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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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NNUE in stockfish existed long time before we successfully implemented leela data in training. But it's not "inspiration". It's direct usage of leela data to produce a good net - but NNUE technology itself isn't inherited/inspired from leela. In fact latest nets use mix of different data, as you can see there - https://github.com/official-stockfish/Stockfish/pull/3856
The NNUE paper (original, English translation) came out in April 2018 and the first NNUE engine in May, so it's only few months after the A0 paper and I think it's too close to be an influence.
One major project that really sparked those discussions is the Maia neural networks. In summary, they trained neural networks to approximate human play at different skill levels. The same concept could potentially be applied to an individual player, assuming you have enough data about that individual player's games, and are able to quickly train an approximating network on that small handful of games.
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