llama 3.1
Meta's open-source language model
Episodes
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#6154: Who Checks the Labels? Weak vs Strong SupervisionHuman labels, rule-based labels, or a teacher model writing the exam — what actually makes supervision "strong," and who verifies it? -
#6012: Inside the Decode Loop: How LLMs Generate One Token at a TimeThe model doesn't choose tokens or decide when to stop — the engine does. A step-by-step tour of one decode iteration. -
#2189: Scaling Multi-Agent Systems: The 45% ThresholdA landmark Google DeepMind study reveals that adding more AI agents often degrades performance, wastes tokens, and amplifies errors—unless your sin... -
#248: The Sycophancy Trap: Getting Honest Feedback from AIIs your AI just telling you what you want to hear? Learn how to break the "sycophancy trap" and get truly objective feedback from your agents. -
#48: Renting vs. Building: The Hidden Choices in AI InferenceEver wonder how AI magic happens? We demystify AI inference, exploring where and how models truly operate.