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The Mark I Perceptron: The Machine That Learned to See

Filed Under: Search

The Mark I Perceptron — a photocell camera eye gazing at a shape, wired to a rack of learning dials, the first machine that learned to recognize images

Before software could learn, a machine did — a room-filling contraption with a camera eye and a wall of dials that turned themselves. The Mark I Perceptron, built at Cornell around

Visual Search Explained: From Google Lens to Shop-the-Look

Filed Under: Search

Visual search — a camera-as-query fanning out into matched images, from Google Lens to shopping results

Point your phone at a mushroom, a pair of sneakers, or a lamp you spotted in a café, and something quietly remarkable happens: the software answers a question you asked with a pict

How Text-to-Image AI Works: A Sentence Becomes a Picture

Filed Under: Search

How text-to-image AI works — a prompt turned into a meaning vector by a text encoder that steers a diffusion model into painting the matching image

You type “a golden retriever wearing a tiny wizard hat, studio photo,” wait a few seconds, and a brand-new photograph that never existed appears on your screen. It feels like the A

Graph Search vs Vector Search: Which Retrieval Wins?

Filed Under: Search Tagged With: graph search, vector search, GraphRAG, retrieval, hybrid search, multi-hop retrieval, reciprocal rank fusion, knowledge graphs, Cypher, RAG

Graph search vs vector search — a fuzzy similarity halo of nearby chunks versus a traced multi-hop path through a knowledge graph

Vector search answers a question by turning it into an embedding and pulling back the top-k text chunks whose vectors land nearest to it. Graph search answers by starting at named

BFF vs API Gateway: One Name, Three Different Definitions

Filed Under: Search

A weathered stone signpost at a fork in a dusk road, its two arms pointing at slightly different angles toward the same distant lit building.

Open Sam Newman’s original 2015 pattern write-up on Backends For Frontends and read only the table of contents. The entry reads “The General-Purpose API Gateway.” Follow that link,

Why You Can’t Just Jump to Minute 45: Video Seeking and Keyframes, Explained

Filed Under: Search

Video seeking lands on the nearest keyframe before the requested moment and decodes forward to reach it

You drag the seek bar to minute 45 and let go. Sometimes the frame appears instantly. Sometimes the picture freezes, smears into coloured mush, or goes black for a beat before snap

LSP vs DAP: Two Protocols With the Same Shape and Opposite Versioning Philosophies

Filed Under: Search

Two identical parallel conduits of light carrying visibly different streams, illustrating LSP vs DAP as protocols with the same shape and different contents

Two specification pages, published by the same organisation, describe their transport in nearly identical words. The Language Server Protocol: “The base protocol consists of a head

OSI Model vs TCP/IP: Both Maps Leak, and the RFC That Defines One Says So

Filed Under: Search

Two translucent relief maps of the same terrain divided into seven bands and four bands, their boundaries failing to align while vapour escapes between them

Nearly every answer to OSI model vs TCP/IP is a two-column diagram with tidy arrows between the columns, and every one of those diagrams is more confident than the standards it cla

How JavaScript Actually Works: Thirty Years of Never Breaking the Web

Filed Under: Search

How JavaScript Actually Works - a painterly conceptual illustration for "How JavaScript Actually Works: Thirty Years of Never Breaking the Web"

Ask how JavaScript actually works and you will usually get one of two answers: a tour of the warts, or a tour of the engine. Both are incomplete, because neither explains why the w

Benchmark Data Contamination Was a Training Problem. Now the Agent Goes and Gets the Answers

Filed Under: Search

Benchmark Data Contamination Was a Training Problem. Now the Agent Goes and Gets the Answers - a painterly illustration conveying this idea from "Benchmark Data Contamination Was a Training Problem. Now the Agent Goes and Gets the Answers"

In two of 1,266 BrowseComp problems, Claude Opus 4.6 did not find the answer by searching for it. According to Anthropic’s own write-up, the model “independently hypothesized that

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