A method and system for teaching an object of a deictic reference to a machine. A processor of the machine teaches the object of the deictic reference to the machine which results in the machine learning the object. The teaching includes: the processor finds an item in a region indicated by a physical pointing gesture, by the user, that points to the object; the processor shines a laser light on the item and in response, the processor receives a negative spoken indication from the user that the item shined on by the laser light is not the object; in response to the negative spoken indication from the user, the processor interacts with the user in an iterative procedure wherein the machine learns the object in a final iteration of the procedure. The processor stores the learned object in a storage repository.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for teaching an object of a deictic reference to a machine, said method comprising: a processor of the machine teaching the object of the deictic reference to the machine which results in the machine learning the object, said teaching comprising: said processor finding an item in a region indicated by a physical pointing gesture, by the user, that points to the object; in response to a determination that a reference describing the item is not in a dictionary of the machine, said processor shining a laser light on the item and in response, said processor receiving a negative spoken indication from the user that the item shined on by the laser light is not the object; in response to the negative spoken indication from the user, said processor interacting with the user in an iterative procedure, wherein during each iteration of the procedure, said processor shining the laser light on a portion of the item or on something thing that is physically coupled to the item and in response, said processor receiving from the user (i) a first spoken indication that the laser light has shined closer to the object than in the previous iteration, (ii) a second spoken indication that the laser light has shined further from the object than in the previous iteration, or (iii) a third spoken indication that the laser light has shined on the object, wherein the machine learns the object in a final iteration of the procedure in which the processor receives the third spoken indication from the user; and said processor storing the learned object in a storage repository. 2. The method of claim 1, said method further comprising: said processor executing a task with respect to the learned object. 3. The method of claim 1, wherein the machine is an automobile or a robot. 4. The method of claim 1, said method further comprising: after the machine has learned the object, said machine moving to the item and picking up the object to develop: a larger database of the object, a measure of a weight of the object, and surface friction presented by the object. 5. The method of claim 1, said method further comprising: after the machine has learned the object, said machine speaking words communicating that the machine understands the name of the object. 6. The method of claim 1, wherein the machine includes a conversational system. 7. The method of claim 1, said method further comprising: integrating computer-readable code into the machine, said code being executed by the processor to implement said finding the item, shining a laser light on the item, said receiving the negative spoken indication from the user, and said interacting with the user in the iterative procedure. 8. A computer program product, comprising a computer readable storage device having computer readable code stored therein, said code containing instructions executable by a processor to implement a method for teaching an object of a deictic reference to a machine, said machine comprising the processor and the storage device, said method comprising: said processor teaching the object of the deictic reference to the machine which results in the machine learning the object, said teaching comprising: said processor finding an item in a region indicated by a physical pointing gesture, by the user, that points to the object; in response to a determination that a reference describing the item is not in a dictionary of the machine, said processor shining a laser light on the item and in response, said processor receiving a negative spoken indication from the user that the item shined on by the laser light is not the object; in response to the negative spoken indication from the user, said processor interacting with the user in an iterative procedure, wherein during each iteration of the procedure, said processor shining the laser light on a portion of the item or on something thing that is physically coupled to the item and in response, said processor receiving from the user (i) a first spoken indication that the laser light has shined closer to the object than in the previous iteration, (ii) a second spoken indication that the laser light has shined further from the object than in the previous iteration, or (iii) a third spoken indication that the laser light has shined on the object, wherein the machine learns the object in a final iteration of the procedure in which the processor receives the third spoken indication from the user; and said processor storing the learned object in a storage repository. 9. The computer program product of claim 8, said method further comprising: said processor executing a task with respect to the learned object. 10. The computer program product of claim 8, wherein the machine is an automobile or a robot. 11. The computer program product of claim 8, said method further comprising: after the machine has learned the object, said machine moving to the item and picking up the object to develop: a larger database of the object, a measure of a weight of the object, and surface friction presented by the object. 12. The computer program product of claim 8, said method further comprising: after the machine has learned the object, said machine speaking words communicating that the machine understands the name of the object. 13. The computer program product of claim 8, wherein the machine includes a conversational system. 14. A system comprising: a machine comprising a processor, a memory coupled to the processor, and computer readable program code configured to be executed by the processor via the memory to implement a method for teaching an object of a deictic reference to the machine, said method comprising: said processor teaching the object of the deictic reference to the machine which results in the machine learning the object, said teaching comprising: said processor finding an item in a region indicated by a physical pointing gesture, by the user, that points to the object; in response to a determination that a reference describing the item is not in a dictionary of the machine, said processor shining a laser light on the item and in response, said processor receiving a negative spoken indication from the user that the item shined on by the laser light is not the object; in response to the negative spoken indication from the user, said processor interacting with the user in an iterative procedure, wherein during each iteration of the procedure, said processor shining the laser light on a portion of the item or on something thing that is physically coupled to the item and in response, said processor receiving from the user (i) a first spoken indication that the laser light has shined closer to the object than in the previous iteration, (ii) a second spoken indication that the laser light has shined further from the object than in the previous iteration, or (iii) a third spoken indication that the laser light has shined on the object, wherein the machine learns the object in a final iteration of the procedure in which the processor receives the third spoken indication from the user; and said processor storing the learned object in a storage repository 15. The system of claim 14, said method further comprising: said processor executing a task with respect to the learned object. 16. The system of claim 14, wherein the machine is an automobile or a robot. 17. The system of claim 14, said method further comprising: after the machine has learned the object, said machine moving to the item and picking up the object to develop: a larger database of the object, a measure of a weight of the object, and surface friction presented by the object. 18. The system of claim 14, said method further comprising: after the machine has learned the object, said machine speaking words communicating that the machine understands the name of the object. 19. The system of claim 14, wherein the machine includes a conversational system.