 have a read on that. Is this slow yeah but that's out of our control.
Yeah some stuff was said that may not have been said well it happened and people move on.
In the end this is what needs to be know.
Is our technology great if yes how much money will we make over the next 2 decades.
It was also stated years ago how much new inventions can be made with what Akida can do.
Kachoo
Regular
What did that tweet actually say. I see many tweets that competing companies congratulate others for accomplishments? So it's really hard to know what your implying?
Stable Genius
Regular
I’m not sure which article you are referring to. I have read numerous papers from TATA employees testing and referring to SNN’s and Brainchip therefore I though it was one of their papers you were talking about.
Not sure what your agenda is this morning. It’s obvious by you’re tone you’re unhappy with the company. I hope venting on here makes you feel better.
Usually if for example I go to a restaurant and I don’t like the food I simply don’t go back. I’m not one to return and try and tell the staff how to do their job. Apart from it not being my personality type I appreciate I’m not qualified to do so.
I found your comment earlier to imply the board are incompetent quite distasteful.
Personally I am very pleased with the boards composition. I’d rather we be paying less at this stage for them, or having it KPI based when we aren’t profitable, however I accept to hire top quality people we need to pay top dollar. The board and staff have extensive experience and are highly respected within the industry.
I hope you can add value to the forum in the future.
Bravo
If ARM was an arm, BRN would be its biceps💪!
What a New Lawsuit Means for Companies Marketing AI Tech
April 14, 2023 - By TFL
A new lawsuit is calling foul on the developers of an artificial intelligence (“AI”)-powered e-commerce personalization app, accusing them of falsely characterizing the app’s capabilities in order lure in investors and customers. According to the complaint that they filed with a California federal court early this month, RETAILERX, Inc. d/b/a Pantastic Networks and its founder Neil S. Rafer (collectively “Pantastic”) claim that LimeSpot Solutions Inc.’s founders Aidin Tavakkol and Essan Parto, among others (the “defendants”) engaged in “extensive fraud” by misrepresenting and/or omitting LimeSpot’s “supposedly ‘state of the art’ neural network, machine learning, and/or deep learning technological capabilities over a period spanning approximately seven years.”
Setting the stage in the complaint, Pantastic claims that beginning in 2016, Mr. Tavakkol explicitly misled Mr. Rafer as to the core of his company LimeSpot, telling Rafer that LimeSpot “was centered around its machine and deep learning technology that was revolutionizing online marketplaces and, unlike its competitors, contained a system of neural networks that allowed its platform to analyze large sets of data and function and learn in an automated manner without any manual human input and/or adjustment.” Fast forward to 2022 and the parties reached an agreement in furtherance of which Pantastic would acquire LimeSpot so that it “could utilize the neural network and machine and deep learning technology that LimeSpot had been touting for many years.”
Such AI-centric representations about LimeSpot came in the form of “pitch decks and related scripts that the defendants created and presented to [it], investors, and prospective customers,” Pantastic claims. Among some of the alleged misrepresentations included in these decks …
– LimeSpot’s technology is different from competitors, who only offer “a manual mix of technology and human intervention;”
– LimeSpot’s implementation has “deep personalization;”
– LimeSpot’s “patent-pending technology” and “core IP” is powered by “machine learning” and “artificial intelligence;”
– AI is “being automated and taken over by learning systems … we’ve been a part of it for the past 4 years;”
– “Most importantly we wanted to build a global network effect for our AI brain”; and
– The chart “clearly shows the network effect, and how the machine is learning and doing a better job.”
Additionally, Pantastic maintains that the defendants made representations regarding LimeSpot’s “‘automated artificial intelligence, machine learning, and deep learning technology’ … in written and oral communications, including but not limited to in person, emails and online chats, telephone and videoconferences, webpages, blog posts, investor updates, slide decks and presentations, and marketing and promotional materials up until the date of this complaint.”
Not long after the acquisition was finalized, things went south after, per Pantastic, which alleges that once its team began working with the defendants and others on the LimeSpot team to complete a series of tasks to begin integrating LimeSpot’s technology into Pantastic’s platform, they “began to uncover that apparently the technology which Defendants had claimed they had for over seven years never existed.” (Emphasis courtesy of the complaint.)
To the contrary, Pantastic asserts in its new lawsuit that “LimeSpot’s technology did not include the promised AI, machine learning, and deep learning capabilities that consisted of a system of neural networks and could analyze large sets of data and function and learn in an automated manner.” In fact, LimeSpot’s tech was “an utter failure because numerous and frequent human input was constantly required and no neural networks existed, thus negating the entire alleged value of LimeSpot and its purported ‘technology.’”
Despite such “shocking discoveries,” Pantastic contends that it “still attempted in good faith to work with the defendants for approximately six months to come up with an alternative solution that would at least allow Pantastic to obtain some value from LimeSpot’s technology, although still nothing close to the essential capabilities repeatedly promised.” However, the company claims that it has been left with “no choice but to file this action seeking declaratory relief and money damages related to the defendants’ myriad of wrongful acts.”
With the foregoing in mind, Pantastic sets out claims of fraud, negligent misrepresentation, unfair business practices, restitution/unjust enrichment, conversion, breach of contract, breach of covenant of good faith and fair dealing, promissory estoppel, and declaratory judgment. Among other things, Pantastic is seeking a declaration from the court that the parties’ deal “never legally came into being, and/or [is] wholly tainted, invalid, illegal, void, rescinded, and/or unenforceable,” and that as a result, LimeSpot owes Pantastic all monies paid under the agreements related to the purchase of LimeSpot by Pantastic, a sum that is redacted in the complaint.
THE BIGGER PICTURE: The lawsuit comes on the heels of the Federal Trade Commission releasing guidance in February, in which it alerted companies to avoid making unsupported claims about “new tools and devices that supposedly reflect the abilities and benefits of AI.” In a post published on the FTC’s site on February 28, the FTC Division of Advertising Practices’ Michael Atleson stated that while AI is “an ambiguous term with many possible definitions,” often referring to a variety of “tools and techniques that use computation to perform tasks such as predictions, decisions, or recommendation,” one thing is for sure: AI is currently a hot marketing term that will inevitably be “overus[ed] and abus[ed].”
Against that background, this lawsuit might prove to be the first of many lawsuits that take issue with the merits of companies’ marketing of AI products, especially amid increased allocation of angel and venture funding to AI startups and growing M&A activity in this space.
The case is RetailerX, Inc. v. Aidin Tavakkol, et al., 3:23-cv-01705 (N.D. Cal.)
Pantastic Accuses App Developer of Overstating AI in New Lawsuit
A lawsuit is calling foul on the developers of an AI-powered e-commerce app, accusing them of overstating the app’s capabilities.
www.thefashionlaw.com
D
Deleted member 118
Guest
I was just stating what someone wrote about revenue and the company, but I do know I’m onto a real winner here in 5 plus years time no matter how bumpy the journey is.
Bravo
If ARM was an arm, BRN would be its biceps💪!
Global Artificial Intelligence/Machine Learning Medical Device Market to Reach $35.45 Billion by 2032 - Exclusive DeepTech M-A-P™ Analysis by BIS Research
BIS Research, the global leader in providing market intelligence on deep technologies, has released its latest study titled Artificial Intelligence/Machine Learning Medical Device Market – A Global and Regional Analysis.
Similar threads
