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Forbes
41 minutes ago
- Forbes
Axelera AI Accelerators Smoke Competitors In Machine Vision Research Study
Axelera CEO Fabrizio Del Maffeo Holds The Company's PCIe AI Accelerator As AI-accelerated workloads proliferate across edge environments—from smart cities to retail and industrial surveillance—choosing the right inference accelerator has become a mission-critical decision for many businesses. In a new competitive benchmark study conducted by our analysts at HotTech Vision and Analysis, we put several of today's leading edge AI acceleration platforms to the test in a demanding, real-world scenario: multi-stream computer vision inference processing of high-definition video feeds. The study evaluated AI accelerators from Nvidia, Hailo, and Axelera AI across seven object detection models, including SSD MobileNet and multiple versions of YOLO, to simulate a surveillance system with 14 concurrent 1080p video streams. The goal was to assess real-time throughput, energy efficiency, deployment complexity and detection accuracy of these top accelerators, which all speak to a product's overall TCO value proposition. Measuring AI Accelerator Performance In Machine Vision Applications All of the accelerators tested provided significant gains over CPU-only inference—some up to 30x faster—underscoring how vital dedicated hardware accelerators have become for AI inference. Among the tested devices, PCIe and M.2 accelerators from Axelera showed consistently stronger throughput across every model, especially with heavier YOLOv5m and YOLOv8l workloads. Notably, the Axelera PCIe card maintained performance levels where several other accelerators tapered off, and it consistently smoked the competition across all model implementations tested. SSD MobileNet v2 Machine Vision AI Model Inferencing Test Results Show Axelera In The Lead YOLOv5s Machine Vision AI Model Results Shows The Axelera PCIe Card Wins Hands-Down But Nvidia Is ... More Competitive That said, Nvidia's higher-end RTX A4000 GPU maintained competitive performance in certain tests, particularly with smaller models like YOLOv5s. Hailo's M.2 module offered a compact, low-power alternative, though it trailed in raw throughput. Overall, the report illustrates that inference performance can vary significantly depending on the AI model and hardware pairing—an important takeaway for integrators and developers designing systems for specific image detection workloads. It also shows how dominant Axelera's Metis accelerators are in this very common AI inference application use case, versus major incumbent competitors like NVIDIA. Power consumption is an equally important factor, especially in AI edge deployments, where thermal and mechanical constraints and operational costs can limit design flexibility. Using per-frame energy metrics, our research found that all accelerators delivered improved efficiency over CPUs, with several using under one Joule per frame of inferencing. SSD MobileNet v2 Power Efficiency Results Shows Axelera Solutions Win In A Big Way YOLOv5s Power Efficiency Results Show Axelera Solutions Ahead But Nvidia And Hailo Close The Gap Here, Axelera's solutions out-performed competitors in all tests, offering the lowest energy use per frame in all AI models tested. NVIDIA's GPUs closed the gap somewhat in YOLO inferencing models, while Hailo maintained respectable efficiency, particularly for its compact form factor. The report highlights that AI performance gains do not always have to come at the cost of power efficiency, depending on architecture, models and workload optimizations employed. Beyond performance and efficiency, our report also looked at the developer setup process—an often under-appreciated element of total deployment cost. Here, platform complexity diverged more sharply. Axelera's SDK provided a relatively seamless experience with out-of-the-box support for multi-stream inference and minimal manual setup. Nvidia's solution required more hands-on configuration due to model compatibility limitations with DeepStream, while Hailo's SDK was Docker-based, but required model-specific pre-processing and compilation. The takeaway: development friction can vary widely between platforms and should factor into deployment timelines, especially for teams with limited AI or embedded systems expertise. Here Axelera's solutions once again demonstrated simplicity in its out-of-box experience and setup that the other solutions we tested could not match. Our study also analyzed object detection accuracy using real-world video footage. While all platforms produced usable results, differences in detection confidence and object recognition emerged. Axelera's accelerators showed a tendency to detect more objects and draw more bounding boxes across test scenes, likely a result of its model tuning and post-processing defaults that seemed more refined. Still, our report notes that all tested platforms could be further optimized with custom-trained models and threshold adjustments. As such, out-of-the-box accuracy may matter most for proof-of-concept development, whereas other, more complex deployments might rely on domain-specific model refinement and tuning. Axelera AI's Metis PCI Express Card And M.2 Module AI Inference Accelerators Our AI research and performance validation report underscores the growing segmentation in AI inference hardware. On one end, general-purpose GPUs like those from NVIDIA offer high flexibility and deep software ecosystem support, which is valuable in heterogeneous environments. On the other, dedicated inference engines like those from Axelera provide compelling efficiency and performance advantages for more focused use cases. As edge AI adoption grows, particularly in vision-centric applications, demand for energy-efficient, real-time inference is accelerating. Markets such as logistics, retail analytics, transportation, robotics and security are driving that need, with form factor, power efficiency, and ease of integration playing a greater role than raw compute throughput alone. While this round of testing (you can find our full research paper here) favored Axelera on several fronts—including performance, efficiency, and setup simplicity—this is not a one-size-fits-all outcome. Platform selection will depend heavily on use case, model requirements, deployment constraints, and available developer resources. What the data does make clear is that edge AI inference is no longer an exclusive market GPU acceleration. Domain-specific accelerators are proving they can compete, and in some cases lead, in the metrics that matter most for real-world deployments.
Bloomberg
an hour ago
- Bloomberg
UniCredit Boosts Its Equity Stake in Commerzbank to About 20%
UniCredit SpA, the Italian lender that hopes to acquire Commerzbank AG, increased its equity stake in the German firm and became its largest shareholder after converting derivatives into stock. The move gives Milan-based UniCredit about 20% of the effective voting rights and it intends to eventually convert its remaining 'synthetic position' to boost its Commerzbank holding to roughly 29%, according to a statement Tuesday. UniCredit announced the change after receiving approvals from the European Central Bank, German antitrust authorities and the US Federal Reserve.
WIRED
an hour ago
- WIRED
Coffee! Coffee Now! Get Your Caffeine Fix with These Prime Day Deals
If you need to mainline some caffeine, these are the best brewers and concentrates to get that java into your system. All products featured on WIRED are independently selected by our editors. However, we may receive compensation from retailers and/or from purchases of products through these links. What's more WIRED than coffee? Before you plug into the matrix, you need your coffee fix. We know because we've been testing all the various ways of making coffee for years now. These are the best Prime Day deals on WIRED-tested and -approved coffee brewers, espresso makers, grinders, concentrates, pods, and more. If it's good at getting caffeine to your brain and on sale for Prime Day, it's here. Want more Prime Day goodness? Read our Best Prime Day Deals and Prime Day Liveblog for more discounted tech and gadgets. Deals on Espresso Machines We'll start with the strong stuff. If espresso, lattes, or cappuccino are what you're after, these are the best we've tested. Italian coffee titan De'Longhi has created something close to automated perfection here. the Rivelia is the best automatic latte and cappuccino maker we've tested. And we do mean automatic. It will grind, brew, froth up milk, and deliver as many as 18 different variations on espresso, latte, cappuccino, and iced-coffee drinks. Our main gripe is that all that can be overwhelming, but then, that's kind of a good problem to have. This semiautomated espresso machine (7/10, WIRED Review) made the quad shot I'm drinking right now. It's not quite a coffee shop-level pull (nothing home-brewed ever is), but it's close enough. It also makes a good cup of drip coffee and cold brew as well. If you want want a machine that can do it all, and do it well, this is a good choice. It's also very beginner-friendly, you don't have to be a barista to get good results. Deals on Drip Coffee Machines and French Presses Photograph: Matthew Korfhage $359 $241 (33% off) Amazon A stalwart from our 'buy-it-for-life' guide, the Moccamaster is crafted from metal, steel, and copper and is designed to last a lifetime. The warranty goes five years, and the machine is fully repairable even after that's over. The appeal, beyond longevity, lies in its precision. The Moccamaster can hold brewing temperatures within a variance of 4 degrees Celsius and extract coffee within very tight parameters. This will make you great cups of coffee, probably for longer than you'll be around to drink them. Espro's P7 uses double mesh strainers that lock together and uses two seals on top of that. There's no sediment to be found here, just a nice bold cup of coffee. The spout could be bigger, but so long as you pour slowly, it's not a big deal. Coffee Pod Machines and Coffee Concentrates Coffee! Coffee now! For those with no patience for the art hassle of brewing fancy coffee, we have pod machines, which eliminate the guesswork and deliver the caffeine right freaking now. If even that is too slow, try a concentrate. The Bruvi BV-01 is our favorite pod coffee maker. It's not too big, and looks nice on your kitchen counter. The proprietary B-Pods are unfortunately only sold online as of now, but they come in coffee, tea, and espresso varieties, and they're meant to biodegrade in a landfill. The OG coffee pod brewer, the K-Mini does a solid job at what it's meant to do: brewing exactly one cup of coffee. It's not the best coffee you've ever had, but it's also not the worst. It gets the job done, and in our testing these machines will last a surprisingly long time. Javvy (formerly 'Javy') comes in a wide range of flavors and isn't overly sweet. You only need a teaspoon or two for a full 8-ounce cup, and the original flavor is smooth enough that you can almost forget you're drinking a concentrate, with no bitter or funny aftertaste. If it's caffeine you're after, this is the juice you want. It packs 150 milligrams of caffeine into a single tablespoon-size serving. Somehow manages to not taste too acidic or bitter either, which is an achievement.
