Edge AI enables real-time intelligent systems at the edge with personalized decision-making, problem-solving, pattern recognition and learning capabilities.
Dealing with data and increasing intelligence is ultimately a strategic priority, especially for supporting the future needs of vertical systems – consisting of hardware and software. – in accordance with the European Chips Act and the European Green Deal.
The potential frontier of AI: Assessing its benefits and applications
Edge AI, which stands for the convergence of Internet of Things (IoT) technology, edge computing, and artificial intelligence (AI), allows processing data at the edge and brings many benefits such as reduced latency, requirements of bandwidth, power consumption and memory usage while available. to increase security and data protection. Edge AI has an important role to play in various industrial areas and requires specialized resources to be maintained in terms of software, AI algorithms, platforms and datasets.
The intelligence at the edge of the device allows processing information locally and responding in real time to conditions and situations instead of communicating with a central cloud or server. Automated systems must respond in real time to what is happening in certain situations. Decisions take time, and latency is very important in different AI applications in different industries.
Edge functionality redefines the interface of the connected device. Moving data processing and analytics to the edge and using AI techniques with built-in security make new real-time applications, to some extent, untenable. worry about data bandwidth and network reliability.
Converting raw data into useful information reduces bandwidth and data storage requirements while increasing security and privacy and reducing energy consumption. For smart applications, the AI computing concept of edge and performance is characterized by the emergence of different features, including micro-edge, deep-edge, and meta-edge.
Chips Project JU EdgeAI
The Chips JU EdgeAI project is an important step for Europe’s digital transformation towards smart operational solutions and a clear result of the European Chips Act initiative. The project actively contributes to Europe’s own technologies and processes to strengthen its AI design and development capabilities.
By developing AI-based electronic components and processes, edge processing platforms, AI architectures and middleware, and methods (to simplify, advance and optimize the design of smart devices end), the project supports the development of vertical AI solutions. For industry verticals in the digital industry, energy, agriculture, food and beverage, and digital society, the latest AI technologies are driving improvements in security, reliability, and energy efficiency. across industrial structures and to democratize the deployment of AI across EU sectors. research and industrial development.
Working within a dynamic European environment
The European Chips Act strengthens Europe’s silicon competitiveness and resilience and helps achieve digital and green transitions. With major projects such as Chips JU EdgeAI, it contributes strongly to European supply, stability, and scientific leadership in semiconductor technologies and applications.
The European Chips Act aims to jointly shape the European chip ecosystem by connecting Europe’s world-class research, design, manufacturing, and testing capabilities. This includes Europe’s technological dominance by strengthening Europe’s research and technology leadership, strengthening its capacity in chip design, manufacturing and packaging, increasing production and education capacity, and developing develop solid global semiconductor supply chains. As semiconductor chips determine the performance of digital systems, they are critical to fundamental digital technologies (including AI, edge computing, smart connectivity and more) as discussed in the decade of the EU’s 2030 Digital.
In this context, the EdgeAI project has created a strong European ecosystem that includes projects and initiatives dealing with the latest AI technologies. These activities culminated in joint events such as the European Conference on EDGE AI Technologies and Applications – EEAI 2024 which was held this year on 21-23 October 2024 at Hotel Regina Margherita, Cagliari, Sardinia, Italy.
EEAI 2024 aims to provide a European forum for sharing the latest scientific research and industrial results using the latest AI technologies and applications. Its scope covers the AI technology package after emerging research and innovation from hardware to software, AI architectures, architectures, algorithms, data types and methods for different applications. .
Developing new technological solutions
The Chips JU EdgeAI project focuses its activities on the development of the development of AI technologies according to the collection of AI technologies, which deals with research and innovation across the stack layers, from AI hardware , interfaces, designs, software, algorithms, designs and methods, and data types in applications in different industrial sectors.
The development of AI solutions across the spectrum of AI technologies is leading to the emergence of multimodal edge AI implementations that provide real-time edge processing for various industry sectors, resulting in with the integration of a combination of AI HW / SW blocks in a different AI. -system-based, AI software algorithms across continuous development, AI models, compression, optimization and hybrid and scalable architectures Systems on Chip (SoC) and Systems on Module (SoM) of designs.
Edge devices are currently used with SoC/SoM to build single-board computers with very few resources. Energy efficiency and cost are important metrics here, and building systems with, for example, two processors with different computing power/power characteristics can lead to a more efficient solution that based on AI.
The Chips JU EdgeAI project provides a valuable addition for edge processing, processing data directly at the data source or offloading it to connected components. Algorithms and processes have been developed to power advanced HW architectures that complement CPUs with specialized processing units such as graphite graphics units (GPUs), neural processing units (NPUs ), tensor processing units (TPUs), and neuromorphic processing units to enable AI on modular chip platforms. for industry sectors including digital industry, energy, agri-food and drink, and digital society.
Freedom
This work is carried out as part of the Chips JU EdgeAI project “Edge AI Technologies for Optimized Performance Embedded Processing”, which received funding from Chips JU under grant agreement No 101097300. KDT JU receives support from the European Union’s Horizon Europe research and innovation. program with Austria, Belgium, France, Greece, Italy, Latvia, Netherlands, and Norway.
Please note, this article will appear again in the 20th edition of our quarterly publication.
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