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.
#6191: What Actually Happens During Fine-Tuning
Sixteen bytes per parameter in, two out — a walk through the forward pass, backward pass, and optimizer that turn a dataset into new weights.
#6190: When Your AI API Quietly Changes Under You
Same API name, different model behind it. How to tell when the thing you tested stops being the thing you're using.
#6189: What "Real" Improvement Actually Means in AI Evals
A p-value isn't the probability your result was luck. Here's what chance actually means in AI benchmarks — and why bold numbers need cross-examinat...
#6185: Why AI Labs Sell a Tier Above the Flagship
Fable, Deep Think, SuperGrok Heavy — what the $300/month top tier actually does that the flagship can't.
#6184: Anthropic's Unreleased Model Two, Explained
Anthropic trained a model better than what it sells — and never released it. What that gap actually tells us.
#6180: Mapping Code-Switching: 113 Pairs, No Community
Researchers count 113 code-switched language pairs — but a pair is just a label on a file, not a community of speakers.
#6179: Voice Cloning: 10 Seconds to Steal Your Voice
Ten seconds of audio is all it takes to clone a voice. Here's what the law actually protects — and what it doesn't.
#6178: Why Your Voice Clone Sounds American
Your cloned voice drifts toward American English. Here's what's actually happening — and why "neutral" is a myth.
#6177: How Voice Cloning Works From Six Seconds of Audio
Six seconds of reference audio is all Chatterbox needs. The real work happened in the half-million hours of training before you showed up.
#6176: Do Audio Models Hear How You Said It?
A benchmark called LISTEN found audio models score near chance when emotion lives in the voice, not the words. What does that mean for real calls?
#6175: Video Models Can't Tell Time: What Motion Benchmarks Reveal
Frontier models score 48% on tasks where humans hit 98% — the gap is motion, speed, and sequence, not scene description.
#6174: What Your Voice Reveals: Accent, Distance, and Movement in Audio AI
What can AI actually hear in your voice? Accent detection, speaker distance, whale songs, and the gap between deployed audio models and chatty gene...
#6173: Auditing a Sycophantic Model From the Inside
A stumped lab, a fawning model, and the diagnostic playbook nobody has a name for — from eval slicing to persona vectors.
#6172: Recipes vs. Regeneration: AI Photo Editing in 2026
Two ways AI edits photos now: models that write a readable recipe of slider values, and models that just repaint the whole frame.
#6171: AI Audio Restoration: What Actually Ships in 2026
Noise removal and bandwidth extension are shipping products today. Matching a clip to a target EQ is still mostly a research prototype.
#6170: One Endpoint, Many Boxes: Local LLM Routing
A LiteLLM-style proxy can fail over between your own GPU boxes and the cloud — but it can't see your VRAM.
#6169: What It's Like to Be a Token Inside an LLM
A token's-eye view of an LLM's forward pass — no cone, no squeezing, just a hallway where every layer scribbles on you.
#6168: Hebrish: Hebrew-Aware Dictation That Actually Works
Two new speech models fix English-Hebrew code-switching dictation — and the whole training run cost about fifty cents of GPU time.
#6167: Streaming Browser Cookies to a Headless Server
Daniel wants his logged-in browser on the home server. Chrome bolted the front door — so what's left?
#6165: Watching 20 Batch Jobs at Once
Batch APIs give you a discount, then hand you a babysitting job. Here's what actually watches a batch run — and what doesn't.