Gartner AI Hype Cycle for 2020

It feels good to be at Kinaxis in 2020, getting to know my new Rubikloud friends, and planning more cool AI/ML projects for Supply-Chain and Retail, while reading the new "Gartner Hype Cycle for 2020". Looks like we will get to ride this wave of a strong commitment to continued investments in AI and ML, democratization and industrialization of the AI/ML platform, and the technology getting broadly adopted by the companies, the pandemic accelerating rather than hindering these trends.

I've also found today's (Oct 5, 2020) Forbes summary of the AI trends very interesting.

Especially the new additions to the hype cycle. One might dub them 'common-sense AI' :-)

• Small Data is now a category in the Hype Cycle for AI for the first time. Gartner defines this technology as a series of techniques that enable organizations to manage production models that are more resilient and adapt to major world events like the pandemic or future disruptions. These techniques are ideal for AI problems where there are no big datasets available.
• Generative AI is the second new technology category added to this year's Hype Cycle for the first time. It's defined as various machine learning (ML) methods that learn a representation of artifacts from the data and generate brand-new, completely original, realistic artifacts that preserve a likeness to the training data, not repeat it.
• Gartner sees potential for Composite AI helping its enterprise clients and has included it as the third new category in this year's Hype Cycle. Composite AI refers to the combined application of different AI techniques to improve learning efficiency, increase the level of "common sense," and ultimately to much more efficiently solve a wider range of business problems.