🧮 How Markov Chains Compete with Tiny LLMs
A clever community experiment illustrating how classic probabilistic methods can echo neural language patterns — a reminder of the deep links between traditional and modern AI.
A Hacker News user experiments with a Markov chain text generator trained on a scientific paper and compares its results to small-scale language models like NanoGPT. The results show that even simple probabilistic models can reproduce surprising coherence and structure.
🔗 Read more 🔗
🔒 Full Data-at-Rest Encryption Arrives in DuckDB
A significant step for embedded analytics—DuckDB now combines enterprise-grade encryption with its signature simplicity and speed.
DuckDB 1.4 adds comprehensive data-at-rest encryption with AES-GCM and AES-CTR. The post details how headers, WAL logs, and temp files are secured while maintaining near-zero performance impact thanks to OpenSSL acceleration.
🔗 Read more 🔗
🎓 Students Push Back Against AI-Taught University Courses
A telling example of the tension between AI-driven efficiency and students’ demand for authentic human learning in higher education.
University of Staffordshire students criticized the use of AI-generated slides and lectures in a cybersecurity course, arguing it replaced genuine teaching. The school maintained that AI was used responsibly to support, not substitute, educators.
🔗 Read more 🔗
⚙️ Autocomp: An ADRS Framework for Optimizing Tensor Accelerator Code
🔗 Read more 🔗
📘 Freer Monads and Extensible Effects in Haskell
A cornerstone of modern functional programming that shaped how effect systems are designed in real-world Haskell libraries.
This influential paper by Oleg Kiselyov and Hiromi Ishii formalizes freer monads and extensible effects as a simpler and faster alternative to monad transformers in Haskell, improving both theoretical clarity and runtime efficiency.
🔗 Read more 🔗