Skip to content

Latest commit

 

History

History
48 lines (27 loc) · 2.13 KB

IDEAS.md

File metadata and controls

48 lines (27 loc) · 2.13 KB

Roadmap

now: Generate suite of evaluations used in the paper testing AI agents with other reasoning methods like COT and self consistency and run them in parallel to conduct evaluation experiments.

Implement a more sophisticated prompt engineering strategy to guide the model's reasoning process more effectively.

Script that generates an dataset based on a topic input, -> set of questions are asked, then multiple trees of thoughts are run concurrently to generate the decision making rich dataset

Introduce a reinforcement learning, distillment, and finetuning scripts to finely tune the model based on feedback from the Tree of Thoughts algorithm.

Integrate heuristics that autonomously determine the search algorithm based on indicators

Integrate heuristics that autonomously determine the strategy cos or propose

Integrate heuristics that autonomously set the input params:

k = T = b = vth =

multi modal

multi-modality tree of thoughts

multi-modality forest of thoughts

multi-modality world of thoughts

Multi-Modality Tree of Thoughts 🌐🌳

The next big advancement for the Tree of Thoughts algorithm is to extend it to multi-modality, enabling it to handle not only text but also images, audio, and other data types. This will bring us closer to multi-modal superintelligence.

Actionable Steps

  1. Research and identify suitable multi-modal pre-trained models that can handle various data types (e.g., text, images, audio).
  2. Adapt the thought decomposition, thought generator, and state evaluator functions to handle multi-modal data.
  3. Develop a method for combining different modalities in the search tree, allowing the algorithm to reason across different data types.
  4. Implement and test the multi-modal Tree of Thoughts algorithm with various problems and datasets.
  5. Optimize the algorithm for performance and resource usage, ensuring it scales well with large multi-modal datasets.
  6. Publish the results and gather feedback from the community to further improve the multi-modal Tree of Thoughts algorithm.

Join us on this exciting journey to advance the Tree of Thoughts algorithm to multi-modality superintelligence! 🚀