Abstract: Disclosed embodiments relate to instructions for fused multiply-add (FMA) operations with variable-precision inputs. In one example, a processor to execute an asymmetric FMA instruction includes fetch circuitry to fetch an FMA instruction having fields to specify an opcode, a destination, and first and second source vectors having first and second widths, respectively, decode circuitry to decode the fetched FMA instruction, and a single instruction multiple data (SIMD) execution circuit to process as many elements of the second source vector as fit into an SIMD lane width by multiplying each element by a corresponding element of the first source vector, and accumulating a resulting product with previous contents of the destination, wherein the SIMD lane width is one of 16 bits, 32 bits, and 64 bits, the first width is one of 4 bits and 8 bits, and the second width is one of 1 bit, 2 bits, and 4 bits.

Abstract: Evaluating the engagement and attentiveness of persons in a group by preparing a streaming video of the group, extracting faces of the persons in the group, aligning the extracted faces, assigning an identity to each of the faces, recognizing the emotional state of each face by a temporal emotion recognition module, and estimating the attentiveness of each person based on the recognized emotional state of each face of each person. The estimated attentiveness may also include recognizing the gaze of each person.

Abstract: Evaluating the engagement and attentiveness of persons in a group by preparing a streaming video of the group, extracting faces of the persons in the group, aligning the extracted faces, assigning an identity to each of the faces, recognizing the emotional state of each face by a temporal emotion recognition module, and estimating the attentiveness of each person based on the recognized emotional state of each face of each person. The estimated attentiveness may also include recognizing the gaze of each person.

Abstract: A computer implemented approach which simplifies the task of a user in using commodity pricing information in making decisions on purchasing of items. The user is provided a suitable interface using which the constituent commodities and the required respective quantities for each item may be specified. The digital processing system then automatically (without requiring manual entry by the user) retrieves the current prices of the commodities, and provides various types of information which simplifies the purchasing decisions. According to one aspect, alerts are provided when the prices of a commodity does not satisfy pre-specified limits or when the aggregate cost of commodities required for one unit of the item does not satisfy a pre-specified limit. Similarly, information is presented which simplifies hedging decisions and buy or make decisions.