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Signiant Debuts ‘Separating Signal From Noise’ AI, ML Video Series
Story Highlights
In recent years, file-transfer software specialist Signiant has repeatedly realized the benefits of machine learning (ML) and artificial intelligence (AI) to improve its services, employing those technologies to better-determine the best way to move data through any network.
A new five-part video series hosted by Signiant CTO Ian Hamilton shares insights into what Signiant has learned along the way with its deployment of ML and AI, how intelligent transport technology has proven beneficial for media and entertainment companies, and what can be learned from digital signal processing (and how ML can add business value).
“This video series covers artificial intelligence (AI) and machine learning (ML), targeting media technology professionals with a digital signal processing background,” Signiant CTO Ian Hamilton says in the first in the series. “But don’t be scared off if this isn’t your background. Anyone with basic math skills and a natural sense of curiosity should be able to follow along.
Other chapters in the series include:
• In “Neural Networks” Hamilton offers an overview of neural networks, a crucial aspect of most modern ML systems.
• “Digital Signal Processing” tackles digital signals and the operations commonly performed on them.
• Building off the second and third segments, “Machine Learning and Digital Signal Processing” explains how machines learn, highlighting similarities between neural networks and digital signal processing, including why artifacts in those domains can be unintuitive.
• The final segment in the series — “Machine Learning at Signiant” — offers insights into how Signiant’s unique SDCX architecture helps media and entertainment players leverage cloud ML and AI tools across multiple cloud providers.
