ASAP: Fast, Approximate, Graph Pattern Mining at Scale (Usenix) — we present A Swift Approximate Pattern-miner (ASAP), a system that enables both fast and scalable pattern mining. ASAP is motivated by one key observation: in many pattern mining tasks, it is often not necessary to output the exact answer […] an approximate count is good enough. (via Morning Paper)
Binci — tackling the same problem space as Docker Compose, but aimed at ephemeral containers rather than long-running ones (e.g., for test/CI systems).
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Metrics for Investors (Andrew Chen) — detailed take on the metrics through which investors view SaaS businesses.
How to Fit Large Neural Networks on the Edge — This blog explores a few techniques that can be used to fit neural networks in memory-constrained settings. Different techniques are used for the “training” and “inference” stages, and hence they are discussed separately.