On first hearing, "machine learning" and "Artificial Intelligence" sound like technologies that will replace people. Computers will find people and sell them stuff they want, so who needs humans in marketing? Well, it turns out that you do. Computers can do the scut work of counting, but only humans can truly say what counts. Marketers are not going to be replaced by automation, but they can make best use of it so long as they know what it can do and can't do, just like any other tool.

Experts discuss a medical ecosystem where people, policies and technology interconnect, allowing doctors to administer precise treatment to one patient -- the N of 1 -- and then deliver it to everyone. The old "take two aspirin and call me in the morning" cure is antithetical to today's precision medicine approach to healthcare, which zeroes in on an individual's unique genetic makeup, environment and lifestyle to determine an exacting treatment. Traditional healthcare is broadly based on cohort studies that compare risk factors and outcomes for a large set of patients who share similar symptoms. Cohort studies are more credible when the "N" -- the number of patients included in the study -- is very large. That's diametrically at odds with the goal of precision medicine, which aims to find a treatment plan tailored for a particular person: "The N of 1."

"AI is destined to be the perfect tool to fuel organizations' sales efforts and power sales teams with genuinely intelligent tools to more effectively organize their work and sell more." This quote is from an article Jill wrote on LinkedIn titled "#AI Will Reinvent Sales…and Sales Professionals" and sums up nicely what we think about AI in sales too. Technology is fully embedded in today's sales organizations and it goes beyond just a database of customer or prospect information. Sales software does everything from schedule meetings and write emails to identifying sales behaviors that close more deals. That's how artificial intelligence (AI) is changing the sales landscape today. Nudge is a Modern Sales Platform that uses AI to provide sales teams with actionable insights on their target customers.

Are you interested in artificial intelligence, neuromorphic computing, or neuromemristive processors? Do you want to learn about the future of intelligent machine technology? Then make sure to read about our technology page, the articles on our blog and join the discussions on our social media pages such as reddit.com/knowm. We welcome you to explore the site and contact us if you have any questions. Are you interested in building brains or other electric circuits with memristors?

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.

So you got into law school? Congratulations, it's time to start thinking like an engineer. Universities around the world are introducing classes that train students in the use of legal software, assisting with anything from contract creation to legal research. But are students simply training the algorithms that will take their jobs? It's increasingly clear automation won't only affect manufacturing.