SShortSingh.
TopTechnologyAI & MLStartupsProgrammingScienceBusinessFinanceCrypto & Web3World
Back to feed
Programming

TouchGrass: Open-Source AI Tool Plans Outdoor Activities Offline

0
·1 views

TouchGrass is a voice-first outdoor activity planner built for the Hacktoberfest open-source AI challenge. The application uses local AI models via Ollama to generate personalized plans for activities like walking or hiking based on user speech input. It prioritizes privacy by keeping planning prompts and user data on the local device without requiring cloud AI APIs. The developer emphasizes that using open-weight models allows for offline resilience and gives developers freedom to modify or replace the system components.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingDEV Community ·

Developer migrates TypeScript library from tsup to tsdown, discovers contract break

A frontend engineer recently migrated the build system for a TypeScript open-source library from tsup to tsdown. The primary goal was to update the tooling without altering the final npm package delivered to users. While the configuration change was straightforward, the initial tsdown build unintentionally changed the names of key output files. This silent change risked breaking the library's public contract for existing consumers.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

MIT's VISTA harness boosts Claude AI to perfect score on ARC-AGI-3 test with visual prompts

On October 1, researchers at MIT CSAIL published a paper introducing VISTA, a visual interface harness. The system replaced ARC-AGI-3's standard numeric grid interface with 512×512 screenshots and a lossless visual memory archive. Using just a four-sentence prompt without model retraining, VISTA lifted Claude Opus 5.0's performance from 40.68 to a perfect 100 Relative Human Action Efficiency score. The AI completed all 25 test games using 57.4% fewer actions than first-time human players. Researchers concluded perception limitations, not reasoning deficits, had previously constrained AI performance on the benchmark.

0 comments Read more at DEV Community