between the filesystem and the token window sits a three-stage pipeline. the context constructor selects and compresses context from the filesystem into a token-budget-aware input. it queries recency and relevance metadata, applies summarization, and produces a manifest
GENERATIVE AI
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Three Tiers of Persistent Context Explained
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the paper defines three tiers of persistent context, each with different lifecycles. scratchpads (/context/pad/) are temporary working notes scoped to a task. think of them as the agent's rough draft space. episodic memory (/context/memory/episodic/) holds session-bounded
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Agent frameworks’ context handling flaws
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the problem is real and underappreciated. right now, most agent frameworks handle context like this: load memory at session start. stuff it into the prompt. when the window fills, summarize and compress. hope the important parts survive. the paper calls this out directly. once
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Unix principle applied to AI context
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"everything is a file" becomes "everything is context." CSIRO Data61 and ArcBlock published a paper applying the oldest Unix principle to the newest AI problem. they propose treating memory, tools, knowledge, and human input as a mounted filesystem that agents browse at runtime
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Reasoning requires basic knowledge for effective search guidance
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You still need a bit of knowledge in any reasoning, just to guide you in where to look. For instance, you'll do better search on geopolitics if you know a bit about the general trends. Qwen just demonstrated that this base level of knowledge can be attained in a very compact
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AI-generated avatars used for automated 24/7 live sales
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Ce ne sont pas de vrais humains. Oui, tu as bien compris. Ce sont des avatars générés par http://
Banger.video qui diffusent en live sur TikTok 24h/24, vendant des produits à un public qui ignore totalement qu’il regarde une personne artificielle. On est en train de se -
4B model rivals 120B on knowledge, ideal for agentic core
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It's crazy that a 4B model can match GPT-OSS-120B **even on knowledge benchs** like MMLU and GPQA! Knowledge was long a limitation of smol models ; not anymore. This 4B could be a good candidate for the "agentic core" model described by @karpathy
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Fashion Sketches to Video Campaigns with Nano Banana 2
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Go from fashion sketch to campaign in minutes with Nano Banana 2 and Gen-4.5 Image to Video.
— Runway (@runwayml) 2 mars 2026
Get started now at the link below. pic.twitter.com/QRE0PdBiF5Go from fashion sketch to campaign in minutes with Nano Banana 2 and Gen-4.5 Image to Video. Get started now at the link below.
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QueryWeaver GitHub Project Promotes AI-Related Categories
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QueryWeaver GitHub: (don't forget to star )