Prof. Willie LU’s Post

[[ Task Force for AI-Data Networking-Protocol (TF-AID-NP) ]] Working Group for National AI-Data Training and Inference super-Pool Infrastructure Industry experts and executives to join force together for upgrading the national infrastructure to support seamless AI data flow with trust across all networking nodes and optimize AI data processing including training and inference amongst different multiple data centers and between individual datacenter and distributed edge processing nodes. In addition to data center upgrade, we need new protocol for AI-data networking infrastructure as well, especially for building the National AI-Data Training and Inference super-Pool Infrastructure (NAID-TIPI) amongst hundreds of large-scale datacenters operated by different vendors and providers nationwide. AI-generated data info is totally DIFFERENT from traditional NON-AI data packet! Our Internet infrastructure was NOT designed for AI data packet. The TCP/IP mechanism was developed based on physical packet switching of bit-based error correction control protocol based on physical bit-by-bit, for example, we received 8 bits then correcting 1-2 bits automatically, with round-trip latency. But for AI generated traffic, it is NOT based on bits, rather it is based on token-oriented info segment (otherwise the transmission frame overhead is too big and low efficient), with very low latency. Hence we need new protocol to transmit AI-generated traffics and data. Otherwise large amount of AI-generated information will be filtered out in switch, gateway, router and access points automatically. We need new startups to solve these infrastructure protocol issues. For more information about TF-AID-NP, bookmark this following website  and check it weekly as we keep updating the progress frequently: https://lnkd.in/gkz5bKbg To join this mission or sponsor this task force, please contact Chair and PI of TF-AID-NP – Prof. Willie W. LU at: https://lnkd.in/gRynR6di The TF-AID-NP is independently organized and administrated by Palo Alto Research.

[ Task Force for AI-Data Networking-Protocol (TF-AID-NP) ] Working Group for National AI-Data Training and Inference super-Pool Infrastructure Industry experts and executives to join force together for upgrading the national infrastructure to support seamless AI data flow with trust across all networking nodes and optimize AI data processing including training and inference amongst different multiple data centers and between individual datacenter and distributed edge processing nodes. In addition to data center upgrade, we need new protocol for AI-data networking infrastructure as well, especially for building the National AI-Data Training and Inference super-Pool Infrastructure (NAID-TIPI) amongst hundreds of large-scale datacenters operated by different vendors and providers nationwide. AI-generated data info is totally DIFFERENT from traditional NON-AI data packet! Our Internet infrastructure was NOT designed for AI data packet. The TCP/IP mechanism was developed based on physical packet switching of bit-based error correction control protocol based on physical bit-by-bit, for example, we received 8 bits then correcting 1-2 bits automatically, with round-trip latency. But for AI generated traffic, it is NOT based on bits, rather it is based on token-oriented info segment (otherwise the transmission frame overhead is too big and low efficient), with very low latency. Hence we need new protocol to transmit AI-generated traffics and data. Otherwise large amount of AI-generated information will be filtered out in switch, gateway, router and access points automatically. We need new startups to solve these infrastructure protocol issues. For more information about TF-AID-NP, bookmark this following website and check it weekly as we keep updating the progress frequently: https://lnkd.in/gkz5bKbg You can also view Prof. Lu's speech on AID-NP in Palo Alto, California at: https://lnkd.in/gKmtkjJg To join this mission or sponsor this task force, please contact Chair and PI of TF-AID-NP – Prof. Willie W. LU at: https://lnkd.in/gRynR6di The TF-AID-NP is independently organized and administrated by Palo Alto Research.

◤Chief creates THREE RINDS, THREE LINES and leverages four advantages to set it apart from the competition ◢ Chief Telecom’s L.Y.2 AI Data Center is tailored for AI, HPC, Cloud, Data, and Networking Applications, making it a sustainable partner for businesses operations with its four unique advantages and the comprehensive one-stop services. Four Unique Advantages to Meet Diverse Enterprise Needs 1. Advanced Architectural Design: The building incorporates the technical elements of smart building and a seismic isolation design, ensuring robust protection for clients’ digital assets. 2. Customized High-Power HPC Cabinets: to provide 10kW power per rack to meet the demanding power requirements of AI servers. 3. Cloud Exchange Center: Direct connection to the five major public clouds to facilitate private network connection to cloud-based AI services. 4. Digital Convergence Hub: Chief’s IDCs converge domestic fiber and international submarine cable resources to enhance connectivity. ↓↓👀 Read more↓↓ https://lnkd.in/gqSPH76G #AI #LY2 #technology #aicloud #DataCenter #ccx #network #dataexchange #server #ChiefCloudeXchange

The rapid evolution of cloud technology and the rise of generative AI are pushing data centers to expand capacity and accelerate transmission speeds. The industry is already implementing 400G and 800G solutions, with 1T becoming a near-term reality rather than a distant goal. This is just one example of how the exponential increase in data storage and utilization will necessitate innovations in network infrastructure. Generative AI and the massive models that support it require a lot of space and a lot more power. At Belden, our focus is on developing smart infrastructure solutions for data centers, and that includes addressing demand for higher speeds, more capacity, and support for increased computational power. We collaborate closely with partners and clients to create systems capable of delivering enhanced speeds while ensuring predictable and scalable capacity growth. Our design philosophy emphasizes efficiency and innovation, enabling our customers to provide top-tier services while meeting the escalating demand for faster data transmission. By anticipating and adapting to these industry trends, we're helping data centers navigate the challenges of exponential data growth and increasingly complex computational requirements. #datacenterinnovation #smartinfrastructure #AIcomputing #LetsBuildTheFuture

The rapid evolution of cloud technology and the rise of generative AI are pushing data centers to expand capacity and accelerate transmission speeds. The industry is already implementing 400G and 800G solutions, with 1T becoming a near-term reality rather than a distant goal. This is just one example of how the exponential increase in data storage and utilization will necessitate innovations in network infrastructure. Generative AI and the massive models that support it require a lot of space and a lot more power. At Belden, our focus is on developing smart infrastructure solutions for data centers, and that includes addressing demand for higher speeds, more capacity, and support for increased computational power. We collaborate closely with partners and clients to create systems capable of delivering enhanced speeds while ensuring predictable and scalable capacity growth. Our design philosophy emphasizes efficiency and innovation, enabling our customers to provide top-tier services while meeting the escalating demand for faster data transmission. By anticipating and adapting to these industry trends, we're helping data centers navigate the challenges of exponential data growth and increasingly complex computational requirements. #datacenterinnovation #smartinfrastructure #AIcomputing #LetsBuildTheFuture

🌟 Edge and Gen AI: Building Tomorrow's Infrastructure Today 🌟 The future of telecommunications is taking a revolutionary turn with the advent of edge computing and generative AI (Gen AI). This transformation, as highlighted by STL Partners, could be as groundbreaking as the advent of cloud computing. For network service providers (NSPs) and telco operators, these innovations present both vast opportunities and significant challenges. Edge computing and Gen AI are reshaping how data is processed and managed. By bringing computing power closer to end-users, telcos can provide real-time responsiveness and lower latency, which are crucial for AI applications. This convergence of telco and cloud infrastructures allows for innovative edge services that empower enterprises with enhanced data privacy and security. However, implementing these technologies is not without its hurdles. Traditional telcos must navigate retrofitting legacy systems, managing environmentally sustainable data centres, and creating robust partnerships for a seamless edge infrastructure. Yet, with strategic collaboration, like those between Schneider Electric, NTT, and Orange, these challenges can be met efficiently. At TDA Telecoms, we thrive on connecting top talent with forward-thinking companies ready to embrace these transformations. Interested in learning more? Visit tdatelecoms.com and let's discuss how we can support your recruitment needs. #Telecom #EdgeComputing #AI #Infrastructure #FutureTechnology

🌟 Edge and Gen AI: Building Tomorrow's Infrastructure Today 🌟 The future of telecommunications is taking a revolutionary turn with the advent of edge computing and generative AI (Gen AI). This transformation, as highlighted by STL Partners, could be as groundbreaking as the advent of cloud computing. For network service providers (NSPs) and telco operators, these innovations present both vast opportunities and significant challenges. Edge computing and Gen AI are reshaping how data is processed and managed. By bringing computing power closer to end-users, telcos can provide real-time responsiveness and lower latency, which are crucial for AI applications. This convergence of telco and cloud infrastructures allows for innovative edge services that empower enterprises with enhanced data privacy and security. However, implementing these technologies is not without its hurdles. Traditional telcos must navigate retrofitting legacy systems, managing environmentally sustainable data centres, and creating robust partnerships for a seamless edge infrastructure. Yet, with strategic collaboration, like those between Schneider Electric, NTT, and Orange, these challenges can be met efficiently. At TDA Telecoms, we thrive on connecting top talent with forward-thinking companies ready to embrace these transformations. Interested in learning more? Visit tdatelecoms.com and let's discuss how we can support your recruitment needs. #Telecom #EdgeComputing #AI #Infrastructure #FutureTechnology

- AI requires a complete overhaul of current infrastructure. - Taiwan's Chief Telecom emphasizes the need for new data centers and network architecture. The rise of artificial intelligence demands more than just software innovations; it calls for a complete transformation of existing infrastructure. As a central player - Taiwan is well positioned to see the coming barriers to entry and upkeep, so much so that Taiwan's Chief Telecom company stressed the urgency of this evolution, highlighting that the current systems are inadequate for the heavy computational needs and data throughput required by advanced AI applications. The old ways won't suffice. Chief Telecom is investing in new data centers and upgrading network architecture to meet these demands. This isn't just a minor tweak but a significant leap forward. Enhanced fiber-optic networks, advanced cooling systems for servers, and robust cybersecurity measures are part of this new frontier. The emphasis is on creating a resilient and efficient backbone that can support the immense data processing and storage needs. The goal is to ensure seamless AI operations, enabling innovations that can drive industries forward. Taiwan positions itself at the forefront of this infrastructure revolution, setting a benchmark for global tech advancements. In this era of rapid technological progress, the foundation laid today will determine the successes of tomorrow. #AI #Infrastructure #Technology #Taiwan #DataCenters #ChiefTelecom #Innovation

NOKIA Press release Nokia and Lenovo join forces to drive advancements in data center solutions for the AI era Nokia and Lenovo partner to develop high-performance AI/ML data center solutions to meet growing workloads across industries and service providers. Highly reliable, scalable and secure blue-print solutions are needed to support massive storage and high-speed data transfer inside and across data centers globally.   22 October 2024 Espoo, Finland - Nokia today announced a strategic partnership with Lenovo to create comprehensive data center networking and automation solutions that support the massive and highly precise compute, storage and transit needs for Artificial Intelligence, Machine Learning (AI/ML) and other compute-intensive workloads. These solutions will be jointly marketed to enterprises, telcos, and digital infrastructure and cloud providers.   The partners will leverage the Lenovo ThinkSystem AI-ready portfolio of high-performance servers and storage with the Nokia Data Center network solution — which spans data center fabric, IP routing, and DDoS security portfolios, along with the recently announced data center network automation platform, Event-Driven Automation (EDA). The combined solutions will help meet the demanding processing and network performance requirements of modern workloads. As AI models are trained, data centers for inferencing will be needed where AI clusters are networked both within and between the data centers at the edge, which requires high-speed, reliable and secure interconnectivity.   The integration of these portfolios with a validated blueprint architecture enables seamless automation of AI/ML and compute-intensive workloads with enhanced observability, programmability, and extensibility, which are crucial for adapting to dynamic environments. Both Nokia and Lenovo portfolios have built-in security solutions that detect and thwart security threats in real-time, which is essential to combat the scale and frequency of cyberattacks. As well, both companies focus on energy-efficient designs that reduce power consumption and operational costs while promoting sustainability – a key data center concern.  

The unprecedented growth of Ultra Ethernet Consortium underscores the industry-wide support of Ethernet for AI networking. Learn more about UEC's growth and progress toward a 1.0 specification here: https://bit.ly/3PtJBn0 #AI #Ethernet