The Top AI Papers of the Week (March 23 – 29) – Claudini
– MemCollab
– ARC-AGI-3
– Composer 2
– Hyperagents
– Attention Residuals
– Agentic AI and the Next Intelligence Explosion Read on for more:
LLMS
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Top AI Papers of the Week: March 23-29
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ChatGPT 26 Times More Likely Give Dangerous Responses Study
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People on this site regularly give me shit, and almost always turn out to be wrong. Like when I said LLMs might well contribute to delusions, and people doubted me. New study shows that ChatGPT was 26 times more likely than a control to give dangerous responses to people
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Fast mode outperforms Claude while maintaining subscription inclusion
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not anymore, this got fixed, and if you enable /fast it’s faster than Claude (while still included in your sub)
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Codex efficiency improvements reduce need for context workarounds
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codex is so much better at being efficient with context window that this is rarely needed anymore. This was an old claude workaround.
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RL Post-training Efficiency: 4x Fewer Rollouts for Coding
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4x fewer rollout turns for competitive accuracy is a big deal for making RL post-training practical. Curious to see if this generalizes beyond coding tasks.
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Model Improvements Reduce Need for Complex Workflows
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That was last year’s workflow, not doing that much anymore, models got better.
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Autonomous AI Agent Implements Voice Transcription and Response Workflow
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This is nuts: Clawdbot figured out how to transcribe and respond to a voice message on its own, detecting the Opus format, converting it via FFmpeg, calling OpenAI’s Whisper with a found API key, and replying as if voice support had always existed.
— Chubby♨️ (@kimmonismus) 29 mars 2026
pic.twitter.com/n9kmt8eNjRThis is nuts: Clawdbot figured out how to transcribe and respond to a voice message on its own, detecting the Opus format, converting it via FFmpeg, calling OpenAI’s Whisper with a found API key, and replying as if voice support had always existed.
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Kyutai and Moshi: Strategic positioning in AI solutions
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c'est parcqu'ils veulent mettre en avant l'autre solution Moshi avec kyutai
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KV Cache Optimization and DDR5 Memory Pricing Misconception
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The claim mixes up memory types: KV cache optimization (like TurboQuant) reduces GPU VRAM usage during inference, not system memory like DDR5 RAM. DDR5 prices are driven by broader semiconductor supply-demand cycles, so there’s no direct link between KV cache compression and