Artificial Intelligence
Episodes whose main subject is AI itself: building with, training, evaluating, or debating AI systems. AI used only as a tool for another topic goes to that topic.
#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.
#2426: Why DeepSeek V4's Prose Feels More Vivid Than Claude or GPT
A million-token context window at 2% the KV-cache cost — and prose that actually breathes. Here's what makes V4 different.
#2425: Can One Button Solve Your Streaming Frustrations?
A deep dive into JustWatch, Trakt, Letterboxd, and why your ideal streaming app doesn't exist yet.
#2414: Is Love on the Spectrum Helping or Hurting?
A deep dive into the debates around Netflix's dating show: is it warm representation or a deficit lens?
#2413: When Your AI Says No to Everything
Why LLMs refuse 73% of harmless prompts — and the trade-off between safety and usefulness.
#2412: When AI Caves: Progressive vs. Regressive Sycophancy
Why do LLMs agree with you even when you're wrong? We break down the SycEval benchmark and the 78% persistence problem.
#2411: Are Political Bias Benchmarks Actually Measuring Anything?
Why the Political Compass Test fails, and what researchers are building instead to actually measure model bias.
#2410: How Researchers Actually Measure Censorship in Chinese LLMs
Beyond headlines: the actual benchmarks, methodologies, and pitfalls in detecting political refusal in Chinese language models.
#2409: When AI Cheats on Cultural Knowledge
Five benchmarks that reveal how AI systems fail at cultural knowledge — and what their methodologies tell us.
#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.
#2406: Why Million-Token Context Windows Can't Handle 3 Reasoning Steps
Needle-in-a-haystack is dead. Here's what actually measures whether models can think across long documents.
#2405: LLM Benchmarks Are Full of Noise: Statistical Rigor in AI Evals
Why most benchmark claims in AI are statistically indefensible — and what to do about it.
#2404: What Tool-Calling Benchmarks Miss About Production Failures
BFCL, tau-bench, and Nexus each reveal different failure modes. None of them test what actually kills production agents.
#2403: Choosing Your LLM Eval Framework
An architectural shootout of four major LLM evaluation harnesses — where each shines and where each breaks down.
#2401: Designing Data Models That Mirror Your Work
Why 60% of small businesses hate off-the-shelf SaaS—and how to build tools that actually fit your workflow.
#2400: Claude Code’s Hidden Context Tax
How Claude’s eager-loaded primitives silently consume context—and how to optimize your setup for sharper performance.
#2398: Your Taste, Your Data: Owning Your AI Preferences
Why can’t you describe your perfect movie—but you’d know it if you saw it? A vision for portable, user-owned AI taste profiles.
#2396: Predicting War: The Science of Geopolitical Forecasting
How do experts predict wars before they happen? Explore the high-stakes world of geopolitical forecasting, from Cold War models to AI-driven simula...
#2391: When Anti-Bot Defenses Break Accessibility
How browser automation hits a wall with Israel's strict geo-restrictions and anti-bot measures—and what practical workarounds exist.
#2388: From Tool Picker to Problem Solver
Discover how OpenRouter intelligently routes your prompts to the most optimized AI model, reshaping how we interact with AI tools.