Artificial intelligence (AI) is the convenient future. It is one of the most promising and transformative opportunities of our time. We are closer to the near future where virtual assistants, bots, and software agents will act more and more like people. Some the biggest advances in AI are being developed inside tech giants such as Google (Deep Mind) and IBM (Watson). But there are still a lot of great opportunities for young startups to explore.

Brands need to be "waking up" up to the potential of bots and be aware of sensors, the cloud and machine learning as we approach the "fourth industrial revolution", Microsoft's UK chief marketing officer told The Drum. Paul Davies, who spoke on the Advertising Week Europe panel dubbed'How smart cities will transform advertising', explained how Microsoft is already looking to an automated, connected future when designing and collaborating on innovations. "We have an app experience for people who are visually impaired, which is powered through bluetooth sensors to help them walk around all the way, through an electric car sharing company called Autolib," he said. "Their mission is to reduce the number of cars in Paris by 25,000 in the next seven years...using data and the cloud to empower that." Davies believes the world is "on the cusp of the fourth industrial revolution, the digital revolution".

Following last week's predictions by Mark Zuckerberg, Google CEO Sundar Pichai showed that the search giant has a vision about artificial intelligence too. Quizzed on parent Alphabet's Q1 2016 investor call about areas where Google is pushing forward innovation, Pichai said search, particularly on mobile devices, has the opportunity to become closer to a personal assistant for users and, to fulfill that vision, must deploy machine learning and AI. "And overall, I do think in the long run, I think we will evolve in computing from a mobile first to an AI first world. And I do think we are at the forefront of development," he said, polishing the search giant's credentials just a week after founder Mark Zuckerberg made a similar claim for Facebook at the F8 developer event. AI-based chatbots, for instance for Facebook Messenger, was a big theme at the social giant's event. Pichai also referenced the "great strides" made by AlphaGo, developed by Google subsidiary DeepMind, which shocked audiences when it beat a professional South Korean Go player in Seoul last month.

Wearing black headsets with tentacle-like sensors stretched over their foreheads, the competitors stare at cubes floating on computer screens as their small white drones prepare for takeoff. Some struggle to move even a few feet, while others zip confidently across the finish line. The competition -- billed as the world's first drone race involving a brain-controlled interface -- involved 16 pilots who used their willpower to drive drones through a 10-yard dash over an indoor basketball court at the University of Florida this past weekend. The Associated Press was there to record the event, which was sponsored with research funding from Intel Corp. Organizers want to make it an annual inter-collegiate spectacle, involving ever-more dynamic moves and challenges, and a trophy that puts the brain on a pedestal. "With events like this, we're popularizing the use of BCI instead of it being stuck in the research lab," said Chris Crawford, a Florida PhD student in human-centered computing. "BCI was a technology that was geared specifically for medical purposes, and in order to expand this to the general public, we actually have to embrace these consumer brand devices and push them to the limit."

Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data and data science. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. In this episode of the O'Reilly Data Show, I spoke with Ira Cohen, co-founder and chief data scientist at Anodot (full disclosure: I'm an advisor to Anodot). Since my days in quantitative finance, I've had a longstanding interest in time-series analysis. Back then, I used statistical (and data mining) techniques on relatively small volumes of financial time series.

That's an interesting question, and I try to answer this is a very general way. The tl;dr version of this is: Deep learning is essentially a set of techniques that help we to parameterize deep neural network structures, neural networks with many, many layers and parameters. And if we are interested, a more concrete example: Let's start with multi-layer perceptrons (MLPs) … On a tangent: The term "perceptron" in MLPs may be a bit confusing since we don't really want only linear neurons in our network. Using MLPs, we want to learn complex functions to solve non-linear problems. Thus, our network is conventionally composed of one or multiple "hidden" layers that connect the input and output layer.

Google made headlines earlier this year when its AlphaGo AI defeated world champion Lee Se-Dol in the ancient board game Go. But a group of researchers want to push the boundaries and see how a computer might fare in a first-person shooter deathmatch. The 2016 Computational Intelligence and Games (CIG) Conference will host a competition to determine the best bot that's capable of winning a multiplayer round of Doom, while playing the way a human does. Some of the biggest names in tech are coming to TNW Conference in Amsterdam this May. That means that unlike enemy AI in video games, which have a complete overview of the level's map, locations of powerups and weapons, the bots will have to rely only on raw visual input that mimics what a human gamer sees when they play a game. The Visual AI Doom Competition will pit bots against each other in two tracks: the first one will see them playing a map known to their programmers with only rocket launchers and health boosts, while the other will feature an undisclosed map with all weapons and items available.

What happens when we teach a computer how to learn? Technologist Jeremy Howard shares some surprising new developments in the fast-moving field of deep learning, a technique that can give computers the ability to learn Chinese, or to recognize objects in photos, or to help think through a medical diagnosis. Get caught up on a field that will change the way the computers around you behave … sooner than you probably think. TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and much more.

IBM Watson project manager Leanne LeBlanc views analytics of healthcare data. Each person generates more than 1,100 terabytes of health-related data across his or her lifetime, the equivalent of more than 300 million books. What alarms Dr. Craig Thompson, president and CEO at Memorial Sloan-Kettering Cancer Center, is that 20% of cancer patients in the U.S. are misdiagnosed. Thompson made those remarks during an IBM investor briefing in February as he discussed the cancer hospital's partnership with IBM Watson. Three years ago, Memorial Sloan-Kettering and IBM Watson formed a partnership to develop Watson for Oncology, a cognitive computing system that can analyze large volumes of data including medical literature, patient health records, and clinical trials, to offer personalized, evidence-based treatment recommendations for cancer patients.

Artificial Intelligence has become a part of our collective consciousness and it's not going anywhere anytime soon. Think about your daily life. When and how are you connected to technology? Upon a little bit of reflection you'll realize how often technology influences and informs you. From Google search results, to personalized advertising, technology and data analysis is all around us.