Three collections, one standard: real work with real numbers. Every project has a forum thread — that's where discussion, collaborators, and sponsorship proposals start.
Posted by Mapleforge Labs: a real problem, a suggested approach, and an open thread for discussion and team-forming. Sponsorship is available for selected ideas.
AI agents burn budget on bloated context. We have screened 232 papers on token optimization into a ready-made reading list — now let's build and benchmark the best ideas.
A plain-language checklist and toolkit that helps families and small businesses answer: 'Is our smart-camera footage and personal data actually secure — and what is our AI assistant doing with what we tell it?'
Past conference work as case studies: problem, approach, and results with the real numbers, plus links into their discussion threads.
A case study of AI in the systems analysis & design curriculum: 43 students built client-evaluated prototypes with AI tools, and we measured what changed.
54 participants ran a 14-task protocol against a domain AI agent embedded in a learning management system. Task success was high — incorrect information was the real story.
Projects the company has sponsored — what was funded (tools, tokens, fees), where they stand, and the papers they produced. This shelf is the proof that sponsorship is real, and it stays current.
The first sponsored projects are being selected from community proposals now. If yours should be one of them, see the Sponsorship page — funding is project-by-project, with no published cap.
