Latest news with #edgeComputing
Forbes
04-07-2025
- Business
- Forbes
Post-Transformer Model Systems Can Drive Change
Chipset on circuit board for semiconductor industry, 3d rendering What if you could have conventional large language model output with 10 times to 20 times less energy consumption? And what if you could put a powerful LLM right on your phone? It turns out there are new design concepts powering a new generation of AI platforms that will conserve energy and unlock all sorts of new and improved functionality, along with, importantly, capabilities for edge computing. What is Edge Computing? Edge computing occurs when the data processing and other workloads take place close to the point of origin, in other words, an endpoint, like a piece of data collection hardware, or a user's personal device. Another way to describe it is that edge computing starts to reverse us back away from the cloud era, where people realized that you could house data centrally. Yes, you can have these kinds of vendor services, to relieve clients of the need to handle on-premises systems, but then you have the costs of transfer, and, typically, less control. If you can simply run operations locally on a hardware device, that creates all kinds of efficiencies, including some related to energy consumption and fighting climate change. Enter the rise of new Liquid Foundation Models, which innovate from a traditional transformer-based LLM design, to something else. A September 2024 piece in VentureBeat by Carl Franzen covers some of the design that's relevant here. I'll include the usual disclaimer: I have been listed as a consultant with Liquid AI, and I know a lot of the people at the MIT CSAIL lab where this is being worked on. But don't take my word for it; check out what Franzen has to say. 'The new LFM models already boast superior performance to other transformer-based ones of comparable size such as Meta's Llama 3.1-8B and Microsoft's Phi-3.5 3.8B,' he writes. 'The models are engineered to be competitive not only on raw performance benchmarks but also in terms of operational efficiency, making them ideal for a variety of use cases, from enterprise-level applications specifically in the fields of financial services, biotechnology, and consumer electronics, to deployment on edge devices.' More from a Project Leader Then there's this interview at IIA this April with Will Knight and Ramin Hasani, of Liquid AI. Hasani talks about how the Liquid AI teams developed models using the brain of a worm: C elegans, to be exact. He talked about the use of these post-transformer models on devices, cars, drones, and planes, and applications to predictive finance and predictive healthcare. LFMs, he said, can do the job of a GPT, running locally on devices. 'They can hear, and they can talk,' he said. More New Things Since a recent project launch, Hasani said, Liquid AI has been having commercial discussions with big companies about how to apply this technology well to enterprise. 'People care about privacy, people care about secure applications of AI, and people care about low latency applications of AI,' he said. 'These are the three places where enterprise does not get the value from the other kinds of AI companies that are out there.' Talking about how an innovator should be a 'scientist at heart,' Hasani went over some of the basic value propositions of having an LLM running offline. Look, No Infrastructure One of the main points that came out of this particular conversation around LFMs is that if they're running off-line on a device, you don't need the extended infrastructure of connected systems. You don't need a data center or cloud services, or any of that. In essence, these systems can be low-cost, high-performance, and that's just one aspect of how people talk about applying a 'Moore's law' concept to AI. It means systems are getting cheaper, more versatile, and easier to manage – quickly. So keep an eye out for this kind of development as we see smarter AI emerging.
Yahoo
27-06-2025
- Business
- Yahoo
Crusoe Introduces Crusoe Spark: Modular AI Data Centers for Scalable Edge Computing
SPARKS, Nev., June 26, 2025 (GLOBE NEWSWIRE) -- Crusoe, the industry's first vertically integrated AI infrastructure provider, today announced the launch of Crusoe Spark™, a turnkey, prefabricated modular AI factory designed to bring powerful, low-latency AI compute to the network's edge. These AI-optimized modular data centers integrate all necessary infrastructure—including power, cooling, remote monitoring, fire suppression, and racks that support the latest GPUs—into a single, portable unit. Crusoe Spark enables rapid deployments with diverse power sources for on-prem AI, edge inference, AI capacity expansion needs, with units delivered as fast as three months. AI at the edge is transforming industries by enabling real-time decision-making and intelligence directly where data is generated, without the latency and bandwidth limitations of a remote cloud system. This capability is critical for applications including autonomous vehicles needing instant reactions, real-time patient monitoring in healthcare, predictive maintenance in manufacturing, and smart city infrastructure optimizing traffic flow and public safety. This rapidly expanding market is driven by the explosive growth of IoT devices and the demand for immediate, localized AI insights. Crusoe's leadership in AI infrastructure is built upon its deep experience in hyperscale development and energy infrastructure, including its 1.2-gigawatt site in Abilene, Texas. Crusoe Spark extends this expertise to solve the critical challenge of deploying powerful AI compute closer to where data is generated and decisions are made. With over 400 modular units already deployed globally, operating in some of the harshest conditions, Crusoe brings proven reliability to the edge. 'As AI becomes ubiquitous in everyday life, it needs infrastructure solutions to match its diverse needs. This means gigawatt scale AI factories in some cases and low latency inference at the edge in others. We're excited to announce the launch of Crusoe Spark, enabling the rapid deployment of AI everywhere you need it,' said Chase Lochmiller, CEO and co-founder of Crusoe. 'These highly efficient and mobile data centers are designed for high density clusters of GPU's to be deployed on-prem, at the edge or anywhere else you want easily accessible intelligent infrastructure. The modular and ruggedized design enables us to efficiently scale to meet your needs, even in the most challenging environments.' The announcement follows Crusoe's announcement of its strategic partnership with Redwood Materials to deliver scalable, renewable, and rapidly deployable power solutions for AI factories. About CrusoeCrusoe is on a mission to align the future of computing with the future of the climate. Crusoe provides a reliable, scalable, cost-effective, and environmentally friendly solution for AI infrastructure by harnessing large-scale clean energy, building AI-optimized data centers, and empowering builders to reach their AI potential. Crusoe is empowering the AI revolution. Media ContactStephanie SchlegelOffleash for CrusoeCrusoe@ in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Yahoo
26-06-2025
- Business
- Yahoo
Embedded AI Market Size to Surpass USD 25.68 Billion by 2031
NEW YORK, June 26, 2025 /PRNewswire/ -- According to a new comprehensive report from The Insight Partners, the global embedded AI market is observing healthy growth owing to expansion of IoT ecosystem, and Integration of AI to enhance defense capabilities. The embedded AI market is expected to reach US$ 9.87 billion in 2024 and is projected to reach US$ 25.68 billion by 2031; it is expected to record a CAGR of 12.4% from 2025 to 2031. The embedded AI market is experiencing rapid growth, driven by increasing demand for real-time data processing, edge computing, and intelligent decision-making in devices. Embedded AI integrates artificial intelligence directly into hardware systems, enabling faster responses, reduced latency, enhanced data privacy, and greater reliability. It plays a crucial role in sectors like automotive, industrial automation, consumer electronics, healthcare, and IoT. As advancements in low-power AI chips and edge technologies continue, the market is poised for significant expansion, supporting smarter, more autonomous systems across various industries and applications. To explore the valuable insights in the Embedded AI Market report, you can easily download a sample PDF of the report – The report runs an in-depth analysis of market trends, key players, and future opportunities. Embedded AI refers to the integration of artificial intelligence capabilities directly into hardware devices, enabling them to process data and make decisions locally without relying on cloud connectivity. It is widely used to provide real-time, low-latency responses in applications such as autonomous vehicles, smart cameras, industrial automation, and IoT devices. By operating on-device, embedded AI improves speed, enhances privacy, reduces bandwidth use, and ensures continuous operation even without internet access. Overview of Report Findings Integration of AI to Enhance Defense Capabilities: With the increasing complexity of modern combat environments, defense forces require advanced tools that improve situational awareness and streamline decision-making. Addressing this need, Safran Electronics & Defense unveiled its Advanced Cognitive Engine (ACE) at Eurosatory 2024 in June. This innovative artificial intelligence system is designed to be integrated into all Safran Electronics & Defense products. ACE enables enhanced situational awareness, real-time decision support, and significantly reduces the cognitive burden on military personnel in high-pressure scenarios. By embedding AI directly into its systems, Safran aims to deliver smarter, faster, and more autonomous capabilities to forces on the ground. This launch marks a major step forward in the company's strategy to harness the power of AI for next-generation defense operations and battlefield efficiency. Growing Demand for Real-Time Data Processing: Embedded AI enables devices to process data locally without relying on cloud connectivity. This real-time processing is critical in applications like autonomous vehicles, industrial automation, and healthcare, where immediate decision-making is essential. To cater the growing demand for real-time data processing, market players are launching solutions, which contributes to the market growth. For instance, in March 2025, Quvia, the AI-powered QoE platform formerly known as Neuron, announced Q, a suite of embedded AI tools designed to maximize productivity and efficiency for connectivity, digital operations, and customer experience teams in the aviation, maritime, and enterprise sectors. With Q, customers can easily access network performance and QoE insights using natural language queries. In addition, new AI tools will help them unlock next-level productivity, boost operational efficiency, and elevate end-user May 2025, Qlik, a global leader in data integration, data quality, analytics, and artificial intelligence, announced an expanded set of capabilities coming soon in its Qlik Cloud Analytics solution — equipping enterprises with tools to detect anomalies, forecast complex trends, prepare data faster, and take immediate action through embedded decision workflows. Expansion of the IoT Ecosystem: The rapid proliferation of IoT devices across smart homes, industrial systems, healthcare, agriculture, and smart cities is significantly driving demand for embedded AI. As billions of connected devices generate vast amounts of data, there is a growing need for real-time, low-latency, and energy-efficient processing at the AI enables these devices to process data locally, reducing reliance on cloud computing, minimizing bandwidth usage, and enhancing privacy. This intelligent on-device processing allows IoT systems to operate autonomously, respond faster to changing conditions, and support more advanced applications—ultimately making IoT ecosystems more responsive, efficient, and scalable. Geographical Insights: In 2024, North America led the market with a substantial revenue share, followed by Europe and Asia Pacific, respectively. Asia Pacific is expected to register the highest CAGR during the forecast period. Stay Updated on The Latest Embedded AI Market Trends: Market Segmentation Based on component, the embedded AI market is segmented into hardware, software, and services. The software segment held the largest share in the embedded AI market in 2024. Based on data type, the embedded AI market is segmented sensor data, image and video data, numeric data, categorial data, and others. The numeric data segment held the largest share in the embedded AI market in 2024. Based on vertical, the embedded AI market is segmented into healthcare, BFSI, IT and ITES, retail and ecommerce, telecom, manufacturing, and others. The qualified electronic signature segment held the largest share in the embedded AI market in 2024. Based on end-user, the embedded AI market is segmented into manufacturing, BFSI, pharmaceuticals, government agencies, legal, and others. The manufacturing segment held the significant share in the embedded AI market in 2024. Competitive Strategy and Development Key Players: A few of the major companies operating in the embedded AI market are Oracle, Microsoft, IBM, AWS, NVIDIA, Google, LUIS Technology, Siemens, AMD, and Salesforce. Trending Topics: Edge AI, Neural Processing Unit (NPU), AIoT (Artificial Intelligence of Things), Autonomous systems, AI-enabled devices, AI-driven automation, etc. Global Headlines on Embedded AI Market Safran launches ACE embedded AI solution Qlik Expands Embedded AI Capabilities for Smarter Decisions and Faster Intelligence Quvia Launches Q: Embedded AI Tools to Maximize Productivity and Efficiency Artificial Intelligence Meets Embedded Development with Microchip's MPLAB® AI Coding Assistant Purchase Premium Copy of Global Embedded AI Market Size and Growth Report (2025-2031) at: Conclusion The embedded AI market is poised for substantial growth as demand for intelligent, real-time processing at the edge continues to rise across industries. By enabling devices to operate autonomously with low latency, enhanced privacy, and reduced dependence on cloud infrastructure, embedded AI is transforming applications from automotive and industrial automation to healthcare and smart cities. Advances in specialized hardware and algorithms further accelerate adoption, driving innovation and efficiency. As technology evolves, embedded AI will become increasingly integral to next-generation devices and systems, solidifying its role as a critical enabler of the digital and connected future. Trending Related Reports: About Us: The Insight Partners is a one stop industry research provider of actionable intelligence. We help our clients in getting solutions to their research requirements through our syndicated and consulting research services. We specialize in industries such as Semiconductor and Electronics, Aerospace and Defense, Automotive and Transportation, Biotechnology, Healthcare IT, Manufacturing and Construction, Medical Device, Technology, Media and Telecommunications, Chemicals and Materials. Contact Us: If you have any queries about this report or if you would like further information, please contact us: Contact Person: Ankit MathurE-mail: +1-646-491-9876Home - Logo: View original content to download multimedia: SOURCE The Insight Partners Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
National Post
26-06-2025
- Business
- National Post
VeriSilicon Expands DSP Portfolio with Silicon-Proven ZSP5000 Vision Core Series for Edge Intelligence
Article content SHANGHAI — VeriSilicon ( today released the ZSP5000 Digital Signal Processing (DSP) series IPs, which are based on its fifth-generation silicon-proven DSP architecture. This product line adopts a highly scalable and energy-efficient design, and has been deeply optimized for compute-intensive workloads such as computer vision and embedded AI. Combined with the configurable nature of the architecture, this series of IP can provide excellent solutions with both energy and computing efficiency for various edge devices. Article content The ZSP5000 series IPs include ZSP5000, ZSP5000UL, ZSP5000L, and ZSP5000H, delivering scalable vector processing performance ranging from 32 to 256 8-bit Multiply-Accumulate (MAC) operations per cycle. For even higher performance, VeriSilicon's multi-core ZSP5400H can combine multiple ZSP5000H cores in a multi-cluster architecture to further scale computing capability. Article content The ZSP5000 series features a rich and intuitive instruction set optimized for ease of programming and efficient performance tuning, while its dedicated instructions accelerate common imaging and signal processing tasks such as vector-scalar arithmetic, horizontal reductions, permutations, shifts, table lookups, clamping, and averaging. It integrates the ZTurbo coprocessor interface, allowing customers to easily add custom instructions and hardware accelerators within the same pipeline, and is compatible with the OpenCV Application Programming Interface (API), ensuring seamless integration with the mainstream computer vision frameworks. Additionally, the ZSP5000 series is equipped with a full-featured memory subsystem, a multi-channel 3D DMA engine, and a scalable multicore configuration, supporting flexible deployment for a broad spectrum of applications. Article content The ZSP5000 series IPs are backward compatible with VeriSilicon's scalar ZSPNano series, efficiently handling mixed MCU and DSP workloads. VeriSilicon also offers comprehensive ZView development tools, including an Eclipse-based Integrated Development Environment (IDE), cycle-accurate simulator, optimizing compiler, debugger, and profiling tools, streamlining software development and system integration. Article content 'With the growing adoption of OpenCV and the increasing demand for computer vision workloads alongside NPUs in edge intelligence computing, we are introducing the ZSP5000—our next-generation DSP IP series. It supports the industry-standard OpenCV API, enables streamlined interfacing with NPUs via our FLEXA interface, and integrates built-in audio processing capabilities for multi-modal applications,' said Weijin Dai, Chief Strategy Officer, Executive Vice President, and General Manager of the IP Division at VeriSilicon. 'Energy efficiency is key at the edge, and the ZSP5000 series IPs feature an optimized memory access architecture to minimize processor power consumption. It also features ZTurbo, a custom instruction extension mechanism designed for targeted applications, which enables further power and performance optimization through seamless integration of hardware accelerators. Our leading customers are already leveraging these capabilities to achieve significant advancements in power and performance.' Article content Article content Article content Article content
National Post
23-06-2025
- Business
- National Post
Digi International Announces Anterix Active Solution for Industrial Connectivity at the Edge in Utilities and Critical Infrastructure
Article content The Digi IX30 Cellular Router with Anterix Active Powers Secure, Resilient Communications for Private and Public LTE Deployments Article content MINNEAPOLIS — Digi International, (NASDAQ: DGII, a global leader in Internet of Things (IoT) connectivity solutions, announces the market launch of Digi IX30-0EG4, an edge computing industrial IoT cellular router solution. Article content The Anterix Active designation reinforces Digi's commitment to helping critical infrastructure operators deploy private LTE networks that are secure, reliable, and built for the future. Article content Digi IX30-0EG4 has achieved the Anterix Active designation, providing full support for Anterix's nationwide 900 MHz private LTE spectrum. This industrial IoT edge computing solution is specifically designed for hazardous and mission-critical applications on both public and private LTE networks. It is tailored for energy and utilities applications such as real-time monitoring and control, smart grid automation, demand response, renewable energy integration, DERMS, and SCADA systems. Fully integrated with Digi Remote Manager ®, this solution's capabilities improve security and scalability while ensuring speed, reliability and efficiency. Article content Digi IX30-0EG4 is a C1D2 and NEMA TS2-rated cellular router engineered to deliver secure, reliable connectivity for industrial assets. With support from Anterix, the large holder of licensed spectrum in the 900 MHz band (896-901/935-940 MHz) throughout the contiguous United States, plus Alaska, Hawaii, and Puerto Rico — Digi IX30-0EG4 helps utility operators unlock the full potential of private LTE networks. This low-band spectrum is ideally suited for wide-area coverage, deep penetration through obstacles, and consistent performance across vast and challenging terrains. Offering a powerful combination of coverage and capacity, it supports the always-on, secure communication channels required for grid resiliency, operational visibility, and long-term infrastructure modernization. Article content 'The Anterix Active designation reinforces Digi's commitment to helping critical infrastructure operators deploy private LTE networks that are secure, reliable, and built for the future,' said Vitaly Kurduban, Senior Product Manager at Digi International. 'Digi IX30-0EG4 provides advanced edge intelligence, streamlined integration, and ruggedized performance that is purpose-built for evolving needs — accelerating the transformation of the energy and utilities sector.' Article content Powered by Digi Remote Manager (Digi RM) and Digi Accelerated Linux (DAL OS), Digi IX30-0EG4 enables centralized configuration, deployment, and monitoring of mission-critical infrastructure at scale. Digi RM serves as the command center of the network, allowing operators to manage tens of thousands of distributed devices from a single interface — whether on a desktop, tablet, or smartphone. Meanwhile, DAL OS delivers secure edge programmability and interoperability with legacy serial protocols, and support for MQTT Sparkplug B — allowing seamless integration into modern SCADA, telemetry, and automation systems. Article content With a high density of I/O ports, Digi IX30 reduces the need for external hardware, eliminating potential failure points while simplifying deployments. Its range of SKUs includes edge compute capabilities and support for public, private, and hybrid cellular networks, offering unmatched deployment flexibility. Article content 'We are excited to see Digi International with the Digi IX30-0EG4 industrial router continue to add to the portfolio of devices as a member of the Anterix Active Ecosystem,' said Steve Ryan, Vice President, Ecosystem and Partnerships at Anterix. 'With its proven reliability and rich feature set, Digi IX30 delivers a critical building block for utilities seeking secure, private LTE communications — particularly for applications that demand continuous uptime, edge control, and long-term adaptability.' Article content The Anterix 900 MHz spectrum is designed to meet the rigorous demands of utility broadband communications, offering dedicated performance, coverage, and security. Article content Key Features of Digi IX30 with Anterix Support: Article content Anterix Active designation — Full support for 900 MHz band private LTE networks Industrial-grade ruggedness — C1D2, NEMA TS2, wide temperature range, and DIN-rail mountable Edge intelligence and I/O — High port density, analog/digital I/O, GNSS, dual Ethernet Digi Remote Manager — Centralized network visibility, management, and security at scale DAL OS — Programmability, legacy protocol support, and seamless SCADA integration Flexible deployment — Support for public, private, and hybrid LTE networks in one SKU Article content Digi IX30-0EG4 with Anterix Active support is available now through Digi's authorized distributors. Article content Article content Article content Article content Article content Contacts Article content Article content Article content
