▶

AgenteAbierto · YouTube Analyzer

DocType: YouTube Video

Reproductor de Video

Campo embed (DocField):
embed · Text/HTML

Open Source AI Is Getting Too Big to Run

Todos los campos y metadatos del DocType YouTube Video · agenteabierto_web
Documento activo
nameData · PK
Identificador único del documento. Clave primaria autogenerada por Frappe Framework.
qW5UDpHZBPw
titleData · Req
Título descriptivo del video de YouTube. Campo de texto principal visible en listas y vistas.

None

embedText · HTML
Código embed de YouTube (iframe). Este campo alimenta directamente el reproductor. Contiene la URL con video ID y parámetros.
None
youtube_urlData · URL
URL completa del video en YouTube. Usada para extraer el video_id y construir el embed dinámicamente.

None

descriptionText · Long
Descripción detallada del contenido del video. Puede incluir resumen, puntos clave, transcripción parcial o notas del editor.
None
categoryLink · Select
Categoría temática del video. Permite clasificar y filtrar el contenido por área de conocimiento o temática.
None

Campos del Sistema Frappe

ownerData · System

contacto@interconectando.com

creationDatetime · Auto
2026-07-28 11:57:49.614209
modifiedDatetime · Auto
2026-07-28 11:57:49.614209
modified_byData · System
contacto@interconectando.com
docstatusInt · 0=Draft 1=Sub 2=Can

0

Mapa de DataKeys y Fieldnames

fieldnamefieldtypedata_key
nameDataqW5UDpHZBPw
title

Data

Open Source AI Is Getting Too Big to Run
embedTexthttps://www.youtube.com/embed/qW5UDpHZBPw
youtube_urlDatahttps://www.youtube.com/watch?v=qW5UDpHZBPw
descriptionLong TextTwo major open-model releases arrived this week from very different directions. Both geographically and conceptually. Kimi K3 is a 2.8-trillion-parameter Chinese model that jumped from #18 to #1 in the Frontend Code Arena, ahead of Claude Fable 5. WHAT?! Inkling is the first major model from Mira Murati’s Thinking Machines Lab, and the company states directly that it is not the strongest model available. WHAT?! Both strategies make sense once we examine what the companies are building. In this episode, we explain K3’s 896-expert architecture, why Moonshot recommends at least 64 accelerators, how LoRA customization works, what community quantization changed for Inkling, and which organizations gain meaningful control from open weights. Attention Span is here to explain the technical and business choices shaping AI. 👉 Subscribe for high-signal AI mechanics 👉 Into videos? Check our IG https://www.instagram.com/turingpost_tv and TikTok https://www.tiktok.com/@turingpost_tv 👉 More analysis: TuringPost.com 👉 Interviews: @realturingpost Links: About LoRA https://www.turingpost.com/p/lora Moonshot AI: The Chinese Unicorn Revolutionizing Long-Context AI https://www.turingpost.com/p/moonshotai Thinking Machines Lab, “Inkling: Our open-weights model” https://thinkingmachines.ai/news/introducing-inkling/ Thinking Machines Lab, Inkling Model Card https://thinkingmachines.ai/model-card/inkling/ Thinking Machines Lab, Tinker https://thinkingmachines.ai/tinker/ Moonshot AI, “Kimi K3: Open Frontier Intelligence” https://www.kimi.com/blog/kimi-k3 Arena, Kimi K3 Frontend Code Arena result https://x.com/arena/status/2077824029126504525 Semianalysis about Kimi K3 https://x.com/SemiAnalysis_/status/2077966560447074689 Arena, Code Arena methodology https://arena.ai/blog/code-arena/ Artificial Analysis, Kimi K3 https://artificialanalysis.ai/models/kimi-k3 Artificial Analysis, Inkling https://artificialanalysis.ai/articles/thinking-machines-has-released-inkling-the-new-leading-u-s-open-weights-model Unsloth, community Inkling quantizations https://unsloth.ai/docs/models/inkling #AI #ArtificialIntelligence #OpenSourceAI #LLM #MachineLearning #GenerativeAI #KimiK3 #MiraMurati #AIModels #TechNews

category

Link

doc.category
published_dateDate2026-07-17 21:00:19
is_publishedCheck0