Weekly Web Harvest for 2026-09-20

The research project IDOVIR strives for making results in the field of digital architectural reconstruction available in a comprehensible, permanent, and open-access form and to facilitate scientific discussion of the research results.

Source: Home – IDOVIR

This document outlines the intended behavior and values of MAI models, the models developed by Microsoft AI. It summarizes our approach to training and operating them, following a set of design principles we call Humanist AI. This document, and our approach more generally, is still under development so we are not using it to train our models today. Instead, we’re sharing it broadly for public consultation. We’ll take feedback, iterate on it, and publish a revised version toward the end of the year, which we’ll use to guide our model development in 2027 and beyond.

Source: Humanist AI Code of Conduct | Microsoft AI

h/t D’Arcy Norman

LrLexicon is a free, open-source Lightroom Classic plugin that automatically generates photo keywords using AI. Select photos, run one command, and get AI-suggested keywords covering subject, setting, mood, and photographic technique — reviewed and editable before anything is written to your catalog.

Source: jdpjamesp/LrLexicon: AI auto-keywording plugin for Lightroom Classic. Bring your own AI (OpenAI, Ollama, LM Studio, or any OpenAI-compatible API) to generate photo keywords, reviewed before writing to your catalog.

Here we introduce a genomic pretrained network with species tree and alignment representations (GPN-Star), which is a biologically grounded genomic language model featuring a phylogeny-aware architecture that leverages whole-genome alignments and species trees to model evolutionary relationships explicitly.

Source: Predicting genome-wide functional constraints with GPN-Star | Nature