Abstract: Provided are a method and an apparatus for providing an intelligent voice response at a voice assistant device. The method includes obtaining, by a voice assistant device, a voice input from a user, identifying non-speech input while obtaining the voice input, determining a correlation between the voice input and the non-speech input, and generating, based on the correlation, a response comprising an action related to the correlation or a suggestion related to the correlation.

Abstract: Provided is a video decoding method including: obtaining, from a bitstream, intra prediction mode information indicating an intra prediction mode of a current block; determining an interpolation filter set to be used in prediction of the current block, based on at least one of a size of the current block and the intra prediction mode indicated by the intra prediction mode information; determining a reference location to which a current sample of the current block refers according to the intra prediction mode; determining, in the interpolation filter set, an interpolation filter that corresponds to the reference location; determining a prediction value of the current sample, according to reference samples of the current block and the interpolation filter; and reconstructing the current block, based on the prediction value of the current sample.

Abstract: A source device for transmitting content to a sink device is provided. The source device may include an interface configured to perform high-bandwidth digital content protection (HDCP) authentication with the sink device, and a controller configured to determine an HDCP version supported by the sink device, convert the content so as to be encrypted in the HDCP version supported by the sink device in response to a determination that another HDCP version applied to the content is not supported by the sink device, encrypt the converted content in the HDCP version supported by the sink device, and control the interface to transmit the content to the sink device.

Abstract: A semiconductor chip stack includes first and second semiconductor chips. The first chip includes a first semiconductor substrate having an active surface and an inactive surface, a first insulating layer formed on the inactive surface, and first pads formed in the first insulating layer. The second semiconductor chip includes a second semiconductor substrate having an active surface and an inactive surface, a second insulating layer formed on the active surface, second pads formed in the second insulating layer, a polymer layer formed on the second insulating layer, UBM patterns buried in the polymer layer; and buried solders formed on the UBM patterns, respectively, and buried in the polymer layer. A lower surface of the buried solders is coplanar with that of the polymer layer, the buried solders contact the first pads, respectively, at a contact surface, and a cross-sectional area of the buried solders is greatest on the contact surface.

Abstract: A method of guiding a semiconductor manufacturing process includes receiving semiconductor manufacturing process data corresponding to a target semiconductor product, generating first semiconductor characteristic data corresponding to the semiconductor manufacturing process data by using a technology computer-aided design (TCAD) model trained through machine learning based on training data including TCAD simulation data, generating second semiconductor characteristic data corresponding to the semiconductor manufacturing process data by using a compact model generated based on information of measurement of at least one semiconductor characteristic of a first semiconductor product, generating, based on the first semiconductor characteristic data and the second semiconductor characteristic data, a plurality of process policies respectively corresponding to a plurality of strategic references, by using a plurality of strategy models; and providing a final process policy corresponding to the target semiconductor p