BRN Discussion Ongoing

[Tothemoon24]

The transformational era of AI in healthcare: Multimodal AI and Neuromorphic AI​

By Express Computer on June 20, 2024
By Anup S S, Practice Head, Artificial Intelligence, Tata Elxsi
Artificial Intelligence is undergoing steady research and development with its influence being felt across industries, specifically in the healthcare sector. From optimising drug combinations to diagnostic assistance and toxicity studies, AI is set to redefine every facet of healthcare. The healthcare sector is also acknowledging the critical need for an interdisciplinary approach that integrates engineering with medical science. This paradigm shift signals an era in which AI’s extensive capabilities will revolutionise diagnostics, patient treatment protocols, drug development and delivery, and prescription practices in the next decade.
Impact of digital and connected technologies in healthcare
In the constantly evolving healthcare landscape, the fusion of Multimodal AI and Neuromorphic Technology represents a pivotal moment. Firstly, Multimodal AI refers to the generative capabilities of AI like processing information from multiple modalities, including images, videos, and text. In healthcare, these modalities often include both visual and clinical data. Visual data may include medical images from scans, while clinical data encompasses patient records, parameters, and test reports. Multimodal AI integrates these diverse data types to provide a comprehensive understanding, draw meaningful insights and give suggestions based on data and image analytics.
Neuromorphic Technology, on the other hand, comes from the combination of “neuro” (related to the nervous system) and “morphic” (related to form or structure). It refers to a method of computer engineering in which computational elements are modelled after systems in the human brain and nervous system. These are AI-powered by brain-like computing architectures and can process larger amounts of data with less computing power, memory, and electric power consumption. For one, Neuromorphic Technology utilises Artificial Neural Networks (ANN) and Spiking Neural Networks (SNN) to mimic the parallel processing, event-driven nature, and adaptability observed in biological brains.
The fusion of Multimodal AI and Neuromorphic Technology transitions from reactive medicine to a proactive and preventive healthcare paradigm. This synergy goes beyond the collaboration of cutting-edge technologies; it opens the door to a future where wellness is the primary focus. These technologies hold promise to transform healthcare by enhancing diagnostics, enabling personalised medicine, predicting long-term prognosis, and contributing to innovations in therapeutic interventions. For example, Multimodal AI can help in accurate and personalised management of diseases based on data from different sources including lab reports, imaging studies, clinical history and so on. Neuromorphic, on the other hand, can make the medical devices extremely portable with low-energy consumption. This can eventually lead to implantable smart devices that can monitor vital functions on a continuous basis with minimal discomfort to the user.
How connected technologies help to prevent diseases, lower costs & manage chronic conditions
Multimodal and Neuromorphic AI are further enhanced by connected technologies in healthcare. For instance, connected devices help provide more personalised and prognostic insights based on individual variations. Combining visual and clinical data along with machine learning operations to correlate with prior case records further helps prevent diseases and paves the way for a seamless deployment, continuous monitoring, and collaborative development across various stakeholders in the healthcare ecosystem.
What’s more, these technologies also help in lowering healthcare costs. Even with limited resources, a first-level AI-based screening in small facilities can play a pivotal role in early detection of many diseases. AI-based technologies also provide unbiased, objective, and repeatable analysis without any additional costs involved.
Further, connected healthcare with multimodal AI helps patients manage and monitor chronic conditions like Diabetes/HT/Cardiac Diseases with continuous monitoring and personalised medications. The adaptability of multimodal AI to changing data patterns ensures that prognostic models can dynamically adjust based on evolving patient conditions and improve prognosis predictions. It also helps in the discovery of new insights, contributing to medical advancements and innovations. For instance, personalised prognostic models include both visual and clinical data. These models account for individual variations and correlate with prior case records and provide more accurate predictions of disease outcomes.
Additionally, Multimodal AI and Neuromorphic AI technologies also play a vital role in the management of emergency interventions. In such cases, adaptive intelligence for dynamic adjustments enhances the precision of diagnostic processes. This event-driven processing aligns with the dynamic nature of healthcare data allowing for more accurate and timely diagnoses.
Responsible AI: Ethics and regulations in healthcare technology
In the realm of AI, addressing bias stands as a pivotal ethical imperative, particularly in fields like medical analysis where the demand for precise and unbiased inference is ethically, legally, and morally paramount. This requires rigorous testing using diverse, unbiased anonymised datasets, continual monitoring to mitigate biases, and a steadfast dedication to achieving fair outcomes across diverse patient populations.
The foundation of responsible AI in healthcare is laid upon a robust ethical framework that guides the entire lifecycle of Neuromorphic and Multimodal AI systems. This means ensuring transparency, fairness, and accountability at every stage of AI implementation by stakeholders of the industry. It is imperative to define strong ethical boundaries, implement robust audits, and establish legal frameworks to prevent data manipulation and ensure the highest standards of integrity.
As thought leaders in the healthcare industry, it is our commitment to responsibly integrate these technologies for a future where healthcare is not only reactive, but anticipatory, personalised, and universally accessible.

 

[DingoBorat]

Is it a coincidence that, just when 8M shorts ae taken out, there is another unfavorable article from MF?

With MF, it's usual that many-a-mickle-makes-a-muckle.

However this is a more temperate, though still negative, review of BRN.

https://www.msn.com/en-au/lifestyle...&cvid=2de0ef4bba8f41b39d5155aab5784e0f&ei=166

You will probably be disappointed by the absence of coffee shop comparisons.

However, I think this passage reflects poorly on the accounting principles used for tech company assets.

Revenues were down an eye-watering 95% year over year, which took many by surprise. The company produced a net loss of around $29 million on these sales, with reasonably flat growth in accounts receivable. During the year, it also released its second generation Akida technology.

The bulk of the $29M "loss" was R&D investment in producing the second generation Akida., yet there is no acknowledgement of the intrinsic value of Akida 2 IP. It's not like we spent all this money and have nothing to show for it.

In JORC terms, Akida 2 IP is a proven resource, as is Akida 1 IP. You only need to look at the EAP comments on the Akida Generations page: https://brainchip.com/akida-generations/

At present, Akida IP is an off-the-books asset. As far as most investors are concerned, they cannot see it.

It's better than money in the bank, because of its earning potential ... and it is also the Magic Pudding - no matter how much you use, there's always more where that came from.

'It's better than money in the bank, because of its earning potential ... and it is also the Magic Pudding - no matter how much you use, there's always more where that came from"

Hmmm Magic Pudding...

 

[Tothemoon24]

Loading…

openaccess.thecvf.com

This is above my pay rate of $1.21 hr

Seems Brainchip may of been part of this challenge, below can be found on page 6 of the above paper

 

[manny100]

I tend to skim over anything put out by MF but... is this a new disclaimer. Almost like they want to start hedging their bets..

View attachment 65459

MF want you to subscribe instead of buying a retail favorite stock. Also shorters with huge bets on have the ability to assist their agenda by getting Financial digital 'rags' to support their agenda. Not saying its happening here.

 

[charles2]

Pilfered the last penny from my last piggy bank today (a hollow feeling..... for the piggy)

And now own 64k more shares.

If there is a better time to buy than now ......well in advance I confess, I will have missed it.

Call me penniless!

For now.

 

[SharesForBrekky]

Here are links to what SiFive is currently showcasing at the RiscV Europe Summit at the moment (24-28 June):

SiFive announces Essential Gen4 RISC-V CPUs for embedded applications - CNX Software

As the RISC-V Summit Europe 2024 is underway, SiFive has announced the fourth generation of its "Essential" RISC-V CPUs (Essential Gen4) with improved

www.cnx-software.com

SiFive Announces 4th Generation of Popular Essential Product Line to Spur Innovation Across Embedded Applications

www.sifive.com

Link to the Europe Summit page:

RISC-V Summit Europe 2024 – RISC-V International

riscv.org

 

[7für7]

Hi i’am new here! Can some tell me if I can buy those chips already in the supermarket? Which flavours are available? Thanks in advance

 

[Pom down under]

"How Arm’s Machine Learning Solution Enables Vision Transformers at the Edge," a Presentation from Arm

Stephen Su, Senior Segment Marketing Manager at Arm, presents the “How Arm’s Machine Learning Solution Enables Vision Transformers at the Edge” tutorial

www.edge-ai-vision.com

You’ll need to login

 

[AARONASX]

Apologies if already shared

BrainChip (ASX:BRN): An exciting AI stock with an immense opportunity ahead

BrainChip (ASX:BRN) is commercialising neuromorphic processing technology known as Akida and has a very substantial opportunity ahead.

stocksdownunder.com

 

[schuey]

Hi i’am new here! Can some tell me if I can buy those chips already in the supermarket? Which flavours are available? Thanks in advance

View attachment 65501

In the "SALE" section.......Bitter Flavour

 

[KKFoo]

Apologies if already shared

BrainChip (ASX:BRN): An exciting AI stock with an immense opportunity ahead

BrainChip (ASX:BRN) is commercialising neuromorphic processing technology known as Akida and has a very substantial opportunity ahead.

stocksdownunder.com

Thanks for the article, just bought a bit more and keep my fingers crossed..

 

[hotty4040]

In the "SALE" section.......Bitter Flavour

Bitter ( possibly ), but definitely on the edge of spikiness, i.e. BETTER.

A bit of interest today perhaps, ? Maybe it's a better " butter " bet....


Akida Ballista >>>>> Can you tell TALK from MUTTER <<<<<

Remember that one !

hotty...

 

[Bravo]

​

​

Tech Translated: Neuromorphic computing​

s+b a PwC publication

What is neuromorphic computing? Neuromorphic computer systems aim to mimic brain functions, with the ultimate goal of matching—or even surpassing—the capabilities of the human mind. This ranges from using software to model and process information in the way that living organisms do, through trying to match the brain’s (as yet) unbeaten combination of low power and high performance with the use of radical new hardware architectures, including novel components such as memristors (transistors that behave like neurons).

What business problems can it address?​

“With the enormous potential of AI becoming more obvious by the day, one of the major concerns for the field is that flexible intelligence as we understand it actually maps onto binary computing very poorly, and is inefficient as a result,” explains Dina Brozzetti, a managing director in PwC US’s products and technology practice. “If AI could truly learn and evolve its understanding of the world without prior programming, just like us, but at the same low energy cost—a human brain uses only around the same energy as a 20-watt light bulb, to do calculations a supercomputer would struggle to perform—then it could be the most transformative watershed in computing since the switch from vacuum tubes to transistors.”
Beyond immediate applications for AI and machine learning specifically, neuromorphic computing has implications for all human–machine intellectual collaboration—particularly data analysis and research and development—as well as internet of things, smart cities, autonomous vehicles, human augmentation, sensory processing, industrial management and more. This wide-ranging potential is why in 2023 PwC US listed neuromorphic computing as one of the Essential Eight emerging technologies.

How does it create value?​

Today’s computers are limited by their internal configuration: a transistor is only connected on either side of its gate. But a neuron is connected to thousands of other neurons simultaneously. Additionally, rather than the binary on–off approach of today’s digital systems, neurons respond to both the quantity and duration of incoming signals, giving vastly more capacity to process information despite far lower energy needs. “This will both massively reduce IT overhead and give us an important tool for addressing climate change through reduction of energy use,” says Scott Likens, Global AI and Innovation Technology Leader, PwC United States.
There are hurdles: neuroscientists are still struggling to understand and model even simple animal brains, and memristors are more theory than reality. However, applying neuromorphic principles in both software and hardware has still led to impressive advancements, such as UC Santa Cruz’s SpikeGPT, a neural network that uses 22 times less energy than comparable systems. Neuromorphic systems can also self-improve through evolution, just like living creatures do, with potential for dramatic positive feedback loops in many fields of R&D.
“If a scalable breakthrough can be made, neuromorphic processors will lead to a dizzying number of new applications that we can only begin to speculate about, and at the same time truly integrate AI into our lives,” says Likens. “Something the size of your phone will be able to run tasks that currently require a supercomputer and enable new forms of AI that could see today’s generative AI models seem positively slow and limited in comparison.”

Who should be paying attention?​

Anyone whose work involves information processing in which neurons still beat silicon could ultimately be impacted if neuromorphic computing takes off. Innovation-focused teams—in technology in general and medical technology in particular—as well as transportation and logistics, engineering and construction, automotive, chemicals, and pharmaceuticals and life sciences should all keep on top of developments in case of a breakthrough. The ubiquity of digital technology means leaders such as CTOs, CISOs, and COOs across industries should be aware of the potential of neuromorphic computing to radically alter computing’s capabilities.

How can businesses prepare?​

“The field is still largely confined to academic/corporate R&D labs,” says Brozzetti, “so first, task a team with upskilling their knowledge, investigating possible applications in your industry, and deciding whether it makes sense to invest in either researching directly internally or engaging with external partners. Connect with researchers to help strengthen these efforts and find ways to collaborate to realize the potential benefits early.” At that point, it may be possible to identify possible use cases—for example, integration into an existing embedded IT product—and inclusion in your long-term product development road map.

Tech Translated: Neuromorphic computing

Potentially the key to the next generation of true artificial intelligence, neuromorphic computing could revolutionize business.

www.pwc.com

Incidentally, last year PwC estimated AI could impact global GDP by 15 trillion!

 

[Boab]

Apologies if already shared

BrainChip (ASX:BRN): An exciting AI stock with an immense opportunity ahead

BrainChip (ASX:BRN) is commercialising neuromorphic processing technology known as Akida and has a very substantial opportunity ahead.

stocksdownunder.com

This report is now on the Brainchip website under "Resources" and select "PR".

 

[Diogenese]

​

View attachment 65504​

​

Tech Translated: Neuromorphic computing​

s+b a PwC publication

What is neuromorphic computing? Neuromorphic computer systems aim to mimic brain functions, with the ultimate goal of matching—or even surpassing—the capabilities of the human mind. This ranges from using software to model and process information in the way that living organisms do, through trying to match the brain’s (as yet) unbeaten combination of low power and high performance with the use of radical new hardware architectures, including novel components such as memristors (transistors that behave like neurons).

What business problems can it address?​

“With the enormous potential of AI becoming more obvious by the day, one of the major concerns for the field is that flexible intelligence as we understand it actually maps onto binary computing very poorly, and is inefficient as a result,” explains Dina Brozzetti, a managing director in PwC US’s products and technology practice. “If AI could truly learn and evolve its understanding of the world without prior programming, just like us, but at the same low energy cost—a human brain uses only around the same energy as a 20-watt light bulb, to do calculations a supercomputer would struggle to perform—then it could be the most transformative watershed in computing since the switch from vacuum tubes to transistors.”
Beyond immediate applications for AI and machine learning specifically, neuromorphic computing has implications for all human–machine intellectual collaboration—particularly data analysis and research and development—as well as internet of things, smart cities, autonomous vehicles, human augmentation, sensory processing, industrial management and more. This wide-ranging potential is why in 2023 PwC US listed neuromorphic computing as one of the Essential Eight emerging technologies.

How does it create value?​

Today’s computers are limited by their internal configuration: a transistor is only connected on either side of its gate. But a neuron is connected to thousands of other neurons simultaneously. Additionally, rather than the binary on–off approach of today’s digital systems, neurons respond to both the quantity and duration of incoming signals, giving vastly more capacity to process information despite far lower energy needs. “This will both massively reduce IT overhead and give us an important tool for addressing climate change through reduction of energy use,” says Scott Likens, Global AI and Innovation Technology Leader, PwC United States.
There are hurdles: neuroscientists are still struggling to understand and model even simple animal brains, and memristors are more theory than reality. However, applying neuromorphic principles in both software and hardware has still led to impressive advancements, such as UC Santa Cruz’s SpikeGPT, a neural network that uses 22 times less energy than comparable systems. Neuromorphic systems can also self-improve through evolution, just like living creatures do, with potential for dramatic positive feedback loops in many fields of R&D.
“If a scalable breakthrough can be made, neuromorphic processors will lead to a dizzying number of new applications that we can only begin to speculate about, and at the same time truly integrate AI into our lives,” says Likens. “Something the size of your phone will be able to run tasks that currently require a supercomputer and enable new forms of AI that could see today’s generative AI models seem positively slow and limited in comparison.”

Who should be paying attention?​

Anyone whose work involves information processing in which neurons still beat silicon could ultimately be impacted if neuromorphic computing takes off. Innovation-focused teams—in technology in general and medical technology in particular—as well as transportation and logistics, engineering and construction, automotive, chemicals, and pharmaceuticals and life sciences should all keep on top of developments in case of a breakthrough. The ubiquity of digital technology means leaders such as CTOs, CISOs, and COOs across industries should be aware of the potential of neuromorphic computing to radically alter computing’s capabilities.

How can businesses prepare?​

“The field is still largely confined to academic/corporate R&D labs,” says Brozzetti, “so first, task a team with upskilling their knowledge, investigating possible applications in your industry, and deciding whether it makes sense to invest in either researching directly internally or engaging with external partners. Connect with researchers to help strengthen these efforts and find ways to collaborate to realize the potential benefits early.” At that point, it may be possible to identify possible use cases—for example, integration into an existing embedded IT product—and inclusion in your long-term product development road map.

Tech Translated: Neuromorphic computing

Potentially the key to the next generation of true artificial intelligence, neuromorphic computing could revolutionize business.

www.pwc.com

View attachment 65507


View attachment 65508






Incidentally, last year PwC estimated AI could impact global GDP by 15 trillion!

View attachment 65505

Clunk! (Penny dropping)

If AI could truly learn and evolve its understanding of the world without prior programming, just like us, but at the same low energy cost—a human brain uses only around the same energy as a 20-watt light bulb, to do calculations a supercomputer would struggle to perform—then it could be the most transformative watershed in computing since the switch from vacuum tubes to transistors.

Together with Edge Impulse, BRN is on the threshold of cracking the golden egg - AI that can truly learn.

LLMs and Chat GPT use human operators to manually label objects in an image frame.

EI has developed an automatic system of labelling objects in an image by using a NN to classify new objects on the basis of an established model. Obviously, using Akida will maximize the efficiency of the classification process.

I guess that objects unfamiliar to the model will still need some human intervention, and these could be flagged for attention.

AutoLLM omelette anyone?

PS: Never ask an auditor for a technological explanation - They wouldn't know a memristor if it bit their donkey.

 

[Bravo]

Video Transcript Arm CEO, Renee Haas​

Moving on arm holdings getting added to the NASDAQ 100 today, the British semiconductor company will also be incorporated in several other NASDAQ indexes.

Shares of arm up nearly 100 and 40% since its public debut back in September, Haas arm holding CEO joining us now, Renee, it is good to see you and, and maybe start on that news, Renee, I'm just interested in how you, you know, how you think about it.

What does it mean for arm to be included like this?

Do you see it, Renee as you know, maybe a kind of milestone for the company.

What, what are you telling your team?

Well, uh thanks for having uh having me.

It's certainly a milestone.

It's something we're, we're proud of.

Uh the NASDAQ 100.

That's a, that's an elite company.

So for arm to be included on it, it's a, it's a very, very cool day and the employees and company are excited and so as you have this day and you're excited, I am curious because there's been so much talk lately, Renee about retail investors, right?

We've seen some glimmers again in the market of the meme stock trade.

I think Tesla is a part of this phenomenon as well with its retail stock, uh retail shareholder participation in its recent vote, for example.

So how are you thinking about that cohort of people who are interested in, in potentially owning arm holding stock?

You know, honestly, I don't think about it that much.

Uh My focus is really on the strategy trying to grow the company.

Uh One of the things I love most about my job is that I'm usually having discussions about technology in 2026 2027 2028.

Uh thinking about, you know, the question you just asked, I, I understand the question but it's actually not where I spend a lot of my focus.

Uh Renee, let's talk about one area I'm guessing is a focus for you, which is the mega trend of A I, you know, Rene we spend so much time on this show, of course, talking about it.

Investors are very excited and I, I know Renee, you, you know, I would argue, I'm sure, you know, um I think in fact, the last time we spoke, Renee, you said, you know, basically you can't run A I without ac pu can you just walk us through Renee?

You know how you think about the opportunity for arm here?

How, how big is the opportunity when we talk about this mega trend of A I?

How do you quantify it, Renee?

Yeah, I think that Uh And, and I was around, you know, during the.com uh era, in fact, to me.com kind of started even in the late nineties with the browser and then the build out of the internet.

Uh To me, this is much more profound uh because what A I is going to do is that it is going to really, really change people's lives in terms of productivity, whether that's call centers, it can become 100% automated uh healthcare, uh bioresearch where you can cut the research of a cancer drug from 10 years to five years to three years.

This is all gonna be capable with A I and then every device that we use the data center, the automobile, your PC, your smartphone, they all need to run A I there, there's, there's no quibble around that.

And since 70% of the world's devices today use arm and they have to use A I on top of the arm based platform already.

It's just natural that we're going to be involved in it.

So it's something we spend a lot of time on.

But I don't think it's hyped at all.

I think it is going to be something that uh when we look back in terms of what the capabilities are and what it unleashes, it's gonna be a momentous time in history.

Well, Renee, it's so interesting the relationship between A I and arm because I gotta tell you coming up to the drumbeat of your IP O last September when there was a lot of talk about A I, we were talking to a lot of who were saying A I is not really the story for Arm yet that it's still early.

And so it seems though that you have been gaining a little steam in that area.

So can you tell our, our listeners and viewers right now kind of where you are for Arm in that cycle?

Yeah, I thank you for the question.

I think respectfully, uh the analyst maybe didn't quite understand or have a, an appreciation at the pace at which things were moving.

Uh There was a belief that A I meant you're running a large language model in the data center.

But if you look nine months later, we have an A I PC, we had Chet Chet G BT 40 running on a mobile phone doing voice recognition, which is being done in conjunction with the cloud and the local device.

You have Gemini uh an A I tool that runs on your cell phone.

Nobody was talking about those things a year ago and to be fair, it's not because the analyst didn't understand it.

It's just the pace that this is how this is moving.

And by definition, uh because of all the investments taking place in terms of training, all that training needs to find its way into applications.

And most of those applications will be in your handheld devices.

Or your consumer devices.

So I think even the analysts probably didn't have a sense of just how fa how fast things are going.

And one of the things we'd like to talk about is that software is moving far faster than the hardware.

So I think that's the key learning that we've seen and, and perhaps the analysts as well.

And Renee, let's talk, let's talk smartphones as well.

I'm just get your take because you know, we, we've had analysts um come on the show, Renee and say, listen, they, they think A I is gonna prove to be a real tailwind for the smartphone market, at least, you know, the premium segment is that how you see it, Renee and what, what would that mean for or I think it will be a tailwind.

You know, remember that these smartphones iterate every single year and they add new and new technology which puts a lot of strain on the system in terms of battery performance heat.

Now, when you have to run A I applications in addition to all the applications you were running before, uh that's a complex design problem.

It's also a problem that arm is very, very good at solving.

And since most of these devices are already arm based and the software runs on arm, it's pretty natural that we're going to be in the center of all of that.

So uh we're pretty excited about the tailwind, not just for phones, but for a IP CS, uh automobiles, consumer devices.

I think all of them are going to see a tailwind in the next number of years.

Renee, it seems as though when you talk about the speed at which things are moving, that the speed has maybe moved a little bit more on the enterprise side, we've seen an enormous amount of demand on the consumer side, perhaps less so.

And so I'm curious to get your take because you're so enmeshed with this, what sort of the killer app on the consumer side could potentially be for A I or the killer use case?

Yeah, I, I don't think we know yet is the honest answer.

If you think about the, the move from three G to four G, you know, a number of years ago, no one could tell you that the killer app was gonna be, uh, I now can order a car on demand.

That'll know where I'm standing or I can now get a rental property at a very, very low discount and I can find them all very quickly.

But that's Airbnb and Uber, you know, those, those apps were unleashed with four G. Now, when we think about A I at the consumer, I think first off, we need to get the hardware capable, which is happening and then the apps will follow.

But uh the history has kind of shown that that's how the model tends to work.

So I don't know that the killer app is out there yet, but I'm also very confident that it will be very soon.

Renee, it is always great to have you on Yahoo Finance.

Thanks so much for joining us.

Thank you.

Analysts underestimated how quickly AI would grow: Arm CEO

Arm Holdings (ARM) was added to the Nasdaq 100 (^NDX) on Monday as shares are up nearly 140% since its public debut in September. Arm Holdings CEO Rene Haas joins Market Domination Overtime to discuss the milestone and the British semiconductor company's outlook. Haas states that AI "is going to...

finance.yahoo.com

 

[Bravo]

I like it. This might be the understatement of the year.

 

[Bravo]

HIGHER PERFORMANCE + IMPROVED POWER EFFICIENCY???...​

​

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​

SiFive announces 4th-gen of popular essential product line to spur innovation across embedded applications​

Press release, DIGITIMES Asia, TaipeiWednesday 26 June 20240

SiFive is seeing growing adoption, with more than two billion SiFive RISC-V-based chips already in the market.

SiFive, Inc. the gold standard for RISC-V computing, unveiled a major upgrade of its SiFive Essential product family at the RISC-V Summit Europe 2024. Developed over a decade, the field-proven Essential IP is already in use in billions of products including mobile phones, sensors, SSDs, FPGA platforms, surveillance cameras, smartwatches, and more.
This full-portfolio refresh brings higher performance, improved power efficiency, and more flexible interfaces, with configuration and integration options to cover virtually any possibility. The SiFive Essential Gen4 products are available on June 25.
"The best RISC-V embedded solutions just got much better with this fourth generation," said John Ronco, SiFive SVP of Product. "With the benefits of cost-effective flexibility, performance, and low power, RISC-V has won the battle for embedded. As legacy ISAs have reduced R&D and support, we are expanding SiFive's broad portfolio of market-leading Essential products and reaffirming our commitment and support for customers in these critical areas of innovation."
SiFive has seen strong momentum across embedded segments where the Essential Gen4 products will bring impressive flexibility and features to enable customers to better tailor their designs. More than two billion SiFive RISC-V-based chips for embedded devices have shipped to date, and the market continues to grow rapidly.
"The embedded space in 2024 represents a huge ($257 billion) market opportunity, growing with an 8.3% CAGR through 2030. RISC-V and SiFive have been increasingly gaining momentum and taking share from the other ISAs. SiFive is launching the products that these customers need while also innovating at the high performance and advanced AI levels," said Rich Wawrzyniak, Principal Analyst at The SHD Group. "It is a mistake to discount the importance of embedded products as the flexibility and software portability of RISC-V makes designing products with multiple cores—including the highest performance cores—easier, creating a clear pathway for RISC-V into the next generations of high-performance chips."

Essential Gen4 IP Portfolio Features:​

The Essential Gen4 IP Portfolio offers the most comprehensive RISC-V CPU and system IP portfolio, featuring up to 40% runtime power reduction. It includes eight different baseline embedded cores, both 32-bit and 64-bit, ranging from 2-stage single-issue to 8-stage superscalar designs.
The portfolio boasts an improved L2 cache, enhanced L1 memory, extensive configuration and integration options, on-chip memory selection, advanced power management, security features, and support for system, peripheral, and front ports. It also includes robust debug and trace capabilities and leading software support, including embedded Linux, FreeRTOS, and Eclipse C/C++ IDE.
Essential Gen4 portfolio:

	2-3 stage single issue (lowest power & area)	8-stage single issue (Performance efficiency)	8-stage dual issue (High performance)
64-bit app processors		U6 Gen 4	U7 Gen 4
64-bit real-time Embedded processors	S2 Gen 4	S6 Gen 4	S7 Gen 4
32-bit real-time Embedded processors	E2 Gen 4	E6 Gen 4	E7 Gen 4

Source: SiFive

SiFive announces 4th-gen of popular essential product line to spur innovation across embedded applications

SiFive is seeing growing adoption, with more than two billion SiFive RISC-V-based chips already in the market.

www.digitimes.com

Last I heard from Rich Wawrzyniak was when he had this to say.

And then you also have what Phil Dworsky had to say.

 

[Food4 thought]

Pilfered the last penny from my last piggy bank today (a hollow feeling..... for the piggy)

And now own 64k more shares.

If there is a better time to buy than now ......well in advance I confess, I will have missed it.

Call me penniless!

For now.

 

[Bravo]

JUNE 25, 2024

SoftBank targets Japan health services with AI JV​

BY KAVIT MAJITHIA


SoftBank Group reportedly plans to roll out an AI-powered medical service analysing healthcare data in Japan through a joint venture with US company Tempus AI, with the aim of launching within one to two years.
Nikkei Asia reported the two companies will each own a 50 per cent share in the JV, initially valued at around JPY30 billion ($188 million), with work on the project to begin next month.
The companies will begin by collecting and analysing patient data, along with using photographs from Japanese hospitals and universities to train AI models, showcasing common patterns among patients.

It will provide services to hospitals with the view of improving healthcare services, initially targeting cancer trends and then expanding to cardiac diseases, Nikkei Asia reported.
After being established in Japan, the JV will expand to overseas markets including south-east Asia.
Tempus AI was founded in 2015 and raised $200 million from SoftBank Group in April. It also counts Google as a backer.
It made its trading debut on the Nasdaq earlier this month, raising $410 million on a valuation of more than $6 billion.
In the US, it operates as a healthcare diagnostics company, using AI to interpret medical tests and help professionals provide more accurate treatment for patients.
SoftBank CEO Masayoshi Son is preparing to hold a press conference this week to announce further details about the project with Tempus AI, added Nikkei Asia.

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