Collaboration combines Cloudian HyperStore AI data lake software and Supermicro hardware to deploy hyperscale infrastructure

Cloudian, the leader in secure S3-compatible AI data lake platforms, and Supermicro , the leader in Total IT Solutions for AI, Cloud Storage, and 5G/Edge, today announced a strategic collaboration to deliver a groundbreaking data management solution designed to simplify and accelerate large-scale AI implementations. This comprehensive solution integrates exabyte-scalable storage and GPU-based computing to accelerate and simplify AI deployment in data-intensive use cases such as genomics, healthcare imaging, autonomous vehicles, video surveillance, security, and scientific research.

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Petabytes of unstructured data used in large-scale AI training processing must be available to the GPU servers with low latencies and high bandwidth to keep the GPUs productive. Cloudian software deployed on Supermicro’s extensive portfolio of Intel and AMD based storage servers meets this need with a robust, highly-performant and easy-to-manage solution optimized for next-gen AI workflows.

“As AI users transition towards increasingly capacity-intensive applications, the need for hyperscale-class infrastructure that enables direct access to massive data sets is critical,” said Jon Toor, CMO of Cloudian. “Our collaboration with Supermicro merges our enterprise-proven, exabyte-scalable AI data lake platform with Supermicro’s leading GPU compute expertise, delivering the industry’s richest technology stack for large-scale AI computing.”

“Supermicro is thrilled to partner with Cloudian to introduce this workload-intensive data-management solution,” said Michael McNerney, Senior VP of Marketing and Network Security, Supermicro. “Combining Supermicro’s NVIDIA-Certified Systems with Cloudian’s exabyte-scale software enables the next wave of large-scale AI deployments. In addition to these, Supermicro’s SuperServer storage systems offer high capacity to help drive deep insights into learning massive data sets seamlessly and efficiently.”

Key capabilities offered by Cloudian and Supermicro’s collaboration include:

• Exabyte Scale: A modular architecture that supports massive scale with geo-distribution, non-disruptive growth, and secure multi-tenancy, ideal for graphics and data-intensive workloads.

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• Military-Grade Security: The most comprehensive set of security certifications in the industry, including data immutability for robust ransomware protection.
• Highest S3 API Compatibility: Fully-native S3 API ensures seamless operation with S3 applications and AI tools such as PyTorch, TensorFlow, Kafka, and Arrow.
• Bi-modal Data Access: Allows the interchange of file-based and object-based data to simplify data management.
• Rich Platform Portfolio: Storage server hardware options include Supermicro Petascale All-Flash storage servers for high-performance, Supermicro SuperServer 90 drive bay storage servers for high-capacity, in addition to other 1U, 2U and 4U high products in the Supermicro family.

Designed for enterprise-class deployment, the Cloudian platform provides a comprehensive software infrastructure for data-intensive computing. Cloudian’s data lake provides a consolidated repository to ingest, catalog, enrich, and preserve data through real-time analysis and deep learning.

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[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

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Does your phone have artificial intelligence (AI)? The latest buzzword in smartphones, AI is being heralded as the next big leap in photography. Marketers claim that new devices equipped with AI can perform incredible feats with minimal effort from users. In reality, AI is simply the modern term for technology that has been present in cameras for years. Remember the ‘auto mode’ on your camera that you tried to move away from? It’s back, now more tempting, accessible, and impressive than ever.

Smartphone photography has only had three giant waves of innovation. First, it was related to camera lens size; then the megapixel count dominated most of the discussions for quite a long time. Today, it all comes down to software and artificial intelligence being applied to photos. Computational photography—a third wave—changes the belief that cell phones equipped with really tiny lenses are just incapable of matching full-size single-lens reflex camera quality. At least, the latest genre of smartphones, including Google Pixel 8 and iPhone 15, prove differently.

Knowing this, cameras have always been an exciting part of any smartphone because users need to be able to capture every moment of every day through pictures. It is thus that an image quality shaped today by smartphones—considering the optical limitations of compact devices—also turns out with correct exposure, detailed clarity, and vibrant color.

While this has partially been made possible by innovation with lenses and sensors, it is the powerful AI and machine learning technologies that make all the difference.  Traits Inbuilt AI technology in smartphone cameras can now combine professional-grade capabilities with intuitive editing features earlier confined to expensive software.  From grainy, low-resolution cameras, they became indispensable—until today, high-quality photo capable devices. But while it packs impressive hardware, the real magic lies in the AI-powered software of today’s smartphones.

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Defining AI Cameras

An AI camera leverages artificial intelligence (AI) to enhance image quality and streamline the image editing process. AI, a branch of computer science, focuses on creating machines or software that can perform tasks typically requiring human intelligence, such as learning, reasoning, and problem-solving.

AI technologies used in cameras include machine learning, computer vision, deep learning, and neural networks. Machine learning allows computers to learn from data and improve performance without explicit programming. Computer vision allows computers to understand and process visual information, such as images and videos. Deep learning, a subset of machine learning, uses multiple layers of artificial neural networks to learn from vast amounts of data and perform complex tasks. Neural networks, systems of interconnected nodes, mimic the structure and function of biological neurons in the brain.

AI cameras utilize these technologies to detect faces, objects, scenes, and other elements in images, adjusting settings accordingly. For instance, an AI camera can recognize a person’s face and apply beautification filters or portrait mode to enhance their appearance. It can also identify landscapes or sunsets, enhancing colors and details to make them more vivid and dramatic.

How AI Enhances Imaging and Photography

In smartphone cameras, AI utilizes machine learning algorithms trained on extensive image datasets. These algorithms analyze real-time data from the camera sensor and intelligently adjust various aspects of image processing, including:

• Scene Detection: AI identifies the scene (portrait, landscape, food, etc.) and adjusts camera settings accordingly.
• Object Recognition: AI recognizes objects within the frame (people, animals, buildings) and optimizes settings for specific details.
• Noise Reduction: AI algorithms detect noise caused by low light and apply effective noise reduction techniques.
• HDR (High Dynamic Range) Processing: AI combines multiple exposures to create images with a wider dynamic range, capturing details in both highlights and shadows.
• Color Correction: AI adjusts color balance and saturation for a natural or artistic look based on the scene.

Operating Mechanism of AI Cameras

AI camera enhances the photos by algorithms and data that apply—automatically—filters, effects, presets, and more. Algorithms are basically rules or instructions that give guidance to perform any task on those computers; the data acts as the input or output for algorithms.

These algorithms, coupled with the data, train the AI cameras to recognize different aspects of images and optimize them. For instance, the face detection algorithm detects faces and marks them within an image. A face recognition algorithm matches these faces with a database and identifies persons. Then a face beautification algorithm can be applied to features like skin smoothing, teeth whitening, and eye enlargement.

AI cameras also have filters, effects, presets, and other enhancements applied to images. Filters change colors, contrast, and brightness to different tones so that the image looks unique. The effects are those that add new elements to the photo, like stickers, frames, or text. Presets are basically filter-and-effect mixes done in a certain way to achieve a particular style or mood.

Different filters, effects, and presets are used depending on the situation and the overall preference of the users. For example, a noise reduction filter is used to remove unwanted pixels or grains, an HDR effect combines multiple exposures to realize a higher dynamic range, while a vintage preset can give an image an antique look.

Users can instruct AI cameras to either set custom settings or re-edit images manually. They will have the possibility to select modes or options that will help them achieve the result they need, adjust various intensities of filters, crop, rotate, resize, flip, etc.

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Addressing AI Challenges in Smartphone Cameras

While AI holds significant potential, several challenges must be addressed to fully unlock its capabilities in smartphone cameras:

• Power Consumption: Running complex AI algorithms requires significant processing power. This can strain smartphone batteries and limit the real-time performance of AI features on lower-end devices. As chipsets become more powerful and energy-efficient, AI features will become smoother and more accessible across different smartphone tiers.
• Privacy Concerns: AI algorithms require vast amounts of training data, often including user-generated images. Manufacturers must ensure robust data privacy practices to protect user data used for training AI models. Transparency regarding data collection and usage is crucial to maintain user trust.
• Bias in Algorithms: AI algorithms are only as good as their training data. Biased training data can result in biased AI-powered features. Smartphone camera manufacturers must use diverse datasets for training to avoid biases in scene detection, object recognition, and other AI functionalities.
• User Customization: While AI automation simplifies photography, some users might prefer more control over their photos. Providing options to adjust AI settings or toggle certain features on and off allows users to balance automation and creative control.

Key AI Technologies in Smartphone Cameras

Computational photography: AI in smartphones identifies many scenes automatically, changing relevant settings, from exposure to focus and color balance. Machine learning models are trained on very large data sets that would enable the recognition of classes and settings of objects. Very soon now, this will enable real-time image enhancement and complex photo compositions—something otherwise requiring post-processing.

Face Detection and Object Tracking: The advanced smartphones are equipped with AI-powered face detection, which efficiently detects and puts a focus on human faces in the frame. It further believes in tracking moving objects, thus becoming very useful for capturing sharp images of desired moving objects in any kind of sports or wildlife photography environment​.

Low-Light and AI Picture Night Modes: One of the many places that genuinely benefit from AI in smartphone cameras is low-light performance. More advanced algorithms capture light while reducing noise, which allows one to take clearer and brighter images at night or in poorly lit environments using just a smartphone—something previously thought unimaginable.

Video Stabilization: AI also contributes to video stabilization, therefore the footage is professional in a way. Work well under handheld shooting or fast-moving object capturing.

Ethics and Authenticity: The question of ethics in AI-equipped smartphone cameras is related to the authenticity of photos taken by them. According to experts, AI algorithms have evolved to such a degree that manipulation by them would hardly represent reality correctly anymore. Faces beautified, environmental features changed within a scene—everything would change without requiring explicit consent from the user.

Examples of AI-driven features in Smartphones

Case Studies: Leading Smartphones with Advanced AI Imaging

#1 Apple’s Deep Fusion and Smart HDR photos

Apple has long been at the forefront of innovation, particularly in smartphone technology. Among its most notable advancements are Deep Fusion and Smart HDR, two AI-driven imaging technologies that have significantly enhanced the photographic capabilities of the iPhone. This case study delves into the intricacies of these technologies, examining how they leverage advanced AI to deliver stunning photo quality.

The evolution of smartphone photography has been driven by the need for better image quality in varying conditions. Traditional camera sensors and processors had limitations in dynamic range and detail capture. Apple sought to overcome these challenges through the integration of artificial intelligence in its imaging pipeline, resulting in the development of Smart HDR and Deep Fusion.

Smart HDR: High Dynamic Range Photography

Smart HDR (High Dynamic Range) was introduced with the iPhone XS. This technology aims to capture more detail in both the bright and dark areas of a photo.

How Smart HDR Works:

1. Multiple Frames Capture: When a photo is taken, the camera captures multiple frames at different exposures.
2. AI-Powered Analysis: Advanced algorithms analyze these frames in real time.
3. Composite Image Creation: The AI combines the best parts of each frame to create a single image with enhanced dynamic range, better detail, and improved color accuracy.

Deep Fusion: Detail Enhancement

Deep Fusion, introduced with the iPhone 11 series, focuses on improving the detail and texture of photos, particularly in medium to low-light conditions.

How Deep Fusion Works:

1. Pre-Shutter Capture: The camera captures four short and four secondary frames before the shutter button is pressed.
2. Post-Shutter Capture: One long exposure shot is taken when the shutter is pressed.
3. AI-Driven Processing: The neural engine analyzes these nine images, pixel by pixel, selecting the best parts from each to create a final, highly detailed photo.

Key Technologies and Innovations

• Neural Engine: The core of these technologies is Apple’s Neural Engine, a specialized hardware component designed to accelerate machine learning tasks.
• Real-Time Processing: Both Smart HDR and Deep Fusion perform complex computations in real-time, ensuring that users experience minimal delay in capturing and processing images.
• Semantic Rendering: AI algorithms understand different parts of the image (e.g., sky, faces, foliage) and apply specific adjustments to each, enhancing the overall quality.

#2 Google’s Pixel Series

Google’s Pixel smartphones have earned a reputation for their exceptional camera capabilities, driven by innovative AI-powered features. Among these, Night Sight and Super Res Zoom stand out as groundbreaking technologies that have redefined low-light photography and digital zoom performance. This case study explores the technical workings and impact of these features, showcasing how Google leverages advanced AI to enhance mobile photography.

Smartphone cameras have historically struggled with low-light photography and digital zoom, often resulting in noisy, blurred images. Google’s Pixel series addressed these challenges by integrating sophisticated AI algorithms and machine learning techniques into their camera systems, significantly improving photo quality under difficult conditions.

Night Sight: Revolutionizing Low-Light Photography

Introduced with the Pixel 3, Night Sight allows users to capture sharp, vibrant photos in extremely low-light conditions without the need for a flash.

How Night Sight Works:

1. Multiple Frame Capture: When Night Sight is activated, the camera captures a series of frames at varying exposure levels.
2. Motion Metering: The AI analyzes motion in the scene to decide whether to merge frames or discard them, ensuring sharp images even if there is slight movement.
3. AI-Powered Alignment and Merging: Using machine learning, the camera aligns the images, merges them, and reduces noise.
4. Color Balancing and Detail Enhancement: The AI adjusts color balance and enhances details to produce a bright, clear image that looks natural.

Night Sight’s effectiveness is largely due to its sophisticated AI algorithms, which optimize the image processing in real-time, allowing for high-quality photos even in near-darkness.

Super Res Zoom: Enhancing Digital Zoom with AI

Super Res Zoom, first introduced with the Pixel 3, uses AI to improve the quality of photos taken with digital zoom, providing results that rival optical zoom.

How Super Res Zoom Works:

1. Multi-Frame Capture: The camera captures multiple frames in quick succession as the user zooms in.
2. Sub-Pixel Shifts: Slight hand movements between frames cause sub-pixel shifts, which the AI uses to gather more data about the scene.
3. AI Image Processing: The AI analyzes these frames, aligns them, and combines the information to create a higher-resolution image.
4. Detail Enhancement: Machine learning algorithms enhance details and reduce noise, resulting in a sharp, clear photo even at high zoom levels.

Super Res Zoom effectively overcomes the limitations of traditional digital zoom by using AI to synthesize the details from multiple frames, providing a clearer, more detailed image.

Key Technologies and Innovations

• HDR+: Both Night Sight and Super Res Zoom benefit from HDR+ technology, which captures multiple images and combines them to improve dynamic range and reduce noise.
• Machine Learning: Google’s custom-built machine learning models are at the heart of these features, enabling real-time image analysis and enhancement.
• Computational Photography: Integrating computational techniques allows the Pixel cameras to perform complex image processing tasks that were previously impossible on smartphones.

#3 Huawei’s P Series

Huawei’s P Series smartphones have consistently pushed the boundaries of mobile photography. Central to this innovation is the AI-powered scene recognition technology, which utilizes advanced AI to optimize camera settings for a wide range of scenarios. This case study explores how Huawei’s P Series, particularly through models like the P30 and P40, leverages AI to enhance imaging capabilities, providing users with professional-grade photography tools.

AI-Powered Scene Recognition

Huawei’s AI-powered scene recognition automatically detects the type of scene being photographed and adjusts the camera settings accordingly. This feature is powered by the Kirin chipset’s Neural Processing Unit (NPU), which enables real-time analysis and optimization.

How AI-Powered Scene Recognition Works:

1. Scene Detection: The AI analyzes the scene in real-time, identifying various elements such as people, landscapes, animals, and objects. The system can recognize over 1,500 scenarios in 25 categories.
2. Parameter Adjustment: Based on the detected scene, the AI adjusts the camera settings, including exposure, color balance, contrast, and sharpness, to optimize the image.
3. Continuous Learning: The AI continuously improves its recognition and adjustment capabilities through machine learning, leveraging data from millions of images.

Key Technologies and Innovations

• Kirin Processor with NPU: The NPU in Huawei’s Kirin processors is specifically designed to handle AI tasks, enabling efficient and real-time scene recognition and image processing.
• Dual-NPU Architecture: In newer models like the P40, the dual-NPU architecture allows for faster and more accurate AI computations, enhancing overall camera performance.
• Collaboration with Leica: Huawei’s partnership with Leica brings advanced optics and imaging expertise, further enhancing the AI-driven photography experience.

How AI camera in Smartphones Improves User Experience

AI cameras revolutionize smartphone photography by offering numerous benefits that enhance user experience:

• Improved Image Quality: AI adjusts to various lighting conditions, enhances colors and details, and reduces noise and blur. It compensates for smartphone hardware limitations like small sensors and fixed apertures, resulting in professional-looking, realistic images.
• Time and Effort Savings: AI automates tasks, eliminating the need for post-processing or external apps. It selects optimal settings and enhancements based on scenes and subjects, providing real-time or quick editing capabilities. This makes photography convenient and enjoyable.
• Expanded Creative Possibilities: AI introduces a range of filters, effects, presets, and enhancements that transform images in diverse ways. It suggests new styles based on user preferences or trends, allowing for personalized and expressive photography experiences.

Also Read: AiThority Interview with Christine Livingston, Managing Director – Global AI Leader, Protiviti

Future Outlook

5G smartphones represent a significant advancement in mobile internet technology, promising more reliable connections and faster speeds. With lightning-fast download and upload capabilities, large media files such as movies and high-resolution images can be transferred in seconds. This speed enhancement will simplify the capture, editing, and sharing of high-quality photos and videos, providing users with unprecedented convenience.

The evolution of smartphone camera technology, augmented by various lenses, artificial intelligence, machine learning, and 5G connectivity, signifies an exciting future for mobile photography. Manufacturers continuously enhance the capabilities of smartphone cameras, paving the way for groundbreaking innovations in the coming years. Enthusiasts in both technology and photography can capitalize on the growing demand for high-tech camera smartphones by creating blogs or vlogs, leveraging the current low competition in this burgeoning market.

[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

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Collaboration to accelerate enterprise digital transformation and integrate Hitachi’s industrial applications with Singtel’s Paragon ecosystem

Singtel, a leading communications technology group in Asia, and Hitachi Digital, representing Hitachi’s broad end-to-end digital transformation services and technology capabilities,announced a new collaboration that will pair Hitachi’s deep AI expertise with Singtel’s Paragon platform, the all-in-one orchestration platform for 5G, edge computing and cloud.

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Hitachi Digital will deploy Paragon at the Hitachi Americas’ Santa Clara R&D Labs, followed by a pilot in a U.S. factory for Industry 4.0 use cases. The pilot will aim to validate the interoperability of Hitachi AI applications on quality assurance, workplace safety, immersive training and pre-emptive maintenance on Paragon. The trial will also enable the integration of Paragon with Hitachi industry cloud applications and digital services to enable enterprises to transcend the limitations of complex, low-latency connectivity and productivity experiences.

Hitachi’s pre-built Industrial AI applications together with the Paragon platform’s network and multi-cloud orchestration capabilities will be used to create multiple Paragon-related offerings to help clients improve and accelerate their cloud operations. Subsequently, Hitachi Digital Services will go to market with these offerings as a Singtel Paragon authorized System Integrator – presenting a unique value proposition to enterprise customers looking to leverage multiple network protocols in delivering digital transformation in industrial settings.

Mr. Bill Chang, CEO of Singtel’s Digital InfraCo, said, “Enterprises in the fast-growing Industry 4.0 sector depend on high quality, reliable connectivity to ensure smooth operations. We are pleased to collaborate with Hitachi Digital, leveraging Paragon to manage its connectivity and cloud needs across Hitachi’s manufacturing facilities. Integrating Hitachi’s advanced AI applications with Paragon’s ecosystem will enhance our suite of solutions for manufacturing enterprises and enable them to seamlessly transform their operations powered by AI.”

Mr. Frank Antonysamy, Chief Growth Officer, Hitachi Digital, said, “Hitachi has invested heavily in combining decades of digital, data, cloud, AI, cybersecurity, and connectivity expertise to establish transformative solutions for Industry Cloud deployments. Our applications and consulting services in this area have been an integral part of the digitalization movement impacting businesses around the world. We anticipate that this partnership with Singtel will enable us to once again increase the capabilities of next gen technologies in enterprise environments, enabling a new level of productivity for customers.”

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Organizations have often struggled with industrial 5G deployments because of complex and fragmented solutions. AI has added a new layer of complexity to this equation as organizations now also attempt to accelerate AI adoption in these scenarios. Singtel Paragon is a comprehensive solution that enables them to connect with the 5G network and securely deploy edge computing and AI rapidly on telco infrastructure, thus reducing time-to-market and shortening the innovation curve.

The collaboration between Singtel and Hitachi will bring together interoperable solutions with expert delivery services, which will greatly benefit organizations seeking to address industrial AI complexity.

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[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

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Nokia has announced that it has been selected by Telehouse America to update its NYIIX Peering Exchange production network in eight POPs located in the Northeastern United States. Once deployed, Nokia’s IP and optical interconnection solution will allow NYIIX to launch up to 400 Gigabit Ethernet (GE) interconnection services on the newly designed NYIIX Astron peering platform. These services will target OTTs, CDNs, eyeball networks, cloud service providers, online gaming providers, the education sector as well as global enterprises including financial services companies, media, professional sports customers and many others operating in the New York, New Jersey, and Philadelphia metropolitan areas beginning in November 2024.

Charles Marsh, VP for US Majors/Regionals and Enterprise at Nokia, said – “Our background of developing and deploying industry leading IP routers allowed us to build a very competitive solution portfolio for the data center market in recent years. This new project with Telehouse America and NYIIX, one of the pioneers in the US IXP market, is an excellent opportunity for Nokia. We thank them for their confidence and look forward to helping them grow their business”.

The NYIIX Peering Exchange is one of the largest neutral IXPs in the world. Its mission is to provide the internet community with a neutral and scalable peering infrastructure, and to assure reliability and stable internet connectivity. To maintain this quality, and to prepare for future growth, Telehouse America needed a network upgrade to allow customers served from NYIIX to benefit from a new, massively scalable and future proof network platform that could handle the unpredictable demands from major life events, including large sporting matches with international appeal.

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Nokia has been building a robust portfolio for data center networking that includes Data Center Fabric solutions, as well as a broad range of products such as Interconnect routers, edge and core routers, and data center switching platforms.

Nokia has deployed a complete solution for Telehouse America that includes the Service Router Operating Systems (SR OS), 7750 Service Routers, 7250 Interconnect Routers and QSFP-DD 400G coherent optics. Nokia will also provide related professional services, such as network operator training and certification.

Akio Sugeno, VP Internet Engineering and Business Development at Telehouse America, said: “We selected Nokia because they offered us a comprehensive and scalable solution that meets our current and future networking needs. Nokia has proven expertise in designing and deploying high-performance networks for internet exchange points. With Nokia, we can deploy the brand-new NYIIX Astron architecture, which is based on EVPN technologies and will allow us to offer 10, 100 and 400 Gigabit ports for peers. This will be a complete departure from the previous architecture, which was MPLS/VPLS based. This is a very important deployment for NYIIX because it will enable us to offer our customers faster, more reliable, and more secure connectivity across our locations in the US. We are delighted to partner with Nokia and leverage their innovative technology and services.”

Telehouse began operating in 1989 and is a global provider of carrier-neutral data centers, serving 3,000+ customers, including carriers, content providers, enterprises and financial services companies. Its US operation, Telehouse America, is a pioneer in the US data center industry, operating leading data center and colocation facilities in New York for over 35 years, providing direct access to major carriers with 99.999% SLA uptime.

[To share your insights with us as part of editorial or sponsored content, please write to sghosh@itechseries.com]

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Plus, a leading provider of highly automated and autonomous driving software solutions, announced today the launch of a new and breakthrough technology offering called PlusProtect™. PlusProtect is AI-based software that enhances next-generation safety systems for all vehicle types with industry-leading functionalities like high performance automatic collision mitigation.

Safety systems help contribute to enhanced road safety. According to the National Highway Traffic Safety Administration (NHTSA), 60,000 rear-end crashes a year involve a heavy vehicle striking another vehicle.

PlusProtect is an AI-based perception software for road safety

PlusProtect is a scalable technology that allows global Tier 1 automotive suppliers and vehicle manufacturers to offer greatly enhanced safety features in their next-generation safety systems. These features would address, if not exceed, the performance requirements mandated for automatic emergency braking (AEB) on all passenger vehicles and light trucks by September 2029. AEB is also expected to be mandated in heavy vehicles (gross vehicle weight rating of more than 10,000 pounds).

Key features offered by PlusProtect include high performance AEB, expanded-coverage lane departure warning, traffic jam assist, predictive fuel optimization, self-calibrated sensors, and over-the-air updates. Additional options include GSR-compliant features and an easily-extracted event data recorder that can provide a recording of a vehicle’s operational data immediately preceding and following a safety critical event.

The highly advanced features in PlusProtect are made possible by using cameras and radars to see objects more than approximately 650 feet (200 meters) ahead. Compared to safety systems which react to obstacles in its lane, PlusProtect has full situational awareness to understand where the vehicle is located and what objects are in its own lane as well as nearby lanes.

PlusProtect technology helps to significantly reduce false positives and can also handle AEB on curved roads. Combined with Plus’s powerful, proprietary AI-based autonomous driving software and cutting-edge perception technology, the vehicle has a remarkably accurate view of the world around it. It is also able to predict the movement of surrounding vehicles and obstacles and assist the driver by reacting quickly and automatically in order to help mitigate potential forward collisions.

“While improved road safety underlies all of our solutions, we created PlusProtect specifically to enable Tier 1s and OEMs to build market-leading next-generation safety systems. Features such as high-performance collision mitigation not only necessitate a new technology approach, adopting PlusProtect as part of the integrated safety solutions also helps them pave the way for higher levels of automation in their product portfolio,” said Shawn Kerrigan, COO and Co-Founder at Plus.

PlusProtect is built on a flexible architecture

PlusProtect is built on a flexible architecture that adapts easily to different sensor configurations and handles variations in platform, such as U.S. and Europe truck designs and both left- and right-hand driving. Long range cameras continuously auto-calibrate, offering cost-effective and accurate depth at extended ranges. With global deployments across the U.S., Europe and Australia, PlusProtect offers more advanced capabilities and reliability across diverse applications.

Kerrigan emphasized that advanced safety technologies like PlusProtect do not replace skilled, alert drivers exercising safe driving techniques. Proactive, comprehensive driver training is also essential. He noted that responsibility for safe vehicle operation always rests with the driver and that limitations exist. Drivers should become familiar with these limitations before operating any equipped vehicle.

Plus is a global provider of autonomous driving software solutions that span AI-based perception software PlusVision™ to next-gen safety technology PlusProtect™, highly automated PlusDrive®, and driver-out SuperDrive™. Headquartered in Silicon Valley, California with operations in the U.S., Europe, and Australia, Plus is named by Forbes as one of America’s Best Startup Employers and by Fast Company as one of the World’s Most Innovative Companies. Plus’s large AI model, engineered to solve the driving intelligence problem, is already powering vehicles in commercial use today.

Source: Plus

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T-Mobile is teeing up more 5G firsts!

Today, T-Mobile (NASDAQ: TMUS) announced it is deploying cutting-edge 5G solutions at the PGA Championship to elevate the fan experience for the millions watching at home and hundreds of thousands at Valhalla Golf Club from May 15–19.

Through T-Mobile’s 5G Advanced Network Solutions (ANS), PGA of America will leverage golf’s FIRST 5G private network in the U.S. to enable operational efficiencies that bring unprecedented broadcast viewing experiences for golf fans everywhere. Plus, T-Mobile is enhancing the experience for spectators onsite with network slicing and the nation’s leading 5G network.

Fans will get:

• Enhanced views of Hole 13: For the first time in golf, 5G will be implemented into a live broadcast. Using the capabilities of a T-Mobile 5G private network, CBS Sports will be able to use 5G-connected cameras for new angles of the iconic Hole 13, and cinematic quality footage, giving fans more hero shots of their favorite players at Valhalla.
• More content with the T5G Range Live Show: Fans can watch brand-new pre-championship coverage live on PGA digital and social channels. T-Mobile’s 5G private network and 5G POV cameras will bring fans an exclusive, up-close look at the action on the practice range while PGA coaches and expert commentators provide valuable insights and analysis on the players’ warm-up sessions. Fans will also get detailed stats, including ball speed, apex, curve, distance and more.
• A Club Magenta experience on the course: Guests at Valhalla can get up close and personal with T-Mobile athletes like Tony Finau, Wyndham Clark and Max Homa in a live Q&A at Club Magenta, a VIP lounge with benefits like premium views and complimentary phone charging. And T-Mobile customers can flash their Magenta Status to get even more perks like Fast Lane access to the Club Magenta tent, free T-Mobile merch including chairs for the course AND Magenta cocktails.

“Sports organizations typically come to T-Mobile to see if 5G can help them enhance operations, the fan experience, or the event broadcast, and we’re delivering all of the above and more at the PGA Championship,” said Callie Field, President, T-Mobile Business Group.

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Callie added, “5G firsts are always exciting, but it’s so rewarding to see how our T-Mobile for Business solutions are making a tangible difference — from making it easier for producers to capture and create amazing new broadcast moments to helping fans experience even more action.”

5G Behind the Scenes at T-Mobile

Producing a live broadcast like the PGA Championship in the face of variables like crowd size, traffic flow and the layout of the course is an incredible effort. It’s also a huge infrastructure lift for fans to have a good experience both onsite and watching from home.

5G is changing that thanks to:

Streamlined operations with reduced wiring and cabling: 

More wireless cameras can mean the course is freed of thousands of feet of wiring and cabling, resulting in faster setup and teardown, and major cost savings potential. Plus, the private network is portable and can be deployed without a major installation effort. The 5G private network also adds capacity to make other systems — like security cameras or ticketing — wireless as well.

Fiber-like data transmission speeds for broadcast quality video without the cumbersome cables:

Wired, 4K cameras are confined to cables, so they’re limited in number, placement and mobility. And – until now – wireless cameras have been limited to HD versus full 4K resolution. Thanks to T-Mobile’s 5G private network and Sony PDT-FP1 portable data transmitters combined with Sony’s ultra-low latency encoders/decoders, Sony’s FX6 cameras are getting a glass-to-glass latency averaging under 100 milliseconds. These faster speeds open capacity to support more wireless cameras and give production teams creative freedom to provide new angles all around the course.

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Critical business operations powered through a network slice:

By carving out a dedicated channel within the broader 5G macro network, a network slice can help optimize performance and increase the reliability of the concession payment terminals as well as ticketing scanners. This ensures they run smoothly and deliver peak performance and customer experiences, all while the fans onsite at the tournament use their phones without any interruptions.

“We’re thrilled to introduce groundbreaking technology to one of golf’s most significant events through this partnership with T-Mobile,” said Jeff Price, Chief Commercial Officer of the PGA of America.

Jeff added, “T-Mobile has paved the way for unprecedented innovation that will continue to thrill our fans. And this is just the beginning.”

GenAI Experts Series Part 1: Building Brand in the Age of AI

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On the first day of MWC Barcelona 2024 held recently, Leo Ma, Vice President of Huawei Cloud Core Network Product Line, delivered a compelling keynote speech at the 5.5G Core Summit. In his speech, Leo elaborated on the extraordinary advancement of the 5.5G intelligent core network and its far-reaching influence on future communications technologies, and further emphasized the key role of service, network, and O&M intelligence in advancing the communications industry. Leo stated that “the 5.5G intelligent core network incorporates service, network, and O&M intelligence. It helps operators to cope with the changes in users, services, communications models, and networks, and also helps them rebuild the service entry, redefine business models, and reshape cloud-based O&M approaches.”

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Service Intelligence Rebuilds the Service Entry for Operators

With the development of intelligence technologies and the introduction of more XR devices, single-modal communications have evolved to multi-modal communications. New Calling, pioneered by service intelligence, has been deployed in 31 provinces of China after only being launched last year, and currently serves up to 50 million users. Along its deployment, multiple innovative services have been put into commercial use, such as visualized voice calling, real-time translation, and fun calling. These services can provide users with multi-modal data exchanges, including speech-to-text, speech-to-image, and gesture-to-animation conversions. Besides these novel experiences, service intelligence also helps operators rebuild the service entry, transforming voice-only operations into content operations and transitioning voice and video calling into multi-modal communications to support immersive XR applications. Huawei is continuing its rapid innovation drive with the launch of voice driven avatars, enabling users to customize their own avatars based on rendering in real time. In the soon future, enterprises can also customize virtual brand ambassadors for promoting their brands.

Network Intelligence Redefines Business Models

There are three technical gaps that impede operators from achieving experience monetization on MBB networks: service experience cannot be assessed, services cannot be dynamically optimized, and the operations are not closed-loop. To bridge the aforementioned gaps, Huawei proposed the Assessment, Optimization, and Monetization (A.O.M) concept and implemented the concept through the Intelligent Personalized Experience (IPE) solution. Assessment: Service experiences can be assessed in real time, which is the basis of experience monetization. Optimization: Service experiences can be dynamically optimized, helping to maximize network efficiency. Monetization: After a guarantee is completed, an experience report is immediately sent to the user, so that they can readily identify the guarantee effects. The network intelligence currently empowered by the A.O.M concept helps operators achieve differentiated experience monetization. This is not purely a technology innovation, it is more of a comprehensive upgrade of operators’ business concepts and patterns as well as a reshaping of business models.

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O&M Intelligence Reshapes Cloud-based O&M Approaches

O&M intelligence becomes the key to efficient telecom network operation, driving the evolution from automatic deployment to end-to-end automatic delivery, and then to rule-driven and large model-based O&M. The Digital Assistant & Digital Expert (DAE) draws on such an innovative and intelligent O&M approach. Enabling a visualized topology on the GUI and harnessing its strengths in a multi-modal large model, the DAE dives into core O&M workflows. Take monitoring and troubleshooting network problems, such as link, cloud resource, or license faults, as an example. After the digital assistant detect faults, the digital expert can analyze these faults. In the future, troubleshooting is expected to be further automated. At an FOA site (for POC) for an operator in China, the DAE helps close 80% of trouble tickets, saving 750 person-days per month.

The launch of the 5.5G intelligent core network marks not only a leap in technical capabilities, but also a big step for the entire communications industry in shifting towards intelligent, efficient, and personalized services. As the 5.5G core network develops and extends to more scenarios, it will empower the communications network to be more intelligent, reliable, and efficient, bringing brand-new communications experiences to users, and opening up new business models and growth opportunities for operators.

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At MWC 2024, Huawei launched the Intelligent Factory Solution, which was part of Huawei’s Manufacturing and Large Enterprise Session on “Delve into Industries, Creating a Better, Greener, and Smarter Future”. The session gathered industry leaders and experts to share the latest solutions and best practices in product R&D,  production, and operation management, while also encouraging cooperation.

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Liu Chao, CEO of Huawei’s Manufacturing and Large Enterprises Business Unit, said: “The integration of digital technology and the real economy is advancing. Huawei will continue to leverage technological innovation and industry know-how to provide intelligent products and solutions that cover the entire value chain of manufacturing enterprises. We will also collaborate with partners to serve end customers better.” Liu continued to explain that Huawei aims to help enterprises upgrade their ICT infrastructure to accelerate product R&D and innovation, improve production efficiency while reducing costs, and ensure streamlined, sustainable enterprise operations.

Wang Zhiya, COO of Huawei’s Manufacturing and Large Enterprises Business Unit,  hosted the launch of the Intelligent Factory Solution. This solution adopts a technology architecture of “one cloud, one network, and one platform”, which streamlines the engineering data flow, business information flow, and production process flow.

Specifically, “one network” integrates IP, industrial passive optical network (PON), and 5G, making it possible to seamlessly connect numerous devices on a large scale across multiple scenarios. In addition, “one network” also bolsters the data collection efficiency to an industry-leading 1 million data points per second.

Furthermore, Huawei Cloud provides data and application enablement, as well as other services, to support intelligent applications such as advanced production scheduling and digital twins. This can help manufacturers shorten the order-to-delivery cycle while improving overall equipment effectiveness.

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Regarding enterprise ICT infrastructure upgrades, Tamás Szabó, Officer of Data Center at BorsodChem, shared his experience in building green data centers.

For intelligent enterprise applications, Lili Yin, General Manager of Europe at Quicktron Robotics, introduced the Smart Logistics Operations System Solution, co-created with Huawei. Yin also shared project on quick warehouse AMRs powered by Huawei’s AirEngine Wi-Fi 6.

Huawei believes that with constant interaction, exchange, and collaborative efforts, enterprise digitalization and intelligence will progress, leading to more growth and a brighter future for the industry.

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Iridium’s advanced portfolio of easily integrated assured PNT solutions will protect global industries and digital critical infrastructure

Iridium Communications a leading provider of global voice and data satellite communications, announced that it had entered into an agreement to acquire Satelles, Inc., the leader in highly secure satellite-based time and location services that complement and protect GPS and other GNSS-reliant systems.

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The service, named Satellite Time and Location (STL), is an easy-to-adopt, highly secure solution that increases the efficiency and reliability of timing systems for digital infrastructure like 5G base stations, data centers, and other critical infrastructure and protects against GNSS vulnerabilities using low-cost hardware that doesn’t require outdoor antennas. This acquisition continues Iridium’s philosophy of investing in differentiating technologies uniquely suited to its network that significantly outperform competing solutions.

The market for assured Positioning Navigation and Timing (PNT) services, estimated to reach $3.5 billion in 2032, is evolving to require integrated small-form-factor devices instead of the server rack-size solutions connected to outdoor GPS antennas that are available today. Time synchronization and location data play an important role in the global economy, particularly in the commercial sector for major industries supported by critical infrastructure, such as financial services, telecommunications, cyber security, and transportation.

These industries and others rely on an estimated 10,000 data centers globally and their hundreds of millions of data processing and storage servers. Each of these servers requires time synchronization and can benefit from the in-server room efficiency and resilience delivered by Iridium STL.

Iridium will now work to reduce the size and cost barriers to adoption, enabling deployment of a more accessible solution for integration with autonomous systems, consumer devices, vehicles and traditional markets like aviation, maritime and land mobile. It also provides an opportunity for Iridium’s existing partner eco-system to add to their portfolio of solutions and harden their GNSS-reliant products and infrastructure.

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“This market is growing; it’s a perfect application of our network, and this solution solves a problem for critical industries better than anything else,” said Iridium CEO, Matt Desch.  “Acquiring Satelles makes perfect sense for Iridium and is consistent with what our strategy has always been, which is to take advantage of our unique network to do what others can’t or do it better than anyone else can.  STL is the superior solution available today, and we have been following and investing in Satelles’s technology roadmap to allow us to create even more opportunity. We’re excited to formally bring the Satelles team “in-house,” to the Iridium family.”

The STL service utilizes the stronger broadcast paging channels of the Iridium satellite constellation to deliver precise timing information, which provides truly global, secure time and location signals that are 1,000 times more powerful than GNSS constellations. The service is resilient to regional GNSS outages, works inside buildings and is being used today to secure digital infrastructure for financial markets, governments, and major corporations.

STL will become a new business line of Iridium, led by Satelles CEO, Dr. Michael O’Connor who will report to Iridium CEO, Matt Desch.  “Bringing STL into the Iridium family is going to be a supercharger for this capability that will benefit our customers and our society. I look forward to a bright future together,” said O’Connor.
Iridium is assuming all rights to the Satelles patent portfolio and anticipates the Iridium STL line of business will generate over $100 million in service revenue per year, by 2030, and additional revenue from equipment and engineering.

A long-standing investor in Satelles, Iridium had an ownership stake of around 20 percent from three previous investments in the company. For the remaining approximately 80 percent, Iridium will pay about $115 million, net of cash remaining in the Company, which will be financed through a tack-on to its term loan. Iridium expects to complete the acquisition in the next few weeks.

As previously announced, Iridium will be speaking at today’s Raymond James Annual Institutional Investors Conference at 4:00 p.m. ET, where additional details regarding this transaction will be shared.  The presentation from the conference can be viewed via webcast through the events page of Iridium’s Investor Relations website. Commentary will also be included during our first quarter 2024 earnings call in April.  This transaction is the first acquisition of another company in Iridium’s history.

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CloudRAN.AI, a trailblazing Singapore-based company, made its official debut at the Mobile World Congress (MWC) 2024 in Barcelona. The firm specializes in providing pure software-driven Private 5G network solutions, tailored for vertical industries seeking to harness the power of edge cloud computing and AI to fuel their digital transformation.

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With a vision to seamlessly integrate production processes with advanced technologies, CloudRAN.AI aims to empower businesses to achieve industrial digitalization with ease and efficiency. The company’s CloudNative P5G solution stands out for its exceptional adaptability across various ecosystems, eliminating the need for additional hardware acceleration and simplifying the deployment of Private 5G networks within existing IT infrastructures.

CloudRAN.AI’s cutting-edge interference management technology and artificial intelligence algorithms not only enhance the efficiency of network deployment but also deliver comprehensive coverage without the complexity of traditional radio frequency planning. The company’s OpenAPI strategy further opens up a world of possibilities by providing open interfaces for uppper application, fostering innovation and integration.

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The Private 5G solutions offered by CloudRAN.AI are designed for stability, user-friendliness, and cross-platform compatibility, ensuring that clients maintain a competitive edge in the market. As CloudRAN.AI embarks on this journey, the company looks forward to collaborating with clients to explore the vast potential of Industry 4.0 and achieve mutual growth.

AI CloudRAN.AI is a leading provider of AI-driven Private 5G solutions, committed to enabling vertical industries to connect, compute, and innovate at the edge. With a focus on software-defined networking, CloudRAN.AI is shaping the future of industrial connectivity and cloud computing.

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