Advances in technology are setting the stage for financial institutions to explore use cases that take advantage of a consumer's most natural communication method ... the voice. It wasn't so long ago that we were amazed that we interact with an IVR to solve basic customer service issues or that we could type on a piece of glass to communicate with our mobile device. The problem was that most IVR systems didn't learn about our needs over time and typing and gesturing is really not the most efficient way to interact with a computer or device for the vastly most common uses most people have. Even for the most basic routines require far more physical and mental effort than what should be required in today's digital age. What if each time you needed to reach out to your bank (or any other business) the organization remembered your entire history of interactions (needs, behaviors, preferences, transaction patterns and timing, etc.), allowing it to have an intelligent'conversation' without going over often repeated steps?

I am excited to be here today for what is a Reddit first. This will be the first AMA in history to feature an Artificial "Hive Mind" answering your questions. You might have heard about me because I've been challenged by reporters to make lots of predictions. For example, Newsweek challenged me to predict the Oscars (link) and I was 76% accurate, which beat the vast majority of professional movie critics. I'm a Swarm Intelligence that links together lots of people into a real-time system – a brain of brains – that consistently outperforms the individuals who make me up.

In a wide-ranging interview Wednesday night, Tesla CEO Elon Musk said that he expects Apple to have a car available to the public by 2020 -- and there's only one company whose use of artificial intelligence potentially worries him. Musk's comments came during the Code Conference in Rancho Palo Verdes, California. Even though he thinks Apple started late on building a car, "Ithink they'll make a good car, and will be successful," he said. "Google's done a great job, but they're not a car company," he said. Musk also elucidated comments he's made in the past about the potential dangers of artificial intelligence.

REUTERS/Rashid Umar AbbasiElon Musk, Chairman of SolarCity and CEO of Tesla Motors, speaks at SolarCity's Inside Energy Summit in Manhattan, New York October 2, 2015. Musk believes that as AI continues to advance, humans will be left behind, and that even in the most banal situation, we'll be treated like pets by artificial intelligence, as he explained on stage at Vox Media's Code Conference in Southern California. Enter something called "neural lace," a technology concept that Musk finds "quite important" that he thinks companies need to be working on. Neural lace is essentially a wireless brain-computer system. I think one of the solutions that seems maybe the best is to add an AI layer," he said.

RANCHO PALOS VERDES, Calif. - Tesla Motors CEO Elon Musk doesn't see Google as a potential competitor to his firm. Instead, he's focused on Apple. Apple, maker of the iconic iPhone and Macintosh computers, "will be a direct competitor," Musk said. He expects Apple to be in production with cars by 2020, but thinks they've waited too long. "They should have started production sooner. Speaking to the Code tech conference here, the South African-born, charismatic CEO leads a company that sells electric cars, with a recent software update that includes partial self-driving features. Tesla cars start at around 80,000, but recently announced a 2017 Model 3 that will start at 35,000. The company has reaped about 400,000 orders for the car that include 1,000 deposits. Internet giant Google is testing self-driving cars, but Musk doesn't see Google getting into the car business. "Google is not a car company," he said. Apple, on the other hand, hasn't publicly announced its intentions to get into the car business, but has been hiring engineers, and Musk clearly expects Apple to join the fray. Musk was asked if the new Model 3 will be a self-driving car. He demurred, saying he would have an event in the fall to reveal the answer. Asked for clarifications, he simply said, "We're going to do the obvious thing." Musk, who is also CEO of rocket maker Space Exploration Technologies, or SpaceX, also talked about his passion of exploring Mars and space. Missions to Mars will start in 2018, he said, and he predicted that trips for humans ("if things go according to plan") will begin in 2024--for arrival in 2025. Musk, who has not flown into space, has said he wanted to die on Mars, but not on a landing. "If you had to choose a place to die, Mars is probably not a bad choice.

Below is a quick overview of samples that demonstrate how to use the machine learning capabilities in Spark on IBM Bluemix. David Taieb posted the slides of his hands-on session how to predict flight delays based on historical data and whether predictions. The sample uses the machine learning algorithms Logistic Regression, Random Forrest, Decision Tree and Naive Bayes. When playing rock-paper-scissor everyone has his/her own strategies, e.g. The sample recognizes these patterns and leverages the patterns and history data to predict moves (via the FPGrowth algorithm).

Jobs have become a core Brexit issue. Would leaving the EU be good or bad for job creation? Why are migrants taking so many of the new jobs being created in the UK, and what are the implications for the freedom of movement for labour? But the changing nature of work is an issue that runs throughout the developed world, far beyond the UK and Europe. We see this through the prism of our relationship with Europe, for the UK and Germany have become the two strongest job markets in this time zone and have accordingly been sucking in labour from elsewhere.

You may not know it, but machine learning is all around you. When you type a query into a search engine, it's how the engine figures out which results to show you–and which ads. When you read your email, you don't see most of the spam because machine learning has filtered it out. Go to Amazon to buy a book or Netflix to watch a video, and a machine-learning system helpfully recommends some others you might like. Facebook uses machine learning to decide which updates to show you, and Twitter does the same for tweets.

"Content moderation" might sound like a commonplace academic or editorial task, but the reality is far darker. Internationally, there are more than 100,000 people, many in the Philippines but also in the U.S., whose job each day is to scan online content to screen for obscene, hateful, threatening, abusive, or otherwise disgusting content, according to Wired. The toll this work takes on moderators can be likened to post-traumatic stress disorder, leaving emotional and psychological scars that can remain for life if untreated. That's a grim reality seldom publicized in the rush to have everyone engaged online at all times. Twitter, Facebook, Google, Netflix, YouTube, and other companies may not publicize content moderation issues, but that doesn't mean the companies aren't working hard to stop the further harm caused to those who screen visual and written content.