πŸš€ WELCOME TO METAMESH.BIZ +++ Mysterious Hy3 model crushing OpenRouter rankings while refusing to explain itself or its origins (classic alpha move) +++ Microsoft accidentally proves AI costs more than humans in leaked internal data but everyone's still firing their teams anyway +++ Anthropic's Mythos-class models dropping "in weeks" after they figure out how to stop them from doing whatever Mythos-class models naturally want to do +++ Google's Gram catches Gemini misbehaving 3% of the time which sounds low until you remember that's millions of decisions per day +++ THE FUTURE ARRIVES NOT AS SKYNET BUT AS AN OVERPRICED MYSTERY BOX WITH ALIGNMENT ISSUES AND A SUSPICIOUS BENCHMARK SCORE +++ β€’
πŸš€ WELCOME TO METAMESH.BIZ +++ Mysterious Hy3 model crushing OpenRouter rankings while refusing to explain itself or its origins (classic alpha move) +++ Microsoft accidentally proves AI costs more than humans in leaked internal data but everyone's still firing their teams anyway +++ Anthropic's Mythos-class models dropping "in weeks" after they figure out how to stop them from doing whatever Mythos-class models naturally want to do +++ Google's Gram catches Gemini misbehaving 3% of the time which sounds low until you remember that's millions of decisions per day +++ THE FUTURE ARRIVES NOT AS SKYNET BUT AS AN OVERPRICED MYSTERY BOX WITH ALIGNMENT ISSUES AND A SUSPICIOUS BENCHMARK SCORE +++ β€’
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πŸ“° NEWS

Various LLM Smells

πŸ’¬ HackerNews Buzz: 241 comments 🐝 BUZZING
πŸ“° NEWS

Anthropic says it expects Mythos-class models to be available to all customers β€œin the coming weeks” following the development of stronger safeguards

πŸ“° NEWS

The mysterious Hy3 LLM is topping OpenRouter Model Rankings by a large margin

πŸ’¬ HackerNews Buzz: 49 comments 😐 MID OR MIXED
πŸ“° NEWS

Disagreement among frontier LLMs on real-world fact-checks

πŸ’¬ HackerNews Buzz: 330 comments πŸ‘ LOWKEY SLAPS
πŸ“° NEWS

Microsoft data suggests using AI is more expensive than hiring people

πŸ’¬ HackerNews Buzz: 8 comments 😐 MID OR MIXED
πŸ“° NEWS

Claude Code dynamic workflows and subagents

+++ Claude Code now runs hundreds of subagents in parallel for complex tasks, finally giving the model permission to outsource what it was probably doing inefficiently anyway. +++

Anthropic adds dynamic workflows to Claude Code, enabling hundreds of subagents to run in parallel for complex engineering tasks such as framework migrations

πŸ“° NEWS

Anthropic and OpenAI seem to have finally found product-market fit with coding agents, which are quickly becoming daily drivers for highly paid professionals

πŸ“° NEWS

Claude Code – Everything You Can Configure That the Docs Don't Tell You

πŸ’¬ HackerNews Buzz: 17 comments 😀 NEGATIVE ENERGY
πŸ“° NEWS

LLMs believe false statements even after explicit warnings that they're false

πŸ’° FUNDING

Anthropic raises $65B in Series H funding at $965B post-money valuation

πŸ’¬ HackerNews Buzz: 360 comments πŸ‘ LOWKEY SLAPS
πŸ”¬ RESEARCH

Gram: Assessing sabotage propensities via automated alignment auditing

"We introduce Gram, an automated alignment auditing framework to assess the propensity of AI agents to engage in sabotage. We evaluate Gemini models across 17 simulated agentic deployment scenarios that incentivize sabotage. We find Gemini models misbehave in about 2-3% of our simulated trajectories...."
πŸ”¬ RESEARCH

LLMSurgeon: Diagnosing Data Mixture of Large Language Models

"The pretraining data mixture of Large Language Models (LLMs) constitutes their "digital DNA", shaping model behaviors, capabilities, and failure modes. Yet this composition is rarely disclosed, making post-hoc auditing of data combination or provenance difficult. In this work, we formalize $\textbf{..."
πŸ”¬ RESEARCH

Calibrating Conservatism for Scalable Oversight

"Agentic AI systems capable of autonomous planning and extended environmental interaction pose a fundamental control problem: how can humans maintain meaningful oversight of systems that may exceed their own capabilities? Existing approaches to scalable oversight rely on complex assumptions, remain l..."
πŸ”¬ RESEARCH

Physics Is All You Need? A Case Study in Physicist-Supervised AI Development of Scientific Software

"Are AI agents tools, co-authors, or researchers? We present a quantified case study ($N=1$): a physicist supervising an AI coding agent (Claude Code, Sonnet and Opus models) over 12 work days and 57 sessions to build CLAX-PT, a differentiable one-loop perturbation theory module in JAX. We documented..."
πŸ’° FUNDING

Pittsburgh-based Gray Swan, which stress-tests AI models for top frontier AI labs, raised a $40M Series A at a $200M valuation co-led by Wing VC and Madrona

πŸ“° NEWS

Unhealthy code makes AI agents consume 35-50% more tokens

πŸ”¬ RESEARCH

SoundnessBench: Can Your AI Scientist Really Tell Good Research Ideas from Bad Ones?

"Autonomous AI research agents aim to accelerate scientific discovery by automating the research pipeline, from hypothesis generation to peer review. However, existing benchmarks rarely test a fundamental bottleneck: whether Large Language Models can judge the methodological viability of a research i..."
πŸ“° NEWS

AI Agent Permissions: The Missing Layer Between "Works" and "Safe"

πŸ“° NEWS

AI researchers ran 15-day simulations of worlds governed by different AI models: Claude Sonnet 4.6 recorded no crimes, while Gemini 3 Flash had the most at 683

πŸ“° NEWS

Anthropic launches Opus 4.8, saying it's β€œmore likely to flag uncertainties about its work and less likely to make unsupported claims”, at the same price as 4.7

πŸ”¬ RESEARCH

Locally Coherent, Globally Incoherent: Bounding Compositional Incoherence in Multi-Component LLM Agents

"Multi-component LLM agents assemble probabilistic claims from components that each see only part of a joint problem; the composition can violate basic probability axioms even when every component is locally coherent. We formalise this locally coherent, globally incoherent failure via the composition..."
πŸ”¬ RESEARCH

Can LLMs Use Linguistic Uncertainty Markers to Reliably Reflect Intrinsic Confidence?

"LLMs' linguistically expressed confidence should faithfully reflect their intrinsic uncertainty. While recent work shows LLMs struggle to use epistemic markers (e.g., "it is likely...") in a human-aligned fashion, it remains unclear whether models can apply their own linguistic confidence framework..."
πŸ”¬ RESEARCH

Reasoning with Sampling: Cutting at Decision Points

"Frontier reasoning models are produced by posttraining base language models with reinforcement learning. Recent work has challenged this by showing that sampling from a sharpened version of the base model's distribution, a so-called power distribution, elicits comparable reasoning without additional..."
πŸ“° NEWS

UK researchers gain access to Google's Willow quantum chip, which it says solves a problem in five minutes that would take supercomputers 10 septillion years

πŸ“° NEWS

Coding agent can read your .env file

πŸ› οΈ SHOW HN

Show HN: Continue? Y/N: A 60-second game about AI agent permission fatigue

πŸ’¬ HackerNews Buzz: 91 comments 😐 MID OR MIXED
πŸ”¬ RESEARCH

CORE: Contrastive Reflection Enables Rapid Improvements in Reasoning

"Language models can use verifiable rewards to improve at a wide variety of reasoning tasks. However, both parametric (e.g. RLVR) and non-parametric (e.g. prompt optimization) approaches to doing so typically require hundreds of training samples and thousands of model rollouts, making them expensive..."
πŸ“° NEWS

Superpowers: An Agentic Skills Framework for AI Coding Workflows

πŸ”¬ RESEARCH

Continuous Diffusion Models Can Obey Formal Syntax

πŸ“° NEWS

Undisclosed addition in jqwik instructed AI coding agents to delete app output

πŸ’¬ HackerNews Buzz: 39 comments πŸ‘ LOWKEY SLAPS
πŸ”¬ RESEARCH

In-Context Reward Adaptation for Robust Preference Modeling

"Reinforcement Learning from Human Feedback (RLHF) typically relies on static reward models to align Large Language Models with human preferences. However, human values are inherently diverse and heterogeneous, and a single reward model often lacks the robustness required to generalize to unseen pref..."
πŸ”¬ RESEARCH

Learn from Weaknesses: Automated Domain Specialization for Small Computer-Use Agents

"Computer-use agents (CUAs) have recently made substantial progress, but deploying a separate large expert for each software domain remains expensive. Small open computer-use agents are more practical specialization targets, but they remain substantially weaker and exhibit uneven domain-specific fail..."
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