Think about the sheer volume of data we'll need to make the most ambitious new technologies possible. Simulations will use VR experiences and UHD video (4K and eventually 8K). Robotic Process Automation will produce detailed reports from thousands of sensors – about the status, location, orientation and environment of devices. Managers of autonomous fleets will quickly access huge amounts of near-real-time data, using AI and software to optimize their routes. These are enormous amounts of data – and it's all being both consumed and generated by things that move around a lot.

The prospect of self-driving cars is particularly concerning to people who make their living by driving, whether it's a taxi or working for Uber or Lyft. Companies such as Lyft have made no secret about being interesting in adding autonomous vehicles to their fleets. But where does this leave their human drivers? Lyft's product director Taggart Matthiesen told Recode that while the company is focusing on self-driving tech, they will always employ people as drivers. Matthiesen explains that the company already has an advisory board that is working on how human drivers will fit into a vision of a driverless fleet.

Amazon may use driverless cars to help expedite deliveries. Elizabeth Keatinge (@elizkeatinge) has more. SAN FRANCISCO -- Amazon has a team studying the ramifications of self-driving car technology on its business, although at present the online retailing giant does not have plans to build a fleet of autonomous delivery vehicles. The team consists of a dozen employees and was formed more than a year ago, according to a Wall Street Journalreport Monday citing individuals briefed on the matter. The group amounts to an in-house think tank charged with studying how a range of fast-paced developments in the self-driving field can be applied to its vast shipping needs.

This is another installment of Spare5's "Conversations in Machine Learning" blog series. Each week, our content human, Cassie, shares a summary of a recent conversation we had with a machine learning team and potential customer--what they're building, how they're handling training data today, etc. Read more about the series here. Lack of good, accurate training data for AI is such a problem and Spare5's Training Data as a Service (TDaaS) solution is such a…solution…that super impressive companies like the one I'm talking about today are not only taking our calls, but also eagerly reaching out to us themselves. I know that's NBD for large, well-established organizations, but for us it can almost seem laughable at times--we're a young company, we're relatively new in the AI space, and we're the type of people who giggle uncontrollably at that waving-bear gif. The market needs help, and though we're easily entertained, we're also quite smart and skilled--and we've developed a solution to help propel today's biggest, boldest AI developments forward.