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| 2017 || {{dts|April}} || Coverage || An article entitled "The People Behind OpenAI" is published on {{W|Red Hat}}'s ''Open Source Stories'' website, covering work at OpenAI.<ref>{{cite web |url=https://www.redhat.com/en/open-source-stories/ai-revolutionaries/people-behind-OpenAI |title=Open Source Stories: The People Behind OpenAI |accessdate=May 5, 2018 |first1=Brent |last1=Simoneaux |first2=Casey |last2=Stegman}} In the HTML source, last-publish-date is shown as Tue, 25 Apr 2017 04:00:00 GMT as of 2018-05-05.</ref><ref>{{cite web |url=https://www.reddit.com/r/OpenAI/comments/63xr4p/profile_of_the_people_behind_OpenAI/ |publisher=reddit |title=Profile of the people behind OpenAI • r/OpenAI |date=April 7, 2017 |accessdate=May 5, 2018}}</ref><ref>{{cite web |url=https://news.ycombinator.com/item?id=14832524 |title=The People Behind OpenAI |website=Hacker News |accessdate=May 5, 2018 |date=July 23, 2017}}</ref>
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| 2017 || {{dts|April 6}} || Coverage Milestone release || "Learning OpenAI unveils an unsupervised system which is able to Generate Reviews and Discovering perform a excellent {{w|sentiment analysis}}, despite being trained only to predict the next character in the text of Amazon reviews.<ref>{{cite web |title=Unsupervised Sentiment" is publishedNeuron |url=https://openai.com/blog/unsupervised-sentiment-neuron/ |website=openai.com |accessdate=5 April 2020}}</ref><ref>{{cite web |url=https://techcrunch.com/2017/04/07/OpenAI-sets-benchmark-for-sentiment-analysis-using-an-efficient-mlstm/ |date=April 7, 2017 |publisher=TechCrunch |title=OpenAI sets benchmark for sentiment analysis using an efficient mLSTM |author=John Mannes |accessdate=March 2, 2018}}</ref>
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| 2017 || {{dts|April 6}} || AI development Milestone release || OpenAI unveils reuse of an old field called “neuroevolution”, and a subset of algorithms from it called “evolution strategies,” which are aimed at solving optimization problems. In one hour training on an Atari challenge, an algorithm is found to reach a level of mastery that took a reinforcement-learning system published by DeepMind in 2016 a whole day to learn. On the walking problem the system took 10 minutes, compared to 10 hours for DeepMind's approach.<ref>{{cite web |title=OpenAI Just Beat Google DeepMind at Atari With an Algorithm From the 80s |url=https://singularityhub.com/2017/04/06/OpenAI-just-beat-the-hell-out-of-deepmind-with-an-algorithm-from-the-80s/ |website=singularityhub.com |accessdate=29 June 2019}}</ref>
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| 2017 || {{dts|April}} || Staff || Matthias Plappert joins OpenAI as Researcher.<ref>{{cite web |title=Matthias Plappert |url=https://www.linkedin.com/in/matthiasplappert/ |website=linkedin.com |accessdate=28 February 2020}}</ref>
