Speed vs Quality, Hallucinations, and the AI Learning Rabbit Hole - With Nir Zicherman
Impossibile aggiungere al carrello
Puoi avere soltanto 50 titoli nel carrello per il checkout.
Riprova più tardi
Riprova più tardi
Rimozione dalla Lista desideri non riuscita.
Riprova più tardi
Non è stato possibile aggiungere il titolo alla Libreria
Per favore riprova
Non è stato possibile seguire il Podcast
Per favore riprova
Esecuzione del comando Non seguire più non riuscita
Speed vs Quality, Hallucinations, and the AI Learning Rabbit Hole - With Nir Zicherman
-
Letto da:
-
Di:
A proposito di questo titolo
Sara breaks down perceptrons (1957!) as the tiny “matrix of lights” idea that eventually became neural networks—then we jump straight into modern AI chaos.
Oboe’s Nir Zuckerman walks us through the messy reality of building consumer-grade AI for education: every feature is a tradeoff between loading fast and being good, and “just use a better model” doesn’t magically solve it. We talk guardrails, web search, multi-model pipelines, and why learning tools should feel lightweight—more like curiosity than homework. Also: Becca’s “how does a computer work?” obsession and a book recommendation that might change your life.
🧠 AI Concepts & Foundations- Perceptron (Wikipedia)
- Neural Networks Explained
- Scaling Laws for Neural Language Models
- FLOPS (Floating Point Operations Per Second)
🎓 Learning, Education & AI
- Oboe
- AI as a Personal Tutor (Overview)
- Why Tutors Are So Effective
🏗️ Building AI Products
- Speed vs Quality Tradeoffs in LLM Apps
- LLM Orchestration Patterns
- Retrieval-Augmented Generation (RAG)
- LLM Hallucinations: Causes & Mitigation
📚 Books Mentioned
- Code: The Hidden Language of Computer Hardware and Software
- Perceptrons
🧪 History of AI
Ancora nessuna recensione