To the chagrin of absolutely no one, 2020 is finally drawing to a close. It has been a rollercoaster of a year, one defined almost exclusively by the COVID-19 pandemic. But other things have happened, including in the fields of artificial intelligence (AI), data science, and machine learning. To that end, it is time for KDnuggets annual year-end expert analysis and predictions. This year, we posed the question: What were the main developments in AI, data science, machine learning research in 2020, and what key trends do you see for 2021?
Last year’s noted main developments and predictions included continued advancements in many research areas, neurolinguistic programming (NLP) in particular. While there can be debate as to whether 2020’s big NLP advancement was as formidable as some may have originally thought (or continue to think), there is no doubt that there was a continued and intense focus on NLP research in 2020. It should not be difficult to surmise that this continues into 2021 as well.
Topics such as ethics and diversity were taking center stage in 2019, and this past year they stayed there. There seems to have been a transition from thinking of diversity and ethics and related subjects as periphery concerns in machine learning to viewing them as core considerations alongside technology. Let’s hope this trend continues into 2021 and beyond.
What did the experts come up with as the main developments of 2020, and what do they see as the most likely key trends for 2021? The group this year consists of Dan Becker, Pedro Domingos, Ajit Jaokar, Ines Montani, Brandon Rohrer, Dipanjan Sarkar, Rosaria Silipo, Rachael Tatman, and Daniel Tunkelang.