Computer Vision
67 episodes
#6496: How Speech Models See Audio as an Image
Modern speech recognition models like Whisper never hear raw audio; they inspect an eighty-pixel-tall grayscale image of the sound.
#6343: Why Live Video Generation Still Struggles With Timing
A streaming video model can render fifty-eight frames a second while still delivering pictures that are noticeably late.
#6311: How Transformers Process Images and Video
A Vision Transformer divides a standard image into a grid of 16-by-16 pixel patches rather than processing each individual pixel as a token.
#6271: Why Video Search Often Works Better as Text
A one-minute video compressed into a single vector undergoes roughly five orders of magnitude of raw data reduction.
#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.
#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.
#6070: The Papers That Moved AI: From AlexNet to This Year's Fights
The classics all said 'learn it from data and scale it up'. This year's most-discussed AI papers are auditing what scaling took for granted.
#5903: Video Tokens, Omni, and the Local VRAM Math
Video costs ~100 tokens per second. That single number explains why ChatGPT hides video upload and why local inference hits a KV cache wall.
#5656: Why a Headlamp Fails at Precision Electronics Work
A camping headlamp is better than nothing — but it's the wrong tool for board work. Here's what the specs actually say.
#5626: What Multimodal Models Actually Learn From Video
Late fusion, early fusion, and vision laziness — what actually happens when models train on video, audio, and text together.
#5506: AI Is Way More Than Chatbots
The word "AI" quietly became a synonym for "chatbot." Here's what the full model ecosystem actually contains.
#5319: Focus Stacking Without the Phone App Guesswork
Your phone app wants three shots. The optics want three hundred. Here's how to actually stack macro focus.
#5278: Photogrammetry vs Gaussian Splat: Scanning a Room Without LiDAR
No LiDAR? No problem. How capture modes, masking, and vertical parallax shape a phone-based room scan.
#5251: Recovering the Moon That's Already in the Pixels
Image restoration clarifies photos without inventing detail — until the fidelity dial shows up. Here's what's in the toolbox.
#5245: Training a Model on 100 Phone Photos
One drawer of screws, a hundred phone photos, and a schema. When does a small custom model beat a fine-tuned VLM?
#5198: Counting the AI Models Nobody Releases
YOLO is free — the labeled data isn't. Why the custom image models that matter most are the ones you'll never see on Hugging Face.
#4999: Why AI Can't Just Put a Circle on Your Photo
Why multimodal AI models can't simply circle a Dremel bit without rebuilding your entire image from scratch.
#4970: Labels vs. Book Covers: Structured Extraction Tradeoffs
General vision models vs. purpose-built pipelines for extracting data from messy real-world labels and covers.
#4969: How to Train a One-Class Detector from 300 Photos
From photo folder to production YOLO model — the real walkthrough for custom object detection.
#4672: How Magic Eraser Tools Actually Work: Segmentation + Inpainting
Two AI stages — pixel-level segmentation and generative inpainting — explain how your phone erases objects cleanly.
#4575: Measuring Rooms with Fiducial Markers: AprilTag vs ArUco
AprilTags, ArUco, ChArUco — which marker system actually helps you measure a room from a photo? We break down the tradeoffs.
#4462: How AI Imagines Your Skeleton
From image to fully rigged 3D model — the six computational stages that turn photos into animated characters.
#4449: Blur Before You Publish: Image Redaction Tools
How to automatically find and blur QR codes, credit cards, and sensitive text in photos before publishing.
#4169: Change Detection AI for Construction Sites
How AI catches what experts miss in construction site photos — from Siamese networks to transformer models.