BRN Discussion Ongoing

[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

 

[Fact Finder]

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.

View attachment 31756

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.

Great article but am I missing something because it seems obvious that AKIDA technology covers all three categories.

This would be explosive if true. Don’t pull that $3.00 order I might have been off the mark there.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Bravo]

Have I got this right?

 

[Steve10]

Great article but am I missing something because it seems obvious that AKIDA technology covers all three categories.

This would be explosive if true. Don’t pull that $3.00 order I might have been off the mark there.

My opinion only DYOR
FF

AKIDA BALLISTA

5 years for early majority adoption of BRN tech = 2028. Starting 2023.

Is it too early to forecast dividends?

Going rate for tech companies is about 1-2%.

With $500M revenue x 60% NPAT = $300M x 50% payout ratio = $150M / 1.8B SOI = 8.33c per share implies $4.165 to $8.33 SP at 1-2% dividend. yield. $7.5B MC @ PE25 or $15B MC @ PE50 with the latter more likely at PE50. So 1% dividend & $8.33 SP more likely. Timeframe will be within 5 years.

 

[Diogenese]

Have I got this right?


View attachment 31758

You missed Model Compression.

 

[Steve10]

$53.2B AUD edge AI hardware processor market by 2030.

Every 1% market share = $532M x 60% NPAT = $319.2M x 50% payout ratio = $159.6M / 1.8B SOI = 8.87c per share dividend & $8.87 SP at PE50.

BRN should have at least 1% market share by 2028.

 

[Bravo]

Elon Musk is literally reaching out for our help! Can someone please let Rob know so he can get on the blower to him ASAP?


Remember I posted something a little while ago about ChatGPT and how it costs millions of dollars a day to run and how neuromorphic computing could one day be the solution to driving down this staggering expense. Now, if Elon wants to compete with OpenAI's ChatGPT, what better way than to have a mind boggling, science fiction neuromophic based solution to massively reduce power consumption, whilst saving billions of dollars over time, whilst also being generally betterer in every single way?

How To Build An Effective Market-Oriented Team

By utilizing experts from different backgrounds, creating a culture of collaboration and establishing clear objectives, organizations can ensure that they can build effective teams that can achieve success in the global marketplace. Here's why

www.forbes.com

 

[Cardpro]

You missed Model Compression.

Also decentralised Identity

 

[Slade]

In the world of tech, a powerhouse team,
Brainchip and partners, a force to be seen,
Renesas, Arm, Intel, SiFive, Prophesee, Megachips, Nviso, alive.
With Edge Impulse and NASA in tow,
Their progress, nothing can overthrow,
A partnership that leaves shorters behind,
And Elon Musk's plans, unrefined.

Brainchip's shareholders will reap the rewards,
As their profits soar with mighty roars,
Their visions of wealth finally fulfilled,
Their pockets with gains, marvelously filled.

In the world of AI, they're breaking new ground,
And Brainchip's partners are tightly bound,
Their collaboration, a force to reckon,
Their shares, a prize to beckon.

And when the dust finally clears, Brainchip and partners will be the pioneers,
The shorters and Elon Musk, to their dismay,
Their losses mounting with every passing day.

For Brainchip's triumph is here to stay,
Their partnership leading the way, To a future where AI reigns supreme,
And Brainchip shareholders live the dream.

 

[Bravo]

You missed Model Compression.

Thanks @Diogenese. I'll edit and update.

 

[Fastback6666]

Well someone just bought up 598,675 shares at .53 in one order on market - line wiped it out. As soon as the price went to .52 Basically what was for sale at .525 and .53 and some of .535 was bought out within a minute.

The instos are sucking up the cheap shares...stay strong team!

I bought some more today at .525 - giveaway price.

 

[Bravo]

Digital technology: The backbone of a net-zero emissions future

Organizations need to focus on accelerated digitalization to help decarbonization and emissions reduction, and to drive innovation.

www.technologyreview.com

 

[SharesForBrekky]

Part 2 is out and it’s a ripper of a read.

Mind-Boggling Neuromorphic Brain Chips (Part 2)

In my previous column, we discussed how the year 2030 seems set to be an exciting time to be in artificial intelligence (AI) and machine learning (ML) space (where no one can hear you scream). For …

www.eejournal.com

"The first big point to note about this new incarnation is that it can run humongous models like ResNet-50 completely on the neural processor, thereby freeing up the host processor."

Love how the author describes how big the models you can run. Humongous, not sure if you can get any bigger than that can you, haha.

 

[IloveLamp]

Challenges and Emerging Applications for Deep Learning/AI

Developers are working to overcome challenges—such as cost and availability of training data—to implement deep learning in machine vision applications.

www.vision-systems.com

 

[Bravo]

Hack raises security questions over Google smart speakers

It’s always there. Always listening. Having a device like Google Home inside our house is pretty standard these days. From setting alarms to playing our

radiotoday.com.au

 

[Murphy]

Haha, I thought it was the longest acronym ever.

I thought it was a high-tech version of DILLIGAF!

If you don't have dreams, you can't have dreams come true!

 

[IloveLamp]

https://www.vision-systems.com/boards-software/article/14289604/ch

2023 a Breakout Year for RISC-V - EE Times Asia

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.

www.eetasia.com

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.[/url]

 

[Frank Zappa]

In the world of tech, a powerhouse team,
Brainchip and partners, a force to be seen,
Renesas, Arm, Intel, SiFive, Prophesee, Megachips, Nviso, alive.
With Edge Impulse and NASA in tow,
Their progress, nothing can overthrow,
A partnership that leaves shorters behind,
And Elon Musk's plans, unrefined.

Brainchip's shareholders will reap the rewards,
As their profits soar with mighty roars,
Their visions of wealth finally fulfilled,
Their pockets with gains, marvelously filled.

In the world of AI, they're breaking new ground,
And Brainchip's partners are tightly bound,
Their collaboration, a force to reckon,
Their shares, a prize to beckon.

And when the dust finally clears, Brainchip and partners will be the pioneers,
The shorters and Elon Musk, to their dismay,
Their losses mounting with every passing day.

For Brainchip's triumph is here to stay,
Their partnership leading the way, To a future where AI reigns supreme,
And Brainchip shareholders live the dream.

WOW . Top running for Post of the Month .

 

[Learning]

Another Engineer Require.

Check out this job at BrainChip : https://www.linkedin.com/jobs/view/3520402181
Learning 🏖