Abstract: A computer-implemented method for generating an output token sequence from an input token sequence. The method combines a look ahead tree search, such as a Monte Carlo tree search, with a sequence-to-sequence neural network system. The sequence-to-sequence neural network system has a policy output defining a next token probability distribution, and may include a value neural network providing a value output to evaluate a sequence. An initial partial output sequence is extended using the look ahead tree search guided by the policy output and, in implementations, the value output, of the sequence-to-sequence neural network system until a complete output sequence is obtained.

Abstract: A steel obtained via the metallurgy of a high purity pre-alloyed, agglomerated and densified powder, the steel has the following weight composition: Manganese <1%, silicon <1%, chromium 4.50-6.45%, molybdenum 4-6%, vanadium 6.10-6.5%, tungsten 18.20-18.70%, sulfur <0.0020%, phosphorus .ltoreq.0.030%, oxygen .ltoreq.100 ppm, cobalt 5-7%, nitrogen 0.050-0.080%, .ltoreq.aluminum 0.020%, carbon 1.80-1.95%, balance iron and the impurities which are characteristic of producing steel. The steel has for the most part a dispersion of vanadium MC type carbides.