The key technology in these services is of course speech recognition, whose accuracy and adaptability has been gradually increasing.  The least expensive, narrowly targeted systems (e.g., simple organizers) exploit strong expectations about user inputs to recognize, interpret and respond to those inputs; as such they resemble menu-driven systems. More versatile systems, such as car talkers that can handle routing, musical requests, searches for venues, etc., rely on more advanced dialogue management capabilities. These allow for topic switches and potentially for the attentional state of the user (e.g., delaying answering a driver's question if the driver needs to attend to a turn). The greatest current “buzz” surrounds advanced voice-based assistants, notably iPhone's Siri (followed by Android's Iris, True Knowledge's Evi, Google Now, and others). While previous voice control and dictation systems, like Android's Vlingo, featured many of the same functionalities, Siri adds personality and improved dialogue handling and service integration—users feel that they are interacting with a lively synthetic character rather than an app. Besides Nuance SR technology, Siri incorporates complex techniques that were to some extent pushed forward by the Calo (Cognitive Assistant that Learns and Organizes) project carried out by SRI International and multiple universities from 2003–2008 (Ambite et al. 2006; CALO [see Other Internet Resources]).  These techniques include aspects of NLU, ML, goal-directed and uncertain inference, ontologies, planning, and service delegation. But while delegation to web services, including Wolfram|Alpha QA, or chatbot technology provides considerable robustness, and there is significant reasoning about schedules, purchasing and other targeted services, general understanding is still very shallow, as users soon discover. Anecdotal examples of serious misunderstandings are “Call me an ambulance” eliciting the response “From now on I will call you ‘an ambulance’”. However, the strong interest and demand in the user community generated by these early (somewhat) intelligent, quite versatile assistants is likely to intensify and accelerate research towards ever more life-like virtual agents, with ever more understanding and common sense.