Learn how a 3 GB SQLite database was replaced with a 10 MB finite state transducer binary, achieving 99.7% size reduction and faster lookups for static key-value datasets.
Microsoft demonstrates ConferencePulse, a live conference assistant built with a new composable AI stack for .NET, promising unified abstractions for AI models, vector databases, and agent orchestration.
Python developers face significant challenges in creating standalone apps, backing up SQLite databases, and installing on air-gapped systems. New language features aim to address some issues, but tooling gaps remain.
mssql-python now supports Apache Arrow, enabling zero-copy data transfer to Polars, Pandas, and DuckDB, boosting speed and memory efficiency.
A step-by-step tutorial for non-coding engineers to leverage AI via the 5-layer diagonal-axis framework, turning trivial tech into cross-industry tools.
Explore how ConferencePulse uses .NET's composable AI stack—including Microsoft.Extensions.AI, VectorData, and the Agent Framework—to build a live conference app with polls, RAG Q&A, and summaries.
Discover the 7 essential .NET composable AI components used to build ConferencePulse, an interactive conference app with live polls, RAG Q&A, and multi-agent summaries.
Explore how scenario modelling, calibrated uncertainty, and historical error provide more honest insights for English local elections than traditional forecasting.
A real-world data workflow rewrite from Pandas to Polars achieved a 300x speedup (61s to 0.20s), driven by lazy execution, multi-threading, and expression-based transformations. Key mental model shift from eager to lazy evaluation.
Explore scenario modelling for English local elections, where calibrated uncertainty and historical error analysis reveal that models are most useful when they refuse to make a single forecast.
A real Pandas workflow running in 61 seconds was rewritten in Polars, achieving 0.2 seconds. This article explores Polars’ performance advantages, the lazy evaluation mental model, and practical tips for adoption.
Discover how .NET's modular AI stack powers ConferencePulse—a Blazor Server app for live polls, Q&A, and session summaries using composable building blocks.
Microsoft demonstrated ConferencePulse, a fully functional AI-powered conference app built on its new composable .NET AI stack, featuring live polls, RAG Q&A, insights, and summaries.
Explores scenario modelling for English local elections, emphasizing calibrated uncertainty, historical error patterns, and the value of models that refuse to forecast when uncertainty exceeds shocks.
A real data workflow rewritten from pandas to Polars reduced execution time from 61 seconds to 0.20 seconds, highlighting the power of lazy evaluation and efficient memory usage.
A step-by-step guide to creating scenario models for English local elections that embrace uncertainty, using historical error calibration and shock simulations.
10 insights into scenario modeling for English local elections: embracing uncertainty, historical error, refusal to forecast, and tactical voting. Prepare for surprises.
A comprehensive tutorial on single-cell RNA-seq analysis with Scanpy using PBMC-3k data: QC, doublet removal, normalization, clustering, annotation, trajectory inference, and custom scoring.
Explore the challenges of creating standalone Python apps, properly backing up SQLite, and installing Python offline, plus new features in Python 3.15 like frozendict and sentinel values.
Scenario modelling for English local elections reveals that calibrated uncertainty and historical error matter more than shocks. This listicle covers 7 insights, including why models sometimes refuse to forecast.