In the final chapter of the Edge AI Technology Report: Generative AI Edition explores the technical hurdles organizations face as they attempt to leverage edge-based generative AI. It also examines strategic opportunities for innovation in hardware, deployment configurations, and security measures.


Challenges and Opportunities in Edge-based Generative AI

Generative AI is radically changing how we process, analyze, and utilize data, and edge computing is driving this transformation closer to devices and users. To explore this groundbreaking space, join us for The Rise of Generative AI at the Edge: From Data Centers to Devices webinar on Wednesday, January 15th.The webinar will be a fireside chat format with three heavy hitters from the Edge AI landscape.&nbsp;Pete Bernard - Executive Director, Edge AI Foundation Marek Poliks - Technical Success Director, Particle and&nbsp; Daniel Situnayake - Director of Machine Learning, Edge Impulse.<h3 dir="ltr">Event Overview</h3>Date:&nbsp;January 15thTime:&nbsp;18:00 CET, 09:00 PSTDuration:&nbsp;1 hourFormat:&nbsp;Panel Discussion (~45 mins) followed by a Live Q&amp;A (~15 mins)<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzMzODQyMzM4NDk3LXJlZ2lzdGVyICgxKS5wbmciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 100%px;" class="fr-fic fr-dib"><iframe id="JotFormIFrame-243443776787473" title="Clone of GenAI Report: Particle Webinar - Simple form" allowtransparency="true" src="https://form.jotform.com/243443776787473" frameborder="0" style="min-width:100%;max-width:100%;height:580px;border:none;" scrolling="yes" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"> </iframe>This engaging session will discuss the technological enablers, diverse applications, and profound impact of generative AI at the edge. From real-world applications to tackling current challenges, this webinar offers a unique opportunity to gain actionable insights from leading Edge AI experts. Plus, you'll have the chance to engage directly with the panel during a live Q&amp;A session.<h3 dir="ltr">Why Attend?</h3><ul><li dir="ltr">Explore Cutting-Edge Technology: Learn how Particle's Tachyon 5G single-board computer is revolutionizing intelligent edge applications.</li><li dir="ltr">Hear from Industry Leaders: Gain insights from experts deeply embedded in the intersection of AI, edge computing, and emerging technologies.</li><li dir="ltr">Interactive Q&amp;A: Address your questions directly to our panel of esteemed experts.</li></ul><h3 dir="ltr" id="isPasted">Who Should Attend?</h3>This webinar is ideal for:<ul><li dir="ltr">Engineers, developers, and data scientists eager to harness generative AI at the edge.</li><li dir="ltr">Technology leaders exploring innovative AI-powered solutions.</li><li dir="ltr">Anyone passionate about the intersection of AI, edge computing, and 5G technology.</li></ul><h2>Meet the Host: Samir Jaber</h2>Samir Jaber, representing Wevolver, brings unmatched expertise in technology, science, and engineering communication. As editor-in-chief of major reports like the <a href="https://www.wevolver.com/article/the-guide-to-generative-ai-at-the-edge">Edge AI Technology Report: Generative AI Edition,</a> Samir’s nuanced understanding of AI's technological and societal impacts makes him an ideal host for this dynamic discussion.<h2 dir="ltr">Featured Speakers</h2><ul><li dir="ltr">Daniel Situnayake&nbsp;-&nbsp;Director of Machine Learning, Edge Impulse With career-spanning roles at Google, Tiny Farms, and more, Daniel specializes in advancing machine learning for edge devices. His pioneering work with TensorFlow Lite has empowered developers worldwide.</li><li dir="ltr">Marek Poliks&nbsp;-&nbsp;Technical Success Director, Particle Marek’s multidisciplinary expertise blends AI interface design and deep learning research with practical applications in intelligent device infrastructure. His recent accolades include the Google Art + Machine Intelligence Award.</li><li dir="ltr">Pete Bernard&nbsp;-&nbsp;Executive Director, Edge AI Foundation With over three decades of experience in Silicon Valley and at Microsoft, Pete is at the forefront of edge computing innovation, bridging semiconductors, 5G, and AI through his consultancy, EDGECELSIOR.</li></ul><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzMzODQyMjI4NjEwLVN1YmhlYWRpbmcgKDEwODAgeCAzMDAgcHgpICgxKS5wbmciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 100%px;" class="fr-fic fr-dib"><h2 dir="ltr">Reserve Your Spot Today</h2>Don’t miss your chance to stay ahead of the curve. Join us on January 15th to unlock the future of generative AI at the edge.<iframe id="JotFormIFrame-243443776787473" title="Clone of GenAI Report: Particle Webinar - Simple form" allowtransparency="true" src="https://form.jotform.com/243443776787473" frameborder="0" style="min-width:100%;max-width:100%;height:580px;border:none;" scrolling="yes" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp; </iframe>

Join us for The Rise of Generative AI at the Edge: From Data Centers to Devices webinar on Wednesday, January 15th

Discover the Future of AI: Join "The Rise of Generative AI at the Edge" Webinar

Edge AI Technology Report: Generative AI Edition Chapter 3. Advances in model optimization techniques like pruning, quantization, and knowledge distillation pave the way for more efficient deployment of generative AI at the edge. 

Real-world Applications of Generative AI at the Edge

<h2 dir="ltr" id="isPasted">Enabling Effortless AI Transition to the Edge</h2>The global market for edge AI is estimated to reach <a href="https://pages.edgeimpulse.com/5-rising-trends-for-ai-adoption-in-manufacturing">$143.6 billion by 2032</a>. This growing adoption emphasizes the need for businesses to adopt edge-based machine learning solutions. Companies that adopt edge AI will gain a competitive edge, especially those that invest in advanced neural network hardware.&nbsp;BrainChip has introduced its <a href="https://doc.brainchipinc.com/index.html">MetaTF</a> Software Tools to simplify the migration of ML models to the Akida event-based computing platform. MetaTF offers a set of tools for converting existing models so they can work with BrainChip's Akida processors.Key features of MetaTF include:<ul><li dir="ltr">Effortless Model Transition: It offers tools to convert, optimize, and deploy ML models for Akida processors.</li><li dir="ltr">Reduced Computational Load: Akida computing focuses only on relevant event data. This helps to reduce computational overhead as compared to traditional NPUs.</li><li dir="ltr">Familiar Development Environment: It allows developers to work in familiar environments like Jupyter Notebooks and experiment with ML on the edge. This can help to minimize the learning curve.</li><li dir="ltr">Enhanced Model Validation: It offers a simple pathway for companies to test and refine their models on advanced processors.</li></ul>With these capabilities, MetaTF helps companies to adopt edge AI quickly and efficiently. It also helps them find new opportunities for innovation and performance.<h2 dir="ltr">The Unique Challenges of Embedded Devices</h2>Deploying ML solutions on embedded devices comes with challenges that are different from traditional server. Embedded and IoT devices, ranging from sensors and smart phones, are highly diverse. They do not work like servers that follow standard architectures. These devices have their own architecture and operating systems. Also, they may sometimes have no OS.This diversity makes installing and packaging software more complex, especially when they have to scale it to multi-million devices. Software-build technologies are important to address these challenges. They:<ul><li dir="ltr">Simplify the management of complex hardware configurations.</li><li dir="ltr">Ensure repeatability in software deployments.</li><li dir="ltr">Enable the creation of consistent images throughout different devices.</li></ul>These tools are important for overcoming the unique challenges of deploying ML solutions in embedded environments.<h2 dir="ltr">Simplifying Edge Deployment with Edge Impulse and MetaTF</h2>Training ML models for compact, low-power devices is only part of the challenge. Packaging and deploying these models on edge devices present additional hurdles. BrainChip has significant experience with popular embedded systems like <a href="https://buildroot.org/">Buildroot&nbsp;</a>and <a href="https://www.yoctoproject.org/">Yocto</a>. BrainChip Akida System on Chip (SOC) integrates smoothly into different embedding environments of customers.By joining hands with <a href="https://edgeimpulse.com/">Edge Impulse</a>, BrainChip simplifies ML workflows to edge. It also simplify the deployment of event-based AI solutions. Together, they make it easier than ever to implement event-based ML solutions on embedded devices.One standout example of this collaboration is the <a href="https://shop.brainchipinc.com/products/akida%E2%84%A2-edge-ai-box">Akida™ Edge Box</a>. This was created by cooperation with Edge Impulse and <a href="https://www.vvdntech.com/vision/akida-edge-ai-box">VVDN</a>. This solution showcases BrainChip’s expertise in addressing the unique challenges of edge AI deployment by integrating advanced technologies. The key features of Edge Box include:<ul><li dir="ltr">Hardware Configuration: Built on an NXP i.MX 8M application processor. The Edge Box includes dual Akida 1000 chips integrated via a single M.2 PCI card.</li><li dir="ltr">Streamlined Deployment: MetaTF libraries and NXP’s i.MX Yocto Project Board Support Package help integrate models trained in Edge Impulse Studio.</li><li dir="ltr">Real-World Applications: It shows how event computing and embedded system tools can work together for better AI solutions.</li></ul><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1732020180615-Akida_Examples-1200x627.jpg" style="width: 100%px;" class="fr-fic fr-dib"><a href="https://brainchip.com/contact/">Contact BrainChip's architecture team</a> for more information on integrating BrainChip’s event-based AI into embedded systems or to discover the potential of the Akida Edge Box.&nbsp;Bring your AI initiatives to the edge with BrainChip!

How BrainChip's Akida™ Edge Box Simplifies ML Deployment


Brainchip MetaTF Software Tools ease the Transition of ML Models to the Edge

Edge AI Technology Report: Generative AI Edition Chapter 2. Generative AI and edge computing are transforming industries by enabling low-latency, real-time AI on edge devices, allowing efficient, private, and personalized applications without reliance on data centers.

Innovations and Advancements in Generative AI at the Edge

Edge AI Technology Report: Generative AI Edition
Chapter 1. Generative AI's demand for real-time insights is driving a shift from cloud to edge computing, enabling faster, local processing on devices and reducing cloud latency and bandwidth constraints.

Leveraging Edge Computing for Generative AI

A GPU microchip for accelerated AI processing

Unleashing the Power of GPU, understanding the essential strategies for efficient Deep Learning Model Training without compromising on memory and hardware resources in Graphical Processing Units

Maximize GPU Utilization for Model Training: Unlocking Peak Performance

Continual advancements in space technology are reshaping our capacity to manage Earth's affairs with precision and efficiency. Amidst the complexities of urbanization, climate change, and global connectivity, the need for sophisticated infrastructure has become increasingly apparent.&nbsp;Satellites, with advanced functionalities, have emerged as indispensable tools for data acquisition, analysis, and communication, which are crucial for informed decision-making on Earth.With their high-resolution cameras, multispectral sensors, and robust communication capabilities, we can capture and transmit data from a wide range of Earth-related activities, from urban planning and disaster management to agricultural monitoring and environmental protection.By continuously orbiting the Earth, satellites capture detailed images and other sensor data covering the whole planet’s surface. We can use this data to track changes in landscapes, monitor weather patterns, and observe natural disasters like forest fires, floods, and hurricanes in real time.This data is collected and transmitted back to Earth, where it can undergo rigorous analysis. Machine learning algorithms, data analytics, and other advanced computing techniques allow us to interpret the data with ease. For example, predictive modeling is utilized to forecast weather changes or track the migration patterns of endangered species. The ability to process real-time data enables quick decision-making, which is especially crucial during responses to natural disasters and emergencies.&nbsp;Communication is another critical functionality of satellites. They ensure communication lines are able to remain open, even in the most remote parts of the world. This facilitates global connectivity, allowing data, voice, and video communication to be transmitted across diverse geographical landscapes.<h1 dir="ltr">Maintenance in space</h1>On Earth, if something breaks down in a factory or a power plant, we don’t build a replacement. Instead, we send a repair team with spare parts, and even better yet, we monitor the components' wear and replace them before they break down. This preventive maintenance approach minimizes downtime and reduces the costs associated with sudden breakdowns.This methodology is critical in industries where reliability and uptime are essential. By continuously monitoring equipment health through sensors and predictive analytics, we can identify potential problems before they lead to operational failures. However, this approach faces unique challenges in space, where sending a repair team is not feasible due to the vast distances and extreme conditions.The transition from Earth-based maintenance to space requires innovative solutions to overcome these challenges. The harsh space environment, including vacuum conditions, microgravity, and cosmic radiation, makes traditional maintenance methods impractical. Additionally, the delay in communication between Earth and spacecraft further complicates real-time interventions, necessitating a more autonomous approach to maintenance and repair operations in space.<a href="https://www.ant61.com/" target="_blank" rel="noopener noreferrer">ANT61&nbsp;</a>develops autonomous robots that enable the maintenance of satellites without the need to put human lives at risk. ANT61 is providing solutions for both: their Beacon product allows satellite operators to understand what went wrong with their satellites and restore them back to operation.For larger and more expensive satellites, they are building robots that will dock, refuel, and, in the future, refurbish satellites, prolonging their useful life. At the core of these robots lies ANT61 BrainTM, the innovative devices that combine machine vision and decision-making technology, enabling the autonomy of these maintenance robots. Autonomy is very important as, due to the speed of light limitations, it won’t be possible to control every movement of these robots remotely from Earth.<h3 dir="ltr">BrainChip AkidaTM&nbsp;: A revolutionary neuromorphic processor for edge AI applications</h3>The first generation of the ANT61 Brain uses the <a href="https://brainchip.com/akida-neural-processor-soc/" target="_blank" rel="noopener noreferrer">BrainChip AkidaTM</a> chip for power-efficient AI and is currently on board the Optimus-1 satellite, which was deployed recently by the SpaceX Transporter-10 mission. ANT61 will test the ANT61 Brain later this year and perform training and evaluation of various neural networks that we will use for future in-orbit servicing technology demonstrations.The BrainChip Akida™ chip is a groundbreaking advancement in neuromorphic computing, designed to mimic the neural architecture of the human brain. This technology stands out for its ability to process data directly at the point of acquisition, greatly enhancing efficiency by reducing the reliance on distant cloud-based systems for data processing.Akida's unique capability lies in its event-based neural processor, which processes data only when needed, using data sparsity to significantly reduce the number of operations required. This leads to lower power consumption and heat dissipation, making it highly suitable for the demanding conditions of space. Each Akida node consists of four Neural Network Layer Engines (NPEs), which can be configured for various functions, such as convolutional layers or fully connected layers, and support incremental learning and high-speed inference. This configuration flexibility allows the chip to efficiently handle a wide range of AI tasks without needing constant connectivity or high power draw.Akida's scalable architecture enables the chip to support up to 256 nodes in a mesh network, boosting computational power while maintaining a small footprint. This scalability is crucial for space applications where efficiency and performance are vital. The entire neural network can be embedded directly within the Akida fabric, eliminating the need for frequent data transfers that consume significant power and reduce system responsiveness.Another key feature of the Akida chip is its on-chip learning capability, which allows it to adapt and improve its performance over time without external intervention. This feature is particularly beneficial in space, where conditions can change rapidly and autonomy is crucial. By processing and learning from data locally, Akida enhances the autonomy of satellite maintenance robots like those developed by ANT61, enabling them to perform complex tasks with minimal latency and enhanced reliability.The ANT61 team chose to partner with BrainChip because they believe that neuromorphic technology will bring the same exponential improvement in AI as 20 years ago. The shift from CPU to GPU opened doors to deep neural network applications, which are at the core of all AI technologies today. Neuromorphic technology is also perfect for space: the lower power consumption means less heat dissipation, and we can get up to five times more computational power for the same electrical power budget.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1715339791069-Akida_1000_chip-1.jpg" style="width: 100%px;" class="fr-fic fr-dib">Akida AKD1000 is a reference chip implemented with TSMC at 28nm<h1 dir="ltr">The ANT61 vision for the future</h1>Humanity’s expansion to the cosmos requires infrastructure that can only be built by robots. With its in-orbit servicing experience, ANT61 aims to become the main supplier of the robotic workforce for Moon and Mars installations. This will enable companies from Earth to project their ambition to space, providing valuable services and resources for future off-world factories and cities.Neuromorphic computing, exemplified by technologies like the BrainChip Akida™ chip, is set to play a pivotal role in this spacefaring era. This form of computing brings several advantages crucial for space applications, such as low power consumption, high efficiency, and the ability to perform complex computations needed for autonomy. By mimicking the human brain, neuromorphic processors can process large volumes of sensor data efficiently, making real-time decisions without the need to send data back to Earth for processing.The integration of neuromorphic computing into space robotics promises to significantly improve these machines' capabilities. Robots equipped with advanced AI processors can better handle the unpredictable nature of space environments, adapting to new challenges autonomously and performing tasks ranging from construction to maintenance and repair. This capability ensures that space habitats are built efficiently and can be sustained with minimal human oversight.ANT61's vision of utilizing these technologies to support human expansion into space reflects a forward-thinking approach that will not only facilitate the construction of off-world establishments but also ensure their long-term sustainability and success.&nbsp;

Remote satellite maintenance is crucial to critical data acquisition and global communication


Advancing Earth Management Through Neuromorphic Computing Powered Satellites

<h2 dir="ltr" id="isPasted">Join Us for Our Upcoming Webinar: Powering Edge and Endpoint Applications: A deep dive into Reality AI Tools® from Renesas</h2>Mohammed Dogar, Vice President, Head of Global Business Development &amp; Ecosystem, and Jeff Sieracki, Director of AI COE, will sit with tech writer Samir Jaber to unpack the <a href="https://www.renesas.com/us/en/products/microcontrollers-microprocessors/reality-ai#featured_products" target="_blank" rel="noopener noreferrer">Reality AI Tools</a> suite and discuss their impact on Edge AI applications.Why Attend?<ul><li dir="ltr">Learn:&nbsp;Understand the primary functions and benefits of using Reality AI Tools®</li><li dir="ltr">Connect: Hear from Mohammed Dogar, Vice President, Head of Global Business Development &amp; Ecosystem, and Jeff Sieracki, Director of AI COE</li><li dir="ltr">Engage: Opportunities to ask questions and interact with our experts</li></ul>Event Details:<ul><li dir="ltr">Topic: Powering Edge and Endpoint Applications: A deep dive into Reality AI Tools® from Renesas</li><li dir="ltr">Date:&nbsp;May 28th 2024</li><li dir="ltr">Time:&nbsp;5pm CET (add others)</li><li dir="ltr">Location:&nbsp;Online (via Zoom). Registrants will be sent the webinar video after the event.&nbsp;</li></ul><a href="https://us02web.zoom.us/webinar/register/4017151721849/WN_ahhKxtJ0TuWs-Klj5BfGgg" target="_blank" rel="noopener noreferrer" class="button-main-action">Register for free here</a><h2>Webinar speakers</h2><h3>Mo Dogar</h3>Mo Dogar is head of Global Business Development and Technology Ecosystem at Renesas Electronics, responsible for promotion and business expansion of the complete Microcontroller portfolio and other key products. He is instrumental in driving global business growth and alignment of marketing, sales and development strategies particularly in the areas of IoT, e-AI, Security, smart embedded electronics and communications.&nbsp;In addition, Mr. Dogar helps provide the vision and thought leadership behind product and solution development smart society and the evolving IoT economy. With extensive experience as a keynote speaker and thought leader in the electronics industry, recent speaking engagements include keynote addresses at CES, Arm Techcon, Embedded World, Industrial Open Day and a number of other AIoT and electronics events globally. He studied Electronics &amp; Information Engineering at the University of Huddersfield, UK and received Project Management qualifications with an MBA from the Open University in the UK and has worked for a number of industrial and technology companies including Rockwell Automation. In 2001 he joined NEC and subsequently Renesas and has worked in various roles including Engineering, Applications, Marketing and Business Development. &nbsp;<h2>Dr. Jeff Sieracki</h2>Dr. Jeff Sieracki is an extremely applied mathematician who has focused his career on the intersection of modern signal processing and machine learning. Former co-founder and CTO of Reality AI, he joined Renesas as part of an acquisition in 2022 and is now head of AI Engineering at the Renesas AIoT Center of Excellence. Jeff’s work spans signal and sensing problems in commercial industry, medical devices, and DoD applications. He has started, built, and exited three companies, one in each of those application areas. He has been awarded more than 50 technology patents. Jeff holds a PhD in Applied Mathematics and Scientific Computing and was a founding member of the Norbert Weiner Center for Harmonic Analysis and Applications at the University of Maryland, College Park. He holds a Masters in Applied Mathematics and a BS in Physics from the John Hopkins University.<h2>Samir Jaber</h2>Samir Jaber is an editor, writer, and industry expert on topics of technology, science, and engineering. He is the editor-in-chief of the 2024 State of Edge AI and 2023 Edge AI Technology reports with Wevolver. Samir is the Chief Editor and Founder of Wryters, a content marketing and consulting agency. He has comprehensive experience working with Fortune 500 companies and industry leaders as a writer, editor, content manager, and consultant. He is an online content specialist with an academic background in mechanical engineering, nanotechnology, and scientific research. Samir is also a featured author in 30+ industrial magazines with a focus on Artificial Intelligence (AI), the Internet of Things (IoT), 3D printing, Autonomous Vehicles (AV), nanotechnology, materials science, and sustainability. His experience includes award-winning engineering research and patented engineering design in the fields of nanofabrication and microfluidics.This event is a must-attend for all engineers interested in the tools enabling AI at the edge. If you can't make it on the day, all registrants will be sent the webinar recording.&nbsp;&nbsp;<a href="http://Samir Jaber is an editor, writer, and industry expert on topics of technology, science, and engineering. He is the editor-in-chief of the 2024 State of Edge AI and 2023 Edge AI Technology reports with Wevolver. Samir is the Chief Editor and Founder of Wryters, a content marketing and consulting agency. He has comprehensive experience working with Fortune 500 companies and industry leaders as a writer, editor, content manager, and consultant. He is an online content specialist with an academic background in mechanical engineering, nanotechnology, and scientific research. Samir is also a featured author in 30+ industrial magazines with a focus on Artificial Intelligence (AI), the Internet of Things (IoT), 3D printing, Autonomous Vehicles (AV), nanotechnology, materials science, and sustainability. His experience includes award-winning engineering research and patented engineering design in the fields of nanofabrication and microfluidics." target="_blank" rel="noopener noreferrer" class="button-main-action">Register for free now</a>

Credit: Evan Stoddard, Advanced Applications Group Embedded Software Engineer at Avnet

Mohammed Dogar, Vice President, Head of Global Business Development & Ecosystem, and Jeff Sieracki, Director of AI COE, will sit with tech writer Samir Jaber to unpack the Reality AI Tools suite and discuss their impact on Edge AI applications.

Webinar: Powering Edge and Endpoint Applications - A deep dive into Reality AI Tools® from Renesas

Space exploration has captivated humanity for decades with its promise of adventure and scientific discovery. But venturing beyond our atmosphere comes with immense challenges. This is where a new wave of technology is poised to revolutionize the space industry: artificial intelligence (AI) and robotics.&nbsp;This episode of the BrainChip podcast is a conversation between BrainChip CTO Dr Tony Lewis and Mikhail Asavkin, founder of Australian space tech company ANT61. They talk about how AI and intelligent robots are no longer science fiction but the key to unlocking the future of space exploration.&nbsp;<h2 dir="ltr">Reusable Rockets and the Democratization of Space</h2>Over the past decade, we have witnessed a remarkable transformation propelled by innovation and the rise of private industry in the space sector. The ability to recover and relaunch rockets has dramatically reduced the cost of space access, opening the door for a new era of private space exploration companies.&nbsp;This democratization of space has spurred innovation and ignited a global race to push the boundaries of what's possible. Mikhail Asavkin, drawing from his extensive experience in space engineering, sheds light on this evolutionary journey and explains how companies like ANT61 are now able to focus their resources on cutting-edge technologies like AI and robotics, thanks to the more affordable launch options provided by reusable rockets.&nbsp;This shift has fundamentally changed the landscape of space exploration, making it a more accessible and dynamic field.<h2 dir="ltr">The Impact of AI on Space Exploration</h2>Mikhail Asavkin and Dr Tony Lewis also discuss the transformative role of AI in space exploration. Here's why AI is the silent hero propelling us further into the cosmos:<ul><li dir="ltr">Due to the speed of light, communicating with robots on the Moon or Mars in real time is impossible. This is where AI steps in. By enabling robots to make autonomous decisions based on sensor data and their surroundings, AI eliminates the need for constant human intervention from Earth.</li><li dir="ltr">Space exploration demands more than just following pre-programmed instructions. Robots must be able to perceive their environment, identify objects, and navigate complex situations. Advancements in AI, particularly image recognition and deep learning, allow robots to "see" and understand their surroundings, enabling them to perform intricate tasks and make critical decisions independently.</li></ul><h2 dir="ltr">Neuromorphic Computing in Space</h2>The limitations of traditional AI systems, particularly their high power consumption, pose a significant challenge for space exploration. Here's where neuromorphic computing enables new ways of exploring space.&nbsp;Inspired by the structure and function of the human brain, neuromorphic chips are designed to process information similarly. This translates to a dramatic reduction in power consumption compared to traditional AI hardware like GPUs (Graphics Processing Units). For spacefaring robots, this is a game-changer.Neuromorphic technology offers a multitude of benefits for space AI:<ul><li dir="ltr">Neuromorphic chips enable this dream by requiring significantly less power to perform complex tasks like object detection and real-time decision-making.</li><li dir="ltr">Neuromorphic chips excel at real-time processing, allowing robots to make critical decisions without delay. This is essential for tasks like navigating hazardous terrain or performing delicate scientific operations.</li></ul><h2 dir="ltr">Training AI on the Go</h2>Traditionally, training AI models involves massive datasets downloaded from Earth and meticulously labeled by humans – a time-consuming and impractical process in the vast expanse of space.Neuromorphic computers, with their ability to learn and adapt in real time, make this possible. The AI model can continuously improve its capabilities and decision-making abilities by processing sensor data and surroundings. By training on-site, the AI model can adapt to specific situations and environments, making its tasks more robust and efficient.However, the podcast also discusses a significant challenge that remains: ensuring the safety and well-being of human explorers venturing into the unknown. This necessitates further advancements in AI, particularly in areas like risk assessment, anomaly detection, and real-time decision-making.<h2 dir="ltr">Conclusion: New Era in Space Exploration</h2>From enabling autonomous robots to construct lunar habitats to empowering AI models to learn and adapt on the fly, these technologies are revolutionizing how we venture beyond our planet. As we look towards a future where humanity establishes a presence on other celestial bodies, AI and robotics will be our indispensable companions.Listen to the full podcast <a href="https://www.youtube.com/watch?v=yyVWVjYM-nQ&t=3s" target="_blank" rel="noopener noreferrer">here.</a>

In this episode, ANT61 Founder and CEO Mikhail Asavkin joins BrainChip CTO Dr. Tony Lewis to discuss the evolution of Space Technology and its impact on daily life. 

BrainChip Podcast: Robotics in Space discussion with ANT61 Founder Mikhail Asavkin

Have you ever wondered how the next generation of space exploration would be powered? The answer might lie in artificial intelligence (AI), and a new frontier is emerging: AI in space.&nbsp;This episode of the Brain Chip podcast explores the vital role of BrainChip in pushing AI to new frontiers through Akida, which was recently launched into space aboard the Transporter 10 spacecraft, alongside Dr. Tony Lewis, BrainChip’s CTO, and experts from the European Space Agency (ESA) Laurent Hili and Luis Mansilla.<h2 dir="ltr">The Rise of New Space&nbsp;</h2>The podcast begins by highlighting the dramatic shift in space exploration. Gone are the days of solely government-driven endeavors. Private companies like SpaceX are making space more accessible, leading to a new era of "New Space." This increased activity necessitates advancements in spacecraft autonomy and mission efficiency.One solution gaining traction is AI. Implementing AI systems directly on spacecraft can automate complex tasks, freeing human astronauts for critical decision-making and exploration activities. Additionally, onboard AI can analyze data in real time, enabling faster responses to unforeseen situations and optimizing mission parameters. However, the podcast emphasizes the challenges of using traditional AI hardware in space.<h2 dir="ltr">Neuromorphic Computing: A Promising Path Forward</h2>The podcast also explores the complexities of implementing AI in space. One of the most significant hurdles is power consumption. Traditional AI hardware can be power-hungry, a major constraint for spacecraft with limited energy resources. As discussed, traditional computing struggles with the power constraints of space.&nbsp;This is where neuromorphic computing emerges as a game-changer. Unlike conventional processors that rely on the von Neumann architecture, neuromorphic computing takes inspiration from the human brain.Here's how neuromorphic computing breaks the mold:<ul><li dir="ltr">Mimic the brain's structure for parallel processing and potential efficiency gains.</li><li dir="ltr">Consume significantly less power, which is crucial for space where every watt counts.</li><li dir="ltr">Can be tailored for specific AI tasks, further boosting efficiency.</li></ul>While still young, neuromorphic computing holds immense promise for space AI.This is where AI comes in. Artificial intelligence has the potential to revolutionize space exploration by enabling:<ul><li dir="ltr">Onboard decision-making: AI algorithms could analyze sensor data and make real-time decisions without relying on constant communication with Earth, which vast distances and time delays can hinder.</li><li dir="ltr">Autonomous operations: Spacecraft equipped with AI could perform tasks like navigation, anomaly detection, and even scientific data analysis with minimal human intervention.</li><li dir="ltr">Data reduction and filtering: AI can sift through vast amounts of data collected by space instruments, identifying valuable information and reducing the amount that needs to be transmitted back to Earth, saving precious bandwidth.</li></ul><h2 dir="ltr">ESA's Multifaceted Approach to AI in Space</h2>The podcast goes beyond just neuromorphic computing, showcasing the multifaceted approach of the European Space Agency (ESA) to integrating AI into various space missions. As highlighted by ESA, they are exploring AI applications across different departments, including:<ul><li dir="ltr">Beamforming and anti-jamming technologies for improved communication and signal strength.</li><li dir="ltr">Maritime applications such as ice bear detection for environmental monitoring.</li><li dir="ltr">Earth observation tasks like analyzing data from the new SC of the Cloud.</li></ul>They also discussed ESA's adoption of the NASA Technology Readiness Level (TRL) system to assess the maturity of AI technologies for space use. This standardized approach helps prioritize development efforts and ensures that technologies are adequately tested before flight.<h2 dir="ltr">BrainChip's AK100</h2>The podcast discusses BrainChip's AK100 chip and its potential role in ESA's space missions. BrainChip reveals that the AK100 chip is currently at TRL 3, indicating it's in the early stages of development. Further work is required to harden the technology for space environments, including rigorous testing for radiation resistance and mitigation strategies.<h2 dir="ltr">Conclusion: A Collaborative Future for AI in Space</h2>The BrainChip podcast episode offered a glimpse into the exciting and complex world of AI in space. While challenges remain, particularly regarding power consumption and technology validation, the potential benefits of AI for space exploration are undeniable. The collaboration between ESA and BrainChip exemplifies the innovative spirit driving this new frontier.

Listen in as Dr. Tony Lewis, BrainChip's CTO, Laurent Hili (Microelectronics Engineer), and Luis Mansilla (AI Expert) discuss the growing role of AI in space exploration, ESA's investments in this technology, and how BrainChip's Akida chip contributes to this exciting frontier

BrainChip Podcast: Insights on SpaceTech With European Space Agency ESA.

Embedded World 2024, held at Nuremberg Messe from April 8 to 11, was a brilliant event for all engineers, designers, and researchers involved in embedded systems.&nbsp;With almost a thousand exhibitors and a huge schedule of related events, Embedded World has really lived up to its reputation of showcasing the industry's cutting-edge.&nbsp;Wevolver team members took the chance to meet engineers from all over the world. Here are some of the highlights.&nbsp;<h2>OKdo: LLMs at the edge.&nbsp;</h2>At Embedded World 2024, <a href="https://www.wevolver.com/profile/okdo" target="_blank" rel="noopener noreferrer">OKdo</a> - a key player in single-board computing and IoT solutions - &nbsp;showcased its significant advancements in industrial computing technologies. One of the highlights was the display from <a href="https://www.liquid.ai/" target="_blank" rel="noopener noreferrer">Liquid AI</a>. Liquid AI is developing a new generation of AI foundation models built from first principles - going beyond generative pre-trained Transformers (GPTs). Liquid neural net technologies unlock efficiency, robustness, explainability, and state-of-the-art performance. Generative AI on the edge (for exampl,e on a Raspberry Pi 5 or Rock 5a) becomes possible.&nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEzOTUxMTA5ODUwLU9LIHN0YW5kLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 100%px;" class="fr-fic fr-dib">The OKdo Embedded World stand. Credit: OKdo.<h2>Enabling cutting-edge PCB design</h2>Altium, a PCB design software company, &nbsp;introduced its new enterprise-grade system, Electronics Lifecycle Management (ELM), a system for enterprise-level hardware design and development, which was a featured presentation in the Exhibit Hall. The booth experience also featured live demos of solutions, including Altium Designer, Altium 365, Nexar API, and Octopart. Altium is transforming electronic development by allowing anyone in the electronics industry to connect with team members and partners and with solutions and data to work more productively.&nbsp;“Altium is uniquely positioned to reshape the future of electronics development and production. We were extremely excited to share our vision of a transformed industry ― which is fast becoming a reality ― with the world’s leaders in embedded technology at Embedded World 2024.” – VP Enterprise Marketing, Altium, Naomi Hamels&nbsp;See Altium in action below:&nbsp;<iframe width="640" height="360" src="https://www.youtube.com/embed/aZeWMmDGFKg?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true" data-gtm-yt-inspected-9="true" id="253684619" title="Altium at Embedded World 2024" data-gtm-yt-inspected-23="true">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</iframe><h2>Exploring NXP's advancements in motor control and TSN communication&nbsp;</h2>At Embedded World 2024, NXP showcased advancements in smart edge technologies aimed at improving device automation and connectivity. They introduced new technologies and products for various markets, including automotive, industrial, and smart home sectors. Demonstrations highlighted NXP's solutions for software-defined vehicles, smart home interoperability, and industrial automation. The event also featured expert-led tours and demonstrations exploring AI, edge computing, and more.<iframe width="640" height="360" src="https://www.youtube.com/embed/fFeo0q6AdWA?&amp;feature=youtu.be&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true" data-gtm-yt-inspected-9="true" id="597216751" title="Wevolver at Embedded World: NXP Semiconductors" data-gtm-yt-inspected-23="true">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</iframe><h2>The latest in automotive local dimming control with Synaptics</h2>AT EW 2024, Synaptics launched its <a href="https://www.synaptics.com/products/embedded-processors" target="_blank" rel="noopener noreferrer">Astra platform</a> of AI-native embedded processors designed to enhance the capabilities of Internet of Things (IoT) devices. This platform focuses on providing multi-modal, AI-enabled microprocessors (MPUs) and microcontrollers (MCUs) that are optimized for power efficiency and high performance. Astra supports a unified software experience across various operating systems and includes an adaptive AI framework, which facilitates the integration of AI into devices. It also offers robust connectivity solutions, such as Wi-Fi and Bluetooth, and is designed to help developers easily incorporate AI features into their products.During our visit, we also got to see their SmartBridge technology live. This advanced automotive display processor is a local dimming IC that supports large, high-contrast, high-resolution automotive LCDs while consuming lower overall power and cost. SmartBridge can handle up to 30-inch displays and 6k resolutions. It leverages a proprietary algorithm to analyze incoming images and control the brightness of each LED in the array.&nbsp;<iframe width="640" height="360" src="https://www.youtube.com/embed/xGelGpfUJFw?&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true" data-gtm-yt-inspected-9="true" id="506257900" title="Wevolver at Embedded World: Synaptics Incorporated" data-gtm-yt-inspected-23="true">&nbsp;&nbsp;&nbsp;&nbsp;</iframe><h2>Code reading with MVTec Software</h2>At the Embedded World 2024, <a href="http://www.mvtec.com" target="_blank" rel="noopener noreferrer">MVTec Software</a> showcased its extensive portfolio of machine vision software, prominently featuring their products HALCON and MERLIC. These products are designed to integrate seamlessly with various hardware configurations, supporting a broad spectrum of operating systems, AI accelerators, CPUs, and embedded boards. The company emphasized the adaptability of their software to different industrial needs, making it suitable for smart cameras, sensors, and other embedded vision applications.MVTec's presentation revolved around the theme "Embedded Vision = YOUR Hardware + OUR Software," underscoring the customizable nature of their solutions to enhance hardware capabilities with sophisticated vision software. This approach not only facilitates enhanced performance and compatibility across different machine vision standards like GigE Vision, GenICam, and USB3 Vision but also promotes quicker time-to-market for products developed using their systems. The technologies highlighted include advanced features for code reading, optical character recognition (Deep OCR), and deep learning applications such as anomaly detection.<iframe width="640" height="360" src="https://www.youtube.com/embed/CHitadg5uKg?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true" data-gtm-yt-inspected-9="true" id="37302711" title="Wevolver at Embedded World: MVTec Software Demo" data-gtm-yt-inspected-23="true">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</iframe><h2>The 2024 State of Edge AI Report</h2>At Embedded World we were thrilled to share the 2024 State of Edge AI Report with you. &nbsp;This report represents months of hard work, research, and dedication to exploring the dynamic world of Edge AI applications across industries.<h3>Report Highlights:</h3>#1: Industry-specific insights– Each industry is covered by a dedicated chapter that provides industry-specific insights, descriptions, and examples. ,#2: Real-life case studies – Get comprehensive insights from featured sections of real-world case studies.&nbsp;#3: A look into the future - The report also provides a peek into the exciting generative AI technology and its convergence with edge computing before delving into the challenges still hindering Edge AI today.We hope you download the report below!&nbsp;<iframe width="540" height="665" src="https://c8056756.sibforms.com/serve/MUIFAIvLRE9FbYyICZVAlYl6oaSYA1y_4gbHWS82SbbrrHstSB6VMs2aj57Tvg0e16L_UZVprsukgYH2yB927lpe-0uPg3ZEAhJiDPRQb2_oMEFQLYiEcG6zXHV6DwzxZPaJo25g3EzCRsYZ5z3ey0dkbIZE_M-AQ1kRN3i2_dq-vjEv7FQC29p_-Vu8tD5vbyaerZZF9IYqTQ8D" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true" data-gtm-yt-inspected-9="true" data-gtm-yt-inspected-23="true">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</iframe>

Wevolver was present at the recent Embedded World event in Nuremberg to launch the 2024 Edge AI report. 


Embedded World 2024: Trends, Tech, and Trailblazers

Our new report, AI at the Edge: Technology Accelerated by Wi-Fi Services, dives deeply into the convergence of Wi-Fi services and Edge AI and explores how a technology model like WaaS can accelerate the adoption of AI at the edge.&nbsp;Below is an excerpt from the final chapter of the report. To read the full report, including in-depth case studies, download it now.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzExMTI0MjE4NTYyLVJlbGF5IDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;</iframe>The next years of this decade are going to be extremely exciting for AI, particularly Edge AI. And with Wi-Fi Services like Relay2 revolutionizing the access point market, the future is going to be very promising indeed. The surging demand for AI applications that offer real-time, low-latency, and privacy-conscious capabilities will usher in a wave of Edge AI implementations. These deployments are poised to become increasingly precise and efficient, capitalizing on advancements in communication networks, such as Wi-Fi 6, coupled with innovations in artificial intelligence (such as data-efficient AI) and the Internet of Things (IoT).&nbsp;This transformative landscape underscores the pivotal role played by researchers, industry leaders, and open-source communities in steering the trajectory of Edge AI development. The evolution of efficient Edge AI applications relies on the progress of various technologies designed to support edge devices and enhance the computational efficiency of AI functions, including Wi-Fi services.<h3 dir="ltr">Increased Adoption &amp; Integration with Edge AI</h3>As the demand for real-time processing and low-latency applications continues to surge, the integration of Edge AI with Wi-Fi services will follow suit. The agility and scalability of Wi-Fi seamlessly complement the requirements of edge computing and AI. For instance, the latest generation of Wi-Fi, Wi-Fi 6, promises much faster data transfer speeds that can reach up to five times the speeds of Wi-Fi 5. This is complemented by reduced power usage, increased capacity, and enhanced performance, providing higher connection reliability in environments with multiple connected devices. This is where Relay2 sets a standard with its Wi-Fi services, pushing for innovation that leverages advancements like Wi-Fi 6. With a dynamic system that ensures flexibility and security, Relay2 offers virtual access control and simultaneous HD video sessions that can support up to 128 sessions. This is further supported by high performance and management of heavy traffic, capitalizing on an average throughput DL that exceeds 2 Gbps and handles 1,024 clients concurrently.This is bound to grow and enhance the adoption and integration with Edge AI in order to enrich the user experience. By implementing AI at the edge for efficient data processing and leveraging Relay2’s proactive real-time analysis and natural language adaptability, businesses and organizations can elevate their user experience beyond merely improving connection reliability. This synergy allows for efficient processing closer to data sources, reducing latency and enhancing overall system responsiveness.With Wi-Fi 7 being the next generation of Wi-Fi, we could see an even more seamless and immersive user experience and an advanced Edge AI performance, building on its new features such as multi-link operation (MLO), 320 MHz superwide channels, and a 4k quadrature amplitude modulation (QAM). This convergence of state-of-the-art communications and information technologies, such as cloud-native Wi-Fi services, edge computing, IoT, and AI, is driving a massive leap in management efficiency and social productivity. The hybrid edge-cloud architectures and applications are likely to surge in the very near future, ensuring not only high speed and efficiency but also the ability to run multi-modal generative AI and language models at the edge . In the second half of this decade, we will arguably witness an unprecedented increase in the adoption of Edge AI across numerous applications, rendering the technology mainstream.<h3 dir="ltr">Computer Vision &amp; the Impact of Edge AI and Wi-Fi</h3>One area where the convergence of Edge AI and Wi-Fi services is poised to have a high impact is computer vision applications. With the capability to process data locally, Wi-Fi-empowered edge devices can execute intricate computer vision tasks with unparalleled speed and efficiency. This transformative shift not only minimizes reliance on centralized cloud servers but also allows positioning systems to optimize energy and costs, enabling applications such as facial recognition, object detection, and automated surveillance to operate seamlessly in real time.With localization techniques such as Wi-Fi-based positioning systems (WPS) and the advent of convolutional neural networks (CNNs), we can detect and extract spatial patterns from visual data in a remarkable manner. This has the potential to transform industries, including healthcare, retail, automotive, and traffic management. Combining the high-processing capabilities of cloud computing with the real-time features of edge computing and the connectivity enhancements brought about by Wi-Fi technologies can enable AI to lift computer vision to a different level. Consider industrial automation in large factories and warehouses, smart cities with optimized traffic control, retail centers and shopping complexes with enhanced services and store layouts based on monitored customer behavior, and even remote medical services and patient monitoring that enable accurate diagnosis in real time. All these developments can take place by leveraging computer vision that is powered by AI at the edge.While there are still challenges standing before computer vision today, such as high processing power and high-quality data, the potential that Edge AI brings, supported by Wi-Fi capabilities that ensure fast and seamless data transfer - even in remote areas where accessibility would otherwise be difficult - will propel computer vision and enable it to be a much more potent and ubiquitous technology.&nbsp;With on-device inference capabilities and functionalities that enable computer vision within edge and mobile devices, image and pattern recognition can improve significantly, taking advantage of edge computing’s reduced latency, enhanced security, and minimized costs. Integrating AI into the mix enables even low-cost cameras to act as smart cameras, with deep learning methods enabling better identification and interpretation of data patterns. This is further enhanced by leveraging data from multiple devices connected via Wi-Fi, which provides AI with more comprehensive data, reinforcing its precision and understanding.<h2 dir="ltr">Conclusion: Wi-Fi-Powered Edge AI - A Technology for the Future</h2>Wi-Fi and Edge AI represent a technological paradigm shift with far-reaching implications. The convergence of Wi-Fi with Edge AI is not just a technological evolution but a fundamental reshaping of the digital landscape. As this symbiotic relationship matures, it propels us towards a future where Edge AI is not just a technology but an integral and indispensable part of our interconnected world. The potential for transformative applications is immense, urging both developers and sellers to explore the uncharted territories of innovation and contribute to the unfolding narrative of Edge AI's promising future.This not only addresses the computational needs of Edge AI but also aligns with the growing trend of connected devices in smart buildings, industrial settings, healthcare, retail, and smart cities. The integration of Edge AI with Wi-Fi services brings forth a boost in performance, user experience, and security measures, ensuring that sensitive data is processed locally. This transformation leads to the development of robust, always-on systems capable of meeting the stringent privacy requirements of contemporary applications and the ever-growing need for better performance, flexibility, scalability, and reliability.Throughout this report, we explored the capabilities and impact of Edge AI, especially when coupled with Wi-Fi services. We highlighted the valuable insights provided by Relay2, the leading Wi-Fi technology provider for the Edge AI market. Relay2's Service Points technology is designed to deliver exceptional application performance while enhancing security, privacy, and scalability at the edge.&nbsp;The Relay2 ServiceEdge Platform harnesses the power of Wi-Fi Services with Edge Computing to create a digital world where application performance and user experience not only remain uncompromised but are also enhanced. We also dove into particular applications and reviewed some use cases of Wi-Fi services edge computing. And finally, we took a look at the future of these technologies and how they will impact our businesses and way of living in the coming years. All this could not have been done without the support of Relay2 in developing this report.&nbsp;Relay2 is committed to empowering its partners by providing comprehensive, innovative solutions to ensure mutual success leveraging Wi-Fi Services with Edge Computing and the Relay2 ServiceEdge Platform. Therefore, developers and sellers are encouraged to partner with Relay2 to unlock the full potential of technology and shape a seamless digital future. The convergence of Wi-Fi with Edge computing can reshape the digital technology and business landscape, and Relay2 is at the forefront of this transformation.<h2 dir="ltr">Acknowledgments</h2>This report is the result of collaborative efforts between Wevolver and Relay2. Initial input was graciously provided by Relay2’s Eric Chen and Daniel Kwong, sharing their insights, expertise, and case studies, creating a robust technical substructure for the report. Then, the author further expanded upon this information to develop a comprehensive and insightful text, supported by the content and design team at Wevolver. Thank you to all contributors and supporters, and special thanks to Relay2.Download the full report with custom images, case studies and more, below.&nbsp;<iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;</iframe><h3 dir="ltr" id="isPasted">Read excerpts of the report chapters:</h3>Chapter 1: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-1-wi-fi-analytics-services-enabling-edge-ai" rel="noopener noreferrer" target="_blank">Wi-Fi Services Enabling Edge AI</a>Chapter 2: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-2-relay2-and-edge-ai" rel="noopener noreferrer" target="_blank">Relay2 and Edge AI</a>&nbsp;Chapter 3: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-3-applications-case-studies" rel="noopener noreferrer" target="_blank">Applications &amp; Case Studies</a>

The coming years will see a surge in Edge AI advancements, driven by real-time, efficient, and privacy-focused AI applications, alongside innovations in Wi-Fi and IoT, marking a promising future shaped by researchers, industry leaders, and open-source contributions.

AI at the Edge Report. Chapter 4: Future of Edge AI with Wi-Fi Technology

Our new report, AI at the Edge: Technology Accelerated by Wi-Fi Services, dives deeply into the convergence of Wi-Fi services and Edge AI and explores how a technology model like WaaS can accelerate the adoption of AI at the edge.&nbsp;Below is an excerpt from Chapter 3 of the report. To read the full report, including in-depth case studies, download it now.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwNTE0NjU1NDU5LVJlbGF5IDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;</iframe>The applicability of Wi-Fi Edge AI is fairly expansive and is growing by the day, spanning various industries and application areas. The most central aspects of this intersection of technologies are the real-time insights they provide, how these insights impact the speed and type of response, and how they are communicated across the network. Whether it is in smart healthcare, education, retail, or other application areas, Wi-Fi-enabled Edge AI is redefining how technology is leveraged in real time. Relay2 utilizes several Edge AI platforms to enhance the functionality of AI applications on the edge. In this chapter, we will take a look at some interesting use cases of Wi-Fi Edge AI, and we will see the impact of this technology convergence and the new opportunities it is opening in new and emergent technological spaces.<h2>Education / Smart Campus</h2>Wi-Fi Edge AI plays an important role in education-related applications, among which is remote learning integration, facilitating seamless and interactive remote education and bridging the gap between on-site and remote learning experiences. With localized content engagement pattern analysis and personalized experiences for students, Wi-Fi services and edge computing can help enhance and refine education content delivery.&nbsp;Campus facilities can also benefit significantly from integrating such technologies, especially in terms of security and surveillance, where Wi-Fi Edge AI can help analyze surveillance videos locally and in real time to recommend timely actions for security staff. It also powers use cases like attendance automation and traffic patterns, streamlining attendance tracking for educators and student flow analysis for operation enhancement.&nbsp;Another use case of Wi-Fi and edge computing can be seen in revenue generation, in which they enable intelligent, location-based advertising through audience behavior analysis for commercial partners. By leveraging these technologies, educational institutions can help promote campus services better, boost product marketing across campus premises and beyond, and enable efficient digital transactions.One example of applying Wi-Fi and edge computing in education is by WENet, an OEM partner of Relay2 in Vietnam. In order to support the University of Transport Technology in Vietnam in developing a digital technology infrastructure platform, WENet deployed Relay2’s Wi-Fi-enabled edge computing solution, making use of the advantages provided by Relay2 ServiceEdge Platform compared to conventional Wi-Fi networks. From stable bandwidth to fast processing speed, short deployment time, minimal service interruption time, and optimal operating costs, the features brought about by Relay2’s ServiceEdge Platform were highly effective. As a result, over 17 thousand students across three campuses were able to benefit from this platform, especially in terms of the following three key functions:<ul><li>Digital signage interacting with mobile devices to support two-way communication (university-to-student communication and student responses to university requests)</li><li>Students’ access to digital education materials from Relay2’s Service Points</li><li>Students’ ability to order food digitally from the cafeteria</li></ul>Such functions have not only enabled students to benefit from a Wi-Fi-powered edge computing platform but also helped collect analytic data for future AI processing at the edge. Read more about the WENet use case on the Relay2 website.<h2>Smart Healthcare</h2>Undoubtedly, one of the most important aspects of healthcare is real-time monitoring and real-time decision-making. However, as we have seen over the recent years with pandemic-caused crises, healthcare workers are more often than not overworked, and hospitals are resource-limited, which can limit their abilities to provide timely care. In order to ensure patient safety and health within hospital spaces and elsewhere, it is crucial to track, monitor, analyze, and act in real-time. All this can be made available by incorporating Edge AI and Wi-Fi. Whether it is remote monitoring and management, patient activity tracking, patient care, or even assistance during healthcare crises, hospitals, and medical personnel can benefit significantly from integrating Wi-Fi Edge AI into their processes.Smart healthcare comes in the form of connected healthcare, where AI-based smart devices, healthcare management software, and digital instruments are integrated into a “connected” healthcare system using a network protocol like Wi-Fi. As such, medical personnel would have access to all the medical-related information they need to provide the patients with the necessary medical treatment in the most effective and convenient way possible. This has been made possible by utilizing Edge AI and Wi-Fi technologies to empower the Internet of Medical Things (IoMT). In other words, healthcare personnel can leverage the low-latency capabilities of Edge AI processing and the ubiquity of Wi-Fi connectivity to access real-time data from diverse medical sensors, enabling timely decision-making and interventions and fostering a proactive approach to patient care.Consider intensive care units (ICUs), operating rooms, or other healthcare spaces, the use of Edge AI and Wi-Fi can augment the work of doctors, nurses, and clinicians by minimizing limitations, redundancies, and time allocated to activities away from direct patient care (such as documentation). As a result, medical workers can benefit from an emerging ambient intelligence , powered by edge computing, AI capabilities, and Wi-Fi. This can even be expanded to daily living spaces, which would support independent living, chronic disease management, mental health, and physical rehabilitation, particularly of elderly individuals.<h2>Smart Retail</h2>Global retail is almost always in flux, and both retailers and suppliers are grappling with the complexities of ever-changing consumer demand, behavior, and expectations. The continuous shifts in these dynamics create uncertainties in predicting future trends and exert significant stress on international supply chains and store operations. Navigating these challenges necessitates real-time adaptability to stay ahead in the retail industry.Edge AI emerges as a potent solution, offering retailers the capability to swiftly and precisely forecast daily demand while automating crucial aspects of supply chain logistics, customer engagement, and operational agility. This not only addresses challenges related to in-store supply management but also tackles issues in last-mile delivery costs, aligning with consumer expectations regarding timely deliveries.Within physical stores, retailers leverage Edge AI to combat issues such as shrinkage and stockouts, optimizing inventory management. Simultaneously, the application of Edge AI and Wi-Fi contributes to the creation of frictionless in-store experiences while prioritizing the health and safety of both employees and shoppers. The integration of AI in retail is thus transforming operations, offering a multifaceted approach to address the intricate challenges posed by the dynamic retail landscape.D.Phone, one of the largest cell phone retailers out of China, has deployed in-store Wi-Fi to enhance its customer experience and promote engagement as a way to offer a differentiated experience that would distinguish its &nbsp;D.Phone stores from competitors. They opted for Relay2’s wireless broadband solution, taking advantage of its unified native-cloud wireless networking and edge-service delivery.By leveraging Relay2 access points, D.Phone was able to offer high-quality customer experiences and deliver value-added services in-store. With its fast and reliable coverage in demanding environments like customer-dense spaces, including shopping centers and large venues, Relay2 access points enabled D.Phone to meet its customers' expectations and offer them the high-speed connectivity they desire. Moreover, with Relay2’s Edge services, D.Phone was able to run sales-generating applications and computation-intensive services locally and place content right at its &nbsp;D.Phone customers’ fingertips, thus reducing content download time to just seconds. This helped streamline the customer purchasing experience and circumvent bandwidth bottlenecks. It even enabled D.Phone to deliver new services to its customers, including app delivery and couponing. This has displayed an accelerated go-to-market process for D.Phone’s digital merchandise and a reinforced branding strategy. Read more about the D.Phone use case on Relay2’s website.<blockquote>“Relay2’s plug-and-play access points and cloud-based platform [have] given us a solution that lowers the cost of deployment and management.” - Wu Huan, CIO, D.Phone</blockquote><h2>Smart Buildings</h2>With the recent growth in smart homes and building automation systems, edge computing, AI, and Wi-Fi have become increasingly popular in this space. The integration of Edge AI with sustainable architecture and smart buildings has been rapidly gaining momentum and transforming the manner in which we construct and interact with our built spaces. With advantages like enhanced energy efficiency, optimized systems, personalized occupant comfort, and streamlined building maintenance, smart buildings are leveraging the real-time analysis capabilities of Edge AI and its integration with IoT and developing potential for more sustainable architecture and digital integration.Acting as a centralized intelligence hub, AI processes and interprets data obtained from an array of edge devices (IoT devices) such as sensors and actuators scattered throughout the building. This network of devices forms a comprehensive information system, providing valuable insights into various aspects of the building's operations. Through the implementation of AI algorithms, smart buildings gain the ability to efficiently monitor and regulate crucial functions like lighting, heating, ventilation, air conditioning, security, and energy consumption. Such an integration results in an environment that is not only responsive but also adaptive, catering to the dynamic needs and preferences of the building occupants.This can be further supported by Wi-Fi connectivity and cloud-based Wi-Fi services, in particular. Cloud-based Wi-Fi services enable centralized management and control of Wi-Fi networks. This centralized approach simplifies the deployment and maintenance of Wi-Fi connectivity across the building, ensuring a more streamlined and scalable infrastructure. Furthermore, the cloud facilitates the storage and analysis of the vast amounts of data generated by IoT devices in Smart Buildings. AI algorithms require substantial data inputs to make informed decisions, and cloud-based services offer the computational resources needed for processing and interpreting this data. It enables more sophisticated analytics, allowing for better insights into building operations, occupant behaviors, and energy consumption patterns.&nbsp;Similarly, the cloud's scalability can easily accommodate the dynamic nature of Smart Buildings, especially when the number of connected devices grows or changes. Just as importantly, cloud-based services enable remote monitoring, management, and updates of Wi-Fi networks and connected devices. This remote accessibility is invaluable for building administrators, allowing them to troubleshoot issues, implement updates, and optimize network performance without physically being on-site. In this regard, smart buildings can benefit meaningfully from Relay2’s innovative solutions. With advanced networking capabilities, Wi-Fi Edge Computing power, and intelligent analytics, users of Relay2’s ServiceEdge platform can ensure seamless connectivity and optimized operational efficiency.<h2>Smart Agriculture</h2>The Internet of Things (IoT) and edge computing have influenced the agricultural and farming industries quite extensively over the past decade, especially with the rapid rise of low-power wide-area networks (LPWAN) . Wireless communication protocols are, in fact, a vital part of smart agriculture systems, especially since the fields cover large areas that necessitate system components to be placed at remote locations. The integration of Wi-Fi and edge computing has been key to expanding the digital functionalities in agriculture, especially with the advent of AI at the edge, thus increasing the possibilities of smart agriculture over large areas.One type of smart agriculture that has been propelled by Edge AI and Wi-Fi services is precision farming. By deploying sensors and cameras in fields, farmers can gather real-time data on crucial factors such as weather patterns, soil conditions, crop growth, and pest infestations. This localized data processing enables farmers to modify and regulate their irrigation, fertilization, and pest control without delay, leading to an increase in crop yields and resource efficiency. The implementation of edge devices equipped with sensors extends beyond crop monitoring to include livestock health and behavior. Wearable devices on animals, such as cattle, provide early indications of illness or oestrus, empowering farmers to take timely actions, resulting in improved animal well-being, reduced rates of mortality, and higher farm productivity all around.&nbsp;Furthermore, the incorporation of Edge AI has paved the way for autonomous farming machinery, where tractors and drones equipped with edge devices can analyze field data in real time. This enables them to refine their routes, control planting depths, and identify and eliminate weeds in an autonomous manner. Not only does autonomous farming machinery reduce labor costs, but it also minimizes the use of chemicals, aligning agriculture with more eco-friendly practices. This is further empowered with the integration of Wi-Fi Services, allowing for centralized, remote monitoring and seamless connectivity between edge devices across large fields and in remote areas. The seamless integration of Edge AI and Wi-Fi technologies is proving transformative in making agriculture smarter, more efficient, and more sustainable over expansive agricultural landscapes.Relay2 offers smart farms state-of-the-art solutions that can help transform crop production, efficiency, and sustainability. These solutions seamlessly connect and monitor agricultural devices, collect real-time data, and leverage advanced analytics for informed decision-making. By optimizing resources, automating processes, and implementing precision farming, Relay2 empowers farmers to maximize yield and sustainability.<hr>This was an excerpt from Chapter 3 of the AI at the Edge: Technology Accelerated by Wi-Fi Services report. If you would like to read the full report, including in-depth case studies, you can download it below. &nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwNTE0ODA2OTE3LVJlbGF5IDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;</iframe><h3 dir="ltr" id="isPasted">Read excerpts of the other report chapters:</h3>Chapter 1: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-1-wi-fi-analytics-services-enabling-edge-ai" rel="noopener noreferrer" target="_blank">Wi-Fi Services Enabling Edge AI</a>Chapter 2: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-2-relay2-and-edge-ai" rel="noopener noreferrer" target="_blank">Relay2 and Edge AI</a>&nbsp;Chapter 4: <a href="https://www.wevolver.com/article/ai-at-the-edge-report-chapter-4-future-of-edge-ai-with-wi-fi-technology" rel="noopener noreferrer" target="_blank">Future of Edge AI with Wi-Fi Technology</a>&nbsp;

Wi-Fi-enabled Edge AI is redefining how technology is leveraged in real time.

AI at the Edge Report. Chapter 3: Applications & Case Studies

BrainChip Holdings Ltd is a company that specializes in neuromorphic computing. They're known for their innovative approach and strategic vision in the field of artificial intelligence (AI). Their technology aims to redefine how AI is implemented at the edge. This article shares the highlights from their latest investor podcast to provide a holistic view of the company's achievements, strategies, and future direction.<h4 dir="ltr">A Vision for the Future</h4>BrainChip is committed to advancing neuromorphic computing, a cutting-edge field that mimics the neural architecture of the human brain. This approach promises unprecedented efficiency and performance in AI applications, particularly in edge computing scenarios where power and speed are critical.&nbsp;The recent addition of Dr. Tony Lewis to the BrainChip leadership team underscores this commitment. With a rich background in AI, engineering, and neuromorphic technologies, Dr. Lewis brings a wealth of knowledge and a clear vision for the company's future.n this journey. With an illustrious career spanning AI, engineering, and neuromorphic technologies, Dr. Lewis's expertise is set to steer BrainChip towards new horizons.The announcement of Dr. Lewis joining the team heralds a new era for BrainChip, emphasizing the company's dedication to leading the edge in AI technology. Dr. Lewis brings a profound understanding of brain-inspired computing and robotics, with a track record of leading large research groups and pioneering innovations in the field. His appointment is not just a testament to BrainChip's current leadership in neuromorphic computing but also a clear indicator of its ambitious roadmap ahead.Dr. Lewis's background is particularly noteworthy, with a PhD in brain-inspired computing in robotics, positioning him as a perfect fit for BrainChip's mission. His career has been a journey towards this role, marked by significant achievements in neomorphic and robotics research funded by the US government and industrial partners. His experience spans across defense, space, biomedical, environmental monitoring, mobile phones, and personal computers, highlighting a versatile and impactful career.At Qualcomm, Dr. Lewis led the largest research project outside of wireless in corporate R&amp;D, focusing on brain-inspired computing. His foresight into the potential of deep learning and language models has been pivotal, anticipating the significant impact these technologies would have on the industry. His role at HP as the Global Head of the AI and Emerging Compute Lab further honed his skills, preparing him for the challenges and opportunities of being BrainChip's CTO.Dr. Lewis's decision to join BrainChip was driven by the recognition of AI's golden age and the critical role of edge computing in shaping the future. He acknowledges the challenges of cloud processing, including its massive energy consumption and latency issues, underscoring the necessity for efficient, edge-based solutions. BrainChip, with its focus on neuromorphic computing, represents the cutting edge of this transition, offering solutions that are not only technologically advanced but also environmentally conscious and cost-effective.<h4 dir="ltr">Strategic Market Position and Competitive Edge</h4>BrainChip's belief in AI as a significant economic driver is matched by its strategic focus on edge computing. The company's neuromorphic computing platform offers a compelling alternative to traditional AI solutions, providing extreme efficiency, low power consumption, and real-time processing capabilities. This positions BrainChip uniquely in a market that is increasingly moving towards decentralized, edge-based computing solutions.The competitive landscape of AI and neuromorphic computing is diverse, with several players vying for dominance. However, BrainChip sets itself apart through its comprehensive platform that supports a wide range of AI models and applications. The company's IP business model, which includes licensing fees and royalties, offers flexibility and scalability to partners and clients, further solidifying its market position.<h4 dir="ltr">Innovations and Achievements</h4>One of the key highlights from the investor podcast was BrainChip's focus on continuous innovation and product development. The introduction of the AKD1000 processor and the development of the next-generation IP are testament to the company's commitment to advancing neuromorphic computing. These technologies enable a broader range of use cases, from industrial automation to consumer electronics, by supporting more complex AI models and providing easier integration with existing workflows.BrainChip's success is also reflected in its strategic partnerships and collaborations. The company has established relationships with industry leaders, research institutions, and technology developers to enhance its product offerings and expand its market reach. These partnerships not only validate BrainChip's technology but also provide valuable feedback and insights that drive further innovation.<h4 dir="ltr">Looking Ahead: Challenges and Opportunities</h4>As BrainChip continues to navigate the complex landscape of AI and neuromorphic computing, it faces both challenges and opportunities. The fragmented nature of the edge AI market presents a significant challenge, requiring a nuanced understanding of customer needs and industry trends. However, BrainChip's flexible business model and customer-focused approach position it well to adapt and thrive in this dynamic environment.The potential competitive threat from major players like Nvidia moving into the edge computing space underscores the importance of maintaining a competitive edge through innovation and strategic partnerships. BrainChip's commitment to supporting standard machine learning workflows and its unique on-chip learning capabilities provide a strong foundation for sustaining its market leadership.<h4 dir="ltr">Conclusion</h4>BrainChip's journey in the AI industry is marked by bold visions, strategic innovations, and a relentless pursuit of excellence. The company's focus on neuromorphic computing not only sets it apart from competitors but also positions it as a pioneer in the future of AI. With a strong leadership team, strategic partnerships, and a commitment to continuous innovation, BrainChip is poised to lead the generational shift towards efficient, powerful AI at the edge. As the company navigates the challenges and opportunities ahead, its contributions to the field of AI and neuromorphic computing will undoubtedly continue to shape the technological landscape for years to come.

edge processors

Profiles