Data science

TruthTable: A Verifiable Query Engine

TruthTable: A Verifiable Query Engine

TruthTable is a verifiable database engine that produces succinct cryptographic proofs for SQL query execution. It supports a wide range of SQL queries by leveraging query plans, polynomial encoding, and operator-specific PIOPs. It features a query planner with proof-specific optimizations and a novel batch compilation engine (ARCPOP). Benchmarks on TPC-H show average proving times of 55 seconds, verification times of 32 milliseconds, and proof sizes of 24kB, significantly outperforming prior academic and industrial systems in speed and expressiveness.

The 12 KB File That Replaces Weeks of Training (with Tristan Handy)

The 12 KB File That Replaces Weeks of Training (with Tristan Handy)

Tristan Handy, founder and CEO of dbt Labs, details the evolution of analytics engineering from a 2016 study into a tool used by over 100,000 data teams. He explains his decision to use SQL over Spark for accessibility, the concept of "progressive complexity," and how dbt projects transform raw data into modeled tables using a Directed Acyclic Graph. Handy elaborates on the critical role of the semantic layer in ensuring consistent metric definitions for both human users and AI agents, especially in large organizations. He introduces the dbt Fusion Engine, aiming to bring type safety and universal SQL understanding, and discusses how 12-kilobyte skill files can revolutionize large-scale dbt migrations, reducing them from years to weeks by enabling AI agents to absorb vast amounts of expert knowledge.

Binomial Flows: Denoising and flow matching for discrete ordinal data

Binomial Flows: Denoising and flow matching for discrete ordinal data

Shenfeld presents binomial flows, a discrete analogue of Tweedie-based diffusion for ordinal, non-negative integer data. The method pairs binomial thinning for noising with a Poisson-type continuous-time Markov chain whose rate is expressed through a learned denoiser, enabling training with MSE, sampling, and exact likelihood estimation. Results include the best reported CIFAR-10 FID among ordinal discrete diffusion models, obtained by adapting the EDM framework.

See How Customers Actually Use Your Product

See How Customers Actually Use Your Product

Founders often make the mistake of relying on aggregate user metrics like DAU, which obscure how individuals truly use a product. This video introduces the 'dot plot,' a powerful visualization tool mapping individual user activity over time. It reveals hidden patterns, helps identify retention issues, and pinpoints features driving engagement, offering deeper insights than traditional metrics and proving invaluable for both B2C and B2B product health analysis.

Artie: Real Time Data Streaming For The AI Age

Artie: Real Time Data Streaming For The AI Age

Jacqueline Cheong and Robin Tang, founders of real-time data streaming platform Artie, discuss their journey from identifying the critical need for fresh data at companies like OpenDoor to building a production-ready solution, acquiring their first major customer Substack via a cold email, and navigating the complex technical challenges of real-time data processing at scale.

Building Planetary-Scale Data Systems with Venice • Felix GV & Olimpiu Pop • GOTO 2026

Building Planetary-Scale Data Systems with Venice • Felix GV & Olimpiu Pop • GOTO 2026

Félix GV, an architect of LinkedIn's Venice database, discusses its unbundled, planetary-scale architecture. He covers how components like Kafka and RocksDB form independent distributed systems, details their rigorous chaos engineering practices, explains CAP theorem trade-offs in multi-region deployments, and explores the experimental integration of DuckDB for SQL-based analytics.