If network effects are one of the most important concepts for software-based businesses, then that may be especially true of data network effects -- a network effect that results from data. Particularly given the prevalence of machine learning and deep learning in startups today. But simply having a huge corpus of data does not a network effect make! So how can startups ensure they don't get a lot of data exhaust but get insight out of and add value to that data and the network? How can they make sure that the (arguably inevitable) data aspect of their business isn't just a sideshow or accident? How should founders strike the balance between not overbuilding/ building a data team vs. having enough data for those data scientists to work with in the first place? And finally, what are the ethical considerations of all this? The a16z general partners most focused on bio and fintech -- Vijay Pande and Alex Rampell -- join this episode of the a16z Podcast to share their observations and advice on all things data network effects.

The mobile world has fallen hard for VR, says Benedict Evans. But will virtual reality mean real profit for hardware makers? Evans offers his observations on VR and more gleaned from the largest gathering of the mobile industry, Mobile World Congress. The value in mobile keeps shifting, Evans says, from hardware to software, and the platforms on which that software runs. But the players and the business models are far from set when practically anyone can get into handset business. The forces shaping the future of mobile -- from VR to Algerian handset makers just crushing it -- on this segment of the podcast.