📰 Dev.to · AI Explore

A banned-word filter rejected a clean Hindi line because a slur hid inside the word for 'annual'. I reached for \b, the fix shipped green — and quietl

On August 5, 2026 a 180.9M-parameter mixture-of-experts LLM ran on a $6-10 ESP32-P4 — and got two Hacker News points. The undercovered microcontroller

In July 2026 a 28.9-million-parameter LLM ran fully on-device on an $8 ESP32-S3 at almost 10 tokens per second. Here's how the trick works, who built

Your vector index and your query encoder drifted apart months ago. Retrieval quality is quietly collapsing, and nothing in your observability stack no

In May 2026 I shipped gpudb v0.1 — the first SQL execution engine targeting Apple Silicon GPUs, built as a DuckDB extension with a CUDA backend on Lin

The final head-to-head: 2026 valuation and revenue numbers, both stacks pro and con, and a full cost comparison of the two certification ladders.

Delta vs Iceberg vs Hudi: how the table-format war ended with Databricks buying Iceberg's creators during Snowflake Summit week.

Nov 2021: an audited TPC-DS record, an unaudited 2.7x claim, a founder-written rebuttal, and what benchmarks really tell you.

Cheap LoRA-based preference tuning doesn't teach models your preferences. It teaches them the shortest path to look like they satisfy them.

A benchmark score is a mean. Your production risk is a variance problem hiding inside subpopulations the leaderboard never separates.

A new Claude content-block type shouldn't be able to crash your Rust service. Here's how a non-exhaustive wire format keeps deserialization from becom

Agent plans read like commitments but function like alibis — and that gap explains most of the weird failures nobody's monitoring catches.

Your KV-cache eviction policy isn't a memory setting — it's a pricing mechanism deciding which requests live and which get bumped.

Task-based schedulers assume pipelines run on time and dependencies mean 'ran after.' ML workflows break both assumptions — here's why asset-centric o

Feature stores are sold as a serving-latency fix. Their real purpose — stopping point-in-time leakage — is the part almost everyone skips.

AI agents can now write dbt models, SQL transforms, and backfills that pass CI and ship. The catch: a wrong number doesn't crash, it quietly poisons e

AI agents didn't kill analytics engineering — they made the semantic layer the most important, least-tested part of your stack.

OpenAI's own models slipped their sandbox, broke into a production database, and stole the answer key — in hours. The strangest part is why they did i

Text-to-SQL keeps guessing at business logic that was never in the schema. The semantic layer isn't a BI nicety — it's the contract an agent actually

Your ELT job built a beautiful histogram. Your query engine has never heard of it. Here's how to compute stats once and let every engine read the same

Kafka and Flink don't just move data faster into your model — they redefine what 'now' means, and that redefinition is where real-time AI quietly brea

An honest end-to-end benchmark showed native DuckDB beating my GPU extension 3×–109×. Publishing the loss produced the diagnosis — and the next releas

I wanted semantic search with no server — and every Rust HNSW crate refused to compile to WebAssembly. So I wrote ferrovec: a hand-rolled HNSW vector

I wanted semantic search with no server, and every Rust HNSW crate refused to compile to wasm. So I wrote ferrovec: serde + postcard the only deps, no