
Face Recognition Meets Resistance: The rising resistance against face recognition in 2019
An international wave of anti-surveillance sentiment pushed back against the proliferation of face recognition systems.
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An international wave of anti-surveillance sentiment pushed back against the proliferation of face recognition systems.

We here at deeplearning.ai wish you a wonderful holiday season. As you consider your New Year’s resolutions and set goals for 2020, consider not just what you want to do, but what you want to learn...

Earlier language models powered by Word2Vec and GloVe embeddings yielded confused chatbots, grammar tools with middle-school reading comprehension, and not-half-bad translations. The latest generation is so good, some people consider it dangerous.

We here at deeplearning.ai wish you a wonderful holiday season. As you consider your New Year’s resolutions and set goals for 2020, consider not just what you want to do, but what you want to learn: What courses do you want to take this year?

Society awakened to the delight, threat, and sheer weirdness of realistic images and other media dreamed up by computers.

Makers of self-driving cars predicted a quick race to the finish line, but their vehicles are far from the homestretch. A few years ago, some car companies promised road-ready autonomous vehicles as early as 2017.

Society awakened to the delight, threat, and sheer weirdness of realistic images and other media dreamed up by computers.

A year-long Twitter feud breathed fresh life into a decades-old argument over AI’s direction. Gary Marcus, a standard bearer of logic-based AI, waged a tireless Twitter campaign to knock deep learning off its pedestal and promote other AI approaches.

The future of machine learning may depend less on amassing ground-truth data than simulating the environment in which a model will operate. Deep learning works like magic with enough high-quality data. When examples are scarce, though, researchers are using simulation to fill the gap.

An international wave of anti-surveillance sentiment pushed back against the proliferation of face recognition systems.

A year-long Twitter feud breathed fresh life into a decades-old argument over AI’s direction. Gary Marcus, a standard bearer of logic-based AI, waged a tireless Twitter campaign to knock deep learning off its pedestal and promote other AI approaches.

The future of machine learning may depend less on amassing ground-truth data than simulating the environment in which a model will operate. Deep learning works like magic with enough high-quality data. When examples are scarce, though, researchers are using simulation to fill the gap.

Makers of self-driving cars predicted a quick race to the finish line, but their vehicles are far from the homestretch. A few years ago, some car companies promised road-ready autonomous vehicles as early as 2017.

Earlier language models powered by Word2Vec and GloVe embeddings yielded confused chatbots, grammar tools with middle-school reading comprehension, and not-half-bad translations. The latest generation is so good, some people consider it dangerous.

We here at deeplearning.ai wish you a wonderful holiday season. As you consider your New Year’s resolutions and set goals for 2020, consider not just what you want to do, but what you want to learn...
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