On 11 January, U.S. President Donald Trump reportedly used a choice word during an Oval Office meeting about immigration. Just like that, a term that's usually not part of respectable public vernacular had been splashed on the front pages of newspapers and media websites. That evening, a twitter bot called New New York Times, running under the handle @NYT_first_said, tweeted the word: "shithole." The bot scans The New York Times for words that the esteemed newspaper uses for the first time. That tweet went viral and the Twitter account gained a bunch of new followers. We chatted with Max Bittker, the San Francisco-based software engineer who built the bot.

Over the past year, I wrote about a bunch of companies working on voice synthesis technology. They were very much in the early stages of development, and only had some pre-made samples to show off. Now, researchers hailing from the Montreal Institute for Learning Algorithms at the Universite de Montreal have a tool you can try out for yourself. It's called Lyrebird, and the public beta requires just a minute's worth of audio to generate a digital voice that sounds a lot like yours. The company say its tech can come in handy when you want to create a personalized voice assistant, a digital avatar for games, spoken-word content like audiobooks in your voice, for when you want to preserve the aural likeness of actors, or for when you just love the sound of your own voice and want to hear it all the time.

In the movie Transcendence, Johnny Depp plays Dr Will Caster, a researcher in artificial intelligence at Berkeley trying to build a sentient computer. Stuart Russell is Will Caster's real life equivalent. He works on artificial intelligence at the University of California at Berkeley, and is co-author of the definitive textbook on AI. He has also been very vocal about the risks of research in AI succeeding. Earlier this year, Google's DeepMind taught a computer program to play a wide variety of Atari video games at a superhuman level in a matter of hours.

A U.S. company will be deploying the world's most advanced undersea search vessels in a renewed bid to search for missing Malaysia Airlines Flight MH370, which went missing on March 8, 2014, with 239 people on board. Texas-based Ocean Infinity -- which has signed a "no cure, no fee" deal with the Malaysian government to find the jetliner -- will for the first time use a swarm of eight drone-like autonomous underwater vehicles (AUVs) to scour a remote part of the southern Indian Ocean, where the ill-fated plane is believed to have gone down. The company will be paid only if it succeeds in locating the plane, which is believed to have gone down while on its way from Kuala Lumpur to Beijing. According to the Daily Beast, Ocean Infinity will conduct the new search with the latest technology north of the original search area, where an underwater operation for more than three years yielded no concrete clues. Talking about the technology that the company will use, the Daily Beast reported that the system was being used for the first time and that while en route from the Caribbean to the search site, the command ship, Seabed Constructor, paused several times to carry out trials at depths similar to those at the Indian Ocean search site.

Sun 21 Jan 2018 12.37 EST Last modified on Sun 21 Jan 2018 17.00 EST Journalism is largely collaboration: reporters with sources, writers and editors, lawyers advising publishers, producers with distributors, and audiences feeding back their knowledge. Rapid development of artificial intelligence means journalists are likely to collaborate more and more with machines that think. The word itself, machines, feels so industrial era, but "robots" feels too limited. Humans are busy building brains, if not yet minds. So my shorthand for now is AI.

I'm new here and I would like to know where I can start to learn about machine learning and gradually move up the ladder to finally research on deep learning. My singular goal is to learn and contribute towards machine learning and even apply it to solve problems. I get really excited reading all the research posted in this subreddit but most of it just flies over my head.

So I'm a .NET developer been doing it for a few years now. AI has always been a seeming interest of mine. Now I've finally found a "Simple", enjoyable and "practical" use for building a system which could utilize a form of Machine Learning. So to give some context; the project is to classify outliers in a large amount of program errors we get on a day to day basis. So, we'll get roughly 100 or so just general errors ranging from "The phone number you used doesn't exist", these are what I'd like to call general errors, or noise. Then we get other major errors; now these are the ones we'd like to'flag' - the outliers in the noise.

Hello, I'm searching for resource for 3D human pose estimation (single person, real time, single or multiple RGB/RGBD cameras). After a bit of research, it seems that the most advanced real-time human pose estimation that is publicly available are Vnect and OpenPose (for single RGB cameras). I am in search for datasets of 3D pose from RGB sequences (PoseTrack seems to be what I need), but would also be interested in RGBD datasets. Do you have any recommendations on the topic? My goal would be to make a quick and dirty model that could take a sequence of RGB frames and output the 3D pose for the frame.

Want to know more about Amazon Echo, the HP laptop battery recall, ransomware, web printing and switching to Android? I have an Amazon Echo. I am really concerned it is listening all the time. Does it have any privacy settings? A: The fact remains that Echo records all of your commands, and the microphone is always active because the device is always listening for a "wake phrase."

Unveiled at the 2018 Consumer Electronics Show, the Aeolus Robot hopes to deliver the promise of Rosie the robotic maid popularized by The Jetsons. The prototype home robot showed off its skills at the show by mopping floors, moving furniture, and even retrieving drinks from the refrigerator on command. Alexander Huang of Aeolus Robotics told the Washington Post that the household robot will learn its surroundings and the individual inhabitants of the home, adapting its behavior over time. "Right now it's like a child, but we will continue to grow its capability so that it grows from a child to an adult," he said. "The more people that use the robot, the stronger it becomes."