Part 2/11:
Historically, word to V embeddings, introduced around the late 2010s, transformed how machines understand language, enabling models like GPT-3 and GPT-4 to generate human-like text. These breakthroughs laid the foundation for a new epoch in AI, catalyzing innovations in language processing, code synthesis, and more.
Now, many industry insiders and enthusiasts believe that UStar is the next such catalyst—potentially a game-changing "algorithmic breakthrough" that could master not just natural language but also complex reasoning and mathematics at a level previously thought impossible for machines.