The AI revolution is not just about larger models and smarter applications. It is also about the network infrastructure, which em. As AI evolves, service providers must reconsider their architecture to provide the future of global stere connectivity. What was impossible a month ago will soon be basic expectations for customers for the future. The pace of innovation is really stunning and now it is time to invest in innovations that drive this new world ..
The core of how service providers evolves, their architecture is the unique requirements of the AI service and experience. Here are several key areas where AI changes how networks are designed and operated.
Training: need for high bandwidth, low latency, energy efficient network
The workload AI is growing, as well as the size and distribution of training clusters. Web scale providers now spread clusters across metro regions and require a high bandwidth and low latency connection with maintenance performance.
- Traditional centralized network architecture will not be distributed on a scale and the edges based on the edge will be crucial.
- Networks must maintain the pace with AI models that require data exchange in real time across wider geographies.
Inference: New paradigm of dynamic traffic with multiple cloud
AI moves from static inferences of disposable locations to dynamic distributed inference across several clouds. Techniques such as testing time (where models “think” more in conclusion will require massive love to replace real -time data across models.
- Respect more smaller models that gradually work to clarify the results.
- Data flows controlled and will be less predictable and highly adaptive.
- Inference operation AI will move more and more and place new dead on network design.
Agent Application: AI traffic rise with multiple agents
AII AI AI AGE, where AI agents cooperate dynamically, introductory brand new patterns. These applications create latencies sensitive to east-west operation across distributed clouds as agents’ communication in real time to perform tasks.
- Data generated by AI will not flow only in one direction; Networks must process multi -way patterns.
- Service providers must re -evaluate the management of traffic to take into account these adaptive workflows with multiple agents.
In order to get and lead this transformation, service providers must adapt their network to start AI. So far, a perfect playing book is written and we know that many of you are just starting to shape your strategy, but here are a few events that you should also be colored:
1. Build has a durable, distributed architecture
- Slide closer to the edge and reduce the overload of the network core.
- Process unpredictable AI operation formulas with distributed data processing.
- Reduce latency by providing AI services closer to users.
2. Accept the intelligent routing
- Operation at AI needs more than easy connection with high bandwidth-it needs an intelligent, telemetric network.
- Built -in intelligence allows high -speed low -performance connection across wide geographic areas.
3. Conversion of hugs
- Converging IP and optical layers simplify operations and reduce costs.
- Pluggable Optics replaces traditional optical systems, which provides high bandwidth, long connection and at the same time reduces complexity.
It’s not just hype. Providers accept AI will see tangible benefits, include the affected returned, reducing costs and increased experience with customers. For example, by hosting AI infrastructure and the use of insufficiently used fibers and the presence points (POP), providers can generate new income flows. In addition, the monitoring of network slicing by offering AI operations sensitive to the service level agreements (SLA) further increases the profitability of P. On the cost side, the requirements for the AI Edge AI calculation and converging IP and optical networks may significantly reduce. Meanwhile, automation and AI-PEFER observability ensure reliable, high-performance connection, while network planning and AA failure help prevent errors before it occurs, leading to trouble-free and improved customer experience.
Cisco has undertook to build AI-raad networks with our service providers and offers a lot of what is controlled for the future. We provide and develop tools for service providers to manage new traffic patterns, monetize AI and control operational efficient.
For example, our new Agile Services Cisco network (Announced in Cisco Live in Amsterdam a few weeks ago) Providers of services for effective management of operating patterns controlled by AI. And today we have added a new capacity of the collateral at the mobile world congress This includes real -time visibility in connection and offwork connection, which allows service providers to build durable, profitable home and mobile subscribers.
The era AI is here.
The question is: Is your network ready?
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