Category: Edge Data

At our recent SNIA Cloud Storage Technologies (CSTI) webinar “Why Distributed Edge Data is the Future of AI” our expert speakers, Rita Wouhaybi and Heiko Ludwig, explained what’s new and different about edge data, highlighted use cases and phases of AI at the edge, covered Federated Learning, discussed privacy for edge AI, and provided an overview of the many other challenges and complexities being created by increasingly large AI models and algorithms. It was a fascinating session. If you missed it you can access it on-demand along with a PDF of the slides at the SNIA Educational Library.

Our live audience asked several interesting questions. Here are answers from our presenters.

Q. With the rise of large language models (LLMs) what role will edge AI play? Read More

AI is disrupting so many domains and industries and by doing so, AI models and algorithms are becoming increasingly large and complex. This complexity is driven by the proliferation in size and diversity of localized data everywhere, which creates the need for a unified data fabric and/or federated learning. It could be argued that whoever wins the data race will win the AI race, which is inherently built on two premises: 1) Data is available in a central location for AI to have full access to it, 2) Compute is centralized and abundant.

The impact of edge AI is the topic for our next SNIA Cloud Storage Technologies Initiative (CSTI) live webinar, “Why Distributed Edge Data is the Future of AI,” on October 3, 2023. If centralized (or in the cloud), AI is a superpower and super expert, but edge AI is a community of many smart wizards with the power of cumulative knowledge over a central superpower.  In this webinar, our SNIA experts will discuss: Read More