10:06
Toto 2.0: Datadog’s Observability AI Model – Full Install + Live Dashboard
Datadog has released Toto 2, an open-source family of time series foundation models purpose-built for observability and DevOps teleme...
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10:46
Ring-2.6-1T: The 1 Trillion Parameter Open Source Model That NO ONE Can Run
Inclusion AI has released Ring 2.6, a one-trillion-parameter open-weights model under the MIT license, but YouTuber Fahd Mirza argues...
19:11
Your Agent Can Now Train Models — Merve Noyan, Hugging Face
Merve Noyan from the Hugging Face open-source team delivers a broad survey of the current open-model landscape alongside several firs...
22:54
This 100% uncensored AI model is insane… let’s run it
David Ondrej walks through the rationale, setup, and practical use of uncensored large language models running locally in 2026. The v...
11:24
This 100% Local AI Automation Pipeline Blows My Mind
The All About AI channel documents an ambitious experiment: assembling a complete video production pipeline using only locally-run, o...
11:00
NVIDIA Nemotron Elastic: 3-in-1 Elastic LLM Like Russian Dolls in One File
NVIDIA's Nemotron Elastic model family packs three reasoning models — 30B, 23B, and 12B parameters — into a single checkpoint file us...
12:04
Z-Anime: Natural Anime with Studio Quality in Seconds – Run Locally
Fahd Mirza walks through the full local installation and generation workflow for Z-Anime (ZZZ Anime), a newly released anime-focused...
08:43
DFlash Drafter for Gemma 4 26B – Official Speculative Decoding is Here: Run Locally
ZLab, the UC San Diego research team that invented DFlash speculative decoding, has released the first official drafter model paired...
08:41
Gemma 4 31B at 196 tok/s with RedHat DFlash Speculator Locally
This hands-on tutorial from the Fahd Mirza channel demonstrates running Google's Gemma 4 31B model locally at 196 tokens per second u...
23:58
Accelerating AI on Edge — Chintan Parikh and Weiyi Wang, Google DeepMind
Chintan Parikh, product manager for LiteRT at Google AI Edge, and Weiyi Wang from Google DeepMind present at AI Engineer on deploying...