At KDnuggets, we try to keep our finger on the pulse of main events and developments in industry, academia, and technology. We also do our best to look forward to key trends on the horizon. In previous years, we have brought collections of predictions and analysis from experts. What were the main developments in Machine Learning and Artificial Intelligence in 2018, and what key trends do you expect in 2019? Below are the responses from Anima Anandkumar, Andriy Burkov, Pedro Domingos, Ajit Jaokar, Nikita Johnson, Zachary Chase Lipton, Matthew Mayo, Brandon Rohrer, Elena Sharova, Rachel Thomas, and Daniel Tunkelang. Key themes singled out by these experts include deep learning advancements, transfer learning, the limitations of machine learning, the changing landscape of natural language processing, and much more. Be sure to check out collected opinions we shared last week when we asked a group of experts the related question, "What were the main developments in Data Science and Analytics in 2018 and what key trends do you expect in 2019?" Anima Anandkumar (@AnimaAnandkumar) is Director of ML research at NVIDIA and Bren Professor at Caltech.

At KDnuggets, we try to keep our finger on the pulse of main events and developments in industry, academia, and technology. We also do our best to look forward to key trends on the horizon. To close out 2017, we recently asked some of the leading experts in Big Data, Data Science, Artificial Intelligence, and Machine Learning for their opinion on the most important developments of 2017 and key trends they 2018. This post, the first in this series of such year-end wrap-ups, considers what happened in Big Data this year, and what may be on the horizon for 2018. "What were the main Big Data related developments in 2017, and what key trends do you see in 2018?"

At KDnuggets, we try to keep our finger on the pulse of main events and developments in industry, academia, and technology. We also do our best to look forward to key trends on the horizon. To close out 2017, we recently asked some of the leading experts in Big Data, Data Science, Artificial Intelligence, and Machine Learning for their opinion on the most important developments of 2017 and key trends they 2018. This post considers what happened in Machine Learning & Artificial Intelligence this year, and what may be on the horizon for 2018. "What were the main machine learning & artificial intelligence related developments in 2017, and what key trends do you see in 2018?"

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Among main themes were AI and Deep Learning - both real progress and hype, Machine Learning, Security, Quantum Computing, AlphaGo Zero, and more. In 2017 we saw Big Data give way to AI at center stage of the technology hype cycle. This excessive media and practitioner attention on AI included positive news (increasingly powerful machine learning algorithms and AI applications in numerous industries, including automotive, medical imaging, security, customer service, entertainment, financial services) and negative news (threats of machines taking our jobs and taking over our world). We also witnessed a growth in value-producing innovations around data, including greater use of APIs, as-a-Service offerings, data science platforms, deep learning, and cloud machine learning services from the major providers. Specialized applications of data, machine learning, and AI included machine intelligence, prescriptive analytics, journey sciences, behavior analytics, and IoT.

At KDnuggets, we try to keep our finger on the pulse of main events and developments in industry, academia, and technology. We also do our best to look forward to key trends on the horizon. To close out 2017, we recently asked some of the leading experts in Big Data, Data Science, Artificial Intelligence, and Machine Learning for their opinion on the most important developments of 2017 and key trends they 2018. This post, the first in this series of such year-end wrap-ups, considers what happened in Machine Learning & Artificial Intelligence this year, and what may be on the horizon for 2018. "What were the main machine learning & artificial intelligence related developments in 2017, and what key trends do you see in 2018?"

At KDnuggets, we try to keep our finger on the pulse of main events and developments in industry, academia, and technology. We also do our best to look forward to key trends on the horizon. To close out 2017, we recently asked some of the leading experts in Big Data, Data Science, Artificial Intelligence, and Machine Learning for their opinion on the most important developments of 2017 and key trends they 2018. This post, the first in this series of such year-end wrap-ups, considers what happened in Big Data this year, and what may be on the horizon for 2018. "What were the main Big Data related developments in 2017, and what key trends do you see in 2018?" We solicited responses from numerous individuals, and asked them to keep their answers to under approximately 200 words, though we were not overly strict and allowed interesting responses to go longer.

At KDnuggets, we try to keep our finger on the pulse of main events and developments in industry, academia, and technology. We also do our best to look forward to key trends on the horizon. We recently asked some of the leading experts in Big Data, Data Science, Artificial Intelligence, and Machine Learning for their opinion on the most important developments of 2016 and key trends they 2017. "What were the main Artificial Intelligence/Machine Learning related events in 2016 and what key trends do you see in 2017?" Common themes include the triumphs of deep neural networks, reinforcement learning's successes, AlphaGo as exemplar of the power of both of these phenomena in unison, the application of machine learning to the Internet of Things, self-driving vehicles, and automation, among others. We generally asked participants to keep their responses to within 100 words or so, but were amenable to longer answers if the situation warranted.

At KDnuggets, we try to keep our finger on the pulse of main events and developments in industry, academia, and technology. We also do our best to look forward to key trends on the horizon. We recently asked some of the leading experts in Big Data, Data Science, Artificial Intelligence, and Machine Learning for their opinion on the most important developments of 2016 and key trends they 2017. "What were the main Big Data related events in 2016 and what key trends do you see in 2017?" We generally asked participants to keep their responses to within 100 words or so, but were amenable to longer answers if the situation warranted.

At KDnuggets, we try to keep our finger on the pulse of main events and developments in industry, academia, and technology. We also do our best to look forward to key trends on the horizon. Over the past few weeks, we published a series of posts outlining expert opinions in data science, machine learning, artificial intelligence, and related fields. In an encore post of this series, we bring you the collected responses to an amalgam question -- including experts from all of the previous posts' fields -- while adding a second dimension this time around. I'd like to thank one of my researchers, Alekh Agarwal, for great input here. The way to increase the number of women in AI, ML and data science is two-fold. First, we must expand the definitions of the fields to include their interaction with the other sciences, including the biological and social sciences.