I've written a few times recently about various projects that are helping develop robots capable of learning by watching how a task is performed. The machines typically observe something like a YouTube video in their attempt to pick up the skill, but the tasks have generally been quite manual in nature, such as the correct handling of kitchen utensils. A recent study from researchers at MIT set out to test whether machines could also use a similar method for picking up something so intuitively human. The researchers were hoping to train robots to be able to instinctively predict how an encounter with a human might unfold. It's the kind of intuition that we develop subconsciously as a result of our lifetime of experience.

Have we learned nothing from Tay, the Microsoft chatbot that spewed foul racist garbage after only a few hours of interacting with trolls on Twitter? Sure, Reddit models a colloquial tone, as Sophie Kleeman at Gizmodo points out, and its many communities discuss a wide range of subjects, but it is also frequently the boneyard where all grace and decency go to die. Will OpenAI's learning systems absorb strategies for choosing careers and college majors, or only gain expertise in nihilistic lulz and platform-specific acronyms? At least, a success from the researchers on this front would break new ground: They'd have created the only brain ever to get smarter by reading Reddit.

Artificial intelligence has been tasked with many projects in its brief history, but assisting in the latest United Nations projects aimed at ending world poverty, could represent the noblest goals yet posed to the artificial thinking of machine learning. It may also be the most challenging as its measurements and assessments would be applied to the entire world. Ending world poverty by 2030 is the most ambitious of 17 global missions, planned by the United Nations in 2015. These Sustainable Development Goals will require substantial amounts of data and data analysis. Marshall Burke of Stanford University's Earth System Science explained to Quartz the need for some measure to gauge the success of the project. "How are we going to know if we've eliminated poverty if we don't collect data?

A new bot called Wonder will remember anything you want, and then return the information you need via a text message. Once you enter your phone number on the Wonder website, the bot will send you a text explaining how it works – and then you just reply back with the information you want it to store. Using CUDA and GPUs in the Amazon cloud to train the deep learning models, the bot is able to understand the texts coming in and remember the things you're wondering. When you're trying to remember something later, you ask Wonder a question, like "When's the next company meeting?," What's my wife's favorite Starbuck's order?" or anything else you previously told the bot to remember.

Pop culture's many takes on artificial intelligence New technique using artificial intelligence to read satellite images could aid efforts to eradicate ...

After birthing a virtual assistant that knows a little of everything, SRI International is working on ones that know a lot about just one thing. The nonprofit research center is arguably best known in the tech world for spinning off Siri, whose virtual assistant tech Apple acquired in 2010. SRI also incubated Tempo, an AI-driven calendar app that Salesforce bought last year. Now, SRI believes it can infuse AI into even more settings--shopping, banking, travel, business-to-business applications, and so on--allowing for deeply knowledgeable chatbots that know how to carry a conversation. The goal, says William Mark, SRI's president of information and computing services, is to have assistants that are much better at specific tasks than a general-interest assistant like Siri.

Deep Learning is a new area of Machine Learning research that has been gaining significant media interest owing to the role it is playing in artificial intelligence applications like image recognition, self-driving cars and most recently the AlphaGo vs. Lee Sedol matches. Recently, Deep Learning techniques have become popular in solving traditional Natural Language Processing problems like Sentiment Analysis. For those of you that are new to the topic of Deep Learning, we have put together a list of ten common terms and concepts explained in simple English, which will hopefully make them a bit easier to understand. We've done the same in the past for Machine Learning and NLP terms, which you might also find interesting. In the human brain, a neuron is a cell that processes and transmits information.

OK, they didn't literally run for any hills. But the EFF wrote a very panicked blog post warning of the dangers to come if an AI trained to hack wasn't parented properly. The histrionic post made a few headlines, but missed the point of the competition entirely. If the AI playing Def Con's all-machine Capture the Flag had feelings, they would've been very hurt indeed. The seven different AI agents were projects of teams that hailed from around the world, coming together to compete for a 2 million purse.

Pop culture's many takes on artificial intelligence

Stanford scientists have found a low-cost method to map poverty in areas previously devoid of data, by combining satellite images and making use of machine learning. These improved poverty maps could help organisations and policymakers distribute funds more efficiently and evaluate policies, researchers said. One of the biggest challenges in providing relief to people living in poverty is locating them. The availability of accurate and reliable information on the location of impoverished zones is surprisingly lacking for much of the world, particularly in African countries. Aid groups and other international organisations often fill in the gaps with door-to-door surveys, but these can be expensive and time-consuming to conduct.