The Fraunhofer Heinrich-Hertz-Institut (HHI) has launched the HYPERCORE project, aimed at developing energy-efficient, secure, and high-performance communication infrastructure for the hyper-connected society. The project, funded by the German Federal Ministry of Education and Research (BMBF), focuses on optimizing metro and core networks, exploring a combination of all three physical dimensions (time, frequency, and space) for increasing transmission capacity. The project involves developing multiband transmission systems, coherent OTDR systems for network control, and expanding digital twin technology for optical communication networks. Field tests are planned for 2026 in Kiel and Berlin.

➀ Starting with your first NAS, Arm-powered NAS is a good choice for beginners; ➁ Arm-powered NAS is more affordable due to the lower cost of Arm processors; ➂ An Arm processor is sufficient for basic NAS tasks and doesn't require a powerful CPU; ➃ Arm CPUs use less power than x86 chips, saving on utility bills; ➄ Arm NAS can be used for various tasks, including home surveillance, without requiring high power consumption.

➀ HBM4 is the key to advancing AI by providing high capacity and performance for large-scale data-intensive applications; ➁ HBM4 improves AI and ML performance through increased bandwidth and memory density, reducing bottlenecks and improving system performance; ➂ HBM4 is designed with energy efficiency in mind, achieving better performance per watt and is crucial for the sustainability of large-scale AI deployments; ➃ HBM4's scalability allows for growth without becoming too expensive or inefficient, making it crucial for deploying AI in various applications.

➀ A 30 billion parameter LLM is demonstrated with a prototype inference device equipped with 16 IBM AIU NorthPole processors, achieving a system throughput of 28,356 tokens/second and a latency below 1 ms/token; ➁ NorthPole offers 72.7 times better energy efficiency and lower latency compared to GPUs at the lowest GPU delay; ➂ NorthPole architecture is inspired by the brain, optimized for AI inference, and demonstrates superior performance in LLM推理.

➀ The rise of indoor solar cells is transforming how we power our homes and devices, aiming for sustainability and energy efficiency; ➁ Indoor solar cells efficiently harness solar power from artificial light sources, reducing carbon footprints; ➂ Technological advancements are driving the efficiency and versatility of indoor solar cells, making them suitable for various applications.

➀ Infineon Technologies AG has launched a new XENSIV PAS CO2 5V sensor to improve building energy efficiency. The sensor uses Photoacoustic Spectroscopy (PAS) technology to tailor ventilation based on real-time occupancy, reducing carbon emissions and improving indoor air quality. It is suitable for HVAC systems, room controllers, and thermostats in both commercial and residential settings. ➁ The sensor delivers real-time, accurate air quality data, with a compact size and a fast response time. It is dust-proof and complies with the WELL TM Green Building Standard. ➂ All key components of the sensor are developed internally, and it offers configuration options for power consumption management.

1. Samsung and LG Electronics showcase AI-applied appliances and robots, contributing to energy savings; 2. Home & Mobile sector highlights AI-driven energy efficiency and personalized services; 3. LG's 'ThinQ ON' and Samsung's 'Bixby' voice assistant lead the way in AI home solutions.

➀ Reversible computing is a model where the computational process is time reversible, aiming to minimize heat generation; ➁ Vaire Computing is developing near-zero energy chips using reversible computing principles; ➂ The company aims to disrupt the industry with its innovative technology.

➀ u-blox introduces CloudTrack, an end-to-end asset-tracking service that redefines the IoT landscape; ➁ The service offers ultra-low-power positioning, global connectivity, and seamless cloud integration; ➂ It provides businesses with transparent, pay-as-you-go pricing without hidden fees or concerns about data usage.

➀ Introduces new CUDA libraries for accelerated computing, offering order-of-magnitude speedups and reduced energy consumption. ➁ Includes libraries for LLM applications, data processing, and physical AI simulations. ➂ Highlights real-world examples of energy-efficient and high-speed computing in industries like recycling and video conferencing.

➀ Researchers at Central University have developed a hybrid RF-VLC technology that promises reliable indoor communication with reduced power consumption. ➁ The system integrates RF and VLC to provide both communication and illumination while consuming less power. ➂ Initial evaluations show significant energy savings and potential reduction in electromagnetic radiation.

➀ Smart manikins equipped with sensor technology and mathematical modeling help optimize office temperatures for energy efficiency and comfort. ➁ 'HVAC' and 'ANDI' manikins measure thermal radiation and humidity to create a virtual thermal model of a human workplace. ➂ The research aims to optimize building energy needs and improve conditions in operating rooms and other environments.

➀ The 'KitchenGuard' project at TU Ilmenau is developing a new sensor to make cooking more relaxed, energy-efficient, and safer using AI. ➁ The sensor enhances induction cooktops with smart cooking functions and intuitive control. ➂ The project has received a 12-month EXIST startup grant to support its innovative business idea.

1. The Fraunhofer Institute for Energy Economics and Energy System Technology (IEE) is developing models and methods to assess the impact of local restrictions on realizable wind energy capacities and yields. 2. These models help in evaluating the usability of existing and planned sites and estimating repowering potentials. 3. The project, funded by the Federal Ministry for Economic Affairs and Climate Action, aims to accelerate the expansion of wind energy by providing tools for optimal land use and early warning systems for potential shortfalls in energy targets.

1. Researchers at ETH Zurich have developed a new method to significantly reduce the amount of environmentally harmful fluorine in lithium-metal batteries, making them more sustainable. 2. This new approach involves using electrostatic attraction to control the formation of a protective layer in the battery, enhancing stability and reducing costs. 3. The method has been successfully tested in coin-sized batteries and is now being scaled up for use in pouch cells, commonly used in smartphones.

1. Nuvoton Technology introduces the Arm Cortex-M23 M2L31 microcontroller series, focusing on energy-efficient computing. 2. The series features high power efficiency and robust processing capabilities, suitable for battery management and industrial automation. 3. It includes advanced features like ReRAM and USB Type-C PD 3.0 support, enhancing sustainability and security.

1. Researchers from UC Santa Cruz have discovered a method to run large language models (LLMs) at a mere 13 watts without compromising performance. 2. The key to this efficiency is the elimination of matrix multiplication in LLM processing, which, when optimized, significantly boosts performance-per-watt. 3. The broader applicability of this approach to AI in general is yet to be determined.

1. Mobix Labs Inc. has announced a strategic partnership with TalkingHeads Wireless to develop cost-effective and energy-efficient 5G base stations. 2. THW's 5G radio solution incorporates AI technology to optimize energy consumption in towers. 3. Mobix Labs contributes with a range of products including ICs, antennas, and active optical cables and transceivers.

1. Cambridge GaN Devices (CGD) has introduced the ICeGaN™ GaN power IC, designed for high-efficiency applications in data centers, inverters, and industrial power supplies. 2. The new ICeGaN™ P2 series features a low RDS(on) of 25 mΩ, supporting multi-kW power applications. 3. CGD's Chief Commercial Officer, Andrea Bricconi, highlighted the growing demand for GaN solutions in data centers due to the increasing energy consumption from AI growth.