摘要: 多年前,在我讀碩士的時候,垂涎一位台灣女神老師的美色,跑去旁聽她的課。正當我捧著兩腮,眼冒星星地看著女神,花痴地流著口水時,聽到她說:人工智能是不可能取代人的。當時她正在展示兩條新聞,都是關於某位大人物的去世。一條由人工智能機器人編寫,內容是某年某月,誰誰誰死了,頭銜是什麼,過往生平如何。另一條是記者寫的,內容類似於“天陰沉沉地下著小雨,彷彿全世界都在垂淚哀悼……”當女神老師斬釘截鐵地表示,應該拋棄人工智能的作品而選擇人類的作品的時候,我意識到女神老師和前沿領域脫節了。

摘要: Bound for a foreign country where you don’t speak the language? Good news: Google has you covered. This afternoon, the Mountain View tech giant announced that Translate, its free multilingual machine translation service, is now more robust. Offline, translation accuracy has improved by an order of magnitud in some cases.

摘要: Technology advances at an amazing rate. A decade ago, the thought of self-driving cars and everyone having an AI assistant in their pocket and home was reserved for Sci-Fi films. Arecent study showed that currently 40% of the world’s population is connected to the internet, 90% of all the world’s data was created in the last two years, and five million jobs will be operated by robots by next year. As our world becomes more driven by technology and data, our way of living becomes more vulnerable to technology availability.

摘要: Computer Vision models have learned to identify objects in photos such precision that some may outperform humans in some data sets. But when these same object detectors are released into the real world, their performance decreases dramatically, creating reliability problems for self-driving cars and other critical systems for security that using the machine vision .

摘要: The modern financial services industry is in the midst of a wave of technological innovation–from retail banks providing 24/7 service through smartphone apps, to fintech startups revolutionizing payments, to securities firms executing transactions with ever greater speed and precision. At the same time, as more of the industrys functions shift to rely on new technology, the threat of data breaches and other cybercrimes increases. For all businesses, but financial firms in particular, the risks often appear through methods of communication. However, if new technology raises cyber threats, it also provides increased measures of defense, and its here where automation can make the biggest difference.

摘要: AI and machine learning algorithms capable of reading lips from videos aren’t anything out of the ordinary, in truth. Back in 2016, researchers from Google and the University of Oxford detailed a system that could annotate video footage with 46.8% accuracy, outperforming a professional human lip-reader’s 12.4% accuracy. But even state-of-the-art systems struggle to overcome ambiguities in lip movements, preventing their performance from surpassing that of audio-based speech recognition.

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