BRN Discussion Ongoing

[Rach2512]

https://www.linkedin.com/feed/update/ugcPost:7339238582076760064?trk=feed_main-feed-card_social-actions-comments

Could someone with more tech knowledge than me reply to Sanjeev the Principal Engineer @ SpaceX, put Brainchip under his nose. The below is in the comments section of the above post from 7hrs ago, I think I read that right.

 

[FJ-215]

Interesting interview with Geoffrey Hinton. Sadly, if he is right, humanity is on its way to being toast.

 

[itsol4605]

Todd Vierra at the EDGE AI FOUNDATION event in Austin

#edgeai #edgeaifoundation #ondeviceai #tinyml #llmontheedge #embeddedai #aihardware #lowpowerai #5vtech #brainchip #edgecomputing #aiip | 5V Tech

At the EDGE AI FOUNDATION event in Austin, we caught up with Todd Vierra, Head of Customer Engagement at BrainChip, an AI IP company building low-power, high-performance solutions for edge deployment. Todd shared how BrainChip is helping shift the AI conversation away from data centers and...

www.linkedin.com

 

[itsol4605]

Can the next generation of AI run at 20 watts?​

Scientists are targeting neuromorphic computing​

Faced with the AI energy crisis, scientists are looking for breakthroughs in neuromorphic computing technology, aiming to make AI run as efficiently as the human brain. Researchers simulated the structure of the human brain and built a supercomputer that consumes only 10 kilowatts of power, occupies two square meters, but is 250,000 to 1 million times faster than a biological brain. Neuromorphic computing can achieve efficient and energy-saving operation by simulating the structure of the brain's neural network, using event-driven communication and memory computing.

The latest progress is led by the US National Laboratory. Scientists are trying to bring science fiction into reality: building a supercomputer with a space of only two square meters and the number of neurons comparable to the human cerebral cortex.

Even more amazing is that calculations show that this neuromorphic computer could run 250,000 to 1 million times faster than a biological brain , while consuming only 10 kilowatts of power (only slightly more than the energy consumption of a household air conditioner), which is undoubtedly a shot in the arm for the current dilemma of AI development.

Artificial intelligence is currently facing an "energy crisis". With the explosive development of technologies such as large language models, its astonishing power consumption has become a heavy burden that cannot be ignored.

Projections suggest that by 2027, the electricity bill alone to run these models could be as much as $25 trillion—more than the U.S. GDP that year.

In comparison, the most powerful intelligent being in nature, the human brain, consumes only about 20 watts per day , which is equivalent to the power of a household LED light bulb.
Scientists can't help but wonder:
Can AI be as efficient as the human brain ?

20瓦就能运行下一代AI？科学家瞄上了神经形态计算

面对AI能源危机，科学家瞄准神经形态计算技术寻求突破，旨在让AI像人脑一样高效运行。研究人员模拟人脑结构，构建仅需10千瓦功耗、占地两平方米但速度比生物大脑快25-100万倍的超级计算机。神经形态计算通过模拟大脑神经网络结构，采用事件驱动型通信和内存计算，能实现高效节能运行。

wallstreetcn.com

 

[itsol4605]

Can the next generation of AI run at 20 watts?​

Scientists are targeting neuromorphic computing​

Faced with the AI energy crisis, scientists are looking for breakthroughs in neuromorphic computing technology, aiming to make AI run as efficiently as the human brain. Researchers simulated the structure of the human brain and built a supercomputer that consumes only 10 kilowatts of power, occupies two square meters, but is 250,000 to 1 million times faster than a biological brain. Neuromorphic computing can achieve efficient and energy-saving operation by simulating the structure of the brain's neural network, using event-driven communication and memory computing.

The latest progress is led by the US National Laboratory. Scientists are trying to bring science fiction into reality: building a supercomputer with a space of only two square meters and the number of neurons comparable to the human cerebral cortex.

Even more amazing is that calculations show that this neuromorphic computer could run 250,000 to 1 million times faster than a biological brain , while consuming only 10 kilowatts of power (only slightly more than the energy consumption of a household air conditioner), which is undoubtedly a shot in the arm for the current dilemma of AI development.

Artificial intelligence is currently facing an "energy crisis". With the explosive development of technologies such as large language models, its astonishing power consumption has become a heavy burden that cannot be ignored.

Projections suggest that by 2027, the electricity bill alone to run these models could be as much as $25 trillion—more than the U.S. GDP that year.

In comparison, the most powerful intelligent being in nature, the human brain, consumes only about 20 watts per day , which is equivalent to the power of a household LED light bulb.
Scientists can't help but wonder:
Can AI be as efficient as the human brain ?

20瓦就能运行下一代AI？科学家瞄上了神经形态计算

面对AI能源危机，科学家瞄准神经形态计算技术寻求突破，旨在让AI像人脑一样高效运行。研究人员模拟人脑结构，构建仅需10千瓦功耗、占地两平方米但速度比生物大脑快25-100万倍的超级计算机。神经形态计算通过模拟大脑神经网络结构，采用事件驱动型通信和内存计算，能实现高效节能运行。

wallstreetcn.com

• 
  
• 
  
• 
  

Can the next generation of AI run at 20 watts? Scientists are targeting neuromorphic computing​

Quantum bits
08:06
Faced with the AI energy crisis, scientists are looking for breakthroughs in neuromorphic computing technology, aiming to make AI run as efficiently as the human brain. Researchers simulated the structure of the human brain and built a supercomputer that consumes only 10 kilowatts of power, occupies two square meters, but is 250,000 to 1 million times faster than a biological brain. Neuromorphic computing can achieve efficient and energy-saving operation by simulating the structure of the brain's neural network, using event-driven communication and memory computing.
"Westworld" is really coming! Scientists are trying to equip AI with human brains.

The latest progress is led by the US National Laboratory. Scientists are trying to bring science fiction into reality: building a supercomputer with a space of only two square meters and the number of neurons comparable to the human cerebral cortex.

Even more amazing is that calculations show that this neuromorphic computer could run 250,000 to 1 million times faster than a biological brain , while consuming only 10 kilowatts of power (only slightly more than the energy consumption of a household air conditioner), which is undoubtedly a shot in the arm for the current dilemma of AI development.

Artificial intelligence is currently facing an "energy crisis". With the explosive development of technologies such as large language models, its astonishing power consumption has become a heavy burden that cannot be ignored.

Projections suggest that by 2027, the electricity bill alone to run these models could be as much as $25 trillion—more than the U.S. GDP that year.

In comparison, the most powerful intelligent being in nature, the human brain, consumes only about 20 watts per day , which is equivalent to the power of a household LED light bulb. Scientists can't help but wonder: Can AI be as efficient as the human brain ?

The answer: neuromorphic computing .

This cutting-edge technology, which aims to simulate the structure and operation of the human brain, is being seen as a key direction for the next generation of AI. One of its core goals is to drive powerful intelligence with "light bulb-level" energy consumption.

Neuromorphic computing: learning from the brain​

In the human brain, there are about 86 billion complex neurons working together and building a huge signal transmission network through 100 trillion synapses.

Inspired by their structure and functionality, neuromorphic computing is built using energy-efficient electronic and photonic networks that mimic biological neural networks, namely spiking neural networks (SNNs), and aims to integrate memory, processing, and learning into a unified design.

Its main features include:

Event-driven communication:
Only necessary circuits are activated during peak and event-driven conditions, thus reducing power consumption.
In-memory computing:
Data processing occurs at the storage location to reduce transmission delays.
Adaptability:
The system learns and evolves on its own over time without the need for centralized updates.
Scalability:
The architecture of neuromorphic systems allows for easy scalability to accommodate more extensive and complex networks without significantly increasing resource requirements.

Unlike current AI models that rely on binary supercomputer processing, it can dynamically adjust based on its understanding of the world, making it smarter, more flexible, and less susceptible to interference.

For example, when a tester wearing a T-shirt with a stop sign walked in front of an autonomous car, the car controlled by traditional AI stopped because it was unable to discern the context.

In contrast, a neuromorphic computer processes information through feedback loops and context-driven checks, which can clearly determine that the stop sign is on the T-shirt and allow the car to continue driving.

This difference is not surprising. After all, neuromorphic computing simulates the most efficient and powerful reasoning and prediction engine in nature. Scientists therefore believe that the next wave of artificial intelligence technology explosion must be a combination of physics and neuroscience.

Prospects for a new round of technological revolution​

At present, relevant research is in full swing. Existing neuromorphic computers have more than 1 billion neurons connected by more than 100 billion synapses. Although it is only a drop in the bucket compared to the complexity of the human brain, it also reasonably proves that this technology can achieve brain-level expansion.

Jeff Shainline of the National Institute of Standards and Technology said:

Once we can implement the complete process of creating a network in a commercial foundry, we can quickly scale up to very large systems, and if we can make one neuron, it will be fairly easy to make a million neurons.

Technology companies such as IBM and Intel are at the forefront of this technological revolution. The TrueNorth chip developed by IBM in 2014 and the Loihi chip launched by Intel in 2018 are both hardware products designed to simulate the neural activity of the brain, paving the way for subsequent new AI models.

In addition, some startups focusing on neuromorphic computing are also beginning to emerge. For example, BrainChip has launched the Akida neuromorphic processor , which is designed for low-power but powerful edge AI and can be widely used in always-online smart homes, factories or city sensors.

At the same time, according to The Business Research Company, by 2025, the global neuromorphic computing market size will grow exponentially to US$1.81 billion , with a compound annual growth rate of 25.7% .

In the longer term, scientists hope that neuromorphic computing will transcend the traditional boundaries of artificial intelligence and get closer to human intelligent reasoning patterns, bringing new technological breakthroughs to the next generation of intelligent systems and even AGI.

 

[7für7]

Interesting interview with Geoffrey Hinton. Sadly, if he is right, humanity is on its way to being toast.

I find it interesting how people believe that AI will bring about the downfall of humanity… but honestly, we don’t need AI for that … humans are already doing a pretty good job on their own.
Through wars, disgusting child and human trafficking, modern slavery, power struggles, greed… the list goes on and on.

So what exactly could AI make worse?

I believe AI is actually a chance to improve human life… through security systems, modern surveillance, fast identification of criminals, and more.
And I think AI can help us build systems and solve problems that humanity alone could never achieve.

Just my opinion… but maybe it’s time to think a little more positively.

 

[davidfitz]

There appears to be a lot of 'support' at 21 cents

 

[Newk R]

There appears to be a lot of 'support' at 21 cents

View attachment 87210

Support at 0.21 is meaningless to me. Support at 2.10 may hold my interest.

 

[Bravo]

At approximately 12:08 minutes into the video, Steve Brightfield discusses the Akida Pico and highlights its suitability for hearing aids and wearables such as smartwatches and glasses. He emphasizes that its energy efficiency allows the battery to last for several days.

At 12:50, he talks about the audio denoising algorithms, noting that some of this technology is already present in Apple Pro devices. He also mentions ongoing discussions with manufacturers of smart glasses.

The interviewer then asks whether products featuring this technology are currently available. Steve responds by saying they are working with manufacturers to integrate more advanced algorithms into products.

Regarding smart glasses, I thought Stephen might be referring to either Meta or Apple, but other possibilities could include Vuzix, Xiaomi, Brilliant Labs and Lenovo.

In September 2024, EssilorLuxottica and Meta extended their partnership beyond 2030, signaling a long-term commitment to developing smart eyewear together.

Apple Vision Pro, which is a mixed-reality headset, is manufactured by Luxshare, a Chinese electronics company.

Back in January, after listening to a podcast featuring Steven Brightfield, I mentioned that I had the impression he may have been hinting at Meta as one of the companies involved in discussions around smart glasses (as above).

So, it’s with great interest that I’ve seen reports today about a new collaboration between Meta and Oakley on a sports-focused line of smart glasses, with an official announcement reportedly scheduled for Friday, 20 June.

The partnership builds on the existing relationship between Oakley and Ray-Ban under their parent company, EssilorLuxottica, which already works closely with Meta on the Ray-Ban Meta smart glasses.

I’ll definitely be tuning into this announcement to learn more. Early reports suggest the glasses are being optimised for sports and athletic use, with a focus on hands-free video recording capabilities. The announcement will also likely reveal specific features, pricing, and availability for the glasses.

Over the past few days, I’ve noticed a recurring theme across industry commentary - battery life continues to be a major challenge for smart glasses, particularly when video capture is involved, which significantly increases power consumption.

Thanks to our collaboration with Onsor, we know BrainChip’s Akida technology can support all-day battery life without the need for external battery packs or cloud connectivity. That’s a capability that most players in this space are still chasing.

If Meta plans to push harder into high-performance, video-centric smart glasses, it seems likey they would need a low-power solution like ours to get them across the line. Edit: As pointed out to me by @Diogenese, monitoring for early signs of a seizure, as in the Onsor glasses, is largely a passive function, similar to wake-word detection. In contrast, continuous video processing and classification is a significantly more active workload for any processor. So, while Akida with TENNs could theoretically help extend battery life, we’d need to wait for real-world performance data before drawing conclusions about its impact in such demanding use cases.

And - whether it’s meaningful or not - we’ve seen a few likes from Meta employees on LinkedIn.

Oh, and then there's also the small fact that Sean recently confirmed that the company that is manufacturing the glasses for Onsor is the same one doing them for Meta, EssilorLuxottica.

So, I welcome you to draw your own conclusions.



Video Start Time : 14.26 when Sean mentions the Onsor frames are made by EssilorLuxottica ,who also make the Meta frames.

channelnews : Meta and Oakley Announce Smart Glasses Reveal for June 20

Meta and Oakley have offically teased the launch of their collaborative smart glasses, scheduled for announcement on Friday, June 20, through a new Instagram account and coordinated social media campaign. The announcement comes via the newly created @oakleymeta Instagram account, which posted a...

www.channelnews.com.au

 

[Bravo]

Meta reportedly planning to add facial recognition to Ray-Ban Smart Glasses​

May 09 2025 Tomislav Bezmalinovic

Image: Meta
Meta's next-generation smart glasses could use AI to continuously analyze the environment and even offer facial recognition.



This was reported by The Information, citing several sources close to the company.

The website writes that the next generation of smart glasses, codenamed Aperol and Bellini, are planned for 2026 and could offer a new feature that Meta internally calls "Super Sensing".

Super Sensing allows the new smart glasses to leave their cameras and sensors on for hours at a time, allowing the AI assistant to remember what happened throughout the day. For example, Meta AI could detect when users have forgotten their keys and proactively remind them to pick up an ingredient for dinner. Super Sensing will likely be turned off by default and will need to be turned on.

A similar feature called "Live AI" will soon be available for the current smart glasses in the US and Canada, but will be limited to 30 minutes of continuous AI usage at a time, according to The Information.

Fading privacy worries​

Currently, the smart glasses' LED light is activated when users take photos or videos or when Meta AI accesses the camera. The idea is to signal to the environment that recording is taking place. Whether this will also apply to the always-on Super Sensing is still being discussed at Meta, writes The Information. According to one of the sources, Mark Zuckerberg has questioned this.

The site also reports that Meta is once again actively working on facial recognition, a feature that was previously considered in 2021 but rejected due to privacy-related concerns. Earlier this year, the company talked again about equipping its smart glasses with software that can identify people by their faces, the site writes.

The Information cited the loosening of privacy regulations under the Trump administration as the reason for this shift. The site previously reported how Metas had changed internal processes to assess and mitigate potential risks to users' privacy in order to get products to market faster.

Just in April, the company changed the privacy policy of Ray-Ban Meta Smart Glasses in two ways. Meta AI is now enabled by default, but can still be disabled if users choose. And it's no longer possible to opt out of allowing Meta to store voice recordings to improve its AI products. However, the voice recordings can be manually deleted.

Meta reportedly planning to add facial recognition to Ray-Ban Smart Glasses

Meta's next-generation smart glasses could use AI to continuously analyze the environment and even offer facial recognition.

mixed-news.com

 

[IloveLamp]

Back in January, after listening to a podcast featuring Steven Brightfield, I mentioned that I had the impression he may have been hinting at Meta as one of the companies involved in discussions around smart glasses (as above).

So, it’s with great interest that I’ve seen reports today about a new collaboration between Meta and Oakley on a sports-focused line of smart glasses, with an official announcement reportedly scheduled for Friday, 20 June.

The partnership builds on the existing relationship between Oakley and Ray-Ban under their parent company, EssilorLuxottica, which already works closely with Meta on the Ray-Ban Meta smart glasses.

I’ll definitely be tuning into this announcement to learn more. Early reports suggest the glasses are being optimised for sports and athletic use, with a focus on hands-free video recording capabilities. The announcement will also likely reveal specific features, pricing, and availability for the glasses.

Over the past few days, I’ve noticed a recurring theme across industry commentary - battery life continues to be a major challenge for smart glasses, particularly when video capture is involved, which significantly increases power consumption.

Thanks to our collaboration with Onsor, we know BrainChip’s Akida technology can support all-day battery life without the need for external battery packs or cloud connectivity. That’s a capability that most players in this space are still chasing.

If Meta plans to push harder into high-performance, video-centric smart glasses, it seems likey they would need a low-power solution like ours to get them across the line. Edit: As pointed out to me by @Diogenese, monitoring for early signs of a seizure, as in the Onsor glasses, is largely a passive function, similar to wake-word detection. In contrast, continuous video processing and classification is a significantly more active workload for any processor. So, while Akida with TENNs could theoretically help extend battery life, we’d need to wait for real-world performance data before drawing conclusions about its impact in such demanding use cases.

And - whether it’s meaningful or not - we’ve seen a few likes from Meta employees on LinkedIn.

Oh, and then there's also the small fact that Sean recently confirmed that the company that is manufacturing the glasses for Onsor is the same one doing them for Meta, EssilorLuxottica.

So, I welcome you to draw your own conclusions.



Video Start Time : 14.26 when Sean mentions the Onsor frames are made by EssilorLuxottica ,who also make the Meta frames.

channelnews : Meta and Oakley Announce Smart Glasses Reveal for June 20

Meta and Oakley have offically teased the launch of their collaborative smart glasses, scheduled for announcement on Friday, June 20, through a new Instagram account and coordinated social media campaign. The announcement comes via the newly created @oakleymeta Instagram account, which posted a...

www.channelnews.com.au

View attachment 87214

I noticed yesterday that meta is also a customer of Andes Technology..... and they're also in collaboration with Baya systems (where Nandan went)

How Taiwan’s Andes Technology makes Facebook’s AI chips｜Industry｜2023-10-25｜web only | CommonWealth English 天下雜誌英文網

In June, tech giant Meta publicly stated for the first time in a technical report that its AI accelerator MTIA was jointly developed with Andes Technology Corporation from Taiwan. How did Andes Technology Corporation, often dubbed “Taiwan’s ARM,” break into the data center accelerator market...

www.linkedin.com

#edgeai #edgeaifoundation #ondeviceai #tinyml #llmontheedge #embeddedai #aihardware #lowpowerai #5vtech #brainchip #edgecomputing #aiip | 5V Tech

At the EDGE AI FOUNDATION event in Austin, we caught up with Todd Vierra, Head of Customer Engagement at BrainChip, an AI IP company building low-power, high-performance solutions for edge deployment. Todd shared how BrainChip is helping shift the AI conversation away from data centers and...

www.linkedin.com

 

[7für7]

ZzzzZZZZZzzzzzzzZZZZZZ

 

[smoothsailing18]

Absolue leader in the market,Sean's words not mine. However I agree.
Go Brainchip

 

[Pom down under]

ZzzzZZZZZzzzzzzzZZZZZZ

Can’t wait for the next quarterly report and at least it’s something to talk about even so it’s never anything positive

 

[itsol4605]

From tinyML to the Edge of AI: Connecting AI to the Real World | Syntiant Corp.

We're headed to the main stage at Sensors Converge! Join our CEO, Kurt Busch, on Thursday, June 26 at 1 p.m., for a forward-looking panel: "From tinyML to the Edge of AI: Connecting AI to the Real World." Moderated by Michael Kuptz of the EDGE AI FOUNDATION, Busch will be joined by execs from...

www.linkedin.com

 

[itsol4605]

#vivatech #inpi #hecparis #deeptech #neurobus #ai #innovation #startups | Neurobus

🏆 1st Place at the INPI Pitch Contest at VivaTech! Huge thanks to INPI France and HEC Paris - Innovation & Entrepreneurship Institute for the opportunity to pitch on stage at Viva Technology! We’re proud that Neurobus won 1st place, showcasing our vision for low-power, bio-inspired edge AI for...

www.linkedin.com

 

[itsol4605]

#vivatech #inpi #hecparis #deeptech #neurobus #ai #innovation #startups | Neurobus

🏆 1st Place at the INPI Pitch Contest at VivaTech! Huge thanks to INPI France and HEC Paris - Innovation & Entrepreneurship Institute for the opportunity to pitch on stage at Viva Technology! We’re proud that Neurobus won 1st place, showcasing our vision for low-power, bio-inspired edge AI for...

www.linkedin.com

Neurobus

Lovable Generated Project

neurobus.space

 

[Pom down under]

Will 0.21 be still there come the end of the week? I’m guessing not and I wonder why

 

[Frangipani]

Sensors Converge

www.sensorsconverge.com

From tinyML to the Edge of AI: Connecting AI to the Real World | Sensors Converge

www.sensorsconverge.com

From tinyML to the Edge of AI: Connecting AI to the Real World​

Thu, Jun 26 | 01:00 PM - 02:00 PM

Converge Main Stage
Add to Calendar
Full schedule

​

Session details:​

As artificial intelligence evolves beyond the data center, a new frontier is emerging at the edge—where smart sensors, microcontrollers, and low-power devices are enabling real-time intelligence closer to the physical world. This panel explores the transformative journey from tinyML—AI on resource-constrained devices—to full-fledged edge AI systems that bridge the gap between digital models and real-world action.

Join industry leaders and innovators as they discuss the latest advancements in on-device learning, edge computing architectures, and AI deployment in environments with limited bandwidth, power, or compute. Topics will include practical applications across industries such as healthcare, manufacturing, agriculture, and smart cities, as well as challenges like model compression, latency, privacy, and security.

Whether you're building smart sensors, designing AI pipelines, or looking to understand the future of decentralized intelligence, this session will offer insights into how tinyML and edge AI are reshaping how machines sense, interpret, and interact with the world around them.

Speakers:​

Scott SmyserNanoveu

Kurt BuschSyntiant

Sumeet KumarInnatera

Steve BrightfieldBrainChip

GP SinghAmbient Scientific

Moderators:​

Michael KuptzEDGE AI FOUNDATION


Format:
Expo Floor Talks
Track:
Expo Floor Talks

 

[CHIPS]

Who is still buying? Or are you too afraid to stock up?
Just curious.

I am considering buying more today as BRN is declining strongly.