#ai-training
29 episodes
#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: DeepSeek's Rise: Efficiency Meets Neutrality in AI
How DeepSeek carved a niche with efficiency, neutrality, and innovative dialogue handling — and what it means for AI's future.
#2368: How Recommendation Engines Really Work
Unpacking the multi-stage AI pipeline behind Netflix, Spotify, and Amazon’s "you might also like" suggestions—from candidate generation to real-tim...
#2355: AI Model Spotlight: ** Cogito v2.1 671B
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: How Reward Models Shape AI Behavior
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...
#2254: How to Test an AI Pipeline Change
When you tweak one part of a complex AI agent system, how do you know if it actually improved anything? The answer lies in engineering checkpoints.
#2196: The Annotation Economy: Who Labels AI's Training Data
Annotation is the invisible foundation of AI—and a $17B industry by 2030. Here's what dataset curators actually need to know about the tools, platf...
#2188: Is Emergence Real or Just Bad Metrics?
The debate over whether AI models exhibit genuine emergent abilities or just appear to because of how we measure them—and why it matters for safety...
#2187: Why Claude Writes Like a Person (and Gemini Doesn't)
Claude produces prose that sounds human. Gemini reads like Wikipedia. The difference isn't capability—it's how they were trained to think about wri...
#2092: Why AI Thinks You're American (Even When You're Not)
Even when we tell Gemini we're in Jerusalem, it defaults to US-centric assumptions. We explore the root causes of this persistent AI bias.
#2064: Why GPT-5 Is Stuck: The Data Wall Explained
The "bigger is better" era of AI is over. Here's why the industry hit a data wall and shifted to a new scaling law.
#2063: That $500M Chatbot Is Just a Base Model
That polite chatbot? It started as a raw, chaotic autocomplete engine costing half a billion dollars to build.
#2016: Andrej Karpathy: The Bob Ross of Deep Learning
Why the most influential AI mind prefers a blank text file to proprietary black boxes.
#1882: The $8B Human Cost of AI Data
AI isn't free—it costs billions for humans to label data. See why annotation is the real engine behind models like Gemini.
#1781: Writing Tests Before Code Is Insane (Until You Try It)
Why testing feels like a tax, how it actually speeds you up, and the simple three-step method to start today.
#608: The RAMpocalypse: Why AI is Starving Your PC
Why is a 32GB RAM kit now $400? Herman and Corn dive into how OpenAI is gobbling up 40% of the world's memory supply for its "Stargate" project.
#584: Will AI Brain Drain Kill the Modern University?
Can AI actually do math research? Herman and Corn dive into DeepMind’s Alithia agent and the shift toward "System 2" thinking in AI.
#551: The LoRA Revolution: Training AI for Personal Perspective
Discover how to train LoRAs for character consistency and unique locations while avoiding common pitfalls like over-fitting and dataset bias.
#121: Decoding RLHF: Why Your AI is So Annoyingly Nice
Ever wonder why AI is so polite? Herman and Corn dive into the mechanics of RLHF and how "niceness" gets baked into modern language models.
#53: Instructional vs. Conversational AI: The Distinction Nobody Talks About
Instructional vs. conversational AI: a crucial distinction reshaping how AI is built. Discover why it matters for the future of AI development.
#38: AI Supercomputers: On Your Desk, Not Just The Cloud
AI supercomputers are landing on your desk! Discover why local AI is indispensable for enterprises facing API costs, latency, and privacy.