Wow so this is how a working modern crystal ball looks like… impressive! I’m still old school man… still manual…
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
Share price being manipulated because there is no revenue nor material news on ASX. It occurs everywhere, and unfortunately, we have a strong track record of no material news for agesShareholders,
Do you believe that our technology has advanced over the last 3 years or not ?
I think yes, you think what ?
Shareholders,
Do you think our website has improved, as in, overall information sharing ?
I think yes, you think what ?
Shareholders,
Do you believe that Antonio lied during the AGM ?
I think yes, you think what ?
Shareholders,
Do you believe that Antonio's comments at the AGM were addressed by fellow Board members after the conclusion of the AGM ?
I think yes, you think what ?
Shareholders,
Do you believe that Sean, who is 3 years 9 months into his tenure will deliver before his 5 year (agreement) is due to expire ?
I think yes, you think what ?
Shareholders,
Do you believe that the Board will suggest that we re-domicle to the US in early 2026 ?
I think not, you think what ?
Shareholders,
Are you happy with how our share price is being manipulated by an automated robotic algorithm, to the point of artificial control ?
I think not, you think what ?
Shareholders,
Do you believe that Tony is the right man to be leading our technology team ?
I think yes, you think what ?
Just some honest, genuine questions that may confirm why you are still invested in our company.
The Akida family, we are growing, please don't loose sight of that FACT !
Tech x
Pom down under
Top 20
Strong don’t you meanwe have a strong track record of no material news for ages
Tothemoon24
Top 20
GlobalFoundries buys MIPS for edge AI network dominion
The chip maker banks on the promise of RISC-VJuly 09, 2025 By Giacomo "Jack" Lee Comment
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GlobalFoundries announced a definitive agreement to acquire chip design company MIPS, in a move focused around AI-enabled network infrastructure.
In its announcement from Tuesday, the New York-headquartered foundry firm shared that MIPS will continue to operate as a standalone business within the new setup. That business revolves around developing processor architectures, now complementing GlobalFoundries’ (GF) semiconductor manufacturing capabilities.
What makes MIPS particularly attractive to GF is its relevance in AI chip design. Recent years have seen the Sunnyvale, California business focus on RISC-V, poaching execs from the likes of AMD and RISC-V rival SiFive to bolster its mission.
Pronounced risk-five, RISC-V is an open standard instruction set (ISA) architecture based on established reduced instruction set computing (RISC) principles. Based on this, the firm’s Atlas portfolio offers compute cores designed for real-time, low-latency processing and, perhaps most pertinently, edge AI processing cores.
With the acquisition, GF is in a strong position to offer custom chip solutions for smart routers, switches, and edge-network devices that incorporate AI and machine learning functions closer to the network’s edge.
With in-house processor IP and fabrication, its custom chips are likely to attract the likes of network equipment vendors such as Cisco, and OEMs like Nokia for SoCs in 5G small cells and base stations.
AI on the edge
The low-latency and high bandwidth efficiency of AI directly embedded in edge devices is driving more interest in the market.As reported by SDxCentral, most initial investment in edge AI is targeted at equipment that enterprises use to support on-prem use cases.
Companies like Verizon have already signed deals with the likes of Nvidia to power enterprise AI services. While ROI remains low and IoT persists as the main edge use case driver, IDC predicts the edge compute market is set for an AI-fueled boost pushing overall segment spend to $380 billion by 2028.
With MIPS on board, GF finds itself in a good position for all this loot. That said, how big of a deal the acquisition is has not been disclosed. The last public record of a MIPS sale was for $60 million, when Tallwood Venture Capital bought the company from Imagination Technologies in 2017.
Since then, the company has changed hands a few times, being bought out by Wave Computing in 2018 for an undisclosed amount.
According to Reuters, Shanghai’s CIP United acquired full licensing rights to MIPS architecture for mainland China and its territories in 2019 for $60 million. Those rights for China will remain in CIP's hands in spite of GF’s global operations of MIPS.
GF’s acquisition of MIPS is expected to close in the second half of 2025.
GlobalFoundries buys MIPS for edge AI network dominion
The chip maker banks on the promise of RISC-V
July 09, 2025 By Giacomo "Jack" Lee Comment
FacebookTwitterLinkedInRedditEmailShare
Sundry Photography/Getty Images
GlobalFoundries announced a definitive agreement to acquire chip design company MIPS, in a move focused around AI-enabled network infrastructure.
In its announcement from Tuesday, the New York-headquartered foundry firm shared that MIPS will continue to operate as a standalone business within the new setup. That business revolves around developing processor architectures, now complementing GlobalFoundries’ (GF) semiconductor manufacturing capabilities.
What makes MIPS particularly attractive to GF is its relevance in AI chip design. Recent years have seen the Sunnyvale, California business focus on RISC-V, poaching execs from the likes of AMD and RISC-V rival SiFive to bolster its mission.
Pronounced risk-five, RISC-V is an open standard instruction set (ISA) architecture based on established reduced instruction set computing (RISC) principles. Based on this, the firm’s Atlas portfolio offers compute cores designed for real-time, low-latency processing and, perhaps most pertinently, edge AI processing cores.
With the acquisition, GF is in a strong position to offer custom chip solutions for smart routers, switches, and edge-network devices that incorporate AI and machine learning functions closer to the network’s edge.
With in-house processor IP and fabrication, its custom chips are likely to attract the likes of network equipment vendors such as Cisco, and OEMs like Nokia for SoCs in 5G small cells and base stations.
AI on the edge
The low-latency and high bandwidth efficiency of AI directly embedded in edge devices is driving more interest in the market.
As reported by SDxCentral, most initial investment in edge AI is targeted at equipment that enterprises use to support on-prem use cases.
Companies like Verizon have already signed deals with the likes of Nvidia to power enterprise AI services. While ROI remains low and IoT persists as the main edge use case driver, IDC predicts the edge compute market is set for an AI-fueled boost pushing overall segment spend to $380 billion by 2028.
With MIPS on board, GF finds itself in a good position for all this loot. That said, how big of a deal the acquisition is has not been disclosed. The last public record of a MIPS sale was for $60 million, when Tallwood Venture Capital bought the company from Imagination Technologies in 2017.
Since then, the company has changed hands a few times, being bought out by Wave Computing in 2018 for an undisclosed amount.
According to Reuters, Shanghai’s CIP United acquired full licensing rights to MIPS architecture for mainland China and its territories in 2019 for $60 million. Those rights for China will remain in CIP's hands in spite of GF’s global operations of MIPS.
GF’s acquisition of MIPS is expected to close in the second half of 2025.
Yeah but you know….
“We are pushing the boundaries to enable AI on the edge.”
Global Foundries are the makers of the Akida 1500 22nm FD-SoI chips.
https://brainchip.com/brainchip-rec...icon-from-technology-partner-globalfoundries/
It looks like the wisdom of our early engagement with RISC-V company SiFive is beginning to shine through.
Chelpis, Andes, Frontgrade all use RISC-V.
MIPS have a suite of patents relating to a switching fabric array for interconnecting NNs. It's possible that this is used in Akida to select the NPU arrangement for the layers of a NN.
US2020034262A1 PROCESSOR ARRAY REDUNDANCY 20180727
processor synchronization within a reconfigurable computing environment for processor array redundancy. Processing elements are configured within a reconfigurable fabric to implement two or more redundant processors, where the two or more redundant processors are enabled for coincident operation. An agent is loaded on each of the two or more redundant processors, where the agent performs a function requiring data validation. The agent is fired on each of the two or more redundant processors to commence coincident operation. The coincident operation can include a lockstep operation. An output data result from each of the two or more redundant processors is compared to enable a data validation result. The data validation result is propagated. The propagating the data validation result can be based on comparing valid output data or can be based on comparing invalid output data.
So maybe BRN was the marriage broker?
https://brainchip.com/brainchip-rec...icon-from-technology-partner-globalfoundries/
It looks like the wisdom of our early engagement with RISC-V company SiFive is beginning to shine through.
Chelpis, Andes, Frontgrade all use RISC-V.
MIPS have a suite of patents relating to a switching fabric array for interconnecting NNs. It's possible that this is used in Akida to select the NPU arrangement for the layers of a NN.
US2020034262A1 PROCESSOR ARRAY REDUNDANCY 20180727
processor synchronization within a reconfigurable computing environment for processor array redundancy. Processing elements are configured within a reconfigurable fabric to implement two or more redundant processors, where the two or more redundant processors are enabled for coincident operation. An agent is loaded on each of the two or more redundant processors, where the agent performs a function requiring data validation. The agent is fired on each of the two or more redundant processors to commence coincident operation. The coincident operation can include a lockstep operation. An output data result from each of the two or more redundant processors is compared to enable a data validation result. The data validation result is propagated. The propagating the data validation result can be based on comparing valid output data or can be based on comparing invalid output data.
So maybe BRN was the marriage broker?
Pom down under
Top 20
Bravo
If ARM was an arm, BRN would be its biceps💪!
Sounds very promising @Diogense!
It says in the article that @Toothemoon posted:
"With the acquisition, GF is in a strong position to offer custom chip solutions for smart routers, switches, and edge-network devices that incorporate AI and machine learning functions closer to the network’s edge."
Talk about being right down our alley! Surely BrainChip would be a great fit as a complementary IP block into MIPS-designed RISC-V SoCs for reducing power and latency in edge ML workloads, enabling local learning, offloading inference, etc.
Prior fab partner for BrainChip - tick
Synergy with RISC-V (i.e. Si-Five, etc. ) - tick
Edge AI focus - tick
GF is pushing into custom SoC development with vertical stacks - tick
If BrainChip wanted to tape out Akida 2 or Akida 3 in silicon, GF would be a natural foundry candidate.
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TheDrooben
Pretty Pretty Pretty Pretty Good
GlobalFoundries buys MIPS for edge AI network dominion
The chip maker banks on the promise of RISC-V
July 09, 2025 By Giacomo "Jack" Lee Comment
FacebookTwitterLinkedInRedditEmailShare
Sundry Photography/Getty Images
GlobalFoundries announced a definitive agreement to acquire chip design company MIPS, in a move focused around AI-enabled network infrastructure.
In its announcement from Tuesday, the New York-headquartered foundry firm shared that MIPS will continue to operate as a standalone business within the new setup. That business revolves around developing processor architectures, now complementing GlobalFoundries’ (GF) semiconductor manufacturing capabilities.
What makes MIPS particularly attractive to GF is its relevance in AI chip design. Recent years have seen the Sunnyvale, California business focus on RISC-V, poaching execs from the likes of AMD and RISC-V rival SiFive to bolster its mission.
Pronounced risk-five, RISC-V is an open standard instruction set (ISA) architecture based on established reduced instruction set computing (RISC) principles. Based on this, the firm’s Atlas portfolio offers compute cores designed for real-time, low-latency processing and, perhaps most pertinently, edge AI processing cores.
With the acquisition, GF is in a strong position to offer custom chip solutions for smart routers, switches, and edge-network devices that incorporate AI and machine learning functions closer to the network’s edge.
With in-house processor IP and fabrication, its custom chips are likely to attract the likes of network equipment vendors such as Cisco, and OEMs like Nokia for SoCs in 5G small cells and base stations.
AI on the edge
The low-latency and high bandwidth efficiency of AI directly embedded in edge devices is driving more interest in the market.
As reported by SDxCentral, most initial investment in edge AI is targeted at equipment that enterprises use to support on-prem use cases.
Companies like Verizon have already signed deals with the likes of Nvidia to power enterprise AI services. While ROI remains low and IoT persists as the main edge use case driver, IDC predicts the edge compute market is set for an AI-fueled boost pushing overall segment spend to $380 billion by 2028.
With MIPS on board, GF finds itself in a good position for all this loot. That said, how big of a deal the acquisition is has not been disclosed. The last public record of a MIPS sale was for $60 million, when Tallwood Venture Capital bought the company from Imagination Technologies in 2017.
Since then, the company has changed hands a few times, being bought out by Wave Computing in 2018 for an undisclosed amount.
According to Reuters, Shanghai’s CIP United acquired full licensing rights to MIPS architecture for mainland China and its territories in 2019 for $60 million. Those rights for China will remain in CIP's hands in spite of GF’s global operations of MIPS.
GF’s acquisition of MIPS is expected to close in the second half of 2025.
"IDC predicts the edge compute market is set for an AI-fueled boost pushing overall segment spend to $380 billion by 2028."
JohnErica34
Emerged
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Attachments
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Or as thay say in the high end computer tech world , .... Vertically Intergrate thee.
Last edited:
Felix
Member
RobjHunt
Regular
I was referring Dodgyknees references to Cybersecurity.Bigger business with work from home staff, staff on the road or travelling and sub office staff all carry devices including lap tops, phones, printers, etc that access the mainframe network. These devices provide openings for hackers.
Government departments have a lot of work from home staff which increase the vulnerability for cyberattack. We have seen plenty of cyberattacks in Australia where private data has been stolen.
Not sure what the C and a couple of Y's is
Tothemoon24
Top 20
The Missing Piece of Smart Things Manufacturing
Remember our vision of 3D printing smart shipping boxes and supply chain sensors at any corner store earlier this week? One underlying technology that can make it possible are new chips that think like the human brain.
Neuromorphic edge chips are now so small and efficient they can be embedded anywhere. We're talking tiny 1-milliwatt processors that work like our brains do—100x faster processing and 500x lower energy consumption.
Companies like BrainChip and SynSense are developing these today. While not ready for any old box yet, they're rapidly approaching the point where intelligence becomes as standard as plastic in manufacturing.
What becomes possible when 1-milliwatt intelligence gets embedded anywhere?
Smart packaging on pallets that knows when something's wrong
Product-level monitoring with chips smart enough to detect issues
Equipment sensors that understand their environment and alert you instantly Connected intelligence in boxes, products, even intelligent documentsHere's the breakthrough:
These chips literally work like our brains do—they only activate when something happens. Smart enough to understand when something's wrong, connected enough to let you know instantly.
Brain-inspired processing that mimics human neurons
1-milliwatt power - operates for months on minimal energy
Microscopic size - getting small enough for embedding anywhere
Incredible economics - intelligence approaching the cost of a stickerImagine designing things by specifying not just shape and material, but exactly where to place micro-intelligence during printing. Every object emerges already smart, already connected.
What becomes possible when intelligence is built into the manufacturing process?
The answer is reshaping entire industries—and we're just getting started. 
#Innovation #3DPrinting #SmartObjects #SupplyChain #Logistics #Manufacturing #EdgeComputing #Neuromorphi
The Missing Piece of Smart Things Manufacturing
Remember our vision of 3D printing smart shipping boxes and supply chain sensors at any corner store earlier this week? One underlying technology that can make it possible are new chips that think like the human brain.
Neuromorphic edge chips are now so small and efficient they can be embedded anywhere. We're talking tiny 1-milliwatt processors that work like our brains do—100x faster processing and 500x lower energy consumption.
Companies like BrainChip and SynSense are developing these today. While not ready for any old box yet, they're rapidly approaching the point where intelligence becomes as standard as plastic in manufacturing.
What becomes possible when 1-milliwatt intelligence gets embedded anywhere?
Smart packaging on pallets that knows when something's wrong Product-level monitoring with chips smart enough to detect issues Equipment sensors that understand their environment and alert you instantly Connected intelligence in boxes, products, even intelligent documentsHere's the breakthrough:
These chips literally work like our brains do—they only activate when something happens. Smart enough to understand when something's wrong, connected enough to let you know instantly.
Brain-inspired processing that mimics human neurons 1-milliwatt power - operates for months on minimal energy Microscopic size - getting small enough for embedding anywhere Incredible economics - intelligence approaching the cost of a stickerImagine designing things by specifying not just shape and material, but exactly where to place micro-intelligence during printing. Every object emerges already smart, already connected.
What becomes possible when intelligence is built into the manufacturing process?
The answer is reshaping entire industries—and we're just getting started. #Innovation #3DPrinting #SmartObjects #SupplyChain #Logistics #Manufacturing #EdgeComputing #Neuromorphi
SharesForBrekky
Regular
A possible company to keep an eye on:
"Integer Technologies is an applied research and product development company founded by scientists and engineers with a passion for protecting freedom with innovation. We perform R&D on next-generation systems and technologies for the Department of Defense and other U.S. Government agencies. We are hardware and software developers with experience transforming research into fieldable technology. Our core portfolio of research includes projects in powerenergy systems, unmanned systems (with an emphasis on maritime systems), digital engineering, cyber security, and advanced manufacturing. Our mission is to create a safer world by translating scientific discoveries into reliable products that address urgent national security needs... at the speed of relevance."
One of the jobs desired qualifications:
"Background in AI/ML applications for edge deployment, including model optimization techniques (e.g., pruning, quantization, or neuromorphic computing)"
A link if you're interested to know a bit more about Integer Technologies:
www.msaerodefense.org
"Integer Technologies is an applied research and product development company founded by scientists and engineers with a passion for protecting freedom with innovation. We perform R&D on next-generation systems and technologies for the Department of Defense and other U.S. Government agencies. We are hardware and software developers with experience transforming research into fieldable technology. Our core portfolio of research includes projects in powerenergy systems, unmanned systems (with an emphasis on maritime systems), digital engineering, cyber security, and advanced manufacturing. Our mission is to create a safer world by translating scientific discoveries into reliable products that address urgent national security needs... at the speed of relevance."
One of the jobs desired qualifications:
"Background in AI/ML applications for edge deployment, including model optimization techniques (e.g., pruning, quantization, or neuromorphic computing)"
A link if you're interested to know a bit more about Integer Technologies:
Integer Technologies, LLC - Aerospace and Defense Alliance of Mississippi
Frangipani
Top 20
One month later…
Another attempt at finding a suitable candidate for the advertised position as “Sales Director, US/ Bay Area” - and it doesn’t seem to be a “lack of applicants” matter in general…
We're #hiring a new Sales Manager- Bay Area in San Francisco Bay Area. | BrainChip
We're #hiring a new Sales Manager- Bay Area in San Francisco Bay Area. Apply today or share this post with your network.
BrainChip hiring Sales Manager- Bay Area in San Francisco Bay Area | LinkedIn
Posted 7:17:58 PM. The Sales Director will spearhead the sales initiatives of BrainChip Inc. in the US (Bay Area)…See this and similar jobs on LinkedIn.
Last edited:
Phew!!!
Frangipani
Top 20
Laurent Hili on the ESA-supported BrainChip -Frontgrade Gaisler partnership:
The partnership BrainChip - Frontgrade Gaisler is a significant step toward deploying AI in space. | Laurent Hili
The partnership BrainChip - Frontgrade Gaisler is a significant step toward deploying AI in space. With growing demand for higher processing capabilities, there is an emerging need for autonomous systems that can process data locally and make timely decisions. GR801 is a promising development...www.linkedin.com
View attachment 88310
"Meh, volumes in Space are low." Or is it? | Alf Kuchenbuch
"Meh, volumes in Space are low." Or is it? I think of our joint neuromorphic Space SoC GR801 quite differently: 1. There are large safety critical markets beyond Space that need intelligence and fault tolerance at ultra-low power. Akida can shine in Space, so why not there? 2. Frontgrade...
Hang on a sec, Felix - I haven't got the contact details yet.
Frangipani
Top 20
Massive growth in global connected devices is also driven by edge AI capabilities | HaiLa
Massive growth in global connected devices is also driven by edge AI capabilities Two key technologies are underpinning edge AI: Low-power RF and low-power AI compute HaiLa and BrainChip partner to show both elements today
Connected, Low-power, Intelligent Devices at the Edge
Article by Patricia Bower, HaiLa VP Product What’s the ‘Edge’ in Edge AI? The amount of data generated by billions of wireless connected devices—such as sensors, wearables, and smart appliances—is growing at an incredible rate. Analysts forecast global growth from 20 billion devices today to over 40
Cloud based AI vs Edge AI Topology
Connected, Low-power, Intelligent Devices at the Edge
HaiLa
4,385 followersJuly 10, 2025
Article by Patricia Bower, HaiLa VP Product
What’s the ‘Edge’ in Edge AI?
The amount of data generated by billions of wireless connected devices—such as sensors, wearables, and smart appliances—is growing at an incredible rate. Analysts forecast global growth from 20 billion devices today to over 40 billion by 2030 (IoT Analytics, State of IoT 2024).Using today’s communications networks, user data is sent from (for example) the smartwatch on your wrist to datacenters located miles from you or even across a continent. The data is processed in these facilities by clusters of artificial intelligence (AI) or machine learning (ML) systems and is generally referred to as cloud compute. There are three issues with this model:
- The time it takes for the data to traverse communications networks to the datacenter (latency)
- The heavy load on datacenter AI clusters, and resulting power consumption, for processing raw data from billions of devices
- The higher potential for personal data privacy breaches
The growing need for faster responses (real-time decision making), reduced loading on datacenters (cloud offload), and improved privacy (anonymized data) has therefore driven the rise of edge AI—where intelligent processing happens directly on the device itself, such as in a sensor or wearable. At the core of this shift are neural processing units (NPUs)—specialized AI processors that enable devices to "think locally” and to rely on optimized AI and ML training models.
Chip technology for datacenter AI processing is extremely energy intense. In these AI clusters, where complex computational tasks - such as climate modelling - are performed, compute operations are measured in exaFLOPS, or a million, trillion floating-point operations per second. Edge AI NPUs can support up to a few teraOPS, or trillion operations per second OPS, and are purpose-built to be extremely power efficient. This is important as many connected devices run on batteries.
What Applications are Driving Edge AI?
Edge AI is already transforming many industries. Here are some notable applications:Patient Monitoring
Hospitals and home-care settings are increasingly using AI-powered sensors to continuously monitor vital signs such as heart rate, respiration, and oxygen levels. By analyzing these signals locally, devices can detect early warning signs of health deterioration and alert caregivers—without the need to stream personal health data to the cloud. This approach protects patient privacy and saves bandwidth.
Personal Health Monitoring
Wearable devices like fitness trackers and smartwatches are incorporating edge AI to offer more intelligent insights into sleep patterns, stress levels, and activity trends. These devices process sensor data in real time, providing instant feedback and recommendations on the go while preserving battery life.
Retail
In retail environments, smart cameras and sensors are used for foot traffic analysis, shelf inventory monitoring, and customer behavior tracking. Edge AI allows these insights to be processed locally without storing or transmitting images, which supports both privacy and efficiency. For example, a store can detect when a shelf is empty and trigger restocking alerts automatically. Using a battery powered, modular solution with integrated, low-power Wi-Fi provides a simple installation into legacy environments.
Industrial Asset Monitoring and Anomaly Detection
Factories and industrial sites rely on sensors to monitor machinery. Edge AI enables these sensors to learn the normal operating patterns of equipment and detect anomalies like unusual vibrations or temperature spikes—early signs of failure. This allows for predictive maintenance, reducing downtime and maintenance costs.
The ability to collect intelligent data directly from edge devices reduces the need for cloud infrastructure and data transmission, which means that edge AI also lowers the overall cost of system deployment and operation.
Leveraging Low-power RF and Neuromorphic AI for Efficient Edge AI
A major technical challenge in deploying edge AI is power consumption. Devices like health monitors or industrial sensors are often required to run for months or years on small batteries—or in some cases, without batteries at all. As mentioned, NPUs optimized for low power are an essential element to perform AI tasks like image recognition or anomaly detection using minimal energy. To address this need, BrainChip’s Akida™ neuromorphic technology relies on the principle of sparsity for power efficient, event-driven AI compute.The inferenced data from NPU AI processing is only part of the equation. Devices must also have the ability to connect and collate this intelligent data from multiple devices in a local or personal area network. This is where low-power radio frequency (RF) technologies like Wi-Fi and Bluetooth Low Energy come in and where HaiLa is setting a new paradigm in just how efficient data transmission can be over these protocols. HaiLa’s extreme low power radio communications technology, paired with power-optimized edge compute, allows devices to send and receive inferenced data without draining energy reserves, making them perfect partners for edge AI systems.
HaiLa and BrainChip: Sensors Converge 2025 Connected Edge AI Demo
At Sensors Converge in Santa Clara this year, HaiLa and BrainChip joined forces to demonstrate object classification via extreme low-power Wi-Fi.HaiLa and BrainChip collaborated to showcase very low power Connected Edge AI Object Classification
This hardware prototype includes a camera module to capture object images, BrainChip’s NPU test platform which is pre-trained to recognize objects from a camera image capture, and HaiLa’s BSC2000 extreme low-power Wi-Fi radio chip which transmits the image class and type data via Wi-Fi to display as a simple icon on a dashboard.
The demo illustrates the potential use of connected, edge AI for applications using image recognition and classification in industrial, retail, and medical sectors where cost effective, low latency, and private data connections are key requirements.
The Future of Edge AI: Connected, Low-power, Intelligent Devices Everywhere
HaiLa’s core specialization in extreme low-power radio technology over standard protocols like Wi-Fi, Bluetooth, and even cellular, delivers one of the critical enablers of pervasive edge AI: extreme low-power data transmission. Together with BrainChip’s innovative edge compute, this opens up a broad range of options for end-users to support energy-efficient, on-device AI.Edge AI represents a powerful shift in how intelligent systems operate—bringing the power of AI directly to the devices at the heart of the connected world. By combining efficient NPUs with low-power wireless communication, edge AI systems can run independently, securely, and with minimal energy use. As more industries adopt this technology, we can expect smarter, more responsive, and more sustainable solutions for multiple applications.
Contact us to learn more:
info@haila.io
sales@brainchip.com
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