Commentary: Agricultural innovation is accelerating thanks to AI.

Disinformation campaigns are not new--think of wartime propaganda used to sway public opinion against an enemy. What is new, however, is the use of the internet and social media to spread these campaigns. The spread of disinformation via social media has the power to change elections, strengthen conspiracy theories, and sow discord. Steven Smith, a staff member from MIT Lincoln Laboratory's Artificial Intelligence Software Architectures and Algorithms Group, is part of a team that set out to better understand these campaigns by launching the Reconnaissance of Influence Operations (RIO) program. Their goal was to create a system that would automatically detect disinformation narratives as well as those individuals who are spreading the narratives within social media networks.

We never have been so closer to the future than we are now. There are news spreading across the media about the robots takeover of our jobs, driverless cars hitting the road with outstanding proficiency in driving standards, while at the same time, virtual assistants make us feel a bit less lonely telling us jokes and spending time with us. In fact, Siri, Alexa or Cortana have something machines didn't have before: a simulated human conscious capable of keep conversations with humans without being uncovered. AI is now at its most advanced development stage ever, but… do we need to worry about how smart are getting the robots? Will we ever need to?

Have you ever been Rickrolled? As they say, good people are too trusting. I just slipped in a #selfpraise moment. But seriously, I wished the quality of the music video was better. Since the joke was on me, I might as well take the opportunity to sing along and dance a bit. For the uninitiated, Rickrolling is a prank and an Internet meme involving an unexpected appearance of the music video for the 1987 Rick Astley song "Never Gonna Give You Up".

Deep Instinct, which uses deep learning to identify threats before they … there's artificial intelligence and machine learning, and some of that is deep …

'Gutfeld!' panel on how constant political correctness is hurting society This is a rush transcript of "Gutfeld!" on May 27, 2021. This copy may not be in its final form and may be updated. You did some fantastic and extensive reporting this weekend on Joe Biden, who he is. ASHLEY PARKER, MSNBC SENIOR POLITICAL ANALYST: Joe Biden, some of it, he has the taste of a five-year-old. It's PB&J chop salad with grilled chicken. He likes orange Gatorade, and he stacks the Oval Office with homemade chocolate chip cookies. That is some extensive reporting for the Food Network. You know in the old days, if you wanted an answer to something, you went to this. That's how I learned to play doctor. No worry it was with Raggedy Andy. But the one thing everybody had was a set of encyclopedias. Every time you had homework, you copy the answers word for word from their pages, what's now called the Biden method. Then as you got older, you discovered the library, a magical place filled with strange artifacts known as books. They were heavy, you turn the pages in order to read them. Of course, libraries are different now, they're not closed. You see -- you see a lot of massages going on in there. Hey, I don't make the rules. But that was really the first search engine, except there was no engine, just a librarian whose hair bun could stop a bullet. Now getting information seems easier. The whole world is in the palm of your hand. And yet for some reason, we still can't find the truth. Because even though we think we are in control, we aren't. We now have everything at our fingertips, but it's the tech giants who decide what we can and can't touch.

Deep Learning Enables Intuitive Prosthetic Control … in the forearm of Shawn Findley, who had lost a hand to a machine shop accident 17 years prior.

Amazon Web Services Inc. is lowering the barrier to entry for machine learning with the launch of its new service Amazon Redshift ML, which it made …

Drones have become a common tool, which is utilized in many tasks such as aerial photography, surveillance, and delivery. However, operating a drone requires more and more interaction with the user. A natural and safe method for Human-Drone Interaction (HDI) is using gestures. In this paper, we introduce an HDI framework building upon skeleton-based pose estimation. Our framework provides the functionality to control the movement of the drone with simple arm gestures and to follow the user while keeping a safe distance. We also propose a monocular distance estimation method, which is entirely based on image features and does not require any additional depth sensors. To perform comprehensive experiments and quantitative analysis, we create a customized testing dataset. The experiments indicate that our HDI framework can achieve an average of 93.5\% accuracy in the recognition of 11 common gestures. The code is available at: https://github.com/Zrrr1997/Pose2Drone

By producing summaries for long-running events, timeline summarization (TLS) underpins many information retrieval tasks. Successful TLS requires identifying an appropriate set of key dates (the timeline length) to cover. However, doing so is challenging as the right length can change from one topic to another. Existing TLS solutions either rely on an event-agnostic fixed length or an expert-supplied setting. Neither of the strategies is desired for real-life TLS scenarios. A fixed, event-agnostic setting ignores the diversity of events and their development and hence can lead to low-quality TLS. Relying on expert-crafted settings is neither scalable nor sustainable for processing many dynamically changing events. This paper presents a better TLS approach for automatically and dynamically determining the TLS timeline length. We achieve this by employing the established elbow method from the machine learning community to automatically find the minimum number of dates within the time series to generate concise and informative summaries. We applied our approach to four TLS datasets of English and Chinese and compared them against three prior methods. Experimental results show that our approach delivers comparable or even better summaries over state-of-art TLS methods, but it achieves this without expert involvement.