#ai-training
45 episodes · Page 2 of 2
#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 Invisible Workforce Behind AI
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 Hidden Human Labor Behind AI
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.
#1495: Can Fictional Twins Save AI From Running Out of Internet?
As high-quality human data runs dry, synthetic data is becoming the new gold standard for training the next generation of AI models.
#1282: The Geometry of Thought: The Mathematics Powering AI
Peeking under the hood of AI to discover the beautiful linear algebra and calculus that make machine reasoning possible.
#1249: The Curse of Competence: Why Your Best Skills Are Invisible
We often ignore our greatest strengths because they feel too easy. Explore the science of expert blindness and the AI tools uncovering hidden talent.
#608: When AI Eats the World's Memory
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: Why Your AI Is a Yes-Man
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: Why Local AI Inference Is Beating the Cloud
AI supercomputers are landing on your desk! Discover why local AI is indispensable for enterprises facing API costs, latency, and privacy.