Facebook announced a ban on deepfake videos, on the heels of a crackdown on counterfeit profiles that used AI-generated faces. Facebook declared this week that it will remove deepfake videos it deems deliberately misleading.
Which countries are ahead in AI? Many, in one way or another, and not always the ones you might expect. The Stanford Institute for Human-Centered Artificial Intelligence published its 2019 Artificial Intelligence Index, detailing when, where, and how AI is on the rise.
An international wave of anti-surveillance sentiment pushed back against the proliferation of face recognition systems.
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.
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.
The number of patents issued for deep learning has doubled every year since 2013. Inventor, engineer, and lawyer Nick Brestoff tracks deep learning patents. He detailed his findings in a blog on InsideBigData and offers advice on how to get patent applications approved.
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