Siraj Raval weighs in on the controversy around OpenAI’s Text Generator.
As a machine learning project grows, so should its infrastructure. In this talk, Alejandro Saucedo covers some of the key trends in machine learning operations, as well as libraries to watch in 2019.
The talk is based on the “Awesome Machine Learning Operations” list maintained by The Institute for Ethical AI & Machine Learning, and focuses on the topics of reproducibility, orchestration and explainability.
This week, this week I’m at (well, near) Microsoft’s headquarters just outside Seattle, Washington, attending internal, possibly even secret, training. In this impromptu Data Point, he chats with fellow attendees about AI, Ethics, and the ever-present Unintended Consequences of technological advancement.
Press the play button below to listen here or visit the show page at DataDriven.tv
While the AI revolution will first automate away most of the jobs first, what happens next? Will they ever become conscious? How will we know? And what shall we do once machines become conscious? Do we need to grant them rights?
Brian Edward Cox, professor of particle physics at the University of Manchester, moderates a panel of experts to discuss the future of AI and Machine Learning.
In this TED talk, Stuart Russell talks about the three rules to make AI safe for humanity.
Kate Crawford, a Principal Researcher with Microsoft Research, on identifying the risks of hidden bias in big data research.
In this video, Siraj Raval explains the “DeepFakes” algorithm and phenomenon, as well as start us thinking about to deal with fraudulent AI generated content.