Latest news with #edgeAI
Forbes
3 days ago
- Business
- Forbes
Edge AI Applications As The Catalyst For AI PC Market Growth
Ajith Sankaran, Executive Vice President, C5i. getty Despite all the buzz, the adoption of high-performance AI PCs with powerful neural processing units (NPUs) has been especially sluggish. Since their launch in mid-2024, these devices have captured just 5% of AI PC market sales. This can be attributed to several factors: • AI PCs typically command a significant price premium without clearly articulated benefits. Many users remain unconvinced that these costs translate to meaningful improvements in computing experiences. • Compatibility concerns persist, particularly with first-generation advanced RISC machine (ARM)-based systems that may not support legacy software. • There is a scarcity of software applications that fully harness AI PC capabilities. According to a 2024 ICD report, the global market for personal computing devices was "set to grow 3.8% in 2024, reaching 403.5 million units." However, this growth is primarily driven by a nearly double-digit growth in tablets. According to Jitesh Ubrani of IDC, 'There seems to be a big disconnect between supply and demand as PC and platform makers are gearing up for AI PCs and tablets to be the next big thing, but the lack of clear use cases and a bump in average selling prices has buyers questioning the utility.' I believe the answer to realizing the potential of AI PCs in enterprise scenarios lies in understanding and utilizing edge AI. To understand why, let's take a closer look at how these systems operate. Edge AI And Its Relationship With AI PCs Edge AI represents the convergence of AI and edge computing, enabling AI algorithms to run directly on local devices rather than in remote data centers. This approach processes data where it's generated, eliminating the need to send information to the cloud for analysis and returning results almost instantaneously. AI PCs are well-positioned to serve as powerful edge AI platforms due to their unique hardware architecture. They integrate three processing components: • A central processing unit (CPU) for general computing tasks. • A graphics processing unit (GPU) for parallel processing workloads. • A neural processing unit (NPU) optimized for AI computations. This triad of capabilities allows AI PCs to handle edge AI applications with efficiency. The performance benefits can be substantial; security company CrowdStrike reported that its software's CPU consumption dropped from 35% to 1% when running on machines equipped with Intel NPUs. Global shipments of AI PCs are projected to reach 114 million units in 2025, accounting for 43% of all PC shipments. I believe that edge AI that incorporates the latest advances in generative AI and agentic AI could provide tangible benefits that justify the premium pricing of AI PC for consumers and enterprises. As more developers create software that leverages NPUs and other specialized AI hardware, the value proposition should become clearer, driving increased adoption across both consumer and enterprise segments. Emerging Edge AI Applications Driving AI PC Demand • Manufacturing Intelligence Manufacturing environments are proving to be fertile ground for edge AI applications. AI systems running locally on AI PCs can monitor equipment health in real time, detecting anomalies and predicting potential failures before they occur. This can reduce costly downtime. Quality control represents another application. AI-powered cameras connected to edge computing systems can inspect products for defects with precision and consistency. • Healthcare Innovations The healthcare sector also stands to benefit from edge AI. Portable diagnostic devices equipped with edge5 AI can analyze medical images such as X-rays, MRIs, and CT scans locally, providing rapid insights without requiring cloud connectivity. This is particularly valuable in remote areas. And wearable health devices using edge AI can analyze biometric data locally, detect anomalies and alert healthcare providers without transmitting sensitive patient information to remote servers. • Retail Transformation In retail, edge AI applications are revolutionizing operations and customer experiences. AI-powered cameras and sensors can track inventory levels in real time, optimizing stock replenishment. The same infrastructure can analyze customer behavior patterns, enabling retailers to deliver personalized recommendations and promotions. These capabilities require significant local processing power that can be provided by AI PCs to analyze video feeds and sensor data in real time. • Security and Privacy Protection Edge AI can deliver faster performance while keeping sensitive data local instead of sending it to cloud services. For example, Bufferzone NoCloud "uses local NPU resources to analyze websites for phishing scams using computer vision and natural language processing." Edge AI applications can enhance banking security by detecting unusual transactions and immediately alerting users. Recommendations For Effective AI PC and Edge AI Adoption 1. Develop edge-native AI applications for real-time decision-making. Prioritize building edge-native AI applications that leverage the NPUs in your organization's AI PCs to execute machine learning models locally. For example, manufacturing firms can deploy vision systems on AI PCs to perform real-time quality inspections directly on production lines, reducing defect rates while eliminating cloud dependency. 2. Deploy agentic AI systems for autonomous workflow optimization. Agentic AI excel at autonomously managing complex, multi-step processes. In supply chain, running agentic AI systems on AI PCs can allow you to dynamically reroute shipments based on real-time traffic data processed at the edge, reducing delivery delays. Financial institutions can also combine agentic AI with edge computing to autonomously monitor transactions for fraud patterns, triggering immediate alerts while keeping sensitive financial data localized. 3. Implement privacy-centric AI architectures for regulated industries. Consider adopting hybrid edge-cloud AI architectures to balance computational demands with regulatory compliance. For example, banks can deploy on-premise AI PC clusters to run agentic AI fraud detection systems, ensuring customer transaction data never leaves internal networks. 4. Build scalable edge AI infrastructure with modular hardware. Invest in AI-optimized hardware ecosystems that support both current and emerging workloads. For instance, consider deploying AI PCs with dedicated NPUs for employee productivity tools and pairing them with edge servers containing GPU/TPU arrays for heavy computational tasks. 5. Integrate generative AI with edge computing for adaptive systems. By fusing generative AI with edge computing, you can enable dynamic system adaptation within your company. For example, manufacturers can deploy small language models on AI PCs to generate equipment repair instructions tailored to real-time sensor data, reducing machine downtime. Conclusion While initial adoption of AI PCs has been slow due to high costs, compatibility issues and a lack of applications, the emergence of edge AI use cases is beginning to demonstrate the value of local AI processing. As developers increasingly leverage NPUs to build edge-native and agentic AI solutions, I believe the value proposition of AI PCs will become more evident, driving broader adoption across consumer and enterprise markets. 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Forbes
30-05-2025
- Business
- Forbes
Japanese Semiconductor Startup Secures $21 Million In Grants For Edge AI
EdgeCortix's Sakura-II module. As Japan races to develop its domestic semiconductor ecosystem, Tokyo-headquartered chip design startup EdgeCortix announced it received 3 billion yen ($21 million) from a government-backed agency to develop specialized chips that can power 'edge AI,' a rapidly growing field of AI that involves running applications on devices themselves instead of on the cloud. The fresh funds, in the form of a project award from Japan's New Energy and Industrial Technology Development Organization (NEDO), bring the five-year-old company's total funding to $86 million, including $49 million in non-dilutive government grants and $37 million in equity financing. It received a 4 billion yen ($27.7 million) subsidy from a separate NEDO program last November. Across three previous equity funding rounds, with the most recent being a $20 million raise in October 2023, the startup's investors include SBI Investment, a CVC unit of Japanese financial services conglomerate SBI Group; Monozukuri Ventures; Seoul-based VC firm Futureplay; and automotive chips maker Renesas Electronics, formerly under Japanese electronics giant NEC. Renesas is also a customer of EdgeCortix. 'Building systems that are significantly more performance-per-watt efficient for AI processing than the current status quo, whether that's GPUs or other types of systems, especially in constrained environments…that is a critical factor for almost all edge applications,' says Sakyasingha Dasgupta, founder and CEO at EdgeCortix, in a video interview. 'That essentially differentiates us from the broader edge AI market.' In addition to the startup's focus on optimizing energy efficiency, Dasgupta adds, what distinguishes EdgeCortix is its architecture, referring to the design and programming that powers chips. Its patented 'Dynamic Neural Accelerator' architecture is an IP core, akin to a 'brain' for AI computing that can direct processors within a chip and adjust the way its components interact. This IP core can be integrated with processors such as neural processing units (NPU), which are tailored for machine learning. The latest grant will finance the development of EdgeCortix's new chiplet, a type of chip that uses interchangeable components, as opposed to monolithic ones. Dubbed 'NovaEdge,' EdgeCortix's chiplet for edge AI is designed for high-performance generative AI inference and on-device learning, the company says. Founded in 2019, EdgeCortix operates as a fabless semiconductor company, meaning it does not own its own fabrication facility, or 'fab.' The NovaEdge chiplet will utilize a 12-nanometer node produced by billionaire Morris Chang's Taiwan Semiconductor Manufacturing Co. (TSMC). EdgeCortix plans to commence mass production at TSMC subsidiary Japan Advanced Semiconductor Manufacturing (JASM)'s facility in Kumamoto, Japan, by 2027. A plant of Japan Advanced Semiconductor Manufacturing Company (JASM). With a wide range of applications, ranging from robotics to industrial automation, EdgeCortix's chips and accompanying software have recently gained traction in the defense industry. Earlier in May, the startup inked an agreement with the U.S. Department of Defense's venture-oriented Defense Innovation Unit (DIU) to use EdgeCortix's products for defense technologies, including AI-powered vision and generative AI. In December, the DIU had announced it would launch a new effort to accelerate the adoption of generative AI in both warfighting and enterprise management. Specifically, on the battlefield, edge AI may help quickly process sensitive information in environments with limited network connectivity or potential cybersecurity threats. Tech giant Palantir–cofounded by billionaires Peter Thiel, Alexander Karp, Stephen Cohen and Joe Lonsdale–has developed a range of edge AI offerings for military purposes, including Skykit, a backpack-sized server that can act as a fully operational intelligence unit for soldiers, analyzing data from sensors on drones and surveillance equipment. In the nascent field of edge AI, the decentralization of AI represents 'a profound shift in the technological landscape,' according to a report published in February by consulting firm Deloitte. Such computing developments may be particularly effective for use cases 'requiring rapid responses or operating in disconnected environments,' including smart home devices, autonomous vehicles, wearable health monitors, and industrial Internet of Things (IoT) systems. Global spending on edge infrastructure is projected to grow from $25.3 billion in 2022 to $55.6 billion by 2027, the report added, citing research from the International Data Center (IDC). A Palantir Technologies Skykit on display. Japan's government-backed investments align with broader efforts to bolster domestic chip design and manufacturing, with the aim of establishing greater independence for advanced AI technologies. Last November, Prime Minister Shigeru Ishiba announced a $65 billion plan to invest in the country's chip and artificial intelligence industry by 2030, according to local media. Central to these efforts is the state-backed chipmaker Rapidus. In March, the Japanese government pledged an additional $5.4 billion to Rapidus, bringing its total government subsidies or grants to around $11.5 billion. Headquartered in Tokyo and backed by industry giants, including financial services groups MUFG Bank and SoftBank, electronics makers NEC and Sony, Toyota, and telecoms provider NTT, Rapidus aims to launch commercial production of 2-nanometer chips—some of the world's thinnest and most advanced—by 2027. A major link in the global semiconductor supply chain, Japan is also home to industry giants including billionaire Uchiyama family's Lasertec, which manufactures chip testing equipment; KKR-backed chip production equipment maker Kokusai Electric; Bain-backed Kioxia, Advantest (chip testing equipment); and Sumco, a silicon wafer supplier.
Yahoo
27-05-2025
- Business
- Yahoo
Gcore Appoints AI Expert Prof. Dr. Feiyu Xu as Board Advisor
Gcore welcomes Prof. Dr. Feiyu Xu, a leading figure with expertise in AI research and industry LUXEMBOURG, May 27, 2025 /PRNewswire/ -- Gcore, the global edge AI, cloud, network, and security solutions provider, today announced it has strengthened its board with the addition of AI expert, Prof. Dr. Feiyu Xu. A renowned AI researcher, Prof. Dr. Xu has held pivotal leadership roles at SAP, Lenovo, and the German Research Centre for AI. Her appointment reinforces Gcore's commitment to driving AI innovation and industry leadership. Prof. Dr. Xu will help shape the company's AI vision, growth strategies, and long-term goals. Since its founding in 2014, Gcore has continually expanded its product suite, most recently with Everywhere Inference, which offers flexible deployment options, including cloud, on-premise and hybrid environments. By running on edge points of presence, Everywhere Inference enables faster processing and response time for end user and applications. As the first Gcore Board Advisor to hold a leading position in AI research and innovation, Dr. Xu will guide Gcore's growth and innovation in the edge AI field. Today, Gcore provides global infrastructure across six continents that enables businesses to train and deploy AI models globally with ultra-low latency. With 180+ edge locations, including more than 50 cloud locations and 14,000 peering partners, Gcore brings AI workloads closer to users for faster, more scalable, and cost-efficient performance. As the company continues to grow, Prof. Xu's expertise will consolidate Gcore's position as a world-leading innovator in AI. Prof. Xu said: "I am thrilled to be joining as Gcore's Board Advisor, a unique tech company with immense potential. Gcore not only provides the infrastructure needed for developing AI applications, but it also actively contributes to the growth of the AI ecosystem in Europe. I am delighted to be part of a team that will shape the future of technology and innovation." Andre Reitenbach, CEO of Gcore, commented: "It is an honor to welcome Prof. Xu as Board Advisor. Prof. Xu's strategic vision and deep expertise in AI will make her an exceptional addition to the board. As a renowned scientist and business leader with a deep understanding of AI, Prof. Xu's insights will play an integral role in advancing Gcore's mission to connect the world to AI anywhere and anytime." About Gcore Gcore is a global edge AI, cloud, network, and security solutions provider. Headquartered in Luxembourg, with a staff of 600+ operating from ten offices worldwide, Gcore provides its solutions to global leaders in numerous industries. The company manages its own global IT infrastructure across six continents, with one of the best network performances in Europe, Africa, and LATAM, due to the average response time of 30 ms worldwide. Gcore's network consists of 180+ points of presence around the world in reliable Tier IV and Tier III data centres, with a total capacity exceeding 200 Tbps. Learn more at and follow them on LinkedIn, Twitter, and Facebook. Photo - View original content to download multimedia: SOURCE Gcore 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
Tahawul Tech
16-05-2025
- Business
- Tahawul Tech
Qualcomm and e& collaborate on Edge AI technologies to drive transformation in UAE
Qualcomm Technologies, Inc. and e& today announced a strategic collaboration to help drive technological development and commercialization across a broad range of advanced connectivity, 5G and edge AI technologies in an effort to accelerate the digital transformation for the government, enterprise and industrial sectors. Edge computing refers to processing data closer to where it is generated—at the 'edge' of the network—enabling faster insights, reduced latency, and enhanced security. This collaboration is intended to benefit key aspects of the UAE economy. Qualcomm Technologies and e& plan to collaborate on: Industrial and enterprise 5G edge AI gateways that will enable core vertical sectors to deploy AI capabilities and other technologies at the network edge, enhancing efficiency, connectivity and performance Edge AI devices, ranging from PCs to XR devices powered by Snapdragon® platforms, which will integrate large language models (LLMs), supporting on-device generative AI capabilities and security-focused AI inferencing from edge to cloud for enterprise and government sectors. Smart mobility and safety solutions designed to improve safety and road-user experiences and future proofing the UAE's transportation infrastructure. Connected industrial IoT solutions for enterprise. 'The cooperation between Qualcomm Technologies and e& will drive significant collaboration across some of the most transformative technology areas, including 5G, next-generation computing and intelligence at the edge. We look forward to working with e& to accelerate innovation and technology advancement across its ecosystem of enterprise and government customers in the UAE and beyond,' said Cristiano Amon, President and CEO, Qualcomm Incorporated. Qualcomm Technologies will also look to utilize its newly established Qualcomm Engineering Center in Abu Dhabi to support this collaboration with e& through evaluating new use cases to accelerate 5G and edge AI adoption in sectors like energy, manufacturing, logistics, retail and smart mobility. 'e& and Qualcomm Technologies have a history of cooperation, and this new agreement will help drive the digital transformation of enterprises significantly enhancing the UAE's role in the global technology landscape. Together, we're bringing powerful AI to the edge — from smart industrial gateways and wearables to mobility and infrastructure — enabling faster, more reliable, and secure experiences across sectors like manufacturing, transport, and government. These innovations will drive real-time intelligence, operational efficiency, and future-ready public services across the UAE,' said Hatem Dowidar, Group Chief Executive Officer, e&.
Zawya
16-05-2025
- Business
- Zawya
Qualcomm and e& collaborate on AI at the edge to drive transformation in the UAE
United Arab Emirates: Qualcomm Technologies, Inc. and e& today announced a strategic collaboration to help drive technological development and commercialization across a broad range of advanced connectivity, 5G and edge AI technologies in an effort to accelerate the digital transformation for the government, enterprise and industrial sectors. Edge computing refers to processing data closer to where it is generated—at the 'edge' of the network—enabling faster insights, reduced latency, and enhanced security. This collaboration is intended to benefit key aspects of the UAE economy. Qualcomm Technologies and e& plan to collaborate on: Industrial and enterprise 5G edge AI gateways that will enable core vertical sectors to deploy AI capabilities and other technologies at the network edge, enhancing efficiency, connectivity and performance Edge AI devices, ranging from PCs to XR devices powered by Snapdragon® platforms, which will integrate large language models (LLMs), supporting on-device generative AI capabilities and security-focused AI inferencing from edge to cloud for enterprise and government sectors Smart mobility and safety solutions designed to improve safety and road-user experiences and future proofing the UAE's transportation infrastructure Connected industrial IoT solutions for enterprise Qualcomm Technologies will also look to utilize its newly established Qualcomm Engineering Center in Abu Dhabi to support this collaboration with e& through evaluating new use cases to accelerate 5G and edge AI adoption in sectors like energy, manufacturing, logistics, retail and smart mobility. 'The cooperation between Qualcomm Technologies and e& will drive significant collaboration across some of the most transformative technology areas, including 5G, next-generation computing and intelligence at the edge. We look forward to working with e& to accelerate innovation and technology advancement across its ecosystem of enterprise and government customers in the UAE and beyond,' said Cristiano Amon, President and CEO, Qualcomm Incorporated. 'e& and Qualcomm Technologies have a history of cooperation, and this new agreement will help drive the digital transformation of enterprises significantly enhancing the UAE's role in the global technology landscape. Together, we're bringing powerful AI to the edge — from smart industrial gateways and wearables to mobility and infrastructure — enabling faster, more reliable, and secure experiences across sectors like manufacturing, transport, and government. These innovations will drive real-time intelligence, operational efficiency, and future-ready public services across the UAE,' said Hatem Dowidar, Group Chief Executive Officer, e&. About Qualcomm Qualcomm relentlessly innovates to deliver intelligent computing everywhere, helping the world tackle some of its most important challenges. Building on our 40 years of technology leadership in creating era-defining breakthroughs, we deliver a broad portfolio of solutions built with our leading-edge AI, high-performance, low-power computing, and unrivaled connectivity. Our Snapdragon® platforms power extraordinary consumer experiences, and our Qualcomm Dragonwing™ products empower businesses and industries to scale to new heights. Together with our ecosystem partners, we enable next-generation digital transformation to enrich lives, improve businesses, and advance societies. At Qualcomm, we are engineering human progress. Qualcomm Incorporated includes our licensing business, QTL, and the vast majority of our patent portfolio. Qualcomm Technologies, Inc., a subsidiary of Qualcomm Incorporated, operates, along with its subsidiaries, substantially all of our engineering and research and development functions and substantially all of our products and services businesses, including our QCT semiconductor business. Snapdragon and Qualcomm branded products are products of Qualcomm Technologies, Inc. and/or its subsidiaries. Qualcomm patents are licensed by Qualcomm Incorporated. About e& e& is a global technology group committed to advancing the digital future across markets in the Middle East, Asia, Africa and Europe. With the group's financial performance in 2024 showing a consolidated revenue of AED 59.2 billion and a net profit of AED 10.8 billion, e& continues to maintain its position as a financial powerhouse, reflected by its strong credit rating and solid balance sheet. Founded in Abu Dhabi over 48 years ago, e& has evolved from a telecom pioneer into a technology group. Its footprint now spans 38 countries, offering a comprehensive portfolio of innovative digital services ranging from advanced connectivity, entertainment, streaming and financial services to AI-powered solutions, cloud computing, ICT, cybersecurity and IoT platforms. The Group is structured around five core business pillars: e& UAE, e& international, e& life, e& enterprise and e& capital, each catering to distinct customer and market needs. These pillars empower e& to lead in various sectors, from telecom and digital lifestyle to enterprise services and venture investments. The ongoing strategic investments in AI, IoT, 5G and cloud services reinforce its leadership in the global technology landscape, driving the future of smart connectivity and innovation. Driven by innovation, sustainability and a commitment to digital empowerment, e& is set on creating a smarter, more connected future for individuals, businesses and communities.
