{"version":"1.0","type":"rich","provider_name":"gaks.ai AI Glossary","provider_url":"https://gaks.ai/glossary","title":"Perceptron — AI Glossary","author_name":"Glenn Katrud Solheim","author_url":"https://gaks.ai","width":600,"height":200,"html":"<div style=\"font-family:sans-serif;border:1px solid #e0e0e0;border-radius:8px;padding:16px;max-width:600px;background:#ffffff;color:#111111;\"><p style=\"margin:0 0 4px;font-size:11px;color:#666;\">AI Glossary — gaks.ai</p><h3 style=\"margin:0 0 8px;font-size:16px;\">Perceptron</h3><p style=\"margin:0 0 12px;font-size:14px;line-height:1.6;\">The simplest form of neural network, a single computational unit that takes a set of inputs, applies weights, and produces a binary output based on whether the weighted sum exceeds a threshold. The perceptron was introduced by Frank Rosenblatt in 1957 and is the conceptual building block from which all modern neural networks are derived.</p><a href=\"https://gaks.ai/glossary/perceptron\" style=\"font-size:12px;color:#0077aa;\">Source: gaks.ai/glossary/perceptron →</a></div>"}