This article was published as a part of the Data Science Blogathon. In this article, we shall discuss the upcoming innovations in the field of artificial intelligence, big data, machine learning and overall, Data Science Trends in 2022. Times change, technology improves and our lives get better. Deep learning, natural language processing, and computer vision are examples of technologies that have emerged as a result of the rise of Data Science as a field of research and practical application throughout the previous century. In general, it has aided the development of machine learning (ML) as a means of achieving artificial intelligence (AI), a field of technology that is fast changing the way we work and live.

This year, I'm honored to be the chair of the Artificial Intelligence and Data Science track at the DataWorks Summit in San Jose. Reviewing the submissions and working with the experienced and sharp committee members has been an education in itself, in particular the chance to see what's trending in the open source world. My day-to-day data science work gives me the chance to dig into a few open source projects, but it's hard to find time to get an overview of which topics and projects are hot and worth exploring more deeply. The key topics emerging this year are deep learning, graph-based machine learning and model inference in production. Not surprisingly, the topics and tools around deep learning (DL) still top the list of big trends, and top-notch research in math and computation are driving progress across vision, speech and text.