Hype Cycle™ for Data Science and Machine Learning, 2022

Download the Gartner® report to learn about self-supervised learning including its maturity, business impact, drivers, obstacles, and recommendations.

Gartner® tells that "Self-supervised learning enables the extended applicability of machine learning to use cases where labeled training datasets are not available. It may also shorten development time and improve the robustness and accuracy of models."

Download the Gartner® Report

Gartner, Hype Cycle for Data Science and Machine Learning, 2022, By Farhan Choudhary, Peter Krensky, 29 June 2022

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Speechmatics Blog

Self-Supervised Learning: Do Believe the Hype

We believe self-supervised learning encapsulates how Speechmatics innovates – by learning more about how humans talk, we can continue to grow our ASR and make accessible to everyone.

Learn more about the impact self-supervised learning has had on Speechmatics' award-winning Autonomous Speech Recognition engine.