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While machine learning and automation tools can simplify marketing processes, many of today's AI companies are also focused on how technology can improve customer experience. Sentient, for example, uses its "distributed AI platform," which runs on an incredible network of 2 million CPUs and 5,000 GPUs (the horsepower in a computer), to help retail clients optimize the customer experience. One of its two marketing products, Sentient Ascend, does A/B testing in real time at massive scale.

With the completion of our platform design and plans for an invitation-only alpha, we are excited to announce a token crowdsale for Lunyr on March 29, 2017 at 16:00 UTC. Lunyr is an Ethereum-based decentralized crowdsourced encyclopedia which rewards users with app tokens for peer-reviewing and contributing information. It aims to be the starting point of the internet for finding reliable, accurate information. The long-term vision is to develop a knowledge base API that developers can use to create next generation decentralized applications in Artificial Intelligence, Virtual Reality, Augmented Reality and more. The platform itself is designed to encourage the continuous growth of highly accurate and reliable content.

It's Monday morning, and you've just stepped into a driverless car with three colleagues to chair your first meeting of the day. You enter the office by placing your hand on a biometric scan, and, sensing your feelings as you start the working week, the lights and temperature are adjusted to improve your mood. Your virtual assistant orders you a coffee, which is brought to your desk by a co-bot working alongside you. This may sound like a sci-fi film, but these innovations could be coming to your workplace sooner than you think… Here, I explore the key technologies set to reshape the professional landscape by 2020, making the workplace of the future much more virtual, mobile, collaborative and flexible. Gartner predicts that 21 million new cars will be equipped with data connectivity this year alone.

DeepMind, the London-based artificial intelligence company owned by Alphabet Inc., claims it overcame a key limitation affecting one of the most promising machine learning technologies: the software's inability to remember. The breakthrough, described in a paper published Tuesday in the academic journal Proceedings of the National Academy of Sciences, may open the way for artificial intelligence systems to be more easily applied to multiple tasks, instead of being narrowly trained for one purpose. It should also improve the ability of AI systems to transfer knowledge between tasks and to master a sequence of linked steps. Neural networks, software which is loosely based on the structure of synapses in the human brain, are considered the best machine learning technique for language translation, image classification and image generation. But these networks suffer from a major flaw scientists call "catastrophic forgetting." They exist in a kind of perpetual present: every time the network is given new data, it overwrites what it has previously learned.

Bank phone trees are dreadful experiences, so many banks are turning to chatbots in the hope to spruce up the experience. Take Capital One's chatbot text message "Eno" ("One" backwards), which allows customers to text to get balance, transaction history and pay bills. Customers can even communicate with emojis -- a "thumbs up" means to confirm and a "money bag" will prompt Eno to list a customer's account balance. Capital One's approach to Eno may offer some clues why traditionally risk-averse banks are just taking baby steps. Capital One is only rolling out the product as a pilot for the time being, and the bank is careful to manage future expectations.

When DeepMind burst into prominent view in 2014 it taught its machine learning systems how to play Atari games. The system could learn to defeat the games, and score higher than humans, but not remember how it had done so. For each of the Atari games, a separate neural network had to be created. The same system could not be used to play Space Invaders and Breakout without the information for both being given to the artificial intelligence at the same time. Now, a team of DeepMind and Imperial College London researchers have created an algorithm that allows its neural networks to learn, retain the information, and use it again.

Nvidia has staked its growth in the datacenter on machine learning. Over the past few years, the company has rolled out features in its GPUs aimed neural networks and related processing, notably with the "Pascal" generation GPUs with features explicitly designed for the space, such as 16-bit half precision math. The company is preparing its upcoming "Volta" GPU architecture, which promises to offer significant gains in capabilities. More details on the Volta chip are expected at Nvidia's annual conference in May. CEO Jen-Hsun Huang late last year spoke to The Next Platform about what he called the upcoming "hyper-Moore's Law" era in HPC and supercomputers that will drive such emerging technologies as AI and deep learning and in which GPUs will play an increasingly central role.

Venture capital investments in artificial intelligence (AI), one of the biggest technological trends these days, are booming. The year 2016 saw almost ten times more funds invested in the space than 2012 did. Virtual and augmented reality (AR/VR), sometimes associated with the creative side of AI, also became a hot topic: More than $1.8 billion was invested in AR/VR, compared with just $86 million in 2012. Applying AI to solve tasks normally considered creative has historical precedent. For example, procedural generation has been used to draw textures, produce 3D models, and automatically generate large amounts of content in video games since the 1980s.

Intel has announced that it plans to acquire the autonomous car hardware firm Mobileye for a cool $15 billion. It's a weighty sum, but the purchase gives Intel cutting-edge machine-learning technology that lies at the center of the nascent autonomous car industry. The buyout of Mobileye, one of our 50 Smartest Companies of 2016, is the second largest ever made by Intel. It's also by far the largest autonomous car acquisition to date, and another sign that the self-driving vehicle sector looks set to explode in the coming years. Many car manufacturers already use Mobileye's hardware to power their autonomous systems, giving the company a position of power throughout the industry.