Abstract: A wear member comprising: an upper leg having a ground engaging surface on an outer side thereof and a mounting surface on an inner side thereof, and a lower leg spaced apart from the upper leg and also having a ground engaging surface on an outer side thereof and a mounting surface on an inner side thereof, the mounting surfaces defining a mounting cavity therebetween and the legs meeting at a front portion, the upper leg defining (i) a lock aperture therein, (ii) a rear edge, and (iii) a lifting feature located adjacent to and between the lock aperture and the rear edge; the lifting feature defining (a) a front surface lower than the upper leg ground engaging surface and being inclined relative thereto, (b) a lower support surface opposite the front surface, and (c) a rear engaging surface extending between the front surface and the lower support surface and being recessed relative to the rear edge; wherein the front surface, lower support surface, and rear engaging surface provide a narrowed portion around

Abstract: Recommendations are generated for users by identifying items held by the users defined by a shallow representation and attributes; defining the items based on a deep representation derived from attributes; generating a deep holding matrix identifying the items held by the users based on deep representations; generating a shallow holding matrix identifying the items held by the users based on shallow representations; generating a similarity score matrix between the deep representations; decomposing the shallow holding matrix into a user latent representation and a product feature latent representation; concatenating the product feature latent representation and product information and pass to a first neural network; concatenating the user latent representation and user information and pass to a second neural network; performing a dot product matrix multiplication on the output of the first neural and the output of the second neural network to generate, for every user and every product, a probability.