Source: Deep Learning on Medium
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Welcome to the first issue of my AI Newsletter which aims to cover top AI stories of the week.
This week Sundar Pichai stresses the need for comprehensive regulation of artificial intelligence. Indermit Gill predicts that the country that leads artificial intelligence this decade will dominate the globe for the whole century. Hollywood is finally embracing AI to predict the performance of upcoming movies. An article in Deccan Herald discusses what is it like to be a human in the age of AI. GitHub now uses AI to recommend open issues in project repositories.
Google and Alphabet CEO Sundar Pichai has emphasized the need for greater regulation of artificial intelligence. He highlighted the dangers of “nefarious uses of facial recognition” as well as “deepfakes” and suggested that regulation should be of a fine balance mitigating “potential harms” and providing “social opportunities.”
Indermit Gill writes an article in Brookings.com predicting that the country that leads in technologies using artificial intelligence will dominate the globe. Technological leadership will require big digital investments, rapid business process innovation, and efficient tax and transfer systems. In those terms, for now, China appears to have the edge over the US and Europe.
Hollywood is finally embracing AI, analysts are looking at film sites such as Rotten Tomatoes and IMDB, data about different films released till now, and what people were watching on YouTube at the time, to help predict whether upcoming movie would be popular.
Despite the excessive hype, a future where AI will be everywhere and in everything is coming sooner than we think. AI has already begun to play a huge part in our everyday life today. However, there is a sore lack of understanding of what AI really is, how it is shaping our future and why it is likely to alter our very psyche sooner or later.
Large and complex open-source projects on GitHub generally have a long list of problems that require addressing. GitHub recently introduced the “good first issues” feature, which matches contributors with issues that are likely to fit their interests. The initial version, which launched in May 2019, surfaced recommendations based on labels applied to issues by project maintainers. But this updated release shipped last month incorporates an AI algorithm that GitHub claims surfaces issues in about 70% of repositories recommended to users.