BRN Discussion Ongoing

[Pom down under]

This is the most boring video I have seen for a long time. I almost fell asleep.
I did not even finish it.

I might watch it tonight then just before I go to bed.

 

[Tezza]

Even a little positivity from the fools

Why is the BrainChip share price surging 17% today?

The BrainChip share price has surged today as investors pile into the ASX AI stock. What's behind the jump? Let's see.

www.fool.com.au

Now I am concerned this is another pump n dump.

 

[Tothemoon24]

​

AI-Driven SDV Rapidly Emerging As Next Big Step

The vision laid out by Qualcomm and other tech executives calls for the AI-driven SDV to lead to a critical shift in computing away from the cloud to directly onboard the vehicle as the industry moves to its next stage with what some are calling the Intelligent SDV.

www.wardsauto.com

​

AI-Driven SDV Rapidly Emerging As Next Big Step​

The vision laid out by Qualcomm and other tech executives calls for the AI-driven SDV to lead to a critical shift in computing away from the cloud to directly onboard the vehicle as the industry moves to its next stage with what some are calling the Intelligent SDV.

David Zoia, Senior Contributing Editor
November 8, 2024
7 Min Read

Qualcomm’s Snapdragon-enabled vehicle already looking beyond SDV.

MAUI, HI – It’s time to turn the page on the software-defined vehicle – rapidly becoming basic table stakes in next-gen vehicle development – toward a new chapter: the AI-defined vehicle.
That’s probably the biggest takeaway at Qualcomm’s recent Snapdragon Symposium here, where the San Diego-based chipmaker and technology company unleashed its new Snapdragon Elite line of digital cockpit and automated-driving processors powerful enough to take advantage of what fast-developing artificial-intelligence technology can bring to the automobile.


Of course, it’s hard to say how quickly the industry will move toward SDVs now that many automakers are pulling back on planned battery-electric vehicles based on new platforms that were expected to lead the transition.

However, at least some suppliers say the shift will continue with or without a broad migration to BEVs, and for its part, Qualcomm predicts the movement remains on pace to creating a market worth nearly $650 billion annually by 2030. The forecast includes hardware and software demands from automakers rising to $248 billion per year from $87 billion today and a doubling in demand from suppliers to $411 billion.

The vision laid out by Qualcomm and executives of other tech developers and enablers on hand here calls for the AI-driven SDV to lead a critical migration in computing away from the cloud to directly onboard the vehicle as the industry moves to its next stage toward what some are calling the Intelligent SDV.

“The shift of AI processing toward the edge is happening,” declares Durga Malladi, senior vice president and general manager of tech planning for edge solutions at Qualcomm. “It is inevitable.”

From Cloud To Car

Two things are making possible this movement away from the cloud and toward so-called edge processing that takes place within the vehicle itself: the rapid and seismic leaps in AI coding and data efficiency and capability, and the increasingly powerful and energy-efficient computers needed to process the information.

Answering the call for greater computing capability is Qualcomm’s new Elite line of Snapdragon Cockpit and Snapdragon Drive platforms, set to launch on production vehicles in 2026, including upcoming models featuring Mercedes-Benz’s next-gen MB-OS centralized electronics architecture and operating system and vehicles from China’s Li Auto.

Current-generation Snapdragon chips also will underpin new Level 3 ADAS technology and central-compute architecture Qualcomm is developing with BMW that will be deployed in BMW’s Neue Klasse BEVs expected to roll out in 2026. That ADAS technology will be offered to other OEMs through Qualcomm as well.

These new top-of-the-line Elite processors are many times more powerful than current-generation Snapdragon platforms, already with a strong foothold in automotive. Qualcomm says that as of second-quarter 2024, it had a new business pipeline for current products totaling more than $45 billion.

Moving computing away from interactions with the cloud and onboard the vehicle as the AI-driven architecture takes hold will result in several advantages, experts here say, including development of safe and reliable self-driving technology.

For automated driving, “you need more serious edge intelligence to map the environment in real time, predict the trajectory of every vehicle on the road and decide what action to take,” notes Nakul Duggal, group manager, automotive, industrial and cloud for Qualcomm Technologies.

And for cockpit operation, relying less on the cloud and more on the vehicle’s computers provides faster response and greater security and privacy. It also ratchets up the ability of the vehicle’s AI-based systems to adapt to the occupant’s preferences.

Qualcomm Snapdragon Elite Brings New Capabilities

In promoting the new Elite line of Snapdragon systems-on-a-chip for automotive, Qualcomm presents a future in which the onboard AI assistant better recognizes natural-speech commands, anticipates needs of the occupants, is capable of providing predictive maintenance alerts and does things like buy tickets to events and make reservations. The vehicle will be able to drop occupants off at their destination and then locate and drive to an open parking spot – and pay if necessary – all on its own. Not sure what that road sign indicated that you just passed? The AI assistant will be able to fill you in. If the scene ahead would make a good picture, the virtual assistant can use the vehicle’s onboard cameras to take a digital photo.

The AI assistant also will have contextual awareness, meaning it might decide it’s better not to play sensitive messages if other occupants are in the vehicle.

“Automakers are looking for new ways to personalize the driving experience, improve automated driving features and deliver predictive maintenance notifications,” says Robert Boetticher, automotive and manufacturing global technology leader for Amazon Web Services. “Our customers want to use AI at the edge now, to enhance these experiences with custom solutions built on top of powerful models.”

Beyond virtual assistants, these new onboard computers will be there to support high-resolution 3D mapping, multiple infotainment screens, personalized audio zones that don’t interfere with what other passengers are listening to and sophisticated cabin-monitoring technology. They will be capable of fusing data from both the ADAS and infotainment systems to provide vehicle occupants with more granular information and intuitive driving assistance that acts more like a human would – guiding the vehicle around a known pothole on your daily commute, for instance.
And the human-machine interface promises to evolve as a result. With AI, the world is edging away from a tactile experience – such as pushing buttons on a screen to access data – to one where infotainment is voice-, video- and sensor- (lidar, radar, camera) driven, Malladi says.

“The bottom line is, the AI agent becomes the one starting point that puts it all together for you,” he says.

AI Landscape Evolving, Rapidly

AI interest was somewhat dormant in automotive until two years ago, when the release of ChatGPT caused a stir in the tech world.

“For a lot of us in the (chip) industry, we were working on AI for a long time,” Malladi says. “But for the rest of the world, it was an eye-opener. Everyone was talking about it.”

Within a year, he says, large-language-model technology took giant leaps in simplicity. While the model used to create ChatGPT was about 175 billion parameters (a measure of its complexity), that has shrunk considerably, Malladi says.

Large-language-model technology “went from 175 billion parameters to 8 billion in two years, and the quality has only increased,” he says. That translates into less required storage capacity, faster compute times, greater accuracy and fewer chances to introduce bugs into the code.

A new AI law is emerging as a result, Malladi adds, in that “the quality of AI per parameter is constantly increasing. It means that the same experience you could get from a (large, cloud-based) data center yesterday you (now) can bring into devices that you and I have.”

Making it all possible inside the vehicle are the new-generation chips now emerging that easily can handle the AI workload.

“We can run with the next generation up to 20 billion parameter models at the edge,” Duggal says, adding that compares to about 7 billion with the current-generation processors. “Everything is in your environment (and processed) locally. This is the big advancement that has happened with the latest AI.”

The chips also are becoming more power efficient, as well, a key factor in the evolution toward BEVs, where automakers are looking to squeeze out as much driving range as possible from their lithium-ion batteries.

The new Snapdragon platform is said to be 20 times more efficient than what is required to generate AI from a data center today.

“The power draw of the devices we now use – that have the power of a mini-supercomputer of 25 years ago – is down to less than an LED lightbulb,” Malladi says.

Moving from the cloud to the edge onboard the vehicle also will save money – it’s closer to zero cost when accessing the data onboard the vehicle, and unlike operation of huge cloud servers, there’s no impact on the electrical grid, making it more environmentally favorable, Malladi points out.

Minimal reliance on vehicle-to-cloud computing also reduces the risk a cloud server won’t be available at a critical juncture, says Andrew Ng, founder and CEO of AI visual solutions provider Landing AI. “AI brings low latency, real-time processing, reduced bandwidth requirements and potentially advanced privacy and security,” he says.

It will take time for AI-based SDVs to begin penetrating the market in big numbers, and automakers will have to carefully determine what features customers will want and avoid packing vehicles with capabilities they won’t appreciate. But the general direction seems clear.

“Bringing AI in is no small task,” Duggal admits, but he says it offers limitless potential and notes nearly every major automaker has shown an interest in the new Snapdragon Elite platform that can help unleash the technology.

Sums up Qualcomm’s Anshuman Saxena, product management lead and business manager for automotive software and systems: “AI is definitely becoming a focal point for the whole industry – and for us too.”

 

[Bravo]

Neuromorphic Computing Market worth $1,325.2 Million by 2030, at a CAGR of 89.7%​

08-11-2024 07:48 PM CET

Press release from: ABNewswire​

Neuromorphic Computing Market

The global Neuromorphic Computing Market in terms of revenue is estimated to be worth $28.5 million in 2024 and is poised to reach $1,325.2 million by 2030, growing at a CAGR of 89.7% during the forecast period.
According to a research report "Neuromorphic Computing Market [https://www.marketsandmarkets.com/M...idPR&utm_campaign=neuromorphiccomputingmarket] by Offering (Processor, Sensor, Memory, Software), Deployment (Edge, Cloud), Application (Image & Video Processing, Natural Language Processing (NLP), Sensor Fusion, Reinforcement Learning) - Global Forecast to 2030" The neuromorphic computing industry is expected to grow from USD 28.5 million in 2024 and is estimated to reach USD 1,325.2 million by 2030; it is expected to grow at a Compound Annual Growth Rate (CAGR) of 89.7% from 2024 to 2030.

Growth in the neuromorphic computing industry is driven through the integration of neuromorphic computing in automotive and space operations. In space, where bandwidth is limited and the communication delay might be considered large, onboard processing capabilities are crucial. The neuromorphic processor analyzes and filters data at the point of collection, reducing the need to transmit large datasets back to Earth. whereas, in automobile sector, neuromorphic processors can make autonomous driving systems more responsive by onboard real-time processing with minimal latency so that safety is ensured along with efficiency.

Download PDF Brochure @ [https://www.marketsandmarkets.com/r...idPR&utm_campaign=neuromorphiccomputingmarket]

Browse 167 market data Tables and 69 Figures spread through 255 Pages and in-depth TOC on "Neuromorphic Computing Market"

View detailed Table of Content here -https://www.marketsandmarkets.com/Market-Reports/neuromorphic-chip-market-227703024.html [https://www.marketsandmarkets.com/M...idPR&utm_campaign=neuromorphiccomputingmarket]

[https://www.marketsandmarkets.com/M...idPR&utm_campaign=neuromorphiccomputingmarket]

By Offering, software segment is projected to grow at a high CAGR of neuromorphic computing industry during the forecast period.

The software segment is expected to grow at a fast rate in the forecasted period. Neuromorphic software has its roots in models of neural systems. Such systems entail spiking neural networks (SNNs), that attempt to replicate the properties of biological neurons in terms of their firing patterns. In contrast to the typical artificial neural networks using continuous activation functions, SNNs utilize discrete spikes for communication, a feature that is also found in the brain. With intelligence embedded directly into the edge devices and IoT sensors, the potential for neuromorphic systems to perform even the most complex tasks such as pattern recognition and adaptive learning with considerably less power consumption remains. This efficiency stretches the lifetime of device operations while cutting down on the overall energy footprint, thus spurring demand for neuromorphic software that can harness these benefits and optimize performance for real-world edge and IoT applications.

By deployment, cloud segment will account for the highest CAGR during the forecast period.

Cloud segment will account for the high CAGR in the forecasted period. Cloud computing benefits from offering central processing power, which enables large-scale computational resources and storage capacities accessible from remote data centers. This is useful because neuromorphic computing, has been very often associated with complex algorithms and large-scale data processing. In the cloud, such huge resources can be utilized to train neuromorphic models, run large-scale simulations, and process enormous datasets. The scalable infrastructure of cloud platforms allows neuromorphic computing applications to dynamically adjust resources according to demand. It is a key factor for the training and deployment of high-scale neuromorphic networks, as their computation requirements are considerable especially during peak loads, driving its demand in the market.

Natural language processing (NLP) segment is projected to grow at a high CAGR of neuromorphic computing industry during the forecast period.

Natural Language Processing (NLP) is a branch of artificial intelligence focused on giving computers the ability to understand text and spoken words in much the same way human beings can. NLP represents a promising application of neuromorphic computing, leveraging the brain- inspired design of spiking neural networks (SNNs) to enhance the efficiency and accuracy of language data processing. Low-power, high-performance solutions are required by the expanding demand for real-time efficient language processing in devices-from smartphones to IoT devices. Neuromorphic computing fits well within these requirements with its energy-efficient architecture. Progress over time with improvements in SNNs is also advancing its ability to approach complex NLP tasks, which are closer to being adapted for commercial and industrial markets . SNNs provide improved energy efficiency, demonstrated through being able to achieve up to 32x better energy efficiency during inference and 60x during training compared with traditional deep neural networks, further underlines the benefits of adding neuromorphic computing to NLP systems. Besides cost-efficiency in the field of NLP systems, such efficiency enables deploying complex language models even on devices with reduced resources. This leads to making neuromorphic NLP applications even more relevant to wider adoption and growth.

Industrial vertical in neuromorphic computing industry will account for the high CAGR by 2030.

Industrial segment will account for the high CAGR in the forecasted period. In the industrial vertical, manufacturing companies use neuromorphic computing for developing and testing end products, manufacturing delicate electronic components, printing products, metal product finishing, testing of machines, and security purpose. Neuromorphic computing can be used in these processes to store the data in chips, and the images can be extracted from the devices for further use. Neuromorphic computing also helps monitor the condition of the machines by analyzing the previous signals and comparing them with current signals. These advantages lead to high demand for neuromorphic processors and software in industrial vertical.

Asia Pacific will account for the highest CAGR during the forecast period.

The neuromorphic computing industry in Asia Pacific is expected to grow at the highest CAGR due to a high adoption rate of new technologies in this region. High economic growth, witnessed by the major countries such as China and India, is also expected to drive the growth of the neuromorphic computing industry in APAC.

BrainChip, Inc. (Australia)

, SynSense (China), MediaTek Inc. (Taiwan), SAMSUNG (South Korea), Sony Corporation (Japan), are some of the key players providing neuromorphic hardware and software in the region. In China, Japan, South Korea, and Singapore, for instance, significant investments have been made in neuromorphic research and infrastructure. This has fostered close relationships between academia, industry, and government, facilitating major breakthroughs in machine learning, natural language processing, and robotics that have propelled the development of neuromorphic technologies.

Key Players

Key companies operating in the neuromorphic computing industry are Intel Corporation (US), IBM (US), Qualcomm Technologies, Inc. (US), Samsung Electronics Co., Ltd. (South Korea), Sony Corporation (Japan), BrainChip, Inc. (Australia), SynSense (China), MediaTek Inc. (Taiwan), NXP Semiconductors (Netherlands), Advanced Micro Devices, Inc. (US), Hewlett Packard Enterprise Development LP (US), OMNIVISION (US), among others.

Neuromorphic Computing Market worth $1,325.2 Million by 2030, at a CAGR of 89.7%

The global Neuromorphic Computing Market in terms of revenue is estimated to be worth 28 5 million in 2024 and is poised to reach 1 325 2 million by 2030 growing at a CAGR of 89 7 during the forecast ...

www.openpr.com

 

[Bravo]

Well, it's 9:57am in Taipei and the tinyML Foundation is underway.

Our very own KEN WU (Senior Design Engineer) at Brainchip will be manning the demo counter, this event being held today
at the Grand Hilai Taipei is yet another great event to demonstrate our Akida Pico, TENN's and I personally think having Ken
on the desk is a huge plus, he has worked in very close with Anil, has hands on experience and will be able to communicate
with many of the local Taiwanese engineers in their local tongue, that is, getting the message across about any detailed questions
that may be posed.

I just wonder if Sean his handed him the company's big fancy pen, just incase someone walks up to the counter and wishes to
sign on the dotted line...dreams are free.

Keep an eye out for any news grabs on this event.

Cheers....Tech.

Hi Tech,

I only just realised this morning that the TinyML Foundation is rebranding itself to the EDGE AI FOUNDATION!!! The new foundation’s mission is to ensure advancements in edge AI benefit society and the environment.

Check out the video below!! No one can deny that the edge is really starting to gain momentum!!

I think it's interesting that the video has been narrated by a woman with an Australian accent, despite the foundation being based in the US. I wonder if we can read anything into that?

This is the video link from the article above.



Here's a pic showing Ken Wu at the TinyML Foundation's (aka EDGE AI FOUNDATION) recent event.

 

[TECH]

Hi Tech,

I only just realised this morning that the TinyML Foundation is rebranding itself to the EDGE AI FOUNDATION!!! The new foundation’s mission is to ensure advancements in edge AI benefit society and the environment.

Check out the video below!! No one can deny that the edge is really starting to gain momentum!!

I think it's interesting that the video has been narrated by a woman with an Australian accent, despite the foundation being based in the US. I wonder if we can read anything into that?


View attachment 72634


This is the video link from the article above.



Here's a pic showing Ken Wu at the TinyML Foundation's (aka EDGE AI FOUNDATION) recent event.

View attachment 72636

Hi Bravo,
Yes, I noticed that the other day when I posted that short video.

The momentum continues to gather pace, and you, like me, can clearly see how Peters early break through with SNN architecture was and still is well ahead of the mob.

Sometimes when I read edge ai articles or view videos I'm thinking to myself, I could have told you that back in 2018/2019.

I will never ever forget the night back in 2019 when at Peters lecture he stated that Akida didn't need the internet to function as all processing & intelligence was done on-chip, that really blew me away.

My prediction 2 years ago about reviewing my holding and satisfaction surrounding Brainchips overall performance is appearing at first glance to be right on..but lets see.

Love our company...

Kind regards (Chris) Tech.

 

[miaeffect]

Conference Program

The CES® 2025 conference program will highlight advancements in digital health, AI, sustainability, gaming, vehicle tech, cybersecurity, beauty and fashion tech, space tech, and more. Register today for CES 2025.

www.ces.tech

Did somebody say Brainchip?!
Smells strong!

 

[Tothemoon24]

Revolutionizing Vision: Neuromorphic Imaging Transforms Speed, Efficiency, and Precision​

Event-based imaging detects changes in light brightness with ultra-fast, independent pixels in microseconds.​

Shawn Wright
09 2024 | 15:39 Clock
0

Reading Time: 3 minutes
Imagine a super-fast camera that continuously captures images from pixels and detects only changes in light brightness. Each pixel works independently and constantly, with microsecond detection. This is the basis for event-based or neuromorphic imaging.
A 2022 McKinsey report identified neuromorphic computing as one of the top ten technology trends with the potential to reshape several markets and industries in the coming decades.

Rapidly capturing change​

In event-based imaging, each pixel on the sensor has a set threshold, and when that threshold is exceeded, the pixel activates, capturing only what has changed from the previous threshold. This approach transmits only relevant data, rather than an entire image, creating an “extreme region of interest” that reduces computing time and processing resources.
Since only the pixels detecting movement are activated, the resulting image has minimal latency due to the small amount of data being updated. Additionally, less power is required to capture the smaller image.

Dynamic range redefined​

Another advantage of neuromorphic pixels is their capability to capture more than 120 dB of dynamic range.
Sensors based on these pixels, like a human retina, can locally adapt to vast changes in brightness, detect edges, signal temporal changes, and sense motion. Their photoreceptors continuously monitor intensity and adjust to the local image over time and space, maximizing dynamic range.
Caltech, MIT, and John Hopkins have been researching this topic since the 1990s. This work, spurred by Northrup Grumman, Rockwell International, and DARPA, evolved under the leadership of researcher Christof Koch.
Christof Koch was a leading professor of computation and neural systems at Caltech, and he was recognized for his work on neuromorphic systems. He later became president of the Allen Institute for Brain Science.

Diverse applications of neuromorphic imaging​

Applications run the gamut:

• Autos: ADAS and cabin monitoring
• Medical: Fluidics and cell tracking
• Sports: Player tracking, swing analysis
• Defense: Rocket, bullet, and bomb analysis
• Industrial: High-speed counting and vibration analysis

Combining event-based and color sensors​

New camera systems can integrate event-based sensors with traditional color sensors to produce images that are both more accurate and visually appealing. By combining these technologies, the resulting images can be fast and precise.
Industrial applications are plentiful due to their speed and low data requirements.
Currently, Sony has partnered with Prophesse, a French company that has commercialized neuromorphic sensors for integration with existing camera modules. According to Prophesse, its sensors produce up to 1000 times less data than a conventional sensor while achieving a higher equivalent temporal resolution of more than 10,000 frames per second.
Based in Zurich, iniVation is a Swiss company also pioneering the field with its Aeveon sensors, which feature 346 x 260 pixels.

 

[Tothemoon24]

Perhaps theses 2 maybe getting together to mix some of the special sauce

SEMIFIVE Joins Forces with Japan’s Semiconductor Industry through MOU with MegaChips​

November 5, 2024 -- SEMIFIVE, a leading design solution provider and pioneer of platform-based custom silicon solutions, announced its agreement of MOU with Japan-based MegaChips on October 10, 2024. SEMIFIVE and MegaChips will collaborate on comprehensive semiconductor design, seeking potential customers in Japan, and offering onsite technical support.
“MegaChips has consistently demonstrated remarkable innovation and technical excellence in the semiconductor field,” said Brandon Cho, CEO and co-founder of SEMIFIVE. “We are thrilled to partner with such a forward-thinking company, and we are confident that SEMIFIVE’s platform can complement their strengths, contributing meaningfully to the cutting-edge advancements that lie ahead. We look forward to collaborating closely as we push the boundaries of technology together.”
MegaChips was founded in 1990 as Japan’s pioneering fabless manufacturer of system LSI semiconductors. The company provides strategic solutions with its ASIC full turn-key services, Application-Specific Standard Product (ASSP), and module. While satisfying customer needs with unique core technology, MegaChips also provides safe and reliable products with high quality through its advanced development capability and technology.
SEMIFIVE, a company specializing in SoC platform and ASIC design solutions, has been expanding its roadmap in response to the increasing demand for AI custom silicon. The company has committed its expertise, knowledge, and resources to the development of advanced SoC design platforms specifically for AI chips. To date, SEMIFIVE has developed three SoC design platforms and has successfully completed more than seven large-scale AI semiconductor projects utilizing these platforms. SEMIFIVE has been consistently expanding its global business with the establishment of a San Jose, USA office in March 2021 and a Shanghai, China office in August 2023.
“MegaChips has consistently demonstrated remarkable innovation and technical excellence in the semiconductor field,” said Brandon Cho, CEO and co-founder of SEMIFIVE. “We are thrilled to partner with such a forward-thinking company, and we are confident that SEMIFIVE’s platform can complement their strengths, contributing meaningfully to the cutting-edge advancements that lie ahead. We look forward to collaborating closely as we push the boundaries of technology together.”
About SEMIFIVE
SEMIFIVE is the pioneer of platform-based SoC design, working with customers to implement innovative ideas into custom silicon in the most efficient way. Our SoC platforms offer a powerful springboard for new chip designs, and leverage configurable domain-specific architectures and pre-validated key IP pools. We offer comprehensive spec-to-system capabilities with end-to-end solutions so that custom SoCs can be realized faster, with reduced cost and risks for key applications such as data center or AI-enabled IoT. With a strong partnership with Samsung Foundry as a leading SAFETM DSP partner, as well as the larger ecosystem, SEMIFIVE provides a one-stop shop solution for any SoC design needs.

 

[TheDrooben]

Now I am concerned this is another pump n dump.

The sustained buying after another predominantly agreed pretty shite quarterly has Larry thinking this is more than just a pump and dump........Larry thinks there is something coming in the next week or two which will take us past the 50c mark.......in Larry's opinion

HAPPY AS LARRY

 

[miaeffect]

Did Chris Jones quit?

Job ad

 

[Diogenese]

Did Chris Jones quit?
View attachment 72644
Job ad
View attachment 72645

When was he demoted?

https://embeddedvisionsummit.com/2024/2024/speaker/chris-jones/?q=/2024/speaker/chris-jones/&
Chris Jones, Director of Product Management at BrainChip

 

[Braintonic]

The sustained buying after another predominantly agreed pretty shite quarterly has Larry thinking this is more than just a pump and dump........Larry thinks there is something coming in the next week or two which will take us past the 50c mark.......in Larry's opinion


View attachment 72639

HAPPY AS LARRY

I'd agree with you Droob.
I am normally not afraid to sell all my shares as I think the share price will tank after a quarterly with f all in it. I watch the volume traded regularly as well as the buyers verses selling ratio trying to predict when to buy back in or sell.
Risky, amateurish? Yes but I've done alright out of it in the past.
Over the last few months and especially this quarterly its been different.
Happy with Sean's interview with SDU and his mention of some news before the end of year (could be just another granted patent?) but still well aware there is a long way to go

 

[CHIPS]

When was he demoted?

https://embeddedvisionsummit.com/2024/2024/speaker/chris-jones/?q=/2024/speaker/chris-jones/&
Chris Jones, Director of Product Management at BrainChip

He moved up the ladder.
Director is one step above Senior Manager, right!?

 

[Braintonic]

I'd agree with you Droob.
I am normally not afraid to sell all my shares as I think the share price will tank after a quarterly with f all in it. I watch the volume traded regularly as well as the buyers verses selling ratio trying to predict when to buy back in or sell.
Risky, amateurish? Yes but I've done alright out of it in the past.
Over the last few months and especially this quarterly its been different.
Happy with Sean's interview with SDU and his mention of some news before the end of year (could be just another granted patent?) but still well aware there is a long way to go

Fwiw which isn't much I am in at the moment and buying more but that could all change by next week.

 

[Pom down under]

The sustained buying after another predominantly agreed pretty shite quarterly has Larry thinking this is more than just a pump and dump........Larry thinks there is something coming in the next week or two which will take us past the 50c mark.......in Larry's opinion


View attachment 72639

HAPPY AS LARRY

 

[Pom down under]

 

[MrNick]

View attachment 72647

Indeed. Anzio Beach Head 1944.

 

[Baron Von Ricta]

Neuromorphic Computing Market worth $1,325.2 Million by 2030, at a CAGR of 89.7%​

08-11-2024 07:48 PM CET

Press release from: ABNewswire​

Neuromorphic Computing Market

The global Neuromorphic Computing Market in terms of revenue is estimated to be worth $28.5 million in 2024 and is poised to reach $1,325.2 million by 2030, growing at a CAGR of 89.7% during the forecast period.
According to a research report "Neuromorphic Computing Market [https://www.marketsandmarkets.com/M...idPR&utm_campaign=neuromorphiccomputingmarket] by Offering (Processor, Sensor, Memory, Software), Deployment (Edge, Cloud), Application (Image & Video Processing, Natural Language Processing (NLP), Sensor Fusion, Reinforcement Learning) - Global Forecast to 2030" The neuromorphic computing industry is expected to grow from USD 28.5 million in 2024 and is estimated to reach USD 1,325.2 million by 2030; it is expected to grow at a Compound Annual Growth Rate (CAGR) of 89.7% from 2024 to 2030.

Growth in the neuromorphic computing industry is driven through the integration of neuromorphic computing in automotive and space operations. In space, where bandwidth is limited and the communication delay might be considered large, onboard processing capabilities are crucial. The neuromorphic processor analyzes and filters data at the point of collection, reducing the need to transmit large datasets back to Earth. whereas, in automobile sector, neuromorphic processors can make autonomous driving systems more responsive by onboard real-time processing with minimal latency so that safety is ensured along with efficiency.

Download PDF Brochure @ [https://www.marketsandmarkets.com/r...idPR&utm_campaign=neuromorphiccomputingmarket]

Browse 167 market data Tables and 69 Figures spread through 255 Pages and in-depth TOC on "Neuromorphic Computing Market"

View detailed Table of Content here -https://www.marketsandmarkets.com/Market-Reports/neuromorphic-chip-market-227703024.html [https://www.marketsandmarkets.com/M...idPR&utm_campaign=neuromorphiccomputingmarket]

[https://www.marketsandmarkets.com/M...idPR&utm_campaign=neuromorphiccomputingmarket]

By Offering, software segment is projected to grow at a high CAGR of neuromorphic computing industry during the forecast period.

The software segment is expected to grow at a fast rate in the forecasted period. Neuromorphic software has its roots in models of neural systems. Such systems entail spiking neural networks (SNNs), that attempt to replicate the properties of biological neurons in terms of their firing patterns. In contrast to the typical artificial neural networks using continuous activation functions, SNNs utilize discrete spikes for communication, a feature that is also found in the brain. With intelligence embedded directly into the edge devices and IoT sensors, the potential for neuromorphic systems to perform even the most complex tasks such as pattern recognition and adaptive learning with considerably less power consumption remains. This efficiency stretches the lifetime of device operations while cutting down on the overall energy footprint, thus spurring demand for neuromorphic software that can harness these benefits and optimize performance for real-world edge and IoT applications.

By deployment, cloud segment will account for the highest CAGR during the forecast period.

Cloud segment will account for the high CAGR in the forecasted period. Cloud computing benefits from offering central processing power, which enables large-scale computational resources and storage capacities accessible from remote data centers. This is useful because neuromorphic computing, has been very often associated with complex algorithms and large-scale data processing. In the cloud, such huge resources can be utilized to train neuromorphic models, run large-scale simulations, and process enormous datasets. The scalable infrastructure of cloud platforms allows neuromorphic computing applications to dynamically adjust resources according to demand. It is a key factor for the training and deployment of high-scale neuromorphic networks, as their computation requirements are considerable especially during peak loads, driving its demand in the market.

Natural language processing (NLP) segment is projected to grow at a high CAGR of neuromorphic computing industry during the forecast period.

Natural Language Processing (NLP) is a branch of artificial intelligence focused on giving computers the ability to understand text and spoken words in much the same way human beings can. NLP represents a promising application of neuromorphic computing, leveraging the brain- inspired design of spiking neural networks (SNNs) to enhance the efficiency and accuracy of language data processing. Low-power, high-performance solutions are required by the expanding demand for real-time efficient language processing in devices-from smartphones to IoT devices. Neuromorphic computing fits well within these requirements with its energy-efficient architecture. Progress over time with improvements in SNNs is also advancing its ability to approach complex NLP tasks, which are closer to being adapted for commercial and industrial markets . SNNs provide improved energy efficiency, demonstrated through being able to achieve up to 32x better energy efficiency during inference and 60x during training compared with traditional deep neural networks, further underlines the benefits of adding neuromorphic computing to NLP systems. Besides cost-efficiency in the field of NLP systems, such efficiency enables deploying complex language models even on devices with reduced resources. This leads to making neuromorphic NLP applications even more relevant to wider adoption and growth.

Industrial vertical in neuromorphic computing industry will account for the high CAGR by 2030.

Industrial segment will account for the high CAGR in the forecasted period. In the industrial vertical, manufacturing companies use neuromorphic computing for developing and testing end products, manufacturing delicate electronic components, printing products, metal product finishing, testing of machines, and security purpose. Neuromorphic computing can be used in these processes to store the data in chips, and the images can be extracted from the devices for further use. Neuromorphic computing also helps monitor the condition of the machines by analyzing the previous signals and comparing them with current signals. These advantages lead to high demand for neuromorphic processors and software in industrial vertical.

Asia Pacific will account for the highest CAGR during the forecast period.

The neuromorphic computing industry in Asia Pacific is expected to grow at the highest CAGR due to a high adoption rate of new technologies in this region. High economic growth, witnessed by the major countries such as China and India, is also expected to drive the growth of the neuromorphic computing industry in APAC. View attachment 72632 BrainChip, Inc. (Australia) View attachment 72633 , SynSense (China), MediaTek Inc. (Taiwan), SAMSUNG (South Korea), Sony Corporation (Japan), are some of the key players providing neuromorphic hardware and software in the region. In China, Japan, South Korea, and Singapore, for instance, significant investments have been made in neuromorphic research and infrastructure. This has fostered close relationships between academia, industry, and government, facilitating major breakthroughs in machine learning, natural language processing, and robotics that have propelled the development of neuromorphic technologies.

Key Players

Key companies operating in the neuromorphic computing industry are Intel Corporation (US), IBM (US), Qualcomm Technologies, Inc. (US), Samsung Electronics Co., Ltd. (South Korea), Sony Corporation (Japan), BrainChip, Inc. (Australia), SynSense (China), MediaTek Inc. (Taiwan), NXP Semiconductors (Netherlands), Advanced Micro Devices, Inc. (US), Hewlett Packard Enterprise Development LP (US), OMNIVISION (US), among others.

Neuromorphic Computing Market worth $1,325.2 Million by 2030, at a CAGR of 89.7%

The global Neuromorphic Computing Market in terms of revenue is estimated to be worth 28 5 million in 2024 and is poised to reach 1 325 2 million by 2030 growing at a CAGR of 89 7 during the forecast ...

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Bugger just getting 1% share of this. I want 2

 

[MrNick]

Must've been good head if you still remember it from 1944...

…..Major Fred Jackson. 1912-1944.