Verizon unveils strategy utilizing artificial intelligence for fulfilling forthcoming AI requirements
**Verizon AI Connect: Powering the AI Ecosystem with Low-Latency Connectivity and Distributed Compute Resources**
In a strategic move to strengthen its network with AI and future-focused capabilities, Meta has partnered with Verizon. This partnership, according to Meta's vice president of network infrastructure, Gaya Nagarajan, will expand into network infrastructure, setting both companies apart in building the AI ecosystem.
Verizon, on the other hand, is building on its strategy to power the AI ecosystem by reimagining existing assets and integrating them into Verizon's intelligent and programmable network. The company is doing this through key partnerships and collaborations, one of which is with Vultr, a global GPU-as-a-Service and cloud computing provider.
J.J. Kardwell, CEO of Vultr, stated that Verizon's connectivity infrastructure is uniquely positioned to support Vultr's growth and extend its global cloud footprint. This partnership will enable Vultr to extend edge computing capabilities, allowing enterprises to deploy AI applications with the required low latency and compute density, especially for globally distributed workloads.
Verizon is also working with NVIDIA to integrate GPU-based edge platforms into Verizon's 5G private networks. This collaboration ties into advancements in AI networking technologies, with NVIDIA's developments in Ethernet hardware optimized for AI workloads complementing Verizon’s network offerings.
Google Cloud and Meta are already leveraging additional capacity from Verizon to support their AI workloads. Google Cloud's AI and data platform will be used by Verizon to transform its customer, employee, and network experience. Bikash Koley, vice president of global networking and infrastructure at Google, stated that Verizon's advanced network capabilities can accelerate the development and deployment of AI solutions.
The partnerships have already resulted in advanced AI solutions for network maintenance and anomaly detection. Ronnie Vasishta, senior vice president of Telecom at NVIDIA, stated that NVIDIA AI and accelerated computing, integrated with Verizon's network, allows enterprises to easily adopt AI-powered services at scale.
Verizon AI Connect, an integrated suite of solutions and products for deploying artificial intelligence (AI) workloads at scale, was unveiled by Verizon Business. This platform leverages Verizon’s extensive physical network infrastructure, offering low-latency, high-bandwidth connectivity essential for the performance-sensitive nature of AI workloads. It is designed to deliver AI workloads as needed, utilizing resources such as the macro 5G network, high-speed fiber connectivity, edge compute environments, and space, power, and cooling infrastructure.
The shift towards real-time decision-making in AI, known as inferencing, is expected to drive demand for additional computing power. McKinsey predicts that 60-70% of AI workloads will shift to real-time inference by 2030, creating an urgent need for low-latency connectivity, compute, and security at the edge. With Verizon AI Connect, Verizon is well-positioned to meet this demand.
In summary, Verizon AI Connect is a critical element in Verizon's strategy to supply the AI ecosystem with low-latency, secure connectivity and distributed compute resources. Its collaborations with Google Cloud, NVIDIA, Meta, and Vultr enhance its capabilities and market position, helping meet current and future AI workload demands at scale and speed. Kyle Malady, the CEO of Verizon Business, stated that there is significant demand for reliable network infrastructure that can support existing AI workloads.
Technology plays a crucial role in Verizon's strategy to power the AI ecosystem, as the company unveiled Verizon AI Connect, an integrated suite of solutions designed to deliver AI workloads at scale using low-latency, high-bandwidth connectivity essential for performance-sensitive AI workloads.
Verizon AI Connect leverages technology such as Verizon’s extensive physical network infrastructure, offering secure connectivity and distributed compute resources to help meet the growing demand for real-time AI decision-making by 2030.
