Abstract: Systems and methods for preference and similarity learning arc disclosed. The systems and methods improve efficiency for both searching datasets and embedding objects within the datasets. The systems and methods for preference embedding include identifying paired comparisons closest to a user's true preference point. The processes include removing obvious paired comparisons and/or ambiguous paired comparisons from subsequent queries The systems and methods for similarity learning include providing larger rank orderings of tuples to increase the context of the information in a dataset In each embodiment, the systems and methods can embed user responses in a Euclidean space such that distances between objects are indicative of user preference or similarity.

Abstract: A forklift apparatus includes a base that moves in a generally horizontal direction. The base carries a mast that includes a lower section and an upper section. The upper section pivots relative to the lower section between a first storage orientation and a second operating orientation. In the second operating orientation, the upper section forms an upward continuation of the lower section. The mast carries a lifting structure that can selectively engage an object. A drive structure moves the lifting structure in a generally vertical direction when the upper section is in the second operating orientation.

Abstract: A forklift apparatus includes a base that moves in a generally horizontal direction. The base carries a mast that includes a lower section and an upper section. The upper section pivots relative to the lower section between a first storage orientation and a second operating orientation. In the second operating orientation, the upper section forms an upward continuation of the lower section. The mast carries a lifting structure that can selectively engage an object. A drive structure moves the lifting structure in a generally vertical direction when the upper section is in the second operating orientation.