They say that a society thrives only when older generations plant the seeds of trees whose shade they may never enjoy. Through university partnerships and outreach, 4,725 students from 108 nations had completed the program as of year-end 2018. In this post, I talk about why we run the Seeds for the Future program. The current acute shortage of tech talent, especially data scientists and AI experts, is exacerbated by the barriers that prevent many women from fully contributing to the global economy. Together, they are dual bottlenecks hindering ICT development.

Recursive self-improving (RSI) systems have been dreamed of since the early days of computer science and artificial intelligence. However, many existing studies on RSI systems remain philosophical, and lacks clear formulation and results. In this paper, we provide a formal definition for one class of RSI systems, and then demonstrate the existence of computable and efficient RSI systems on a restricted version. We use simulation to empirically show that we achieve logarithmic runtime complexity with respect to the size of the search space, and these results suggest it is possible to achieve an efficient recursive self-improvement.