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NNDial is an open source toolkit for building end-to-end trainable task-oriented dialogue models. It is released by Tsung-Hsien (Shawn) Wen from Cambridge Dialogue Systems Group under Apache License 2.0.

AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.

An agent that compiles git maintenance chores into reusable programs, then decides whether to replay them by running checks rather than by guessing the task looks familiar

  • agent-architecture
  • git-automation
  • llm-agents
  • program-synthesis

The Cold Disk Quick Response (CDQR) tool is a fast and easy to use forensic artifact parsing tool that works on disk images, mounted drives and extracted artifacts from Windows, Linux, MacOS, and Android devices

Evidence-based DSM ransomware recovery: preservation, RAM key recovery, copy decryption, and GitLab validation.

A Claude skill for directing, building and verifying code-rendered videos (HTML/Canvas → MP4): principles, gated workflow, QA scripts and evals.

Python's missing "algorave" module. Live code music with Python using MIDI, OSC and/or SuperCollider.

  • algorave
  • algorithmic-music
  • audio
  • improvisation

Translated🎬 AI Video Creation Workflow for AIGC creation | Use AI to make videos, pixel animations, and comic shorts | Storyboards, assets, music, templates, and runnable Python examples | Blender layered animation and 剪映 (Jianying, "CapCut") production methods

Pestinha é um pet virtual de desktop para Windows, com rede neural pulsada, emoções e personalidade que evolui com o usuário. Ele aprende com carinho e consequências, faz travessuras, brinca, trabalha e reage ao ambiente. Tudo funciona localmente, sem depender da nuvem.

TranslatedHelixHarness provides complete foundational capabilities for AI Coding engineering, and also supports different enterprises and teams in combining their own business knowledge, engineering standards, and R&D processes to continuously build and evolve their own dedicated Harness