importantSYS.SOURCE: sshh.io blog• 2026-08-10T14:20:41Z

Analyzing Knowledge Cutoffs and Pre-Training Timelines in GPT and Claude Models

#ai #training data #model training #large language models #machine learning

The article explores methods to infer training data and timelines of large language models like GPT-5 and Opus through probing techniques. It highlights how historical facts, self-reported dates, and model identities reveal insights into their training processes and dataset compositions.

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> TESLA RECALLS 2.98 MILLION VEHICLES IN CHINA DUE TO HIDDEN DOOR HANDLE SAFETY CONCERNS > UNEXPECTED IMPLICATIONS OF KPIS IN ORGANIZATIONAL PERFORMANCE METRICS > BEN MCKENZIE CONDEMNS CRYPTOCURRENCY AS LARGEST PONZI SCHEME IN HISTORY > MIGRATING SYNOLOGY NAS TO UNIFI UNAS PRO 8 USING ROBOCOPY AND SMB MULTICHANNEL: PERFORMANCE INSIGHTS > SHODAN: A SEARCH ENGINE FOR INTERNET-CONNECTED DEVICES > DEVELOPMENT OF A LOW-LATENCY AI GAMING COMPANION FOR SKYRIM > REVERSE ENGINEERING PERIPHERALS: FIRMWARE ANALYSIS AND SECURITY EXPLOITS > EFFICIENT PARALLEL DEVELOPMENT WITH GIT WORKTREE TO AVOID CONTEXT SWITCHING > GPT-2 MODEL IMPLEMENTATION USING PURE CMAKE > DECLARATIVE WEBGPU CONFIGURATION USING S-EXPRESSIONS> TESLA RECALLS 2.98 MILLION VEHICLES IN CHINA DUE TO HIDDEN DOOR HANDLE SAFETY CONCERNS > UNEXPECTED IMPLICATIONS OF KPIS IN ORGANIZATIONAL PERFORMANCE METRICS > BEN MCKENZIE CONDEMNS CRYPTOCURRENCY AS LARGEST PONZI SCHEME IN HISTORY > MIGRATING SYNOLOGY NAS TO UNIFI UNAS PRO 8 USING ROBOCOPY AND SMB MULTICHANNEL: PERFORMANCE INSIGHTS > SHODAN: A SEARCH ENGINE FOR INTERNET-CONNECTED DEVICES > DEVELOPMENT OF A LOW-LATENCY AI GAMING COMPANION FOR SKYRIM > REVERSE ENGINEERING PERIPHERALS: FIRMWARE ANALYSIS AND SECURITY EXPLOITS > EFFICIENT PARALLEL DEVELOPMENT WITH GIT WORKTREE TO AVOID CONTEXT SWITCHING > GPT-2 MODEL IMPLEMENTATION USING PURE CMAKE > DECLARATIVE WEBGPU CONFIGURATION USING S-EXPRESSIONS