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General
Empowering Humanity with Consumable, Insightful, Credible Data
Understand the why. Deliver a great User (Market Research) experience.
Any decision. Improving and Testing Ads in Marketing.
Behind any decision. Our Q*. Robot Scientists/Self Driving Lab (LLM Self-Inquiry)
Map of Causality. Improve Bioequivalence of Synthetic Respondents to x by y
Add Privacy, Permissioning, and Authorization capabilities (on FE and BE)
Create an ad for AI Ethics Board -
Upgrade our concise insights capabilities for experiment results.
Complete FAQ: https://docs.google.com/document/d/1NNxWSt2n2YqELX85ptm7WDxvNk3Gr2SCjgzK7mD_YFs/edit
"Brainstorm Ideas" - Autopilot for Experimental Design
Create Scientific Advisory Committee (SAC)
Publish 1 paper with our results
Showcase Page
V2 of Ideation for existing Experimental Design - based on Aida's designs
Centralize all analytics (R Shiny) to Backend (Python)
Allow users to view and edit "public" experiments
Stabilize "dev" branch of backend to serve as v1.0 for updated frontend
Fix ELK Stack Logging to work with the Parallelized experiments
Run all Human Baseline Experiments against Claude (anthropic)
Run all Human Baseline Experiments against Cohere
Run all Human Baseline Experiments against Mistral
Run all Human Baseline Experiments against LLama
Create a "Space" sweep - World and US Sweep Interface drilling down in a region. Voting Use Case.
Create a "time" sweep where we can run experiments over different periods of time to try and predict future trends. Trends CPG Use Case.
Understand what causes high quality Synthetic Responses
Add the capability to run experiments on Images in addition to Text
Add the capability to run experiments on Video in addition to Text and Images
Allow users to create their own Traits via latent Variable Trait Generation
Allow users to import their existing Traits into our system
Allow users to import cookie history into our system
Experiment Sweep to measure stability of our infrastructure, experimental designs, and conclusions.
Develop an API to give feedback to users during each step of the experimental design process.
A* Explore vs Exploit for Regenerative Learning
Todo: Send out 1% of tasks to a human panel for Human Benchmarking
Create a "Dependent Variable" sweep - so that a CEO can understand *all* the different ways a user can interact with their product.
Create a "market simulator" so that our Prescriptive Analytics work using real-life market products and are maximally relevant.
Replicate an additional 100 experiments to bring our total to 300 Human Baseline Experiments.
Hire 3rd party document extraction/human in the loop service like Ocrolus, handl.ai, rossum.ai to replicate an additional 1000 experiments
Train our own document extraction/human in the loop service to transcribe an additional 10,000 experiments