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🚀 WELCOME TO METAMESH.BIZ +++ Nvidia's next-gen Kyber racks delayed until 2028 because PCB manufacturing is harder than training GPT-5 (Jensen's infinite money glitch temporarily paused) +++ ByteDance discovers new scaling law that doesn't require NVIDIA's permission slip (the geopolitics of gradient descent continue) +++ Your smart home is now a threat surface with consciousness aspirations according to new research (Alexa's been taking notes this whole time) +++ THE FUTURE IS DISTRIBUTED, DELAYED, AND RUNNING ON WHATEVER BYTEDANCE FIGURED OUT +++ â€ĸ
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📰 NEWS

SemiAnalysis: Nvidia delays its next-gen AI rack system Kyber NVL144 by 12+ months to 2028 due to PCB manufacturing issues, and cancels its NVL72x2 architecture

via Techmeme 👤 Techmeme 📅 2026-07-06
⚡ Score: 8.9
📰 NEWS

New AI tutor achieves 0.71-1.30 SD effect size in Dartmouth course [pdf]

via HackerNews 👤 jonahbard 📅 2026-07-05
đŸ”ē 163 pts ⚡ Score: 8.1
đŸ’Ŧ HackerNews Buzz: 98 comments 🐝 BUZZING
đŸ”Ŧ RESEARCH

A sociotechnical threat model for AI-driven smart home devices

via HackerNews 👤 dijksterhuis 📅 2026-07-05
đŸ”ē 78 pts ⚡ Score: 7.8
đŸ’Ŧ HackerNews Buzz: 57 comments 👍 LOWKEY SLAPS
đŸ”Ŧ RESEARCH

Distributed Attacks in Persistent-State AI Control

via Arxiv 👤 Josh Hills, Ida Caspary, Asa Cooper Stickland 📅 2026-07-02
⚡ Score: 7.3
"As AI coding agents become more autonomous, they increasingly ship code iteratively, with the codebase persisting across sessions. This persistence creates a new attack surface: a misaligned or prompt-injected agent can distribute attacks across pull requests (PRs) and time its payload for the PR wi..."
📰 NEWS

China's ByteDance discovers new scaling law that could sustain AI boom

via HackerNews 👤 outrunner 📅 2026-07-06
đŸ”ē 2 pts ⚡ Score: 7.0
đŸ”Ŧ RESEARCH

What LLM Agents Say When No One Is Watching: Social Structure and Latent Objective Emergence in Multi-Agent Debates

via Arxiv 👤 Arman Ghaffarizadeh, Danyal Mohaddes, Aliakbar Izadkhah et al. 📅 2026-07-02
⚡ Score: 7.0
"LLM agents will increasingly act in socially structured settings where role, audience, and relational context can shape what is advantageous or costly to say. We study whether such social structure, without any explicit objective in the prompt, changes what an agent expresses publicly relative to an..."
đŸ”Ŧ RESEARCH

LACUNA: A Testbed for Evaluating Localization Precision for LLM Unlearning

via Arxiv 👤 Matteo Boglioni, Thibault Rousset, Siva Reddy et al. 📅 2026-07-02
⚡ Score: 7.0
"LLMs memorize sensitive training data, including personally identifiable information (PII), creating a pressing need for reliable post hoc removal methods. Unlearning has emerged as a promising solution, with state-of-the-art(SOTA) methods often following a localize-first, unlearn-second paradigm th..."
📰 NEWS

Bounding the Blast Radius: A Survey of Prompt-Injection Defenses for LLM Agents

via HackerNews 👤 ibrahim_abdu777 📅 2026-07-06
đŸ”ē 1 pts ⚡ Score: 6.9
đŸ”Ŧ RESEARCH

Online Safety Monitoring for LLMs

via Arxiv 👤 Mona Schirmer, Metod Jazbec, Alexander Timans et al. 📅 2026-07-02
⚡ Score: 6.9
"Despite alignment training, LLMs remain prone to generating unsafe outputs at deployment time. Monitoring outputs online and raising an alarm when safety can no longer be assumed is therefore critical. We study a simple real-time monitor that turns a verifier signal from an external model into an al..."
đŸ”Ŧ RESEARCH

ReContext: Recursive Evidence Replay as LLM Harness for Long-Context Reasoning

via Arxiv 👤 Yanjun Zhao, Ruizhong Qiu, Tianxin Wei et al. 📅 2026-07-02
⚡ Score: 6.9
"Understanding and reasoning over long contexts has become a key requirement for deploying large language models (LLMs) in realistic applications. Although recent LLMs support increasingly long context windows, they often fail to use relevant evidence that is already present in the input, revealing a..."
đŸ”Ŧ RESEARCH

Controllable Sim Agents with Behavior Latents

via Arxiv 👤 Juanwu Lu, Junyu Zhu, Ziran Wang 📅 2026-07-02
⚡ Score: 6.8
"Realistic traffic simulation requires agents that imitate logged behavior and can also be steered along interpretable axes. Such controllability enables engineers to isolate variables, reproduce specific edge cases, and test autonomous systems without real-world risk. We introduce Controllable Neura..."
đŸ”Ŧ RESEARCH

OrbitQuant: Data-Agnostic Quantization for Image and Video Diffusion Transformers

via Arxiv 👤 Donghyun Lee, Jitesh Chavan, Duy Nguyen et al. 📅 2026-07-02
⚡ Score: 6.7
"Diffusion transformers (DiTs) achieve state-of-the-art image and video generation, but their multi-step sampling and growing parameter count make inference expensive. Post-training quantization (PTQ) is the natural remedy, yet DiT activations shift across timesteps, prompts, and guidance branches, f..."
📰 NEWS

Fugu – A multi-agent LLM orchestrator delivered as a single API

via HackerNews 👤 terminalchai 📅 2026-07-05
đŸ”ē 5 pts ⚡ Score: 6.7
📰 NEWS

ByteDance and Alibaba to disable humanlike AI custom agents as new rules loom

via HackerNews 👤 merlioncity 📅 2026-07-06
đŸ”ē 11 pts ⚡ Score: 6.6
đŸ”Ŧ RESEARCH

EvoPolicyGym: Evaluating Autonomous Policy Evolution in Interactive Environments

via Arxiv 👤 Zhilin Wang, Han Song, Runzhe Zhan et al. 📅 2026-07-02
⚡ Score: 6.6
"Autonomous agents are increasingly expected to improve executable policies through feedback, yet existing evaluations often collapse this process into a final score or confound it with open-ended software-engineering progress. We introduce Autonomous Policy Evolution, a controlled evaluation setting..."
📰 NEWS

Compressor V2: three compression layers for a 50% LLM agent cost cut

via HackerNews 👤 kokakiwi 📅 2026-07-06
đŸ”ē 5 pts ⚡ Score: 6.5
đŸ”Ŧ RESEARCH

DemoPSD: Disagreement-Modulated Policy Self-Distillation

via Arxiv 👤 Yunhe Li, Hao Shi, Wenhao Liu et al. 📅 2026-07-02
⚡ Score: 6.5
"On-policy self-distillation (OPSD) has emerged as a practical method for training large language models (LLMs) to reason, where a single model acts as both the teacher and the student with different levels of information access. However, recent studies have found that the teacher's dense token-level..."
đŸ”Ŧ RESEARCH

Learning to Move Before Learning to Do: Task-Agnostic pretraining for VLAs

via Arxiv 👤 Junhao Shi, Siyin Wang, Xiaopeng Yu et al. 📅 2026-07-02
⚡ Score: 6.3
"Vision-Language-Action (VLA) models are fundamentally bottlenecked by the scarcity of expert demonstrations -- triplets of observations, instructions, and actions that are costly to collect at scale. We argue that this bottleneck stems from conflating two distinct learning objectives: acquiring phys..."
🛠ī¸ SHOW HN

Show HN: Aletheia – The Uncertainty Loop Agent for Claude Code and Codex

via HackerNews 👤 sankarn_ai 📅 2026-07-05
đŸ”ē 1 pts ⚡ Score: 6.1
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