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.

All of us have seen those fear mongering headlines about how artificial intelligence is going to steal our jobs and how we should be very careful with biased AI algorithms. Bias means that the algorithm favors certain groups of people or otherwise guides decisions towards an unfair outcome. Bias can mean giving a raise only to white male employees, increasing criminal risk factors of certain ethnic groups and filling your news feed only with topics and point of views that you are currently consuming -- instead of giving a broad, balanced view of the world and educating you. It is important to be aware that a machine learning model can be biased, but this hardly opens up any new topics to the discussion of AI ethics compared to ethical decisions in general. White males are more likely to get a promotion anyways, court judges may get tired and hand out stricter verdicts and we tend to consume news that we agree with.

A human eye has between six and seven million cone cells, containing one of three colour-sensitive proteins known as opsins. When photons of light hit these opsins, they change shape, triggering a cascade that produces electrical signals, which in turn transmit the messages to the brain for interpretation. This whole process is a very complex phenomenon and making a machine to interpret this at a human level has always been a challenge. The motivation behind the modern-day machine vision system lies at the core of emulating human vision for recognising patterns, faces and rendering 2D imagery from a 3D world into 3D. There is a lot of overlap between image processing and computer vision at the conceptual level and the jargon, often misunderstood, is being used interchangeably.

There are great interests as well as many challenges in applying reinforcement learning (RL) to recommendation systems. In this setting, an online user is the environment; neither the reward function nor the environment dynamics are clearly defined, making the application of RL challenging. In this paper, we propose a novel model-based reinforcement learning framework for recommendation systems, where we develop a generative adversarial network to imitate user behavior dynamics and learn her reward function. Using this user model as the simulation environment, we develop a novel DQN algorithm to obtain a combinatorial recommendation policy which can handle a large number of candidate items efficiently. In our experiments with real data, we show this generative adversarial user model can better explain user behavior than alternatives, and the RL policy based on this model can lead to a better long-term reward for the user and higher click rate for the system.

Get used to people in your house saying "What?" a lot. If you just got a new smart speaker from Amazon or Google, you'll be barking commands out loud, and people around you may wonder what's going on. You'll be engaging in the next step of computing, voice style, using Google or Amazon speakers (or perhaps Siri in Apple's HomePod or Microsoft's Cortana in Invoke from Harman Kardon) to ask for a specific music selection or playlist, the weather, latest news or podcast, the answer to a math problem or how to spell a word. The smart speaker market is dominated by Amazon and Google, so we'll focus here on those two. They were among the most heavily marketed during the holidays, with massive discounts for the entry-level Echo Dot and Google Home Mini at under $25, so we expect them to be under many trees.

Technology behind photography-making tools has hit a plateau. Traditional digital cameras and the associated lenses have already reached an impressive quality and physical upgrades will not dramatically change this state of fact. The next step is code, or AI, in a broad sense. Smartphones are fair competition for DSLR cameras as they try to compensate the drawbacks of tiny physical sensors, with the success we know. The increasingly sophisticated and professional applications of smartphones have achieved an almost similar quality in the technical variables of photography: exposure speed, white balance and color, ISO sensitivity, etc. However, the phone is not able to compete with the combination of the objectives and sensors of a professional camera.

This post was done in partnership with Wirecutter. When readers choose to buy Wirecutter's independently chosen editorial picks, Wirecutter and Engadget may earn affiliate commission. After 45 hours of research and test flying 14 models, we think the DJI Mavic 2 Pro is the best drone for aspiring aerial photographers and videographers thanks to its high-end camera, autonomous obstacle avoidance, long battery life, and portability. Pilots of all skill levels will find it to be exceptionally reliable and easy to fly. The Mavic 2 Pro features a Hasselblad-branded camera (DJI bought a majority stake in the camera brand in 2017), which captures 20-megapixel photographs and 4K videos that look more colorful than those captured by the competition. Its ability to sense and avoid obstacles in all directions and steadily hold its position even in moderate winds lets you focus on your cinematography instead of worrying about keeping the drone steady. It also features DJI's smart-flight modes like ActiveTrack, which directs the drone to autonomously follow and film a subject while still avoiding obstacles. Its 31-minute battery life means you don't have to land for a battery swap as often as other drones, and at 8.4 by 3.6 by 3.3 inches folded and 2 pounds, you can take the Mavic 2 Pro almost anywhere--it fits exceptionally well in our top pick for drone backpacks. It's also compatible with the DJI Goggles FPV headset we recommend. The Mavic 2 Zoom looks and flies identical to the Mavic 2 Pro, but it trades out the Hasselblad camera in favor of a different camera that can zoom 2 times optically and 2 times digitally (with software that avoids losing detail), for up to 4x usable "lossless" zoom.

The last 12 months were filled with ground-breaking products. We saw in-display fingerprint sensors break into the mainstream, the world's first foldable displays in action, and crazy leaps in cameras and computational photography, all on devices small enough to fit in a bag (or a pocket). But among all the great things we got, there were a few things that didn't make it--products and features that were promised in 2018 but won't be arriving until 2019 (if at all): At this point AirPower is the stuff of legend. Announced alongside the iPhone X in 2017, it was supposed to be the first pad capable of charging three devices at once (namely an iPhone, Apple Watch and AirPods). In fact, the only indication that Apple is even working on it was an accidental mention in the quick start guide inside the iPhone box this year.

Another year over, another year to look forward to. But in the context of technology, the prospect on either side of the timeline is no longer as exciting as it was. The consumer tech industry seems to be on a self-imposed consolidation mode, and life-changing innovation is becoming harder to come by. Still, 2018 will be remembered as the year in which everything from smartphones to speakers becomes more powerful and smarter, as they did last year and as they are supposed to. Interestingly, the tech giants have clearly realised that if great innovation cannot be put into users' hands, it's better to improve their overall product experience.