#large-language-models
140 episodes · Page 6 of 6
#89: The Digital Twin Dilemma: Can AI Truly Understand You?
From "digital twins" to "digital nannies," Herman and Corn explore the engineering gap between smart encyclopedias and AI that knows your soul.
#86: The Price of Politeness: Should AI Guardrails Stay?
Herman and Corn debate the hidden costs of AI safety layers and what happens when we strip away the "corporate HR" personality of LLMs.
#85: When Probability Beats Truth: Why AI Must Lie
Why do smart AI systems make up fake facts? Corn and Herman explore the "feature" of digital hallucinations and how to spot them.
#82: The Accidental AI Engine
From video game dragons to digital brains: Herman and Corn explain why your graphics card is the secret engine behind the AI boom.
#81: When AI Judges Can't Tell Humans from Bots
Can a robot tell if you’re human? Herman and Corn explore the "Reverse Turing Test" and why being "messy" might be our best defense.
#72: AI's Hidden Cultural Code: East vs. West
Do AIs think differently East vs. West? Uncover the hidden cultural code embedded in large language models.
#67: Scaling or Pivoting AI for Code
Are LLMs truly the future of coding, or do they need a fundamental architectural pivot? We dive into AI's programming future.
#62: System Prompts vs Fine-Tuning: When to Actually Train Your AI
Prompt or fine-tune? We break down when to train your AI, from Shakespearean emails to law firm docs. Avoid unnecessary fine-tuning!
#60: Single-Turn AI: The Interface Pattern Nobody's Talking About
Forget chatbots. Discover the hidden power of single-turn AI interfaces and how they're quietly reshaping how businesses integrate AI.
#56: The Thought Experiment Nobody Runs
Building an AI model from scratch? It's a brutal reality of trillions of tokens and millions in GPUs. Discover the hidden costs of modern AI.
#52: System Prompts vs. Fine-Tuning: Are We Building Solutions for Problems That Don't Exist?
Are we over-engineering AI solutions? We dive into system prompts vs. fine-tuning and ask: Do you even need to fine-tune?
#42: AI's Secret: Decoding the .5 Updates
Uncover the hidden world of AI's .5 updates. It's not just bug fixes—it's hundreds of millions and countless hours shaping smarter, safer AI.
#41: The Butcher's Bargain: When Smaller AI Is Good Enough
Unlock powerful AI on your device! We demystify quantization, the ingenious trick making local AI a reality.
#37: From Keywords to Meaning: How AI Understands You
Unlock AI's secret language! Discover how vectors and embeddings create a "semantic galaxy" for true understanding and control.
#34: Red Team vs. Green: Local AI Hardware Wars
NVIDIA's CUDA rules AI, leaving AMD users battling a "green wall." Explore the hardware wars and thorny paths forward.
#23: Common Crawl's Cultural Blindspot
Uncover the unseen influences shaping AI. We dive deep into training data, bias, and Common Crawl.
#22: The Input Bottleneck: Why Your Mic Matters for AI
Uncover the secrets to perfect AI dictation! Corn and Herman explore the ultimate speech-to-text hardware.
#14: AGI's Crossroads: Are LLMs a "Dead End" to True AI?
Are LLMs a dead end for true AGI? We dive into the electrifying debate with AI's forefathers.
#13: AI: Not an Overnight Success Story
AI's "overnight success" is a myth. Unravel the true story behind its rise, from humble beginnings to today's innovations.
#11: How Does Fine Tuning Work Anyway?
Unlock the secrets of AI fine-tuning. Discover how your small dataset can shape a giant model.