<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>dzdt</author><text>I think the alphago program is getting similar crazy scale burn-in access to the gpu computing that google will soon offer in its cloud.  Recall alphago was the first program to beat a professional in a tournament setting.  They published in nature.  The emphasis was on their deep learning approach, but the technical details were pretty impressive.  Alphago beat Fan Hui, a 2 dan professional, using a 1202 cpu&amp;#x2F;776 gpu diatributed system.  They don&amp;#x27;t give hardware details, but my back-of-the-envelope estimate based on recent hardware is they were at around the petaflop calculation rate.  In the nature paper they examine how the program&amp;#x27;s ELO rating varies with computation power; it looks like to reach world champion level they need at least an order of magnitude more computation.  They challenged a player at that level (Lee Sedol) for a series in March and express a quiet confidence in winning.  On their blog they give google cloud credit for supplying the compute power, but google cloud doesn&amp;#x27;t yet have gpu units available publicly.  I am thinking alphago is getting to do burn-in on a massive gpu cloud computing center.  Look for public availability shortly after the Sedol match!</text><parent_chain></parent_chain></comment><story><title>History of massive-scale sorting experiments at Google</title><url>https://cloud.google.com/blog/big-data/2016/02/history-of-massive-scale-sorting-experiments-at-google</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>seanp2k2</author><text>I&amp;#x27;m sure they&amp;#x27;re asking about this in interviews now. My experience with Google interviews was that the interviewers were very keen on proving that they knew more theoretical CS than I did vs talking about what the actual work would require or entail.</text><parent_chain></parent_chain></comment><story><title>History of massive-scale sorting experiments at Google</title><url>https://cloud.google.com/blog/big-data/2016/02/history-of-massive-scale-sorting-experiments-at-google</url></story>