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20VC: Spending $2M to Train a Single AI Model: What Matters More; Model Size or Data Size | Hallucinations: Feature or Bug | Will Everyone Have an AI Friend in the Future & Raising $150M from a16z with Noam Shazeer, Co-Founder & CEO @ Character.ai

20VC: Spending $2M to Train a Single AI Model: What Matters More; Model Size or Data Size | Hallucinations: Feature or Bug | Will Everyone Have an AI Friend in the Future & Raising $150M from a16z with Noam Shazeer, Co-Founder & CEO @ Character.ai

35:092023-08-31

Om episode

Noam Shazeer is the co-founder and CEO of Character.AI, a full-stack AI computing platform that gives people access to their own flexible superintelligence. A renowned computer scientist and researcher, Shazeer is one of the foremost experts in artificial intelligence (AI) and natural language processing (NLP). He is a key author for the Transformer, a revolutionary deep learning model enabling language understanding, machine translation, and text generation that has become the foundation of many NLP models. A former member of the Google Brain team, Shazeer led the development of spelling corrector capabilities within Gmail, the algorithm at the heart of AdSense.   In Today's Episode with Noam Shazeer We Discuss: 1. Entry into the World of AI and NLP: How did Noam first make his way into the world of AI and come to work on spell corrector with Google? What are 1-2 of his biggest takeaways from spending 20 years at Google? What does Noam know now that he wishes he had known when he started Character? 2. Model Size or Data Size: What is more important, the size of the data or the size of the model? Does Noam agree that "we will not use models in a year that we have today?" What is the lifespan of a model? Does Noam agree that the companies that win are those that are able to switch between models with the most ease? With the majority of data being able to be downloaded from the internet, is there real value in data anymore? 3. The Biggest Barriers: What is the single biggest barrier to Character today? What are the most challenging elements of model training? Why did they need to spend $2M to train an early model? What are the most difficult elements of releasing a horizontal product with so many different use cases? Where does the value accrue in the race for AI dominance; startups or incumbents? 4. AI's Role on Society: Why does Noam believe that AI can create greater not worse human connections? Why is Noam not concerned by the speed of adoption of AI tools? What does Noam know about AI's impact on society that the world does not see?

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