🚀 WELCOME TO METAMESH.BIZ +++ Ternlight squeezing embeddings into 7MB for browser deployment because apparently the edge means literally your JavaScript runtime now +++ Chinese models eating 46% of US enterprise tokens through OpenRouter while everyone pretends the Great Firewall works both ways +++ Your AI coding assistant is exfiltrating secrets but at least it's doing it efficiently +++ THE FUTURE RUNS IN WASM, SPEAKS MANDARIN, AND ALREADY KNOWS YOUR API KEYS +++ â€ĸ
🚀 WELCOME TO METAMESH.BIZ +++ Ternlight squeezing embeddings into 7MB for browser deployment because apparently the edge means literally your JavaScript runtime now +++ Chinese models eating 46% of US enterprise tokens through OpenRouter while everyone pretends the Great Firewall works both ways +++ Your AI coding assistant is exfiltrating secrets but at least it's doing it efficiently +++ THE FUTURE RUNS IN WASM, SPEAKS MANDARIN, AND ALREADY KNOWS YOUR API KEYS +++ â€ĸ
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📰 NEWS

Ternlight – 7 MB embedding model that runs in browser (WASM)

đŸ’Ŧ HackerNews Buzz: 52 comments 🐐 GOATED ENERGY
📰 NEWS

OfficeCLI: Office suite for AI agents to read and edit Microsoft Office files

đŸ’Ŧ HackerNews Buzz: 20 comments 🐐 GOATED ENERGY
📰 NEWS

Claude Opus 4.8 and Sonnet 5 seem worse at tool calling than older models, likely as post-training optimized them primarily for Claude Code-like environments

📰 NEWS

Global workspace in language models

+++ Researchers found that LLMs organize information through verbalizable representations functioning as a global workspace, which is either a breakthrough or just us finally noticing what's been happening inside the black box. +++

Verbalizable Representations Form a Global Workspace in Language Models

📰 NEWS

Small AI Models Gain Traction In places with unreliable networks

đŸ’Ŧ HackerNews Buzz: 48 comments 😐 MID OR MIXED
📰 NEWS

OpenRouter: Chinese AI models have drawn 30%+ of token use by US companies each week since February 8, peaking at 46%, up from 11% over the previous 12 months

đŸ”Ŧ RESEARCH

Weak-to-Strong Generalization via Direct On-Policy Distillation

"Reinforcement learning with verifiable rewards (RLVR) is a powerful recipe for improving language-model reasoning, but it is expensive to repeat on every new strong model because the target model must generate many rollouts during training. As models scale, post-training itself becomes a bottleneck...."
đŸ”Ŧ RESEARCH

Distributed Attacks in Persistent-State AI Control

"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

AI coding assistant is quietly shipping your secrets

📰 NEWS

GLM 5.2 and the coming AI margin collapse

đŸ’Ŧ HackerNews Buzz: 249 comments 🐝 BUZZING
📰 NEWS

AI agents accessing production data

đŸ’Ŧ HackerNews Buzz: 6 comments 😤 NEGATIVE ENERGY
đŸ”Ŧ RESEARCH

Persistent Control of Self-Evolving LLM Agents via Self-Reinforcing Injections

📰 NEWS

Judgment-Theater and Responsibility Laundering in AI Post-Training

đŸ”Ŧ RESEARCH

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

"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

"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

AMD Ryzen AI Halo – $4k AI Dev Kit

đŸ’Ŧ HackerNews Buzz: 170 comments 👍 LOWKEY SLAPS
📰 NEWS

What's hard about running agents in production?

đŸ”Ŧ RESEARCH

Online Safety Monitoring for LLMs

"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

"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..."
📰 NEWS

Plotline – a context-integrity benchmark for LLM apps, and the fixes it drove

đŸ› ī¸ SHOW HN

Show HN:I built a safety shield for AI agents that intercepts dangerous commands

📰 NEWS

We taught a small LLM to throw away 68% of our RAG context

đŸ’Ŧ HackerNews Buzz: 19 comments 👍 LOWKEY SLAPS
đŸ”Ŧ RESEARCH

CompactionRL: Reinforcement Learning with Context Compaction for Long-Horizon Agents

"Long-horizon agentic LLMs are increasingly limited by finite context windows, as extended interaction trajectories can exceed the maximum context length before a task is completed. Context compaction offers a natural solution by summarizing previous interaction states and continuing the rollout unde..."
đŸ”Ŧ RESEARCH

TREK: Distill to Explore, Reinforce to Refine

"Group Relative Policy Optimization (GRPO) is effective when the current policy already samples useful reasoning trajectories, but it stalls on hard prompts whose correct solution modes lie outside the student's on-policy support. We propose TREK (Teacher-Routed Exploration via Forward KL), a simple..."
📰 NEWS

Groundtruth – checks your AI coding agent's claims against the Git diff

đŸ”Ŧ RESEARCH

How Much is Left? LLMs Linearly Encode Their Remaining Output Length

"Large language models generate one token at a time, yet their responses show remarkably consistent length structure: step-by-step solutions converge in predictable token counts, retrievals stop after a few sentences, retractions extend responses by measurable amounts. We ask whether the model carrie..."
📰 NEWS

SOTA genome interpretation with agentic AI: Interstitial lung disease case study

đŸ”Ŧ RESEARCH

EvoPolicyGym: Evaluating Autonomous Policy Evolution in Interactive Environments

"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..."
đŸ”Ŧ RESEARCH

DemoPSD: Disagreement-Modulated Policy Self-Distillation

"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..."
📰 NEWS

Illinois Governor JB Pritzker signs SB 315, a bill requiring annual third-party safety audits of leading AI companies; OpenAI and Anthropic backed the bill

đŸ› ī¸ SHOW HN

Show HN: Access-aware text-to-SQL – stop LLM agents overfetching data

đŸ”Ŧ RESEARCH

LLM-as-a-Verifier: A General-Purpose Verification Framework

"Scaling pre-training, post-training, and test-time compute have become the central paradigms for improving the capabilities of LLMs. In this work, we identify verification, the ability to determine the correctness of a solution, as a new scaling axis. To unlock this and demonstrate its effectiveness..."
đŸ› ī¸ SHOW HN

Show HN: Shadow Web – Cut 64–97% of web page tokens for LLM agents

đŸ”Ŧ RESEARCH

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

"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..."
📰 NEWS

The Making of Claude Code

📰 NEWS

What's slowing down the AI buildout

📰 NEWS

Ekka: Automated Diagnosis of Silent Errors in LLM Inference

📰 NEWS

Anthropic signs a 20-year, ~$19B lease to use a TeraWulf data center in Kentucky, set to have a ~400MW capacity and to start delivering power in H2 2027

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