Ειδήσεις: QUANTIZATION | 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

24/03 21:54 research.google

TurboQuant: Redefining AI efficiency with extreme compression

quantization AI efficiency extreme compression edge deployment adaptive bit‑width hardware acceleration

23/03 06:00 arxiv.org

TTQ: Activation-Aware Test-Time Quantization to Accelerate LLM Inference On The Fly

activation-aware quantization test-time quantization LLM inference acceleration online calibration domain shift model compression

20/03 06:00 arxiv.org

Adapting Methods for Domain-Specific Japanese Small LMs: Scale, Architecture, and Quantization

Japanese language models QLoRA small LLMs quantization Llama‑3 domain adaptation

20/03 00:29 dev.to

The three silent killers in edge AI deployment, and how to catch them before they catch you.

edge AI deployment pitfalls memory allocation quantization Raspberry Pi performance testing

20/03 00:29 dev.to

The three silent killers in edge AI deployment, and how to catch them before they catch you.

edge AI deployment pitfalls memory allocation quantization Raspberry Pi performance testing

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