A senior engineer’s perspective on building highly available distributed systems Table of Contents Introduction: Why Dynamo Changed Everything The CAP Theorem Trade-off Core Architecture Components Consistent Hashing for Partitioning Replication Strategy (N, R, W) Vector Clocks for Versioning Sloppy Quorum and Hinted Handoff Conflict Resolution: The Shopping Cart Problem Read and Write Flow Merkle Trees for Anti-Entropy Membership and Failure Detection Performance Characteristics: Real Numbers Partitioning Strategy Evolution Comparing Dynamo to Modern Systems What Dynamo Does NOT Give […]

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A simple, experience-driven breakdown of context windows, tokens, retrieval, hallucination, and why AI behaves the way it does. THE PROBLEM Three weeks into learning machine learning, I ran into a problem. Not with models or math, but with my notes. I had taken the time to write things in my own words, build analogies that made sense to me, and note down questions I wanted to revisit. The problem wasn’t quality. It was structure. My notes were scattered across […]

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arXiv:2602.11232v1 Announce Type: new Abstract: Many cloud infrastructure organizations increasingly rely on third-party eBPF-based network functions for use cases like security, observability, and load balancing, so that not everyone requires a team of highly skilled eBPF experts. However, the network functions from third parties (e.g., F5, Palo Alto) are available in bytecode format to cloud operators, giving little or no understanding of their functional correctness and interaction with other network functions in a chain. Also, eBPF developers want […]

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arXiv:2603.04223v1 Announce Type: new Abstract: We introduce Latent Space Distribution Matching (LSDM), a novel framework for semi-supervised generative modeling of conditional distributions. LSDM operates in two stages: (i) learning a low-dimensional latent space from both paired and unpaired data, and (ii) performing joint distribution matching in this space via the 1-Wasserstein distance, using only paired data. This two-step approach minimizes an upper bound on the 1-Wasserstein distance between joint distributions, reducing reliance on scarce paired samples while enabling […]

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arXiv:2601.09719v1 Announce Type: new Abstract: Pre-Layer Normalization (Pre-LN) is the de facto choice for large language models (LLMs) and is crucial for stable pretraining and effective transfer learning. However, Pre-LN is inefficient due to repeated statistical calculations and suffers from the curse of depth. As layers grow, the magnitude and variance of the hidden state escalate, destabilizing training. Efficiency-oriented normalization-free methods such as Dynamic Tanh (DyT) improve speed but remain fragile at depth. To jointly address stability and […]

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I saw a post on X saying Changing a hyphen to an en-dash increases your PDF file size by ~10 bytes. My first thought was that it had something to do with hyphen being an ASCII character and an en-dash not. Changing a hyphen to an en-dash would make a UTF-8 encoded text file a couple bytes longer. (See why here.) Maybe adding one non-ASCII character could cause the file to include a glyph it didn’t before. I […]

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arXiv:2601.07325v2 Announce Type: replace Abstract: We introduce the $widetilde{rho}$-posterior, a modified version of the $rho$-posterior, obtained by replacing the supremum over competitor parameters with a softmax aggregation. This modification allows a PAC-Bayesian analysis of the $widetilde{rho}$-posterior. This yields finite-sample oracle inequalities with explicit convergence rates that inherit the key robustness properties of the original framework, in particular, graceful degradation under model misspecification and data contamination. Crucially, the PAC-Bayesian oracle inequalities extend to variational approximations of the $widetilde{rho}$-posterior, providing […]

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Modernization of enterprise technologies is no longer just about infrastructure improvement. It involves change across all levels-systems and processes, as well as people and culture. Many organizations continue to rely on legacy systems that once performed effectively but can no longer support increasing demands, growing data volumes, and evolving customer expectations. These systems are not only becoming more expensive to maintain, but they also lack scalability, and their security risks are increasing. The alternative is a shift toward […]

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