BRN Discussion Ongoing

[Steve10]

“It’s impossible to list all the applications for which Akida could be used.”

Sound familiar?

View attachment 31753

That's who I was trying to remember when I mentioned limitless applications. Tensor.

 

[skutza]

I don't know about you guys, but the media/articles/talk of the town on this new Akida 2.0 is really making me feel like a genius for having the foresight in loading up early. All I can see is ......... in my head and dreams!

 

[Quatrojos]

Research article based on neuromorphic hardware in Robotic arms. Liked by our CEO SH. https://iopscience.iop.org/article/10.1088/2634-4386/acc204

Two of the authors are from Accenture Labs.

Lazar Supic 2 and Andreea Danielescu 3

 

[Tothemoon24]

Rings a bell , seems like some big power savings with this up coming product




REVIEWED

Here’s how to pre-order Ring’s newest video doorbell​

Rachel Murphy
Reviewed

A new Ring doorbell is coming, and you can pre-order it starting today, March 8, for $179.99. The latest model, the Ring Battery Doorbell Plus, is one of Ring’s most impressive battery-operated video doorbells yet, with better battery life, 1536p resolution (the highest of any Ring battery doorbell yet), and a 1:1 aspect ratio offering a full head-to-toe view of who is your front door. It will ship starting on Wednesday, April 5.

Pre-order the Ring Battery Doorbell Plus on Amazon
Ring says the new Battery Doorbell Plus conserves the battery life when not in use. Energy-saving features like People Only Mode, Motion Zones, and Advanced Motion Detection are available on this doorbell and work to only tap into the battery power when events are detected.

Make smart choices without hours of googling.Subscribe to The Checklist newsletter for expert product advice and recommendations.
The new Ring doorbell claims to have three times the battery life of the first Ring Video Doorbell, however the battery life largely depends on usage (i.e. the number of events the camera captures).

It’s worth noting that the Battery Doorbell Plus supports hardwiring to any existing doorbell wires you may have, offering a trickle-like effect to keep the battery going.
Additionally, the new Ring doorbell comes with a removable and rechargeable battery that is accessible by triggering the quick-release button on the camera’s exterior.

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Some video doorbells need to come down to recharge, so the removable battery is a plus, allowing you to give the appearance your video doorbell is still recording even if the battery is indoors on the charger.
If you don’t have existing doorbell wiring in place, one option is to purchase an additional removable battery to swap in when the internal battery dies.

The Ring Battery Plus works with Alexa, and she can announce when someone is at the door via an Echo speaker or show you a live view of who is there via an Echo Show smart display. The Battery Doorbell Plus supports package detection and alerts, as well as pre-recorded quick reply messages if you can't get to the door.

We’ve tested other Ring video doorbells that run on battery power, like the feature-filled Ring Video Doorbell 4 and the $100 Ring Video Doorbell (second-gen), both of which performed well and we recommend.
We’ll be checking out the Ring Battery Plus Video Doorbell to see how it stacks up against the rest of our top-rated video doorbells.
Pre-order

 

[Steve10]

If BRN IP cost was $5-10 per chip & TAM was worth $1B or so it would be difficult to grow significantly & fast.

But at 20-30c per chip IP cost with 1.15T chips shipped every year this is a 100% no brainer to become big & fast.

Takes a few years for new products to be developed/launched then it will become a money printing machine collecting royalties for many years.

 

[Fact Finder]

View attachment 31750
I really hope my buy order for my 6 shares goes through. But on the other hand I hope my sell order for 76 shares goes through also.
WTF. Nothing like having an early day smile.... hang on I think I might pull it!

Think of how many Retail Food Group shares you could buy for $3.00 and all they need is for the outstanding investigation of the previous management to say it was all their fault and it will fly. Don’t put all your eggs in one basket is my advice.

 

[Cardpro]

As some seem intent on finding comparisons to rate Brainchip's performance against on the ASX when there are absolutely none I will remind readers both here and in the background of what Steven Leibson of Tirias Research said in his Forbes Magazine article dated 6 March, 2023:

"Brainchip’s bio-inspired Akida platform is certainly an unusual way to tackle AI/ML applications. While most other NPU vendors are figuring out how many MACs they can fit – and power – on the head of a pin, Brainchip is taking an alternative approach that’s been proven by Mother Nature to work over many tens of millions of years.

In Tirias Research’s opinion, it’s not the path taken to the result that’s important, it’s the result that counts. If Brainchip’s Akida event-based platform succeeds, it won’t be the first time that a radical new silicon technology has swept the field. Consider DRAMs (dynamic random access memories), microprocessors, microcontrollers, and FPGAs (field programmable gate arrays), for example. When those devices first appeared, there were many who expressed doubts. No longer. It’s possible that Brainchip has developed yet another breakthrough that could rank with those previous innovations. Time will tell."

Edge Impulse described AKIDA technology as science fiction. A data scientist and Phd candidate described the first generation AKIDA 1000 as a "beast".

Against this background the WANCA's have continued to ask what's a neuromorphic chip anyway, well at least those who can say 'neuromorphic'.

"It’s possible that Brainchip has developed yet another breakthrough that could rank with those previous innovations." Mark these words as they are only directed at AKIDA 2000 not the overall mission which Brainchip has embarked upon of creating Artificial General Intelligence.

Brainchip, Peter van der Made and Anil Mankar are creating an entirely new computing paradigm well beyond anything that exists.

They are on track with the timetable set out by Peter van der Made and with each step are opening up engineering possibilities that have only existed in unfulfilled patents and dreams.

The first and second generation AKIDA technology will create industries that do not yet exist.

Peter van der Made has stated recently that his vision of Artificial General Intelligence will be fulfilled in about 7 years which puts it at 2030.

The enormity of what Artificial General Intelligence means is found in the quote of Bill Gates that the person who invents Artificial General Intelligence will have created a company worth ten times Microsoft. I am not saying that his valuation was or is correct what I am pointing you too is the significance he attaches to what Brainchip and Peter van der Made are pursuing.

The late Stephen Hawking and the still living Elon Musk have both stated that Artificial General Intelligence could lead to the destruction of mankind. There are of course many others who are saying and who have said the same thing.

Now in the overly optimistic hope that the above will be sufficient to shut down the mindless comparisons can anyone here point to a technology company on the ASX that could just by its mere existence lead to the destruction of mankind in seven years time.

Of course not this is why Brainchip is not understood by normal retail investors.

Why it is not understood by WANCA commentators who cannot even say neuromorphic.

Why it is extremely obvious that anyone who persists down this road of comparison either is ignorant of just what Brainchip is doing or has some other motive innocent or otherwise.

My opinion only DYOR
FF

AKIDA BALLISTA

We will be ARM / SiFive equivalent for NPU / Edge AI!!!

 

[Dozzaman1977]

I dont think I've seen anything written about VDC research on this forum after one of their directors gave this glowing statement in the recent Akida Gen 2 press release


BrainChip has some exciting upcoming news and developments underway,” said Daniel Mandell, Director at VDC Research. “Their 2nd generation Akida platform provides direct support for the intelligence chip market, which is exploding. IoT market opportunities are driving rapid change in our global technology ecosystem, and BrainChip will help us get there.”
Daniel Mandell, Director, VDC Research




VDC Research is a B2B technology market intelligence and consulting firm, delivering in-depth insights and strategies to vendors, technology decision makers, and investors across the globe since 1971 (for over 50 years)

They Dramatically improve the performance of business through a range of services that identify transformative opportunities, solve persistent challenges, and enable you to execute at unprecedented scale and speed.

​

VDC is proud to be a trusted advisor to many of the world’s leading technology companies.
Including

Heward Packard
Qualcomm
Honeywell
Brother
Motorola
Dell
Blackberry
Arm
Samsung
Oracle
Zebra

​

Their continuous coverage of major technology markets offers clients expert insights and extensive data, enabling breakthrough strategies and superior business performance.

As Daniel Mandall stated quote.........
“Their 2nd generation Akida platform provides direct support for the intelligence chip market, which is exploding. IoT market opportunities are driving rapid change in our global technology ecosystem, and BrainChip will help us get there.”

 

[Fact Finder]

I think someone published something about Brainchip AKIDA and SiFive X280 Intelligence Series being closely entwined:​

​

“2023 a Breakout Year for RISC-V​

Article By : SiFive​

• Category : FPGAs/PLDs
• 2023-03-06
• (0) Comments

No longer just a tool for embedded, RISC-V has arrived, driven by innovation and adoption in the world's largest semiconductor manufacturers, global hyperscale data centers, and consumer device companies.
At SiFive, where we sit at the forefront of RISC-V, we see several interesting trends continuing to drive strong growth across the industry. Artificial intelligence (AI) and machine learning are becoming virtually ubiquitous, from the datacenter to consumer devices and the enterprise, requiring new architectures, data offload and management and low latency, all while carefully managing power consumption with the massive workloads.

In automotive, the fast growth of autonomous and electric vehicles (EVs) and the proliferation in chips in the vehicle from sensors, to safety, to drivetrain and entertainment, is also calling for new designs, flexibility and a support ecosystem that will be around for decades. In mobile and wearables, the capabilities of the devices is surpassing the quality of traditional cameras for instance with AI growing. And here, like elsewhere, footprint, power consumption, and performance have never been more critical.

All of these trends favor RISC-V with it’s superior compute density, flexibility, and high performance and growing ecosystem. RISC-V is now inevitable and, over the next few years, and you will see exciting advances as it moves from a mostly embedded application to critical functions in the highest performance chips, and the start-ups move to established companies with performance that in some cases already exceeds them. We believe the landscape will look very different over the next decade as RISC-V continues to grow. Already taught in the leading universities around the world, it is also being encouraged by governments in the United States, China, India, and Japan, among others, eager to help their domestic industries but also clearly seeing the benefits of the open architecture for the future of their products.

While there is considerable uncertainty in the macroeconomic environment, the chip shortages of 2021–2022 showed how the semiconductor industry is a part of every industry on the planet and companies from auto manufacturers to consumer companies to governments are investing to ensure their supply chains are able to withstand future impacts. Government investments like the Chips Act in the United States will serve to increase manufacturing capabilities and with more manufacturing and prototype capabilities, new innovations will flourish.

Take the AI Dataflow processor, for example, a RISC-V enabled chip that is being used in hyperscale datacenters to offload and manage critical AI data. This rearchitecting of the datacenter allows dramatically lowers latency and power consumption.

2023’s mantra might also be “power matters”. Across the board, we believe the industry is going to be talking a lot more about compute density, and the need for high performance processors that can also be built on a very small footprint and run at low power.

And this will be a breakout year for RISC-V. Companies are leveraging the RISC-V architecture and its proven high-performance and low-power usage across consumer devices like wearables, automotive, aerospace, and beyond. Last year, we saw announcements about the High Performance Space Compute project adopting RISC-V, and there is much more ahead. No longer just a tool for embedded, RISC-V has arrived driven by innovation and adoption in the world’s largest semiconductor manufacturers, global hyperscale data centers, and consumer device companies.”

It must be getting close to the point where I can say something positive without being called a fanboy or upramper.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Fact Finder]

I dont think I've seen anything written about VDC research on this forum after one of their directors gave this glowing statement in the recent Akida Gen 2 press release


BrainChip has some exciting upcoming news and developments underway,” said Daniel Mandell, Director at VDC Research. “Their 2nd generation Akida platform provides direct support for the intelligence chip market, which is exploding. IoT market opportunities are driving rapid change in our global technology ecosystem, and BrainChip will help us get there.”
Daniel Mandell, Director, VDC Research




VDC Research is a B2B technology market intelligence and consulting firm, delivering in-depth insights and strategies to vendors, technology decision makers, and investors across the globe since 1971 (for over 50 years)

They Dramatically improve the performance of business through a range of services that identify transformative opportunities, solve persistent challenges, and enable you to execute at unprecedented scale and speed.

​

VDC is proud to be a trusted advisor to many of the world’s leading technology companies.
Including

Heward Packard
Qualcomm
Honeywell
Brother
Motorola
Dell
Blackberry
Arm
Samsung
Oracle
Zebra

​

Their continuous coverage of major technology markets offers clients expert insights and extensive data, enabling breakthrough strategies and superior business performance.

As David Mandall stated quote.........
“Their 2nd generation Akida platform provides direct support for the intelligence chip market, which is exploding. IoT market opportunities are driving rapid change in our global technology ecosystem, and BrainChip will help us get there.”

It sounds good but has he heard of Retail Food Group and Dominoes then there are all those mining companies with brand new shovels and tin sheds.

He is probably too busy consulting with those listed corporations to do any real research.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Foxdog]

BrainChip on LinkedIn: Mind-Boggling Neuromorphic Brain Chips (Part 2)

Mind-Boggling Neuromorphic Brain Chips (Part 2) https://lnkd.in/dbppZ2KZ - On once benchmark, the Akida achieved 30% better precision while using 50X fewer…

www.linkedin.com

View attachment 31748

For me the most exciting clue of future success is the new confidence being displayed in our company announcements after the release of Gen 2. They're using a different language and aren't pulling any punches when it comes to describing how good the updated tech is. AKIDA Gen 2 seems to have exceeded even their expectations. It also speaks to us having received confirmed feedback from customers. I reckon we'll see some licence deals signed pretty soon and revenue from all sources begin to make waves by second half of 23. My opinion only but things seem to be gaining momentum here.

 

[Dozzaman1977]

It sounds good but has he heard of Retail Food Group and Dominoes then there are all those mining companies with brand new shovels and tin sheds.

He is probably too busy consulting with those listed corporations to do any real research.

My opinion only DYOR
FF

AKIDA BALLISTA

It would of been nice to buy into the dominos IPO in 2005 at $2.20.
I was thinking about investing in the IPO, but i decided to go and buy a Dominos Pizza and garlic bread to see what quality they were,
I could only eat 1 slice of the pizza (it Tasted terrible) and only 1 piece of garlic bread as it also tasted bad and threw the rest in the bin .... So based on that experience i though who the hell would buy these pizzas over good quality made ones and decided not to invest.
History shows i was completely wrong, people love cheap terrible tasting pizzas.

That $10,000 investment would be worth $210,000 at todays share price (and a lot higher in the past years)

I'm happy to stick to my local pub pizza!!!!

 

[Diogenese]

$0.525 - the better the news, the lower the price.

I'll wait till we start earning real revenue and get some really cheap.

 

[BonezDiez]

What a wonderful read, although my comprehension of all the new capabilities is somewhat lacking.
However, I think most of us understand real world comparisons and benchmarking.
Hence, I think this extract from the article is particularly powerful:
......

And so we come to the old proverb that states, “The proof of the pudding is in the eating.” Just how well does the Akida perform with industry-standard, real-world benchmarks?

Well, the lads and lasses at Prophesee.ai are working on some of the world’s most advanced neuromorphic vision systems. From their website we read: “Inspired by human vision, Prophesee’s technology uses a patented sensor design and AI algorithms that mimic the eye and brain to reveal what was invisible until now using standard frame-based technology.”

According to the paper Learning to Detect Objects with a 1 Megapixel Event Camera, Gray.Retinanet is the latest state-of-the-art in event-camera based object detection. When working with the Prophesee Event Camera Road Scene Object Detection Dataset at a resolution of 1280×720, the Akida achieved 30% better precision while using 50X fewer parameters (0.576M compared to 32.8M with Gray.Retinanet) and 30X fewer operations (94B MACs/sec versus 2432B MACs/sec with Gray.Retinanet). The result was improved performance (including better learning and object detection) with a substantially smaller model (requiring less memory and less load on the system) and much greater efficiency (a lot less time and energy to compute).

As another example, if we move to a frame-based camera with a resolution of 1352×512 using the KITTI 2D Dataset, then ResNet-50 is kind of a standard benchmark today. In this case, Akida returns equivalent precision using 50X fewer parameters (0.57M vs. 26M) and 5X fewer operations (18B MACs/sec vs. 82B MACs/sec) while providing much greater efficiency (75mW at 30 frames per second in a 16nm device). This is the sort of efficiency and performance that could be supported by untethered or battery-operated cameras.

Another very interesting application area involves networks that are targeted at 1D data. One example would be processing raw audio data without the need for all the traditional signal conditioning and hardware filtering.

Consider today’s generic solution as depicted on the left-hand side of the image below. This solution is based on the combination of Mel-frequency cepstral coefficients (MFCCs) and a depth-wise separable CNN (DSCNN). In addition to hardware filtering, transforms, and encoding, this memory-intensive solution involves a heavy software load.

Raw audio processing: Traditional solution (left) vs. Akida solution (right)
(Source: BrainChip)

By comparison, as we see on the right-hand side of the image, the raw audio signal can be fed directly into an Akida TENN with no additional filtering or DSP hardware. The result is to increase the accuracy from 92% to 97%, lower the memory (26kB vs. 93kB), and use 16X fewer operations (19M MACs/sec vs. 320M MACs/sec). All of this basically returns single inference while consuming two microjoules of energy. Looking at this another way, assuming 15 inferences per second, we’re talking less than 100µW for always-on keyword detection.

Similar 1D data is found in the medical arena for tasks like vital signs prediction based on a patient’s heart rate or respiratory rate. Preprocessing techniques don’t work well with this kind of data, which means we must work with raw signals. Akida’s TENNs do really well with raw data of this type.

In this case, comparisons are made between Akida and the state-of-the-art S4 (SOTA) algorithm (where S4 stands for structured state space sequence model) with respect to vital signs prediction based on heart rate or respiratory rate using the Beth Israel Deaconess Medical Center Dataset. In the case of respiration, Akida achieves ~SOTA accuracy with 2.5X fewer parameters (128k vs. 300k) and 80X fewer operations (0.142B MACs/sec vs. 11.2B MACs/sec). Meanwhile, in the case of heart rate, Akida achieves ~SOTA accuracy with 5X fewer parameters (63k vs. 600k) and 500X fewer operations (0.02B MACs/sec vs. 11.2B MACs/sec).

It’s impossible to list all the applications for which Akida could be used. In the case of industrial, obvious apps are robotics, predictive maintenance, and manufacturing management. When it comes to automotive, there’s real-time sensing and the in-cabin experience. In the case of health and wellness, we have vital signs monitoring and prediction; also, sensory augmentation. There are also smart home and smart city applications like security, surveillance, personalization, and proactive maintenance. And all of these are just scratching the surface of what is possible.

Any idea where the author gets those akida benchmarks from? No mention of akida in the referenced prophese paper…

 

[jk6199]

Have you seen the amount of volume sells / buys this morning.

Latest news with more to come? I wonder if any rats are jumping ship?

 

[Xray1]

$0.525 - the better the news, the lower the price.

I'll wait till we start earning real revenue and get some really cheap.

We have only some 3 weeks to go till the end of this quaterly period.... So I hope we see another financial improvement to the bottom line therein.
I am also expecting some further positive ASX announcements to be released between now and just before the AGM in May 2023 so that management and the CEO SH will have something to boast about and provide s/holders with positive endorsements on their investment in BRN

 

[Techinvestor17]

Have you seen the amount of volume sells / buys this morning.

Latest news with more to come? I wonder if any rats are jumping ship?

What do you mean by that?

 

[Fact Finder]

It would of been nice to buy into the dominos IPO in 2005 at $2.20.
I was thinking about investing in the IPO, but i decided to go and buy a Dominos Pizza and garlic bread to see what quality they were,
I could only eat 1 slice of the pizza (it Tasted terrible) and only 1 piece of garlic bread as it also tasted bad and threw the rest in the bin .... So based on that experience i though who the hell would buy these pizzas over good quality made ones and decided not to invest.
History shows i was completely wrong, people love cheap terrible tasting pizzas.

That $10,000 investment would be worth $210,000 at todays share price (and a lot higher in the past years)

I'm happy to stick to my local pub pizza!!!!

People who got in and got out of Retail Food Group made money as well but many franchises were sent to the wall and ended up bankrupt as a result of various business practices that the Group engaged in. Dominoes also made shareholders money but had they been requiring the payment of the correct wages to employees the pizzas would have had to sell for more and decent pizzas would likely have been competitive.

When you look in-depth at their business models someone had to be ripped off for it to return profits.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Steve10]

Number 1 emerging technology is neuromorphic computing. The BRN shorters are playing with a volcano about to erupt.

What’s on the 2023 Gartner Emerging Technologies and Trends Impact Radar?​

These trends surfaced in our 2023 Gartner Emerging Technologies and Trends Impact Radar, which highlights 26 emerging trends and technologies to which vendors must respond, whether they are a new or established player in that space.

The Impact Radar portrays the maturity, market momentum and influence of technologies, making it a handy tool for product leaders to identify and track the technologies and trends that will help them improve and differentiate their products, remain competitive and capitalize on market opportunities.

Four Emerging Technologies Disrupting the Next Three to Eight Years​

Most of this year's emerging technologies and trends are three to eight years away from reaching widespread adoption but represent significant innovation in the years ahead.
Let’s look at four we think will prove especially interesting.

No. 1: Neuromorphic computing​

• A critical enabler, neuromorphic computing provides a mechanism to more accurately model the operation of a biological brain using digital or analog processing techniques.
• It will take three to six years to cross over from early-adopter status to early majority adoption.
• Neuromorphic computing will have a substantial impact on existing products and markets.

Neuromorphic computing systems simplify product development, enabling product leaders to develop AI systems that can better respond to the unpredictability of the real world. Their autonomous capabilities quickly react to real-time events and information, and will form the basis of a wide range of future AI-based products. Early use cases include event detection, pattern recognition and small dataset training.

We expect breakthrough neuromorphic devices by the end of 2023, but it will likely take five years for these devices to reach early majority adoption.

The impact is likely to be significant, though, as neuromorphic computing is expected to disrupt many of the current AI technology developments, delivering power savings and performance benefits not achievable with current generations of AI chips.

No. 2: Self-supervised learning​

• Self-supervised learning accelerates productivity by using an automated approach to annotating and labeling data.
• It will take six to eight years to cross over from early-adopter status to early majority adoption.
• Self-supervised learning will have a significant impact on existing products and markets.

Self-supervised models learn how information relates to other information; for example, which situations typically precede or follow another, and which words often go together.

Self-supervised learning has only recently emerged from academia and is currently practiced by a limited number of AI companies. A few companies focused on computer vision and NLP products have recently added self-supervised learning to their product roadmaps, however.

The potential impact and benefits of self-supervised learning are extensive, as it will extend the applicability of machine learning to organizations with limited access to large datasets. Its relevance is most prominent in AI applications that typically rely on labeled data, primarily computer vision and NLP.

No. 3: Metaverse​

• The metaverse fuels the smart world by providing an immersive digital environment.
• It will take eight-plus years to cross over from early-adopter status to early majority adoption.
• The metaverse will have a very substantial impact on existing products and markets.

The metaverse enables persistent, decentralized, collaborative, interoperable digital content that intersects with the physical world’s real-time, spatially organized and indexed content.

It is an example of a combinatorial trend in which a number of individually important, discrete and independently evolving trends and technologies interact with one another to give rise to another trend. The emerging, supporting technologies and trends include (but are not limited to) spatial computing and the spatial web; digital persistence; multientity environments; decentralization tech; high-speed, low-latency networking; sensing technologies; and AI applications.

The features and functionality these ETT bring to the metaverse will need to reach an early majority in order for the metaverse to cross the chasm. We consider all current examples to be precursors or premetaverse offerings because they are potentially capable and compatible but do not yet meet the definition of the metaverse.

While the benefits and opportunities from the metaverse are not immediately viable, emerging metaverse solutions give an indicator of potential use cases. We expect the transition toward the metaverse to be as significant as the one from analog to digital.
Watch webinar: 2023 Leadership Vision for Product Management Leaders

No. 4: Human-centered AI​

• Human-centered AI (HCAI) is a common AI design principle calling for AI to benefit people and society, which could improve transparency and privacy.
• It will take three to six years to reach early majority adoption.
• HCAI will have a substantial impact on existing products and markets.

HCAI assumes a partnership model of people and AI working together to enhance cognitive performance, including learning, decision making and new experiences. HCAI is sometimes referred to as “augmented intelligence,” “centaur intelligence” or “human in the loop,” but in a wider sense, even a fully automated system must have human benefits as a goal.

HCAI enables vendors to manage AI risks, and to be ethical, responsible and more efficient with automation, while complementing AI with a human touch and with common sense. Many AI vendors have already shifted their positions to the more impactful and responsible HCAI approach. The technology-centric approach of developing AI products has led to numerous negative impacts, urging vendors to rethink their AI product strategies.

The potential impact of HCAI is high because it leverages human abilities to make humans more productive and remove avoidable limitations, biases and blind spots.

In short:

• The Gartner Emerging Tech Impact Radar highlights the technologies and trends that have the most potential to disrupt a broad cross section of markets.
• The trends are organized around four key themes, which are critical for product leaders to evaluate as part of their competitive strategy.
• Product leaders must explore these technologies now to capitalize on market opportunities.

Tuong Nguyen is a Director Analyst within the Emerging Technologies and Trends team in Gartner Research. He undertakes analysis on immersive technologies, metaverse, computer vision, SLAM and human-machine interfaces. He advises tech provider product leaders how to factor emerging tech and trends into creating and evolving highly successful product offerings.

4 Emerging Technologies You Need to Know About

Just In: The 2023 Gartner Emerging Technologies and Trends Impact Radar 🎯 According to Gartner experts, these 4️⃣ key themes will prove critical for product leaders to evaluate as part of their competitive strategy: ➡ Smart world ➡ Productivity revolution ➡ Transparency and privacy ➡ New...

www.gartner.com

 

[Fact Finder]

I think someone published something about Brainchip AKIDA and SiFive X280 Intelligence Series being closely entwined:​

​

“2023 a Breakout Year for RISC-V​

Article By : SiFive​

• Category : FPGAs/PLDs
• 
  
• 2023-03-06
• (0) Comments
• 
  

No longer just a tool for embedded, RISC-V has arrived, driven by innovation and adoption in the world's largest semiconductor manufacturers, global hyperscale data centers, and consumer device companies.
At SiFive, where we sit at the forefront of RISC-V, we see several interesting trends continuing to drive strong growth across the industry. Artificial intelligence (AI) and machine learning are becoming virtually ubiquitous, from the datacenter to consumer devices and the enterprise, requiring new architectures, data offload and management and low latency, all while carefully managing power consumption with the massive workloads.

In automotive, the fast growth of autonomous and electric vehicles (EVs) and the proliferation in chips in the vehicle from sensors, to safety, to drivetrain and entertainment, is also calling for new designs, flexibility and a support ecosystem that will be around for decades. In mobile and wearables, the capabilities of the devices is surpassing the quality of traditional cameras for instance with AI growing. And here, like elsewhere, footprint, power consumption, and performance have never been more critical.

All of these trends favor RISC-V with it’s superior compute density, flexibility, and high performance and growing ecosystem. RISC-V is now inevitable and, over the next few years, and you will see exciting advances as it moves from a mostly embedded application to critical functions in the highest performance chips, and the start-ups move to established companies with performance that in some cases already exceeds them. We believe the landscape will look very different over the next decade as RISC-V continues to grow. Already taught in the leading universities around the world, it is also being encouraged by governments in the United States, China, India, and Japan, among others, eager to help their domestic industries but also clearly seeing the benefits of the open architecture for the future of their products.

While there is considerable uncertainty in the macroeconomic environment, the chip shortages of 2021–2022 showed how the semiconductor industry is a part of every industry on the planet and companies from auto manufacturers to consumer companies to governments are investing to ensure their supply chains are able to withstand future impacts. Government investments like the Chips Act in the United States will serve to increase manufacturing capabilities and with more manufacturing and prototype capabilities, new innovations will flourish.

Take the AI Dataflow processor, for example, a RISC-V enabled chip that is being used in hyperscale datacenters to offload and manage critical AI data. This rearchitecting of the datacenter allows dramatically lowers latency and power consumption.

2023’s mantra might also be “power matters”. Across the board, we believe the industry is going to be talking a lot more about compute density, and the need for high performance processors that can also be built on a very small footprint and run at low power.

And this will be a breakout year for RISC-V. Companies are leveraging the RISC-V architecture and its proven high-performance and low-power usage across consumer devices like wearables, automotive, aerospace, and beyond. Last year, we saw announcements about the High Performance Space Compute project adopting RISC-V, and there is much more ahead. No longer just a tool for embedded, RISC-V has arrived driven by innovation and adoption in the world’s largest semiconductor manufacturers, global hyperscale data centers, and consumer device companies.”

It must be getting close to the point where I can say something positive without being called a fanboy or upramper.

My opinion only DYOR
FF

AKIDA BALLISTA

Not significant it was only SiFive talking about AKIDA 2 so they are biased and likely just trying to sell the X280 with AKIDA to their customers. Apologies nothing to see here you can move on now:

“Through our collaboration with BrainChip, we are enabling the combination of SiFive’s RISC-V processor IP portfolio and BrainChip’s 2nd generation Akida neuromorophic IP to provide a power-efficient, high capability solution for AI processing on the Edge,” said Phil Dworsky, Global Head of Strategic Alliances at SiFive. “Deeply embedded applications can benefit from the combination of compact SiFive Essential™ processors with BrainChip’s Akida-E, efficient processors; more complex applications including object detection, robotics, and more can take advantage of SiFive X280 Intelligence™ AI Dataflow Processors tightly integrated with BrainChip’s Akida-S or Akida-P neural processors.”

Phil Dworsky, Global Head of Strategic Alliances, SiFive

My opinion only DYOR
FF

AKIDA BALLISTA