It is trained on a large language model with 13 billion parameters and over 800GB of text. It has thousands of professionally hand-written training sentences based on a careful study of harmful and unlawful language, resulting in a LLM that can identify dozens of types of helpful and harmful language.

Technology Stack:

• OpenAI
• Nodejs
• HuggingFace

Alphy is a Community-based, considerate dynamic new mobile-first app and web-based platform which gives companies the tools they need to better recruit, retain, and advance women. Some of the Feature includes Daily original stories, interviews, and news.Live Talks with leading luminaries of our day. Reimagined learning tracks created by Alphy’s award-winning writers and editors. Original learning games offering friendly team competitions.Social networking in a supportive environment.A jobs and internship board connecting to Alphy’s talent pipeline

Technology Stack:

• NodeJS
• React Native
• MongoDB

RAV research addresses technological opportunities for improving voting for individuals with disabilities throughout the current voting process in the United States. The projects range from solutions that can be implemented with no change to equipment or process, to those that provide direction for next-generation voting systems, with a focus on audio voting, electronic voting interfaces, visual aids for paper ballots, and polling place operations.

Research in Accessible Voting (RAV) was a subcontract of the Research Alliance for Accessible Voting (RAAV) grant from the Election Assistance Commission, led by Dr. Ted Selker . The RAV work was performed at CMU-Silicon Valley and at the Data Democracy Initiative at CITRIS at the University of California Berkeley. New techniques were developed and tested to improve physical, cognitive, and perceptual accessibility of voting. The codebase for RAV projects is currently maintained, and hosted by TechDojo.