Cisco AI

In part 2 of the series, we talk more about Generative AI content rights, the fight for attention, and image generation.

Generative AI uses machine learning, language models, and graphical models annotated and labeled by humans. Learn more about machine learning; try the DevNet "Machine Learning 101" learning lab.

Machine Learning, AI, and Computer Vision technologies come together in the Meraki MV camera, a visual sensor offering critical insights about people and vehicles in physical spaces. Read about customer use cases.

Explore how AI can fall prey to spurious correlations in the context of networking, and how automation can help overcoming these limitations.

See how Tabnine enables team programming with an autocomplete-like tool that predicts what you want to write based on the code you/your team has written previously, as well as best open-source coding practices.

Learn how to build voice assistants that augment Automatic Speech Recognition (ASR) systems by generating pronunciations (phonemes) for words based on their written form (graphemes).

Artificial Intelligence / Machine Learning (AI/ML) and other applications are now taking advantage of the digital transformation creating new models of business and impacting various industries.

How can you quantify the real business value that customers are seeing from AI/ML technology in Cisco DNA Center? In a video case study, the IT staff of REWE Group, one of Europe’s largest supermarket chains, breaks it down.

Cisco AI Network Analytics, within Cisco DNA Center, adds another layer of intelligence to intent-based networking, making networks even smarter, simpler to manage, and more secure.