Digital is a reality. It is evolving to accommodate and exploit AI to help automate work and drive innovation; and so the hype around AI and ML continues. For an increasing number of organizations, leaders are beginning to ask, “Where is the beef?” All the proof of concepts and investments need to start paying the bills. See Toolkit: Presentation for Key Findings From the 2020 Board of Directors Survey.
With this in mind I was most interested to read this weeks’ Economist. In there was the Technology Quarterly: A new revolution. In the set of articles was one about China and AI: Data – a New Trinity. This article was really interesting – as it explored the role and position China has in the use of AI.
One key point drawn out is that those uses of AI and ML that have access to data in all its kinds and forms and colors have an advantage over those that don’t. Examples are given: one is a Chinese firm who apparently has 300,000 staff tagging data every minute of every day – to feed into its ML technologies to drive more effective AI solutions. Such numbers are pretty scary.
But then I remembered synthetic data. We notes in our recent Hype Cycle for Data Science and Machine Learning the following about synthetic data: Synthetic data is utilized in use cases where the available data is limited, incomplete or cannot be sourced easily. Simulation and generative techniques can be used to increase the available training data. If you think about it, if the competition has more data than you, but you have some data you can work with, perhaps you can reduce any gaps with synthetic data. So I wonder – when will synthetic data be (yet another) next big thing?
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