Think back to what you ate for breakfast this morning. Did you picture yourself in your kitchen and visualize the plate in front of you to remember exactly what you ate? That's called an episodic memory – a memory of a particular event that happened at a specific time and place, as opposed to a semantic memory, which refers to more general knowledge or rules that someone understands. Cognitive scientists have long thought that humans were the only animals capable of traveling down memory lane by having episodic memories. Dogs, for example, were known to commit things to semantic memory. When repeatedly trained to sit, stay, or lie down, they learn a rule. But they, like other nonhuman animals, were thought to live exclusively in the here and now – until now.

Why did I bother writing this? Well, here is one of the most trivial yet life-changing insights and worldly wisdoms from my former professor that has become my mantra ever since: "If you have to do this task more than 3 times just write a script and automate it." By now, you may have already started wondering about this blog. I haven't written anything for more than half a year! Okay, musings on social network platforms aside, that's not true: I have written something – about 400 pages to be precise. This has really been quite a journey for me lately. And regarding the frequently asked question "Why did you choose Python for Machine Learning?"

Vocoders just got a serious upgrade. A new speech synthesiser can translate mouth movements directly into intelligible speech, completely bypassing a person's voicebox. Although the synthesiser might not be immediately useful, it's a first step towards building a brain-computer interface that could allow paralysed people to talk by monitoring their thought patterns. To create the speech synthesiser, scientists at INSERM and CNRS in Grenoble, France used nine sensors to capture the movements of the lips, tongue, jaw and soft palate. A neural network learned to translate the sensor data into vowels and consonants, which are emitted from a vocoder.

ORLANDO, Fla., October 18, 2016 View All Press Releases Gartner Reveals Top Predictions for IT Organizations and Users in 2017 and Beyond Analysts Explore the Digital Future at Gartner Symposium/ITxpo 2016, October 16-20 in Orlando Gartner, Inc. today revealed its top predictions for 2017 and beyond. Gartner's top predictions for 2017 examine three fundamental effects of continued digital innovation: experience and engagement, business innovation, and the secondary effects that result from increased digital capabilities. "Gartner's top strategic predictions continue to offer a provocative look at what might happen in some of the most critical areas of technology evolution. At the core of future outcomes is the notion of digital disruption, which has moved from an infrequent inconvenience to a consistent stream of change that is redefining markets and entire industries," said Daryl Plummer, managing vice president, chief of research and Gartner Fellow. "Last year, we said digital changes were coming fast. This year the acceleration continues and may cause secondary effects that have wide-ranging impact on people and technology."

Why did I bother writing this? Well, here is one of the most trivial yet life-changing insights and worldly wisdoms from my former professor that has become my mantra ever since: "If you have to do this task more than 3 times just write a script and automate it." By now, you may have already started wondering about this blog. I haven't written anything for more than half a year! Okay, musings on social network platforms aside, that's not true: I have written something – about 400 pages to be precise. This has really been quite a journey for me lately. And regarding the frequently asked question "Why did you choose Python for Machine Learning?"

Customer: I want to know how to activate the voice mail service. Company: The voice mail service is already active on your SIM. Customer: How much does it cost? Company: The cost of the service, from your mobile phone in Italy is 12.40 cents per call. Here is an example for a conversation with a diligent customer service clerk at a telecommunications company.

Tens of thousands of people are calling on Parliament to recall the "most extreme spying powers ever seen". The Investigatory Powers Bill was just passed through the House of Lords and so is now just weeks away from becoming law. But signatories to a new petition hope that process can be stopped, forcing lawmakers to keep the new powers from being published. The new law forces internet companies to keep a full browsing history of all of their users and give it up to a huge range of government agencies if they are asked. It also gives spies unprecedented powers to read people's messages, as well as forcing technology companies like Apple to hack into their own phones if they are asked.

Think back to what you ate for breakfast this morning. Did you picture yourself in your kitchen and visualize the plate in front of you to remember exactly what you ate? That's called an episodic memory – a memory of a particular event that happened at a specific time and place, as opposed to a semantic memory, which refers to more general knowledge or rules that someone understands. Cognitive scientists have long thought that humans were the only animals capable of traveling down memory lane by having episodic memories. Dogs, for example, were known to commit things to semantic memory. When repeatedly trained to sit, stay, or lie down, they learn a rule. But they, like other nonhuman animals, were thought to live exclusively in the here and now – until now.

Artificial intelligence is getting its teeth into lip reading. A project by Google's DeepMind and the University of Oxford applied deep learning to a huge data set of BBC programmes to create a lip-reading system that leaves professionals in the dust. The AI system was trained using some 5000 hours from six different TV programmes, including Newsnight, BBC Breakfast and Question Time. In total, the videos contained 118,000 sentences. The AI vastly outperformed a professional lip-reader who attempted to decipher 200 randomly selected clips from the data set.

Neil Prakash, an Australian recruiter for the Islamic State group (also called ISIS), was arrested somewhere in the Middle East after surviving drone attacks by the FBI, the New York Times reported Thursday. The 25-year-old, who was linked to militant plots in Australia and had appeared in several ISIS propaganda videos, was believed killed in a U.S. airstrike in Iraq in April. According to the Times, which cited an unnamed senior American military official, Prakash was wounded in an airstrike earlier this year but survived. Another senior U.S. military official reportedly said the former Melbourne resident was arrested some time in the last few weeks by an unidentified Middle Eastern government. Prakash, who converted to Islam from Buddhism and took the name Abu Khaled al-Cambodi, left Australia in 2013 and has been recruiting fighters for ISIS since then.