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Ryohei Fujimaki, CEO & Founder at dotData, Inc looks at the latest trends in AI/ML automation – and how they will speed adoption across industries.
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| Bridging the Skills Gap for AI and Machine Learning |
COVID-19 has impacted businesses across the globe, from closures to supply chain interruptions to resource scarcity. As businesses adjust to the new normal, many are looking to do more with less and find ways to optimize their current business investments.
In this resource-constrained environment, many types of business investments have slowed dramatically. That said, investments in AI and machine learning are accelerated, according to a recent Adweek survey.
The shortage of data scientists — as well as data architects, machine learning engineers skilled in building, testing, and deploying ML models — has created a big challenge for businesses implementing AI and ML initiatives, limiting the scale of data science projects and slowing time to production. The scarcity of data scientists has also created a quandary for organizations: how can they change the way they do data science, empowering the teams they already have?
