אודות פרק זה

אנגלית
ארצות הברית

תעתיק 🔗

חיפוש פרקים ישנים

חפש פרקים קודמים של MTS.

פרקים אחרים בפודקאסט הזה

Former Anthropic pre-training researcher and Core Automation co-founder Rohan Anil explains how compute islands allow decentralized GPU clusters to train frontier AI models without colocation. He details why current scaling hits test-time learning bottlenecks, how butterfly mixing handles asynchro‮…
Ruby Justice Thelot analyzes how algorithmic curation and platform economics have fractured cultural monoculture, flattening mainstream pop while accelerating niche subcultures. He examines empirical data across 11 years of celebrity Wikipedia traffic, Billboard streaming dispersion, and the surgi‮…
Baseten co-head of model training Charlie O'Neill breaks down why recursive self-improvement will be much weaker than fast-takeoff theories predict, pointing to real-world compute and RL bottlenecks. He also unpacks why automating machine learning research faces sharp diminishing returns and intro‮…
MongoDB's head of AI platform Chirag Shah breaks down why production agents fail without dedicated memory and context architecture. He explains how MongoDB built Atlas Agent Engine, why teams are over-indexing on LLM selection, and how multi-agent architectures are replacing traditional full-stack‮…
הצהרה: הפודקאסט והגרפיקה המוטבעים בדף זה הם מ-MTS , שהוא רכושו של בעליו ואינו קשור או מאושר על ידי Listen Notes, Inc.