Establishing the complexity of {\em Bounded Distance Decoding} for Reed-Solomon codes is a fundamental open problem in coding theory, explicitly asked by Guruswami and Vardy (IEEE Trans. Inf. Theory, 2005). The problem is motivated by the large current gap between the regime when it is NP-hard, and the regime when it is efficiently solvable (i.e., the Johnson radius). We show the first NP-hardness results for asymptotically smaller decoding radii than the maximum likelihood decoding radius of Guruswami and Vardy. Specifically, for Reed-Solomon codes of length N and dimension K = O ( N ) , we show that it is NP-hard to decode more than N − K − c log N log log N errors (with 0"> c 0 an absolute constant). Moreover, we show that the problem is NP-hard under quasipolynomial-time reductions for an error amount N-K- c\log{N}"> N − K − c log N (with 0"> c 0 an absolute constant). An alternative natural reformulation of the Bounded Distance Decoding problem for Reed-Solomon codes is as a {\em Polynomial Reconstruction} problem. In this view, our results show that it is NP-hard to decide whether there exists a degree K polynomial passing through K + c log N log log N points from a given set of points ( a 1 b 1 ) ( a 2 b 2 ) ( a N b N ) . Furthermore, it is NP-hard under quasipolynomial-time reductions to decide whether there is a degree K polynomial passing through K + c log N many points. These results follow from the NP-hardness of a generalization of the classical Subset Sum problem to higher moments, called {\em Moments Subset Sum}, which has been a known open problem, and which may be of independent interest. We further reveal a strong connection with the well-studied Prouhet-Tarry-Escott problem in Number Theory, which turns out to capture a main barrier in extending our techniques. We believe the Prouhet-Tarry-Escott problem deserves further study in the theoretical computer science community.