Saturday, 2 November 2019

Artificial Intelligence: Leveraging Data from Edge to Cloud

Artificial Intelligence (AI) will transform every industry, including government, by enhancing organizational effectiveness and speed of operation. But AI will also change the nature and pace of threats organizations will face. If we’re to achieve the full promise of AI and transform data into intelligence and action, we must lead with an insight driven approach to everything we do. In addition, we must take advantage of cognitive capabilities wherever possible. All while leveraging the full potential of data across private, hybrid and multicloud environments – from the edge to the cloud.

Cisco Artificial Intelligence, Cisco Learning, Cisco Tutorial and Material, Cisco Online Exam, Cisco Guides

Artificial intelligence delivers insights when and where they are needed


To gain a competitive advantage, organizations need to start with a solid foundation, one that takes advantage of the best infrastructure options. This should include embedded analytics capabilities across edge, datacenter, and cloud environments. It should also include the capability to deliver insights when and where they are needed. And do so while incorporating continuous intelligence through real-time context. To unlock the strategic value of your data, you must have the ability to:

◒ Process and analyze data from distributed data sources

◒ Stream real-time data from edge devices

◒ Have the ability to store, analyze, apply AI/ML and deliver insight back to the edge devices to make intelligent decisions.

Cisco Artificial Intelligence, Cisco Learning, Cisco Tutorial and Material, Cisco Online Exam, Cisco Guides

Artificial intelligence and cloud-scale architecture


At Cisco, we’ve been working on a cloud-scale architecture that brings together big data, compute farm, and storage tiers. They work together as a single entity yet scale independently to address IT and operational needs. Through this approach, we have created an architecture that enables:

◒ Extremely fast data ingest and data engineering done at the data lake

◒ An AI compute farm that allows for different types of AI frameworks and compute types (GPU, CPU) to work on this data for further analytics

◒ Gradual retirement of data that has been worked on to a storage dense system with a lower $/TB, providing a better TCO (storage tiering)

◒ To seamlessly scale the architecture to thousands of nodes with a single pane of glass management using Cisco Application Centric Infrastructure (ACI).

Cisco Data Intelligence Platform caters to this evolving architecture, bringing together a fully scalable infrastructure with centralized management, plus a fully supported software stack (in partnership with industry leaders in the space) to each of these three independently scalable components of the architecture, including data lake, GPU and object storage.

Cisco Artificial Intelligence, Cisco Learning, Cisco Tutorial and Material, Cisco Online Exam, Cisco Guides

As you think about how to leverage artificial intelligence, ask yourself three key questions:

1. Are you architecting to enable your organization to drive value from data across environments?

2. Is your team ready to manage data spread across multiple clouds?

3. Will you be leveraging the full potential of your data?

Related Posts

0 comments:

Post a comment