{"id":25212,"date":"2018-06-08T21:48:51","date_gmt":"2018-06-08T21:48:51","guid":{"rendered":"http:\/\/www.kurzweilai.net\/?p=316992"},"modified":"2018-06-12T20:51:47","modified_gmt":"2018-06-12T20:51:47","slug":"roundup-ai-powers-cars-photos-phones-and-people","status":"publish","type":"post","link":"https:\/\/hoo.central12.com\/fugic\/2018\/06\/08\/roundup-ai-powers-cars-photos-phones-and-people\/","title":{"rendered":"roundup | AI powers cars, photos, phones, and people"},"content":{"rendered":"
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(credit: BDD Industry Consortium)<\/p><\/div>\n

Huge self-driving-car video dataset may help reduce accidents<\/h4>\n

Berkeley Deep Drive<\/a>, the largest-ever self-driving car dataset, has been released by BDD Industry Consortium<\/a> for free public download. It features 100,000 HD videos on cars and labeled objects, with GPS and other data — 800 times larger than Baidu’s Apollo dataset<\/a>. The goal: apply computer vision research — including deep reinforcement learning for object tracking — to the automotive field.<\/p>\n

Berkeley researchers plan to\u00a0add to the dataset, including panorama and stereo videos, LiDAR, and radar. Ref.: arXiv<\/a>. Source: BDD Industry Consortium<\/a>.<\/em><\/p>\n

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A \u201cprivacy filter\u201d that disrupts facial-recognition algorithms. A \u201cdifference\u201d filter alters very specific pixels in the image, making subtle changes (such as in the corner of the eyes). (credit:Avishek Bose)<\/p><\/div>\n

A \u201cprivacy filter\u201d for photos<\/h4>\n

University of Toronto engineering researchers have created an artificial intelligence (AI) algorithm (computer program) to disrupt facial recognition systems and protect privacy. It uses a deep-learning technique called \u201cadversarial training,\u201d which pits two algorithms against each other — one to identify faces, and the second\u00a0 to disrupt the facial recognition task of the first.<\/p>\n

The algorithm also disrupts image-based search, feature identification, emotion, and ethnicity estimation, and all other face-based attributes that can be extracted automatically. It will be available as an app or website. Ref.: Github<\/a>. Source: University of Toronto<\/a>.<\/em><\/p>\n

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Developers of the more than 2 million iOS apps will be able to hook into Siri\u2019s new Suggestions feature, with help from a new \u201cCreate ML\u201d tool. (credit: TechCrunch)<\/p><\/div>\n

A smarter Siri<\/h4>\n

\u201cApple is turning its iPhone into a highly personalized device, powered by its [improved] Siri AI,” says TechCrunch<\/em>, reporting on the just-concluded Apple Worldwide Developers\u00a0Conference<\/a>. With the new \u201cSuggestions\u201d feature — to be available with Apple’s iOS 12 mobile operating system (in autumn 2018) — Siri will offer suggestions to users, such as texting someone that you\u2019re running late to a meeting.<\/p>\n

The Photos app will also get smarter, with a new tab that will \u201cprompt users to share photos taken with other people, thanks to facial recognition and machine learning,\u201d for example, says TechCrunch<\/em>. Along with Core ML (announced last year), a new tool called \u201cCreate ML\u201d should help Apple developers build machine learning models, reports Wired<\/a>.<\/p>\n

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(credit: Loughborough University)<\/p><\/div>\n

AI detects illnesses in human breath<\/h4>\n

Researchers at Loughborough University in the U.K. have developed deep-learning networks that can detect illness-revealing chemical compounds in breath samples,\u00a0with potentially wide applications in medicine, forensics, environmental analysis, and others.<\/p>\n

The new process is cheaper and more reliable — taking only minutes to autonomously analyze a breath sample that previously took hours by a human expert, using gas-chromatography mass-spectrometers<\/a> (GC-MS). The initial study focused on recognizing a group of chemicals called aldehydes<\/a>, which are often associated with fragrances but also human stress conditions and illnesses. Source: The Conversation<\/a>.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Huge self-driving-car video dataset may help reduce accidents Berkeley Deep Drive, the largest-ever self-driving car dataset, has been released by BDD Industry Consortium for free public download. It features 100,000 HD videos on cars and labeled objects, with GPS and other data — 800 times larger than Baidu’s Apollo dataset. The goal: apply computer vision […]<\/p>\n","protected":false},"author":454,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[46,45,43],"tags":[],"class_list":["post-25212","post","type-post","status-publish","format-standard","hentry","category-airobotics","category-biomedlongevity","category-news"],"_links":{"self":[{"href":"https:\/\/hoo.central12.com\/fugic\/wp-json\/wp\/v2\/posts\/25212"}],"collection":[{"href":"https:\/\/hoo.central12.com\/fugic\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hoo.central12.com\/fugic\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hoo.central12.com\/fugic\/wp-json\/wp\/v2\/users\/454"}],"replies":[{"embeddable":true,"href":"https:\/\/hoo.central12.com\/fugic\/wp-json\/wp\/v2\/comments?post=25212"}],"version-history":[{"count":1,"href":"https:\/\/hoo.central12.com\/fugic\/wp-json\/wp\/v2\/posts\/25212\/revisions"}],"predecessor-version":[{"id":25213,"href":"https:\/\/hoo.central12.com\/fugic\/wp-json\/wp\/v2\/posts\/25212\/revisions\/25213"}],"wp:attachment":[{"href":"https:\/\/hoo.central12.com\/fugic\/wp-json\/wp\/v2\/media?parent=25212"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hoo.central12.com\/fugic\/wp-json\/wp\/v2\/categories?post=25212"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hoo.central12.com\/fugic\/wp-json\/wp\/v2\/tags?post=25212"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}