摘要: Deep learning (DL) became an overnight “star” when a robot player beat a human player in the famed game of AlphaGo. Deep learning training and learning methods have been widely acknowledged for “humanizing” machines. Many of the advanced automation capabilities now found in enterprise AI platforms are due to the rapid growth of machine learning (ML) and deep learning technologies. What’s Next for Deep Learning? attempts to answer this question that originally appeared on Quora.
Deep learning (DL) became an overnight “star” when a robot player beat a human player in the famed game of AlphaGo. Deep learning training and learning methods have been widely acknowledged for “humanizing” machines. Many of the advanced automation capabilities now found in enterprise AI platforms are due to the rapid growth of machine learning (ML) and deep learning technologies. What’s Next for Deep Learning? attempts to answer this question that originally appeared on Quora.
A Deep Dive into Deep Learning in 2019 comments on the “ubiquitous” presence of DL in many facets of AI — be it NLP or computer vision applications. Gradually, AI and DL-enabled automated systems, tools, and solutions are penetrating and taking over all business sectors —from marketing to customer experience, from virtual reality to natural language processing (NLP) — the digital impact is everywhere.
Deep Learning Will Be the End to End Encryption brings forth controversy over public demand of absolute privacy of personal data. This consumer demand is in direct conflict with Facebook’s current AI research endeavors. The AI researchers at Facebook need to “mass harvest” personal data to train learning algorithms.
acebook realizes that the utopian concept of end-to-end encryption was indeed a myth in a research world seeking answers from piles of personal data. For future efforts, researchers are now seriously considering training algorithms on “dead data” on individual devices rather than mass harvesting personal data. In that case, Facebook engineers will install content-moderation algorithms directly on users’ phones to bypass data-privacy violations.
In a controversial post, the author of this KD Nugget post predicts that deep learning may not be the future of AI. The reason behind this, according to the author, is that in future many DL methods will not only become non-complaint, but outright illegal. The post also suggests there is a distinct possibility that future mobile apps will be devoid of DL.
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Full Text: dataversity
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