🚀 Coming from Minneapolis, lets discuss the deep challenges of Large Language Models (LLMs). 🌐 Sundar Pichai, CEO of Google, recently highlighted a significant issue: LLMs often provide wildly incorrect information, a feature they don't yet know how to eliminate. 🛑🍕 From suggesting glue on pizza to dangerous mental health advice, these inaccuracies are a major concern. Despite Google's hesitation, companies like OpenAI are pushing forward. This challenge is here to stay, but Parsimony, a Pangeon startup, is dedicated to finding solutions. 💪🧠🔍 Check out the reel to see how Parsimony is working to improve AI and ensure its safety for everyone! 🌟 #Pangeon #ThePangeon #AI #AGI #OpenAI #FutureTech #GPT #ChatGPT #AIEthics #TechChallenges #Innovation #MachineLearning #AIResearch #StartupJourney 4o
The complexity of ensuring accuracy in Large Language Models is indeed a critical issue. It's encouraging to see companies like Parsimony actively seeking solutions. In my experience, blending different AI technologies often leads to innovative breakthroughs. How does Parsimony approach the integration of various AI methodologies to tackle these challenges?
I think the solution lies with Retrieval-Augmented Generation (RAG) , which is the process of optimizing the output of a large language model, so it references an authoritative knowledge base outside of its training data sources before generating a response.