While it's up for debate whether this has been a help or a hindrance to the field as a whole, there's no doubt that the AI ecosystem is an endless well of fascinating topics to explore. Whether you prefer a technical deep dive or a more casual thought piece, there have been some gems hidden amongst the hype. We've already reviewed our own content for 2018, but we've also taken a moment to look back at stories from around the web that kept us glued to our screens this year. Covering everything from AI's progress with video games to psychopathic algorithms, here are 12 of our favorite articles about AI and machine learning from the last 12 months. Stop Feeding Garbage to your Model: The 6 Biggest Mistakes with Datasets and How to Avoid Them, Hacker Noon – From low quality to unbalanced classes, there are plenty of things that can prevent your dataset from being the best it can be.

A drone equipped with a thermal camera is seen in this file photo. CANBERRA, Australia--Robyn McIntyre, who lives on the outskirts of Australia's capital, was in her family room a few months ago when she thought she heard a "chain saw gone ballistic." It was actually a drone on its way to deliver a burrito or coffee as part of a test from Wing, which like Google is a subsidiary of Alphabet Inc. One recent day, she said delivery drones flew over her house about 10 times in 2½ hours, making it difficult to focus on working or reading the newspaper. "There's one!" said Ms. McIntyre, 64 years old, drinking tea in her living room on a recent Saturday morning.

Apple Music users have finally got one of Spotify's most celebrated features – at least, sort of. They can now get a round-up of who and what they've been streaming through 2018, including their most played tracks and just how long they spent listening to them. Spotify users have long been able to get a big summary of their activity through the year – but Apple Music has never offered such a tool. But the feature comes with a whole host of caveats, needs a third-party app to work, and doesn't offer anything like the in-depth data that is available to Spotify users. Spotify Wrapped, which becomes available in early December every year, includes a whole host of information.

We've all seen the film where robots take over the world, with their mechanical bodies causing Hollywood-style screams from unsuspecting (or maybe very suspecting) victims. And, while these kinds of films let us live an alternate reality for an hour and a half, there's always that niggling thought at the backs of our minds telling us that this could actually happen in the not-too-distant future. In fact, the "father of AI", Alan Turing, was beavering away on it in the 1950s. He developed the Turing Test, which had a judge ask questions to a machine and a human. The judge would then have to decide who was the human and, if the computer could fool the judge at least half of the time, it was considered intelligent.

Each day in the 2010s, it seems, brings another startling development in the field of artificial intelligence -- a field widely written off not all that long ago as a dead end. But now AI looks just as alive as the people you see in these photographs, despite the fact that none of them have ever lived, and it's questionable whether we can even call the images that depict them "photographs" at all. All of them come, in fact, as products of a state-of-the-art generative adversarial network, a type of artificial intelligence algorithm that pits multiple neural networks against each other in a kind of machine-learning match. These neural networks have, it seems, competed their way to generating images of fabricated human faces that genuine humans have trouble distinguishing from images of the real deal. Their architecture, described in a paper by the Nvidia researchers who developed it, "leads to an automatically learned, unsupervised separation of high-level attributes (e.g., pose and identity when trained on human faces) and stochastic variation in the generated images (e.g., freckles, hair), and it enables intuitive, scale-specific control of the synthesis." What they've come up with, in other words, has made it not just more possible than ever to create fake faces, but made those faces more customizable than ever as well.

When Amazon first debuted the Echo Show last year, plenty of people, us included, mocked its unusual design. More than that, we wondered if adding a display to a smart speaker makes sense, or if it was just another one of Amazon's gimmicks. It turns out, however, that being able to see the result of your queries is actually quite helpful; it's easier to glance at your entire shopping list than it is to have Alexa read it line by line. Amazon later followed up with the Echo Spot bedside clock, which offers the same features in a smaller design. But even though the Show and the Spot came out in 2017, it was in 2018 that smart displays came into their own.

Building open domain conversational systems that allow users to have engaging conversations on topics of their choice is a challenging task. Alexa Prize was launched in 2016 to tackle the problem of achieving natural, sustained, coherent and engaging open-domain dialogs. In the second iteration of the competition in 2018, university teams advanced the state of the art by using context in dialog models, leveraging knowledge graphs for language understanding, handling complex utterances, building statistical and hierarchical dialog managers, and leveraging model-driven signals from user responses. The 2018 competition also included the provision of a suite of tools and models to the competitors including the CoBot (conversational bot) toolkit, topic and dialog act detection models, conversation evaluators, and a sensitive content detection model so that the competing teams could focus on building knowledge-rich, coherent and engaging multi-turn dialog systems. This paper outlines the advances developed by the university teams as well as the Alexa Prize team to achieve the common goal of advancing the science of Conversational AI. We address several key open-ended problems such as conversational speech recognition, open domain natural language understanding, commonsense reasoning, statistical dialog management and dialog evaluation. These collaborative efforts have driven improved experiences by Alexa users to an average rating of 3.61, median duration of 2 mins 18 seconds, and average turns to 14.6, increases of 14%, 92%, 54% respectively since the launch of the 2018 competition. For conversational speech recognition, we have improved our relative Word Error Rate by 55% and our relative Entity Error Rate by 34% since the launch of the Alexa Prize. Socialbots improved in quality significantly more rapidly in 2018, in part due to the release of the CoBot toolkit, with new entrants attaining an average rating of 3.35 just 1 week into the semifinals, compared to 9 weeks in the 2017 competition.

As the new owner of Google's media streaming dongle for your TV, you're probably excited to plug it in and get to watching. But beyond the basics, you can get more mileage out of your Chromecast if you make sure to take these tips into account. Before you begin, download the Google Home app from your Android or iOS store to make setup easier. If you've already got the app, or use Google Home devices, it should detect the presence of a new device after you plug the Chromecast in and power it on. Start by connecting all the services you use to the Google Home app for easy operation once your Chromecast is powered up and ready to go.

LOS ANGELES – It's been two years since a new smash hit app has taken over the nation – remember Pokemon Go? But meanwhile, some of our favorite apps have gotten better, stronger and more essential to our lives. Perhaps you have a new phone, or it's been awhile since you updated your app roster. I've put a list together looking at the landscape of free and essential apps that everyone would want on their phones, from email assistants, to best mapping, ride-hailing and photo sharing. Here's the Talking Tech guide to the 12 app categories you want to have represented on your phone, and our multiple choices for downloading.

Among thousands, 10 programming languages stand out for their job marketability and wide use. Anyone can learn it from his/her initial stage in the field of software development. A free alternative to pricey statistical software such as Matlab or SAS, over the last few years R has become the golden child of data science. Why You Should Learn Python Python is one of the top programming languages requested by companies in 2017 / 2018.