#27: Cooking Up Intelligence: How AI Models Get Trained
No se pudo agregar al carrito
Solo puedes tener X títulos en el carrito para realizar el pago.
Add to Cart failed.
Por favor prueba de nuevo más tarde
Error al Agregar a Lista de Deseos.
Por favor prueba de nuevo más tarde
Error al eliminar de la lista de deseos.
Por favor prueba de nuevo más tarde
Error al añadir a tu biblioteca
Por favor intenta de nuevo
Error al seguir el podcast
Intenta nuevamente
Error al dejar de seguir el podcast
Intenta nuevamente
-
Narrado por:
-
De:
How does an AI go from a blank slate to a powerful tool? It's not magic… it's a detailed, multi-stage training process.
In This Episode, You'll Learn:
- The five essential stages of AI training: Data Collection, Tokenization, Pretraining, Post-training, and Continuous Improvement.
- What Supervised Learning is and how labeled "flashcards" or "gold standard" examples help fine-tune a model's accuracy.
- The power of Unsupervised Learning in the pre-training phase, where models find hidden patterns in massive, unlabeled datasets (like Spotify recommendations).
- How Reinforcement Learning from Human Feedback (RLHF) uses a reward system (like ranking bowls of ramen) to make models more helpful and aligned.
This weeks poll: Human Feedback
Todavía no hay opiniones