This article was published as a part of the Data Science Blogathon. Many a time while driving, we need to adjust things like in-vehicle seat relaxation function, interior lighting, music, air-conditioning, fragrances, etc, manually while attempting to keep our eyes on the road. However, it is very inconvenient and sometimes it can potentially put the driver and the co-passengers at the risk. Furthermore, it becomes even more complex when a previous driver has different preferences for cabin temperature, audio playlist, and so on. In light of this, would not it be convenient if our vehicle's heating, ventilation, illumination, music, visor, and air conditioning (HVAC) system could learn our individual preferences, and automatically make these adjustments for us?

Tel Aviv-based Audioburst has been developing a search engine for audio news, which allows users to locate audio content within podcasts and other talk radio programs. Today, the company is capitalizing on its technology to launch personalized playlists that deliver custom news briefs that get better over time the more you use the product. The feature has been built using deep AI learning, the company says. The content itself is drawn from top podcasts and the radio stations in Audioburst's index, and will alert you to new information based on your chosen keywords and topics. To use the feature, you first sign up on the Audioburst website, then select from a set of interests or add your own.