# Chunking Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/chunking
> Markdown URL: https://aitinkerers.org/technologies/chunking.md
> Technology record last updated: 2026-03-28T13:53:36Z
> Generated: 2026-10-23T08:55:43Z

Chunking breaks massive datasets into optimized, semantically coherent segments to maximize retrieval accuracy in RAG pipelines.

Effective chunking is the backbone of high-performance LLM applications. By partitioning documents into fixed-size segments (often 512 tokens) or recursive structures with specific overlaps (typically 10% to 20%), developers ensure that vector databases like Pinecone or Milvus return precise context. This process prevents the 'lost in the middle' phenomenon by maintaining local semantic integrity. Whether you are implementing character-based splits or advanced semantic partitioning, the goal remains the same: provide the retriever with enough signal to answer queries without exceeding the model's context window.

- Official technology site: https://www.pinecone.io/learn/chunking-strategies/
- Public AI Tinkerers demos and talks: 2
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Teaching a robot to always win connect four via LeRobot](https://berlin.aitinkerers.org/talks/rsvp_HveawmqfJoQ)

- Event context: AI Tinkerers Berlin - June 17, 2026 — 2026-06-17 — Berlin
- Public talk page: https://berlin.aitinkerers.org/talks/rsvp_HveawmqfJoQ

### [From AI Agent Demo to Enterprise Reality Usecases](https://ho-chi-minh-city.aitinkerers.org/talks/rsvp_tu-93CcrdmY)

- Event context: AI Tinkerers Ho Chi Minh City: From Prompt to Agent — 2026-03-07 — Ho Chi Minh City
- Public talk page: https://ho-chi-minh-city.aitinkerers.org/talks/rsvp_tu-93CcrdmY

## Related Technologies

- [Action Chunking (ACT)](https://aitinkerers.org/technologies/action-chunking-act) ([Markdown](https://aitinkerers.org/technologies/action-chunking-act.md)) — 1 public demo
- [Algorithm](https://aitinkerers.org/technologies/algorithm) ([Markdown](https://aitinkerers.org/technologies/algorithm.md)) — 2 public demos
- [Embedding](https://aitinkerers.org/technologies/embedding) ([Markdown](https://aitinkerers.org/technologies/embedding.md)) — 2 public demos
- [Hardware](https://aitinkerers.org/technologies/hardware) ([Markdown](https://aitinkerers.org/technologies/hardware.md)) — 2 public demos
- [Hugging Face](https://aitinkerers.org/technologies/hugging-face) ([Markdown](https://aitinkerers.org/technologies/hugging-face.md)) — 42 public demos
- [Imitation Learning](https://aitinkerers.org/technologies/imitation-learning) ([Markdown](https://aitinkerers.org/technologies/imitation-learning.md)) — 1 public demo
- [LeRobot](https://aitinkerers.org/technologies/lerobot) ([Markdown](https://aitinkerers.org/technologies/lerobot.md)) — 1 public demo
- [LLM](https://aitinkerers.org/technologies/llm) ([Markdown](https://aitinkerers.org/technologies/llm.md)) — 123 public demos
- [policy training](https://aitinkerers.org/technologies/policy-training) ([Markdown](https://aitinkerers.org/technologies/policy-training.md)) — 1 public demo
- [RAG](https://aitinkerers.org/technologies/rag) ([Markdown](https://aitinkerers.org/technologies/rag.md)) — 148 public demos
- [Redmind](https://aitinkerers.org/technologies/redmind) ([Markdown](https://aitinkerers.org/technologies/redmind.md)) — 1 public demo
- [Robotic Arm](https://aitinkerers.org/technologies/robotic-arm) ([Markdown](https://aitinkerers.org/technologies/robotic-arm.md)) — 1 public demo
- [SO101](https://aitinkerers.org/technologies/so101) ([Markdown](https://aitinkerers.org/technologies/so101.md)) — 1 public demo
- [Transformers](https://aitinkerers.org/technologies/transformers) ([Markdown](https://aitinkerers.org/technologies/transformers.md)) — 149 public demos
- [Transformers (ACT)](https://aitinkerers.org/technologies/transformers-act) ([Markdown](https://aitinkerers.org/technologies/transformers-act.md)) — 1 public demo