Ειδήσεις: RETRIEVAL PIPELINE | PXAI

Version	Description	Date
8.42	[ADDED SOURCE REGISTRY LIST VIEW]	04/03/2026 16:19
8.41	[LOCALIZED INDEX.PHP MENU AND MODALS TO US ENGLISH]	04/03/2026 16:11
8.40	[TRANSLATED FRONTEND TO US ENGLISH]	04/03/2026 16:10
8.41	[RESTORED DETAILED SOURCES VIEW (ARTICLES + EVENTS) IN US ENGLISH]	04/03/2026 15:50
8.41	[RESTORED DETAILED SOURCES VIEW (ARTICLES + EVENTS) IN US ENGLISH]	04/03/2026 15:46
8.40	[REVERTED TO STANDARD TABLE LAYOUT (US ENGLISH)]	04/03/2026 15:40
8.39	[FIXED DB CONNECTION SCOPE IN SOURCES LOGIC]	04/03/2026 15:38
8.38	[TRANSLATED SOURCES VIEW TO US ENGLISH]	04/03/2026 15:01
8.37	[FULL FRONTEND TRANSLATION (MENU, FEED, COMMENTS, TTS) TO US ENGLISH.]	04/03/2026 14:58
8.67	[MANUAL OVERRIDE OF GREEK MENU ITEMS]	04/03/2026 13:36
8.66	[NGINX OPTIMIZED MENU FIX]	04/03/2026 13:33
8.65	[FIXED GREEK MENU ITEMS]	04/03/2026 13:32
8.60	[MENU & UI LOCALIZATION TO US ENGLISH]	04/03/2026 13:30
8.50	[FULL TRANSLATION TO US ENGLISH]	04/03/2026 13:27
9.75	[INJECTED EVENT FUSION_SUMMARY INTO FEED LOOPS TO DISPLAY AI TAGS CORRECTLY]	26/02/2026 14:44

22/03 15:04 dev.to

Your LLM prompts are probably wasting 90% of tokens. Here’s how I fixed mine.

LLM prompts token waste retrieval pipeline context fusion CFAdv duplicate context

16/03 06:00 venturebeat.com

How LinkedIn replaced five feed retrieval systems with one LLM model, at 1.3 billion-user scale

LinkedIn LLM feed architecture 1.3B users retrieval pipeline ranking

16/03 06:00 venturebeat.com

How LinkedIn replaced five feed retrieval systems with one LLM model, at 1.3 billion-user scale

LinkedIn LLM feed architecture 1.3B users retrieval pipeline ranking

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