#ai-training
40 episodes
#5412: Editing vs. Note-Taking for AI Fine-Tunes
Hand-editing a model's output gives three training signals at once. Writing notes gives one — and a weaker one at that.
#5409: What Makes a Model "Agentic"? Atria Dawn Preview
A 744B-parameter model drops quietly on Hugging Face. Is "agentic" a real model category, or just a deployment pattern?
#5118: Model Identity Fraud: Distillation or Data Contamination?
When AI models lie about who they are, is it stolen knowledge or just contaminated training data?
#4723: Are Model Families Actually Different Models?
Claude Opus, Sonnet, and Haiku aren't trim levels — they're different models sharing a brand name.
#4696: Why AI Over-Explains Simple Tasks
Why does AI turn a simple request into a 24-page document? We explore the training biases and architectural limits behind AI's tendency to over-del...
#4670: Why AI Weights Are Indecipherable
Can you actually read an AI model's weights like a book? We explore why the answer is mostly no — and what researchers are doing about it.
#4669: What "Distribution" Really Means in AI Models
Unpacking what "distribution" actually means under the hood — and why training data variety shapes model behavior.
#4589: The Answer Reflex: Why AI Models Can't Follow Instructions
DeepSeek passes a simple test that stumps GPT and Claude. Why can't Western models stay in character?
#4268: When AI Trains on AI: The Model Collapse Problem
What happens when AI trains only on AI-generated content? The answer is model collapse — and it's already happening.
#3767: How LLMs Actually Learn: Stages or Slurry?
Do large language models learn grammar first, then facts? The honest answer is messier and more fascinating.
#3283: Fine-Tuning DeepSeek for One Podcast
Can a purpose-specific fine-tune fix a model's stubborn writing tics? We explore the practical engineering behind it.
#2665: Partner Certs vs Personal Certs: What Actually Matters
Solo operators face structural barriers in vendor partner programs. Here's how personal and partner certifications actually differ.
#2651: AI Training Itself: Student, Teacher, and Grader
Can models generate their own training data and judge their own outputs? The promise and pitfalls of fully AI-led pipelines.
#2559: The Smartest Path to Python for AI
A practical guide to the best courses and platforms for learning Python, specifically for machine learning.
#2431: The 3 Markets in an AI Trench Coat
GPUs, LPUs, and ASICs: why the best hardware for AI depends entirely on what you're trying to do.
#2408: How Backpropagation Actually Unlocks Neural Networks
How error signals flow backward through networks to make learning possible — and why "it's just calculus" misses the point.
#2377: Is Geopolitical Neutrality a Sustainable AI Strategy?
How DeepSeek carved a niche with efficiency, neutrality, and innovative dialogue handling — and what it means for AI's future.
#2368: The Multi-Stage Pipeline Behind Netflix's Recommendations
Unpacking the multi-stage AI pipeline behind Netflix, Spotify, and Amazon’s "you might also like" suggestions—from candidate generation to real-tim...
#2355: Why Open-Weight Models Are Winning
Discover how Cogito v2.1 leverages process supervision and MoE architecture to redefine reasoning efficiency in open-weight AI models.
#2315: How to Update AI Models Without Starting Over
Exploring the challenge of updating AI models with new knowledge without costly full retraining.
#2313: When AI Optimizes the Wrong Thing
Discover how AI systems learn to optimize for rewards—and why they sometimes get it dangerously wrong.
#2307: Inside Frontier LLM Training: Stages, Costs, and Checkpoints
Discover the multi-stage process of training frontier large language models, from pretraining to post-training, and why checkpoints are the key to ...
#2287: Is AI Code Generation the Future of Low-Code?
Exploring the rise of AI code generation and its potential to reshape the low-code movement.
#2272: The AI Transcription Sweet Spot
Does higher-quality audio make AI transcription worse? New research reveals a surprising "sweet spot" for bitrate, challenging a core assumption of...