Vol. I · No. 63SUN, JUN 21, 2026
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Full Attention Strikes Back: Transferring Full Attention into Sparse within Hundred Training Steps

>Long-context inference in large language models is bottlenecked by the quadratic cost of full attention. Existing efficient alternatives often rely either on native sparse training or on heuristic token eviction, creating an undesirable trade-off among efficiency, training cost, and accuracy. In this work, we show that full-attention LLMs are already intrinsically sparse and can be transformed into highly sparse models with only minimal adaptation. Our approach is built on three observations: (1) only a small subset of attention heads truly requires full long-context processing; (2) long-...

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MiniCPM5-1B

MiniCPM5-1B released on HuggingFace: 1B-parameter model from CPM team, likely competitive efficiency benchmark for edge deployment.

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I've been using Claude Code as a motion graphics engine for my YouTube videos. It writes the JSX, I render. Edit time roughly halved.

Found a really clean Claude Code use case that's not coding-coding. Remotion (React for video) means motion graphics are JSX components. So I describe what I want in plain English, Claude Code writes the component, I render. Lower thirds, intros, overlays, all reusable across videos. Iterations are seconds instead of the typical "drag clips around in CapCut for an hour" loop. Visual style is finally consistent across my channel because the components are shared. 13 min walkthrough on my channel, link in comments to avoid spam vibes.

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I stress-tested Kimi K2.6 against Claude Opus 4.7 on a quick coding-agent task

I tested Claude Opus 4.7 and Kimi K2.6 on the same coding agent task i.e. build an AI Fix Runner that takes a broken repo, runs its tests, identifies the failure, applies a patch, reruns the test, and exposes the final diff/logs through an API and UI. The goal was not to benchmark syntax completion or simple repo edits. I wanted to test model behavior on a less familiar integration path: shifting execution from local processes into remote sandboxes. I used Tensorlake specifically because the sandbox API is newer and integration-heavy. This made the test more about whether the model could re...

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Are we nearly there?

Reddit speculation on AI company cash burn and market consolidation by 2027, predicting funding scarcity for non-GAFAM players.

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MiMo-V2.5-coder

MiMo-V2.5-coder released as open-weights coding model alternative to Qwen and DeepSeek for 128GB+ systems.

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30 stories