Partner POV | Enable seamless telco experiences with HPE Private Cloud AI

Solve key telco challenges with AI

Edge computing and artificial intelligence (AI) are converging and driving major advancements in the telecommunications (telco) sector. Communication service providers (CSPs) face significant challenges in maintaining performance, customer satisfaction, and operational efficiency in an increasingly competitive industry. Telcos must innovate continuously to meet customer expectations and improve network reliability, while working within tight profit margins. AI is a critical tool for overcoming these challenges, allowing telcos to enhance connectivity and remain consistent for the future. Their ability to harness the power of AI for automation, next gen performance, and robust cybersecurity can make the different in their growth and success.

Telco customers expect superior service. They require real-time access to data and resources from multiple locations as well as personalized, on-demand support to ensure they work and communicate seamlessly. To meet their demands, CSPs are implementing AI to accelerate and improve network operations. The following are AI use cases that can help CSPs outpace their competitors:

• Edge computer vision: Deploy AI technologies at the edge to process visual data from surveillance cameras, IoT devices, and other sources locally, eliminating the need for time-consuming data transfers and cloud processing delays. This approach improves real-time decision-making with the added benefits of reducing bandwidth requirements and enhancing data privacy.
• Network anomaly detection: Leverage AI to detect problems or anomalies with the network through continuous monitoring, analyzing packet headers, payload data, and communication patterns to detect activities that may indicate unauthorized access, malware, or cyberattacks. Once suspicious activity is identified, generative AI (GenAI) can be applied to determine the best action to resolve the issue.
• Chatbots for customer service: Elevate customer experiences and agent productivity with automated chatbot responses. AI chatbots can handle a broad range of inquiries, from account management to technical support. Additionally, CSPs can use these tools to collect valuable data on customer interactions and preferences to assist with strategic business decisions.
• Customer retention support: Improve customer satisfaction using AI to analyze customer interactions/behaviors to provide targeted support and personalized offers or services. AI techniques such as real-time analysis, predictive analytics, and personalized recommendations enable CSPs to anticipate customer needs and deliver seamless omnichannel experiences.

These are just some of the AI use cases enabling CSPs to boost performance and efficiency in their operations. With so much to gain, many CSPs are asking the same question: How do we unlock maximum value from AI?

Streamline AI implementation

CSPs need a holistic strategy to realize the benefits of AI. Developing an end-to-end approach is critical to ensure that business goals, specific use cases, and ethical considerations are included in the AI strategy. Not only should CSPs identify the right technologies for enabling AI across the lifecycle and across locations, but the technologies must also create an environment that can adapt quickly as network requirements and industry demands shift over time.

CSPs are moving to the private cloud where self-hosted models save time and resources, enhance data visibility, and increase flexibility. Public cloud solutions (while feature-rich) can expose data and models to threats, with potentially significant consequences to IP. More companies are implementing a private-focused hybrid cloud approach which offers better AI control and security while reducing environmental complexity. This solution, known as HPE Private Cloud AI (PCAI), supports the entire AI development lifecycle and unleashes the productivity of telco teams. A turnkey private cloud solution can make AI adoption simple.

68% of companies (1) report that hybrid cloud is foundational to their AI and GenAI strategies, and more than 50% plan to adopt dedicated private infrastructure. (2)

HPE Private Cloud AI offers important benefits:

• Delivers faster access to data and insights
• Scales resources to meet demand
• Improves efficiency and simplicity to save on costs
• Ensures IT availability while keeping data secure

Why HPE Private Cloud AI?

HPE Private Cloud AI is designed to extend AI capabilities from edge to cloud, so CSPs can deliver enhanced services to more customers. HPE and NVIDIA® have partnered to make the process simpler than ever.

HPE PCAI is the first co-engineered solution to come from NVIDIA AI Computing by HPE—a new joint initiative to help companies unlock the benefits of AI for their industry. NVIDIA AI Computing (or HPE PCAI with NVIDIA) includes AI-optimized infrastructure, networking, software, and foundation models that accelerate the entire AI workflow, so projects reach production faster with higher accuracy, efficiency, and infrastructure performance at a lower overall cost. HPE PCAI is tailored to AI models and designed to scale easily with the growth and utilization of AI use cases. With this proven foundation, our turnkey solution helps to overcome common challenges in operationalizing AI by delivering a flexible, pre-tested, AI-optimized private cloud that CSPs can trust.

HPE GreenLake is the foundation for this breakthrough solution. HPE GreenLake offers a self-service cloud experience where telcos can access a portfolio of cloud services to automate, orchestrate, and manage their hybrid environments—including users and data. CSPs can easily experiment and scale AI projects with a rich ecosystem of AI models and development tools, while maintaining control over costs and data security. Start as small as a single AI pilot and evolve quickly for multiple use cases in one solution using HPE GreenLake intuitive control plane to manage workloads on-prem, colocation, or in the cloud.

Unlike full-stack AI solutions based on reference architectures that can take months to plan, build, and deploy, HPE PCAI is ready to use out of the box. HPE PCAI enables 2x greater AI development productivity and 4x faster time to inference than comparable solutions on the market, and it can be up and running in just three clicks. (3), (4)

Adopt proven technologies from HPE and NVIDIA

HPE and NVIDIA have developed a fully curated solution to succeed with AI. HPE PCAI includes purpose-built infrastructure along with strategic tools for AI development and a library of models for your use cases. The solution features NVIDIA AI computing, networking, and software with robust HPE ProLiant Gen11 inferencing servers, HPE AI storage, and HPE GreenLake to provide a fast, flexible way for telcos to create and manage AI environments.

AI-optimized hardware is delivered as a single rack in small or medium configurations. Small configurations are ideal for basic large language model (LLM) inference (i.e., chatbots for customer service and customer retention support), while medium configurations can support retrieval augmented generation for LLMs (i.e., edge computer vision). Large multi-rack configurations are available for fine-tuning the most complex models (i.e., network anomaly detection).

References

(1), (2) https://www.idc.com/getdoc.jsp?containerId=US50829423

(3) The 4x faster time to inference is in comparison with the typical DIY manual steps to operationalize LLM versus automation in AI essentials (for example, virtual assistant chatbot solution accelerator with RAG)

(4) 90% developer productivity increase is based on 2023 UA data: Reduction in total time to build, train, evaluate and operationalize ML model using bespoke tools in comparison with fully integrated workflows and self-service access to data and ML frameworks