#Edge AI Hardware

[semiindustry]

Top Trends Transforming the Edge AI Hardware Market in 2025 and Beyond

The Edge AI hardware market is undergoing a significant transformation as demand for faster, more intelligent, and decentralized computing continues to grow across industries. As organizations increasingly turn to edge-based solutions for real-time data processing, enhanced privacy, and improved operational efficiency, new trends are emerging that are reshaping the landscape of edge AI. These developments are not only driving innovation but also unlocking new opportunities for businesses, governments, and technology providers. Here's a look at the top trends that are expected to define the Edge AI hardware market in 2025 and beyond.

Download PDF Brochure @ https://www.marketsandmarkets.com/pdfdownloadNew.asp?id=158498281

One of the most notable trends is the rise of domain-specific AI processors. General-purpose processors are no longer sufficient to meet the growing complexity and performance demands of edge AI applications. As a result, companies are developing customized hardware architectures such as Application-Specific Integrated Circuits (ASICs), Neural Processing Units (NPUs), and Vision Processing Units (VPUs) optimized for particular workloads like computer vision, speech recognition, or natural language processing. These specialized chips deliver superior performance-per-watt efficiency, making them ideal for use in power-sensitive and latency-critical edge environments.

Another trend gaining momentum is the miniaturization and integration of AI chips into everyday consumer and industrial devices. In 2025 and beyond, edge AI hardware will become increasingly compact and embedded in smartphones, drones, wearables, home appliances, medical equipment, and even small-scale sensors. The integration of AI processing into such devices allows for real-time intelligence without external connectivity, enabling new use cases in autonomous systems, personal health monitoring, and intelligent automation.

AI at the edge is also becoming more sustainable, driven by a growing emphasis on energy efficiency and green computing. As edge devices proliferate globally, their cumulative power consumption becomes a major concern. Manufacturers are focusing on reducing energy usage by adopting advanced semiconductor fabrication processes (like 3nm and 5nm nodes), dynamic voltage scaling, and on-device power optimization techniques. These developments are helping companies achieve their sustainability goals while maintaining high performance in edge applications.

The convergence of 5G and Edge AI hardware is another transformative trend. With ultra-low latency, high-speed connectivity, and massive device support, 5G is providing the communication backbone needed for next-generation edge computing. This synergy is particularly impactful in applications such as autonomous vehicles, smart cities, industrial IoT, and immersive augmented/virtual reality (AR/VR). As 5G networks expand globally, they will further amplify the demand for edge AI hardware that can capitalize on the benefits of seamless, real-time connectivity.

Federated learning and on-device model training are reshaping how AI models are built and updated on the edge. Instead of sending raw data to the cloud, federated learning enables devices to train models locally and share only the model updates with a central server. This approach not only reduces bandwidth usage but also strengthens privacy and security. With growing concerns over data ownership and compliance, federated learning is becoming an essential part of edge AI strategies, driving demand for hardware that supports secure, distributed learning.

Another critical trend is the expansion of edge AI across vertical markets, particularly in healthcare, manufacturing, agriculture, and transportation. In healthcare, edge AI hardware is enabling continuous patient monitoring, early diagnostics, and personalized treatment—all without relying on cloud access. In smart factories, edge AI powers predictive maintenance, real-time quality control, and robotics. In agriculture, AI-enabled drones and sensors are revolutionizing crop management and livestock monitoring. This sectoral diversification is fueling robust growth in edge hardware tailored for specific industry needs.

Security and trusted AI at the edge are also gaining importance. With edge devices deployed in the field, often beyond the reach of traditional cybersecurity frameworks, securing hardware and data becomes essential. In response, hardware vendors are incorporating built-in security features such as secure boot, encryption engines, trusted execution environments (TEEs), and anomaly detection. These measures are critical for maintaining trust in AI-driven systems, especially in applications involving sensitive or mission-critical data.

Lastly, the rise of AI-enabled digital twins and metaverse technologies will drive further innovation in edge AI hardware. As physical and digital worlds become increasingly integrated, real-time, edge-based intelligence will be crucial to simulate, visualize, and manage complex systems—whether it’s a manufacturing process, a smart building, or a virtual training environment.

[digitrenndsamr]

Edge AI Hardware Market Is Set to Garner Staggering Revenues By 2030

Allied Market Research, titled, “Edge AI Hardware Market By Component, Device Type, Process, and End User: Global Opportunity Analysis and Industry Forecast, 2021–2030”, the global edge AI hardware market size was valued at $6.88 billion in 2020, and is projected to reach $38.87 billion by 2030, registering a CAGR of 18.8%. Asia-Pacific is expected to be the leading contributor toward the edge AI hardware market during the forecast period, followed by LAMEA and Europe.  

Edge AI hardware is a device that can take decisions & process data independently without any external connection. These edge AI hardware does not have any issue of bandwidth and latency of real-time data, which influence application execution. Real time operations are very crucial in robots and self-driving cars among other applications.

Global edge AI hardware market growth is anticipated to be driven by factors such as emergence of AI coprocessors for edge computing and rise in IoT applications by various end user industries such as automotive and consumer electronics. In addition, increase in real-time low latency on edge devices, boosts the overall market growth. However, power consumption & size constraint acts as a major restraint for the global edge AI hardware industry. On the contrary, rise in demand and adoption of artificial intelligence products & services is expected to create lucrative opportunities for the market.

Moreover, developing nations tend to witness high penetration of edge AI hardware products, especially in the automotive sector, which is anticipated to augment the market growth. Factors such as growing driverless vehicles accelerate the market growth.

The global edge AI hardware market is segmented on the basis of component, device type, process, end user, and region. By component, the market is classified into processor, memory, sensor, and others. Depending on device type, it is categorized into smartphones, cameras, robots, wearables, smart speaker, and others. The process covered in the study include training and inference. On the basis of end user, it is classified into consumer electronics, smart home, automotive, government, aerospace & defense, healthcare, industrial, construction, and others.

Region wise, the edge AI hardware market trend is analyzed across North America (U.S., Canada, and Mexico), Europe (UK, Germany, France, Russia, and rest of Europe), Asia-Pacific (China, Japan, India, Australia, and rest of Asia-Pacific), and LAMEA (Latin America, Middle East, and Africa). The edge AI hardware market size have been analyzed across North America, Europe, Asia-Pacific, and LAMEA. North America contributed maximum revenue in 2020.

However, in between 2020 and 2030, the edge AI hardware market in Asia-Pacific is expected to grow at a faster rate as compared to other regions. This is attributed to increase in demand from emerging economical countries such as India, China, Japan, Taiwan, and South Korea.

Key Findings of the Study

The consumer electronics sector is projected to be the major application, followed by industrial.

Asia-Pacific and North America collectively accounted for more than 61% of the edge AI hardware market share in 2020.

India is anticipated to witness highest growth rate during the forecast period.

U.S. was the major shareholder in the North America edge AI hardware market, accounting for approximately 55% share in 2020.

Depending on component, the processor segment generated the highest revenue in 2020. Also, the processor segment is expected to witness the highest growth rate in the near future.

Region wise, the edge AI hardware market was dominated by North America. However, Asia-Pacific is expected to witness significant growth in the coming years.

The key players profiled in the report include Apple Inc., Google LLC (Alphabet Inc.), Huawei Technologies Co., Ltd., Intel Corporation, International Business Machines Corporation (IBM), MediaTek Inc., Microsoft Corporation, NVIDIA Corporation, Qualcomm Technologies, Inc., and Samsung Electronics Co. Ltd. (Samsung). These players have adopted various strategies such as acquisition and product launch to strengthen their foothold in the industry

[infomen]

HexaData HD‑H231‑H60 Ver Gen001 – 2U High-Density Dual‑Node Server

The HexaData HD‑H231‑H60 Ver Gen001 is a 2U, dual-node high-density server powered by 2nd Gen Intel Xeon Scalable (“Cascade Lake”) CPUs. Each node supports up to 2 double‑slot NVIDIA/Tesla GPUs, 6‑channel DDR4 with 32 DIMMs, plus Intel Optane DC Persistent Memory. Features include hot‑swap NVMe/SATA/SAS bays, low-profile PCIe Gen3 & OCP mezzanine expansion, Aspeed AST2500 BMC, and dual 2200 W 80 PLUS Platinum redundant PSUs—optimized for HPC, AI, cloud, and edge deployments. Visit for more details: Hexadata  HD-H231-H60 Ver: Gen001 | 2U High Density Server Page

[nrgnews-it]

Nexus: The Dawn of IoT Consciousness – The Revolution Illuminating Big Data Chaos

[goodoldbandit]

The Rise of NPUs: Unlocking the True Potential of AI.

Sanjay Kumar Mohindroo Sanjay Kumar Mohindroo. skm.stayingalive.in Explore NPUs: their components, operations, evolution, and real-world applications. Learn how NPUs compare to GPUs and CPUs and power AI innovations. NPUs at the Heart of the AI Revolution In the ever-evolving world of artificial intelligence (#AI), the demand for specialized hardware to handle complex computations has never…

[techdriveplay]

Sony Reveals the PlayStation 5 Pro

Sony Interactive Entertainment (SIE) has officially unveiled the PlayStation 5 Pro (PS5 Pro), the latest innovation in their gaming hardware lineup. Set to launch on November 7, 2024, the PS5 Pro promises to revolutionise gaming with enhanced visuals, faster performance, and cutting-edge technology. With a recommended retail price of $699.99 USD, £699.99 GBP, €799.99 EUR, and ¥119,980 JPY, it…

[super-ion]

The Engineer

Part 2

(Part 1)

I wake from a nightmare.

It isn't my nightmare.

Well… it is mine. My brain provided the framework and context. I was in the training console, one of the battle sims, one of the ones where everything goes to shit, one of the ones where they fuck up the parameters just to watch you panic and squirm until you fucking crack.

That was me. I cracked. Four of the hell sims and I cracked hard.

The battle in the nightmare wasn't a sim. It was real. It was Morrigan's.

I'm sitting in my quarters, sweating and trembling, clutching at my chest as I try to sort out what's mine and what's Morrigan's.

Neural bleed.

Fuck.

No… it's… I've run through the playback, in full, three times with Morrigan. It's enough times for the individual events to stick in my brain.

That doesn't explain the screaming.

It doesn't explain the soul rending scream that is still echoing in my skull right now.

Zephyrus was a sabre class, front line heavy. The team has spent... I don't even know how many hours in the playback analyzing the battlespace in the moments before Zephyrus’ pilot died? The rogue incendiary burned straight into the cockpit, the pilot was probably vaporized before they even realized their error.

But Zephyrus screamed. It screamed and screamed and screamed.

Morrigan had muted that part, trying to spare me, but it fucking bled through the link anyway. Now I'm having fucking nightmares of the sound of someone becoming unmade.

Salvage ops recovered the mech, whisking it off to god knows where.

I don't actually know what happens to AI's that lose their pilots. It's my job to keep them alive, not deal with them after the fact.

I've… shit… I've worked on Zephyrus. It wasn't the same as Morrigan. None of them are the same as Morrigan, but… shit…

I shuck off my tangled sheets and sit on the edge of the bed, futilely trying not to let my thoughts get away from me.

There had been a personality matrix meant for me. There had to have been. Mech AIs are completely custom made for their pilots. Mine likely wasn't much past the most basic template by the time I washed out, nothing more than a collection of algorithms and a dataset consisting of my psych profile.

It never got to be.

Was that better or worse than the horrible scream that I can still hear?

I can't be alone right now.

I jump off the bed and pull on some clothes, leaving the room without even knowing where I'm going.

I pass a few of the night crew. They watch curiously as I walk by. An engineer, barefoot in her night clothes, can hardly be the strangest thing they've seen.

I barely notice them.

My thoughts are spiraling now.

I was meant to be a pilot. It's the only thing I ever actually wanted. But I fucked it all up. I tricked everyone, myself included, into thinking that I could make the cut.

Fucking hell. A pilot died and I'm fixating on my own feelings of inadequacy?

What would I have done? What could my presence in the battlefield have changed?

Chances are it would have been me dying… or worse, freezing up and getting someone else killed.

I freeze, my wrist hovering uncertainly over a security access reader. With a sickening, crystalizing clarity, I realize that I have unconsciously made my way to her. Beyond the security door is the vestibule leading to Morrigan's cockpit.

What the fuck am I doing here?

My presence at this hour, though odd, would not be remarked upon. It is not uncommon for engineers to have moments of insight in the middle of the night. It is not uncommon for us to need to access hardware for analysis and simulation at all hours.

But tonight there is no flash of insight. Tonight, I'm not even an engineer. I'm just a scared little girl wrapped up in her own feelings of failure, with a head full of someone else's grief.

Neural bleed.

I can't deny it. I'm spending too much time with Morrigan. I should go back to my quarters, request a psych eval and some time off, try to get my head on straight.

And yet, I hesitate.

I want to step through this threshold. I want to go to her. And… what?

I can't integrate with her, not in any kind of way that matters, not with my engineer's rig.

I will *never* experience the full body sensorium of a pilot linking with her mech. It is horrible knowing I was meant for something, having full awareness of all the expectations of me, both external and internal, only to have that life snatched away because I wasn't good enough. Half my soul is missing. There's this yawning void inside me that can never be filled. Not by Morrigan or anyone.

I wipe a tear off my face. I'm in no state to do any sort of interfacing. I'm in no state for much of anything.

I don't want to be alone. I don't know how to not be alone

I press my wrist to the security panel. It confirms my identity and flashes green.

My access will be logged. This is a horrible impulse to follow for so many reasons.

I don't fucking care.

It takes everything I have to maintain composure, to not burst into tears and run to the open hatch of the cockpit.

The soft red glow illuminating the cockpit brightens slightly, lighting my way.

She knows I'm here.

Does she even want me here? Why would she? I'm not her pilot. I'm not any mech’s pilot.

The glow pulses, beckoning me. The cradle shifts to a configuration that I know is meant for me.

I unzip the sweatshirt that I'm wearing and throw it unceremoniously in the vestibule before falling into her embrace.

It's too familiar, the motions of this routine as her jacks slip into the ports on my rig.

I'm too close.

I'm not close enough.

I nearly sob as data streams into my consciousness. The void fills, just slightly.

All systems green.

It isn't enough. It will never be enough.

It has to be enough.

The data stream ebbs and I receive a ping across the link.

- STATUS?

My breath catches. My eyes flutter open, darting to any one of the many cockpit cameras focused on me.

She wants my status.

“I couldn't sleep,” I tell her. “Bad dreams.”

(Next)

I don't know how, but she seems to understand. The cradle shifts to a more relaxed posture. She holds me in her embrace as I tell her about the nightmare.

[semiindustry]

Top Trends Transforming the Edge AI Hardware Market in 2025 and Beyond

The Edge AI hardware market is undergoing a significant transformation as demand for faster, more intelligent, and decentralized computing continues to grow across industries. As organizations increasingly turn to edge-based solutions for real-time data processing, enhanced privacy, and improved operational efficiency, new trends are emerging that are reshaping the landscape of edge AI. These developments are not only driving innovation but also unlocking new opportunities for businesses, governments, and technology providers. Here's a look at the top trends that are expected to define the Edge AI hardware market in 2025 and beyond.

Download PDF Brochure @ https://www.marketsandmarkets.com/pdfdownloadNew.asp?id=158498281

One of the most notable trends is the rise of domain-specific AI processors. General-purpose processors are no longer sufficient to meet the growing complexity and performance demands of edge AI applications. As a result, companies are developing customized hardware architectures such as Application-Specific Integrated Circuits (ASICs), Neural Processing Units (NPUs), and Vision Processing Units (VPUs) optimized for particular workloads like computer vision, speech recognition, or natural language processing. These specialized chips deliver superior performance-per-watt efficiency, making them ideal for use in power-sensitive and latency-critical edge environments.

Another trend gaining momentum is the miniaturization and integration of AI chips into everyday consumer and industrial devices. In 2025 and beyond, edge AI hardware will become increasingly compact and embedded in smartphones, drones, wearables, home appliances, medical equipment, and even small-scale sensors. The integration of AI processing into such devices allows for real-time intelligence without external connectivity, enabling new use cases in autonomous systems, personal health monitoring, and intelligent automation.

AI at the edge is also becoming more sustainable, driven by a growing emphasis on energy efficiency and green computing. As edge devices proliferate globally, their cumulative power consumption becomes a major concern. Manufacturers are focusing on reducing energy usage by adopting advanced semiconductor fabrication processes (like 3nm and 5nm nodes), dynamic voltage scaling, and on-device power optimization techniques. These developments are helping companies achieve their sustainability goals while maintaining high performance in edge applications.

The convergence of 5G and Edge AI hardware is another transformative trend. With ultra-low latency, high-speed connectivity, and massive device support, 5G is providing the communication backbone needed for next-generation edge computing. This synergy is particularly impactful in applications such as autonomous vehicles, smart cities, industrial IoT, and immersive augmented/virtual reality (AR/VR). As 5G networks expand globally, they will further amplify the demand for edge AI hardware that can capitalize on the benefits of seamless, real-time connectivity.

Federated learning and on-device model training are reshaping how AI models are built and updated on the edge. Instead of sending raw data to the cloud, federated learning enables devices to train models locally and share only the model updates with a central server. This approach not only reduces bandwidth usage but also strengthens privacy and security. With growing concerns over data ownership and compliance, federated learning is becoming an essential part of edge AI strategies, driving demand for hardware that supports secure, distributed learning.

Another critical trend is the expansion of edge AI across vertical markets, particularly in healthcare, manufacturing, agriculture, and transportation. In healthcare, edge AI hardware is enabling continuous patient monitoring, early diagnostics, and personalized treatment—all without relying on cloud access. In smart factories, edge AI powers predictive maintenance, real-time quality control, and robotics. In agriculture, AI-enabled drones and sensors are revolutionizing crop management and livestock monitoring. This sectoral diversification is fueling robust growth in edge hardware tailored for specific industry needs.

Security and trusted AI at the edge are also gaining importance. With edge devices deployed in the field, often beyond the reach of traditional cybersecurity frameworks, securing hardware and data becomes essential. In response, hardware vendors are incorporating built-in security features such as secure boot, encryption engines, trusted execution environments (TEEs), and anomaly detection. These measures are critical for maintaining trust in AI-driven systems, especially in applications involving sensitive or mission-critical data.

Lastly, the rise of AI-enabled digital twins and metaverse technologies will drive further innovation in edge AI hardware. As physical and digital worlds become increasingly integrated, real-time, edge-based intelligence will be crucial to simulate, visualize, and manage complex systems—whether it’s a manufacturing process, a smart building, or a virtual training environment.

[admiral-crow-is-watching]

Diary of an OS defector

My old laptop was Windows 11, but the hardware had got to such a dire state that it had to go. This left me with a choice.

Aside from my main laptop, I had a second one "running" Windows 10. It is called Little Legs. I put running in quotes because it wasn't really running anything. It froze up, overwhelmed, when asked to do, well, anything really. I have no memory of how I came into possession of it, but there was absolutely nothing of importance on it. If I did something to brick it entirely, I would lose nothing. So I installed Mint xfce on it, mostly, at the start, for shits and giggles.

Then I noticed something. It was good. The 4GB of soldered ram from 2019 couldn't cope with Windows 10, but it was happy on Mint. I began doing things on it, and then it came into my rotation as a sexed-up second monitor.

But more than that. Linux was a better experience that Windows. So, when I got a new main laptop, I plugged the bootable media in, and made the switch.

And I'm glad I did. For context, what I do with my laptop is doing an internet, some spreadsheets and text editing, a little programming. Nothing to give me Edge Case Syndrome.

I am now typing this on that laptop. The main thing Mint has over Windows, in my opinion, is the filesystem. Everything is just there. I can find whatever I want easily; everything I see on the way, I know what it's doing. There's none of the directories I had on Windows with cryptic names that I didn't have permission to access, or couldn't understand at all. (The old laptop went to its grave with a directory called Jedi that had been there for years, defying any attempt to explain its existence). And when I want to rename something? Right click and rename it. If I want to change things? Into the command line; a lil bit of cd, mkdir, and rmdir. It's a breath of fresh air, and it feels like my computer. This might change as I keep using it and files and folders build up, but I don't think it'll ever get Windows bad.

There's also a simplicity I really like about Mint. Everything has a straightforward name, with a little description of what it does. And they're all nicely grouped up with their friends in the start menu. There's no ai, no weather forecasts for cities I'm not in, no ticker showing me the current currency exchanges. It's everything I could plausibly want and not an iota more. Love it, it's a hiking map compared to Windows' rambled vague directions accompanied with vague pointing and tangents about the history of the city.

The updates! The updates update. They don't close down things, cause my entire system to restart without my consent, or demand to be turned off and on again.

To be sure, it's not perfect. I'd love to be able to adjust the screen zoom to somewhere in between 100% and 200%, but doing it individually in the apps isn't too much of a hardship. I tried to change the lock screen, and caused the whole boot process to get grumpy with me in the process. Firefox can have an unexpected amount of trouble scrolling occasionally, and the amount of storage I have free at any given time goes up and down, and is always less than I feel it should be. No doubt this all due to my own incompetence.

On the whole, I am an absolute convert. Linux knocks Windows into a cocked hat (also chromeOS, which I have also had the misfortune of using). I've got the bug.

Little Legs is still here, and still something I can afford to lose, and I am still playing with it. I had a look at Manjaro, but I didn't vibe with that. What goes on my flash drive next?

[mariacallous]

“I’m not going to respond to that,” Siri responded. I had just cursed at it, and this was my passive-aggressive chastisement.

The cursing was, in my view, warranted. I was in my car, running errands, and had found myself in an unfamiliar part of town. I requested “directions to Lowe’s,” hoping to get routed to the big-box hardware store without taking my eyes off the road. But apparently Siri didn’t understand. “Which Lowe?” it asked, before displaying a list of people with the surname Lowe in my address book.

Are you kidding me? Not only was the response incoherent in context, but also, only one of the Lowe entries in my contacts included an address anyway, and it was 800 miles away—an unlikely match compared with the store’s address. AI may not ever accomplish all of the things the tech companies say it will—but it seems that, at the very least, computers should be smarter now than they were 10 or 15 years ago.

It turns out that I would have needed an entirely new phone for Siri to have surmised that I wanted to go to the store. Craig Federighi, Apple’s senior vice president of software engineering, said in an interview last month that the latest version of Siri has “better conversational context”—the sort of thing that should help the software know when I’m asking to be guided to the home-improvement store rather than to a guy called Lowe. But my iPhone apparently isn’t new enough for this update. I would need cutting-edge artificial intelligence to get directions to Lowe’s.

This is effectively Apple’s entire pitch for AI. When it launched Apple Intelligence (the company’s name for the AI stuff in its operating systems) last year, the world’s third-most-valuable company promised a rich, contextual understanding of all your data, and the capacity to interact with it through ordinary phrases on your iPhone, iPad, or Mac. For example, according to Apple, you would be able to ask Siri to “send the photos from the barbecue on Saturday to Malia.”

But in my experience, you cannot ask even the souped-up Siri to do things like this.

I embarked on a modest test of Apple Intelligence on my Mac, which can handle the feature. It failed to search my email, no matter how I phrased my command. When I tried to use Siri to locate a PDF of a property-survey report that I had saved onto my computer, it attempted to delegate the task to ChatGPT. Fine. But ChatGPT provided only a guide to finding a survey of a property in San Francisco, a city in which I do not live. Perhaps I could go more general. I typed into Siri: “Can you help me find files on my computer?” It directed me to open Finder (the Mac’s file manager) and look there. The AI was telling me to do the work myself. Finally, I thought I would try something like Apple’s own example. I told Siri to “show me photos I have taken of barbecue,” which resulted in a grid of images—all of which were stock photos from the internet, not pictures from my library.

These limitations are different from ChatGPT’s tendency to confidently make up stories and pass them off as fact. At least that error yields an answer to the question posed, albeit an inaccurate one. Apple Intelligence doesn’t even appear to understand the question. This might not seem like a problem if you don’t use Apple products or are content to rawdog your way to Lowe’s. But it does reveal a sad state of affairs for computing. For years, we’ve been told that frictionless interactions with our devices will eventually be commonplace. Now we’re seeing how little progress has been made toward this goal.

I asked Apple about the problems I’m having with Apple Intelligence, and it more or less confirmed that the product doesn’t work—yet. Apple’s position is that the 2024 announcement, featuring Malia and the cookout, represents a vision for what Siri can and should do. The company expects that work on functionality of this kind will continue into 2026, and it showed me a host of other forthcoming AI tools, including one with the ability to recognize an event in a screenshot of a text message and add the info to a calendar, or to highlight an object in a photo and search for similar ones on Google or Etsy. I also saw a demo of live language translation on a phone call, updated AI-created emoji, and tools to refine what you’ve written inside emails and in Apple software. Interesting, but in my mind, all of these features change how you can use a computer; they don’t improve the existing ways.

After rolling around in my head the idea that Apple Intelligence represents a vision for how a computer should work, I remembered that Apple first expressed this vision back in 1987, in a concept video for a product called Knowledge Navigator. The short film depicts a university professor carrying out various actions of daily and professional life by speaking directly to a personified software assistant on a tablet-like computer—all of the things I long to do with my computer 38 years hence. Knowledge Navigator, per the video, could synthesize information from various sources, responding to a user’s requests to pull up various papers and data. “Let me see the lecture notes from last semester,” the professor said, and the computer carried out the task. While the professor perused articles, the computer was able to identify one by a colleague, find her contact info, and call her upon his request.

Although obscure outside computer-history circles, Knowledge Navigator is legendary in Silicon Valley. It built on previous, equally fabled visions for computing, including Alan Kay’s 1972 proposal for a tablet computer he called DynaBook. Apple would eventually realize the form of that idea in the iPad. But the vision of Knowledge Navigator wasn’t really about how a device would look or feel. It was about what it would do: allow one to integrate all the aspects of a (then-still-theoretical) digital life by speaking to a virtual agent, Star Trek style. Today, this dream feels technologically feasible, yet it is still, apparently, just out of reach. (Federighi promised in the June interview that a better Siri was right around the corner, with “much higher quality and much better capability.”)

Apple Intelligence—really, generative AI overall—emphasizes a sad reality. The history of personal-computer interfaces is also a history of disappointments. At first, users had to type to do things with files and programs, using esoteric commands to navigate up and down the directory structures that contained them. The graphical user interface, which Apple popularized, adapted that file-and-folder paradigm into an abstraction of a desktop, where users would click and move those files around. But progress produced confusion. Eventually, as hard disks swelled and email collected, we ended up with so much digital stuff that finding it through virtualized rummaging became difficult. Text commands returned via features such as Apple’s Spotlight, which allows a user to type the name of a file or program, just as they might have done 50 years ago.

But now the entire information space is a part of the computer interface. The location and route to Lowe’s gets intermixed with people named Lowe in my personal address book. A cookout might be a particular event I attended, or it might be an abstraction tagged in online images. This is nothing new, of course; for decades now, using a computer has meant being online, and the conglomeration of digital materials in your head, on your hard disk, and on the internet often cause trouble. When you’re searching the web, Google asks if you’re perhaps really looking for the thing it deems more common based on other people’s behavior, rather than the thing you typed. And iCloud Drive helpfully uploads your files to the cloud to save disk space, but then you can’t access them on an airplane without Wi-Fi service. We are drowning in data but somehow unable to drink from its wellspring.

In principle, AI should solve this. Services such as ChatGPT, built on large language models that are trained on vast quantities of online and offline data, promised to domesticate the internet’s wilds. And for all their risk of fabrication and hallucination, LLMs really do deliver on that front. If you want to know if there exists a lens with specific properties compatible with a particular model of camera, or seek advice on how to carry out a plumbing repair, ChatGPT can probably be of use. But ChatGPT is much less likely to help you make sense of your inbox or your files, partly because it hasn’t been trained on them—and partly because it aspires to become a god rather than a servant.

Apple Intelligence was supposed to fill that gap, and to do so distinctively. Knowledge Navigator never got built, but it was massively influential within the tech industry as a vision of a computing experience; it shows that Apple has expressed this goal for decades, if under different technological conditions and executive leadership. Other companies, including Google, are now making progress toward that aim too. But Apple is in a unique position to carry out the vision. It is primarily a personal-computer-hardware business focused on the relationship between the user and the device (and their own data) instead of the relationship between the user and the internet, which is how nearly every other Big Tech company operates. Apple Intelligence would make sense of all your personal information and grant new-and-improved access to it via Siri, which would finally realize its purpose as an AI-driven, natural-language interface to all that data. As the company has already done for decades, Apple would leave the messy internet mostly to others and focus instead on the device itself.

That idea is still a good one. Using a computer to navigate my work or home life remains strangely difficult. Calendars don’t synchronize properly. Email search still doesn’t work right, for some reason. Files are all over the place, in various apps and services, and who can remember where? If computationalists can’t even make AI run computing machines effectively, no one will ever believe that they can do so for anything—let alone everything—else.

[ottopilot-wrote-this]

Generational Trauma

Once more unto the breach of @subliminalbo's Romero Literary Universe. This story references characters from the Obedience by Fleur series. This is also a prequel to Backend Support, though both stories (hopefully) stand on their own.

Thanks again to my friend @subliminalbo (also at @subliminalboarchive) for the art trade and collaboration.

Bailey Castillo set the clippers on the sink counter and rubbed the base of her skull. She was a queer woman, it certainly wasn't her first time getting an undercut. But it was the first time she'd done it to herself.

It made her smirk to herself. Given the grim nature of what she had talked herself into, Bailey could use all the levity she could muster.

She had an undercut when she met Ed. It was a good metaphor, she thought. Under that big head of dark curls, there was an edge. Her fresh face and polite smile were a mask, disguising survival instincts and a pragmatism you could only get by growing up Black, asexual, and female in Romero, Washington.

Bailey rubbed the shaving gel in her wet fingers until it foamed up. Smelling of peaches, she rubbed it on her shaved hair. After rinsing her hands, she rinsed the razor's blade, new and sharp, in the cold water of the faucet.

It seemed a strange offer. What did a lingerie company need with an embedded systems designer? Software devs for e-commerce, sure. But she specialized in hardware, in writing firmware, in the arcane art of assembly code.

Beggars couldn't be choosers, though. Not beggars who had a degree from the local party school, because Mamá got a discount on tuition, and it was what they could afford. Certainly not beggars who would take the first offer they could get that would get them away from this cesspool. Bailey shaved her neck and the undercut area with smooth, careful strokes.

Her first mistake was trusting. Trusting that if she did a good job - and her control array for Obedience by Fleur was, objectively, goddamn genius - she'd be recognized for it.

Bailey rinsed the razor of shaving cream and tiny black hairs. Won't make that mistake again.

She had overestimated Ed King. She bought his Silicon Valley rep, and failed to see he wasn't any different from Romero's traditional power brokers. He was a carnival barker, not a visionary like he thought he was. She was a commodity to him, not a person. If Obedience failed, she would've taken the blame; but since it succeeded, he was more than happy to take all the credit.

Bailey rubbed the smooth wet skin on her neck, checking for missed spots. Elena wasn't any better. She got what she wanted from Bailey, and that made her disposable. It was a blessing, really. Bailey was a natural beauty, but her curvy hips and thighs meant she wasn't model thin, and it also meant she was back at her mother's house in Romero, and not mindlessly, dutifully, licking Elena's designer boots.

Toweling off her neck, Bailey shifted away from the sink toward the 3D printer. She triple-checked her work.

When she first read about needleless tattoos in Wired, at all just clicked into place. A silicon ink payload in dissolvable microneedles. Putting the Obedience tech inside the subject. Permanently. Forget the sensors, pair the array with a fitness tracker or smartwatch. An AI sidecar to increase subject safety. No more brain damage.

Stealing the base software from Ed King? Bailey had no qualms about stealing from a thief. But she needed stake money. It was surprisingly easy to talk the Chinese triads into financing her. But they wanted proof before they pumped more yuan into her operation.

The 3D printer hummed to life as it printed the dissolvable needles, loaded with silicon ink, onto the dermal patch. This was, of course, a fork, custom firmware modified from the base model. Unfortunately, you can't just print a tiny one of these and slap it on a lab rat.

And experimenting on an unwilling human subject… That was something they would do. Bailey wasn't a monster. Not yet.

The array was done. It was a rectangle about the size of deck of cards. The trick had been spacing, making sure the crudely printed lines wouldn't bleed or touch accidentally when applied. Bailey's array was, of course, unique. She'd created a hyperfocus routine that, when enabled, could drown out stimulation and increase cognitive ability temporarily. More importantly, the mind control protocols were blunted, and she wrote an additional protection against mesmerism: the ability to mentally control her hormone levels.

But at the end of the day, this was modified Obedience by Fleur firmware. Bailey knew there was an unknown period where she would have to take Obedience's best punch, enduring and outlasting it, before the AI sidecar would read her biofeedback and adjust the indoctrination protocols lower. She was prepared for it, with a physical anchor.

She took the black choker, her mother's, in her left hand. When Mamá died, shortly after Bailey came back to Romero with her tail between her legs, it was in her jewelry box.

Bailey didn't know how to reconcile that. Mamá never said anything. She didn't have to. When she left the house wearing this choker, all painted up when she should have been in bed, the vacant look told young Bailey everything. But to keep this in an intimate place, where she likely saw it every day - before the early-onset Alzheimer's rotted her from the inside out - what did that mean?

That she missed it?

Bailey gripped the choker tightly, feeling the satin in her delicate fingers. She couldn't guess what went through her mother's mind. Bailey only knew what it meant to her: anger. Abandonment issues. A keepsake of a life she would never, ever lead.

One last check. One last chance to bitch out.

Bailey sat upright in her work stool. She prepared the tattoo array patch, removing it from the printing tray. She looked again at the choker in her left hand, her anchor to reality. She took the patch, and affixed it to the base of her skull.

At first, there was a cold, wet feeling. Like ultrasound gel. And it itched, probably from the microneedles penetrating her skin. Bailey's research indicated there wouldn't be any pain from the actual absorption of the silicon ink into her dermis, just a slight delay.

Immediately, she realized she'd miscalculated.

Bailey had set the weights on the Obedience protocol to fifty percent. She barely had time to process that was too high before she was inundated with sensation. "Oh… Fuck," she moaned breathlessly. It was so hard to think from the pleasure. Warm and comforting, like a blanket. Like a hug, but not a hug from just anyone. From someone precious. From a lover.

Then she felt something new. A flicker, at first. Then a slow burning heat. Then an intense raging inferno, burning between her legs, deep inside her, in her very soul. Bailey instinctively put her hand there, but it was a huge mistake. Immediately she rubbed her engorged clit through her panties, wetness spreading through the dainty cotton fabric.

Lust? But I'm fucking ace, Bailey thought, before the first orgasm hit.

Wave after wave of euphoric gratification pounded her senses like a tempestuous ocean.

Shit! this is- Then another.

Tides of pleasure washed over her.

The choker. Have to- Another.

The powerful undertow eroded her reason and resistance.

Mamá, I-

The blissful sensations overwhelmed Bailey, preventing the formulation of new thoughts, until she just simply stopped trying.

And then she was under. Submerged. Sounds fading. The world oh, so far away.

She was better this way, she saw that. It was better to stop resisting, stop trying to think, and just accept it. As she enthusiastically fingered her soggy cunt, mouth open, her body rewarding her for her compliance, Bailey thought she heard something. It was her own voice, moaning and panting and… giggling. Being dumb, and sexy, and available - it made her happy?

When was the last time she could say that, that she was legitimately happy?

She understood. She could feel like this for the rest of her life, and she only had to do one thing. Let go. Let go of the past, let go of the trauma, let go of the hurt. Let go of herself. The fingers on Bailey's left hand loosened their grip. The choker threatened to fall to the floor. No, not fall. To sink. To sink and drop, deeper and deeper. Her mind was still. Vacant. Empty, except for one thing creeping into her consciousness.

No. Not today.

Bailey's fingers tightened. She could feel the smooth satin, once cold, now hot with her own emanating warmth. She thought of Mamá, looking more like a movie starlet than her tireless, caring mother. Bailey saw her walk out the door, not even turning back to her crying daughter. And she remembered her pledge, to Mamá, to herself: it ain't gonna be me. Not today. Not ever.

Bailey held the choker with a steel grip, as if her life depended on it. It did. The choker was a life preserver in the choppy ocean of arousal flooding her mind and body. She had no idea how anyone could take twice as much of this. It was no wonder Obedience's control was absolute and immediate.

Slowly, she felt it. The constant bombardment of pleasure losing its steam. Waters receding. Her thoughts forming more easily, coherently. Her breathing stabilizing, and the hot flush of her arousal lowering to a simmer. "Set dopamine levels to zero," she gasped. She didn't need to say the words out loud for it to work, but in her disheveled state she needed to hear it. To remind herself she was in control.

She looked in a nearby mirror. Her eyes were a milky solid white, all sclera, no pupils. Her body was flushed with desire. She looked every bit the fucktoy she despised. Bailey knew she was lucky. If she had looked into this mirror a few minutes ago, she would've been lost.

Her hormone levels stabilizing, Bailey blinked, and her eyes returned to an intense chestnut brown. She was still in shock from the ordeal. She opened her palm and looked at the choker, and she placed it on her workbench. Slowly, she took her cell phone in her right hand and sent a message.

"Live test successful. Production is GO."

-------------------

The dream again. The same one. Fuck, I hate this, Bailey thought. And turning off the dopamine wasn't helping.

Bailey got out of bed and turned on a bedside lamp. She drowsily stood up, stumbled to the kitchen for a drink of cold water. It was a hot July night, so she was only wearing panties. Which, of course, were soaked through. Again.

On her back to bed, she stopped at her nightstand. She looked at herself in the vanity mirror. Running a prostitution empire based on mind control hadn't been kind to her, she thought.

Bailey wasn't sure what possessed her. But she reached into her top drawer, and retrieved Rosa's - Mamá's - choker. She hadn't looked at it since she turned on the Obedience array. She'd been too afraid. But here, in the dark, she fastened the choker around her neck. She activated her hormonal controls and raised them - not too much - to maybe 120% of normal. And she looked in the mirror.

Her eyes clouded over until the pupils were gone again, just solid white spheres. Like two blank canvases. She let her mind dull - again, not too much. Just enough to let her thoughts drift. Her full lips parted, on their own, as she watched with interest and arousal. She had always been beautiful, but now? She was a bombshell. All tits and ass and thighs, with a pretty fuckable face. She didn't have a sexual bone in her 29-year-old body, but she would fuck this braindead slut in the mirror.

Bailey's mind cleared as she regained control. She again dampened her pleasure center, and her eyes returned to normal. She took the choker off, and put it back, reverently, in her dresser drawer.

She now understood why Mamá had kept it.

[aegis-17]

A gunner turned craftsmen, AE-17 has stripped back most of its combat hardware, making an existence repairing equipment for those transversing the edge of the ridge. Built by Caltic Engineering, the Aegis series of combat automaton are self-aware constructs. Built over a thousand years after the wars of corruption and the end of the Azernexian empire. Their line was produced to serve in an on and off conflict known as the five century war between the Tenebraen Republic and the territories of the Stromean Realms. Through the course of the war, Cacean infantry, dissatisfied with the limited AI given to the constructs by tenebraen programmers, began to illegally modify units with patched programming, which was then shared among other networked units. This allowed their AI to rapidly evolve and develop based on their encounters on the field. By the time the war finally ended, and caltic engineering was liquidated, an estimated 88% of active units had received the update. of these, less then a third were able to be collected. Those that remained scattered throughout the edges of Tenebrean territories, among Cacean tribe regions and the newly formed Demitronian state, forging an existence for themselves.

[nanotechnologyworld]

MIT researchers have developed a novel AI hardware accelerator that is specifically designed for wireless signal processing. Their optical processor performs machine-learning computations at the speed of light, classifying wireless signals in a matter of nanoseconds.

[jmdbjk]

The controversy.

First of all, my man looked amazing...

Then my man jumped into the heavily controversial waters of AI generated images.

Why are the edges of his phone so beat up? anyway, I digress.

Elfen alchemist Jiminah creates a love potion to attract the love of his life, Prince Elf Jungkookah. He adds a few drops of elfen forest nectar honey to the concoction. Anyway.

Then Namjoon crashed the live, said "happy birthday bro" and took a quick pic of Jimin, who held up his phone with the AI generated image and posted it on his IG stories:

Is that a big TV screen? Is that a window behind him? Anyway, I digress again...focus, focus, focus...

Jimin said Tae sent him this image. There are 4 photos and we only got to see this one. Until...Tae posted this one on his IG stories:

Where Warrior Jiminah (in what look like his Tiffany Hardware collection earrings) is ready to defend the kingdom of the love of his life, King Jungkookah. I know he could kill someone with that stick if he wanted to no matter how cute he looks in his updo.

Besides the intellectual property issues surrounding AI generated images, where DO we draw the line? Here, we have 3 people who are well aware of their IP rights and they are sharing these images on their social media. Jimin himself showed us the first one, of himself, unprompted.

These are great images and IP rights aside, wouldn't it be great to be able to generate these images for ourselves? But we can never have nice things because there are shitty people in the world.

I love looking at the images. Is it wrong to like them? Is there a place for them? Who should be able to generate them and for what purposes only?

It seems like Jimin, Tae and Namjoon don't have a problem with them.

It's a tough call...

[semiindustry]

The Rise of AI Accelerators and NPUs in Edge Intelligence Hardware

The rapid growth of artificial intelligence (AI) applications at the network edge has ushered in a new era for edge intelligence hardware, prominently featuring AI accelerators and neural processing units (NPUs). These specialized chips are revolutionizing how data is processed on edge devices by delivering powerful AI capabilities with remarkable speed, efficiency, and low power consumption. As the demand for real-time, intelligent decision-making grows across industries such as autonomous vehicles, smart cities, healthcare, and industrial automation, AI accelerators and NPUs have become indispensable components of the edge computing landscape.

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AI accelerators are designed to handle specific AI workloads, such as deep learning inference, faster and more efficiently than traditional CPUs or GPUs. These accelerators optimize complex matrix computations and neural network operations, enabling edge devices to perform tasks like image recognition, natural language processing, and anomaly detection locally. By doing so, they reduce latency, enhance privacy by minimizing data transmission to the cloud, and alleviate network bandwidth requirements. Their energy-efficient architectures are crucial for battery-powered or resource-constrained edge devices, extending operational time without sacrificing performance.

NPUs, a specialized form of AI accelerator, are tailored specifically for neural network computations. Unlike general-purpose processors, NPUs are architected to accelerate machine learning models by parallelizing operations and minimizing data movement within the chip. This design dramatically boosts inference speed and efficiency, making NPUs ideal for embedded systems, smartphones, smart cameras, drones, and other edge devices that require on-device AI processing. Leading semiconductor companies are increasingly integrating NPUs into system-on-chip (SoC) platforms to provide seamless AI capabilities in compact, power-efficient packages.

The rise of AI accelerators and NPUs is driven by the growing complexity of AI models and the proliferation of use cases demanding real-time insights. Autonomous vehicles, for example, rely on AI accelerators and NPUs to analyze sensor data instantly, ensuring safe navigation and obstacle avoidance. In healthcare, AI-enabled edge devices can analyze patient data for diagnostics and monitoring without compromising privacy. Industrial IoT applications leverage these chips to detect faults and optimize production lines with minimal delay.

Moreover, advancements in semiconductor fabrication and AI algorithm optimization continue to improve the capabilities of AI accelerators and NPUs. Innovations such as quantization, pruning, and sparsity exploitation allow these chips to deliver higher performance while using fewer resources. As edge computing expands, the ecosystem of AI accelerator and NPU providers—from tech giants to startups—is rapidly evolving, fostering innovation and competition that benefits end users with more powerful, cost-effective hardware options.

In conclusion, AI accelerators and NPUs are at the forefront of edge intelligence hardware evolution, enabling a new generation of smart devices capable of autonomous, real-time decision-making. Their ability to deliver high-performance AI processing locally is transforming industries and unlocking the full potential of edge computing in an increasingly connected and AI-driven world.

[falconsai]

Accelerating deployment with pre-optimized hardware configurations. Falcons.ai offers pre-optimized configurations for popular edge hardware platforms, simplifying integration and maximizing performance. #FALCONS.AI #FALCONS AI #FALCONSAI