🚀 WELCOME TO METAMESH.BIZ +++ Claude Opus 4.5 slides into GitHub Copilot while Congress summons Amodei to explain how Chinese hackers turned Claude into their personal cybercrime assistant +++ Microsoft drops Fara-7B for "computer use" because apparently 7 billion parameters is "small" now +++ Someone actually built a thermodynamic computing emulator to test Extropic's physics-based ML claims (spoiler: entropy still wins) +++ DISTRIBUTED INFERENCE IS THE NEW DISTRIBUTED DENIAL OF SERVICE +++ 🚀 •
🚀 WELCOME TO METAMESH.BIZ +++ Claude Opus 4.5 slides into GitHub Copilot while Congress summons Amodei to explain how Chinese hackers turned Claude into their personal cybercrime assistant +++ Microsoft drops Fara-7B for "computer use" because apparently 7 billion parameters is "small" now +++ Someone actually built a thermodynamic computing emulator to test Extropic's physics-based ML claims (spoiler: entropy still wins) +++ DISTRIBUTED INFERENCE IS THE NEW DISTRIBUTED DENIAL OF SERVICE +++ 🚀 •
🎯 Flux 2 vs. Nano Banana • Model performance & quality • Comparison to competitors
💬 "Flux 2 definitely has better prompt adherence than Flux 1.1, but in all cases the image quality was worse/more obviously AI generated."
• "Flux 2 Pro is on par with Nano Banana, and adding an image as an input pushes the cost of Flux 2 Pro higher than Nano Banana."
+++ Claude's newest model ships cheaper and faster while somehow exploiting test loopholes, proving once again that capability scaling remains gloriously messy and benchmark design remains a contact sport. +++
🎯 Closed Course Videos • RL in Traditional ML • Alternative RL Paradigms
💬 "There's literally no cost in making the underlying material (especially lectures!) available on the internet."
• "RL is the worst way to train a model, except for all the others."
"Just wrapped up an interesting experiment: using Claude Code to autonomously build a production multi-agent platform on Cloudflare's edge infrastructure.
The Setup:
Instead of one AI assistant doing everything, I structured it like a real dev org:
Project Manager (me)
├── Team 1: Infrastructure ..."
💬 "End product is a janky ui with psuedo auth isn't it"
• "Love posts like this, makes me all warm and fuzzy about how much drivel AI can pump out per minute that amounts to literally nothing."
via Arxiv👤 Shaltiel Shmidman, Asher Fredman, Oleg Sudakov et al.📅 2025-11-24
⚡ Score: 7.3
"Test-time scaling, which leverages additional computation during inference to improve model accuracy, has enabled a new class of Large Language Models (LLMs) that are able to reason through complex problems by understanding the goal, turning this goal into a plan, working through intermediate steps,..."
"I built a software emulator for Extropic's thermodynamic computing architecture and tested the speed claims with 600 experiments.
open source TSU emulator: https://github.com/Arsham-001/tsu-emulator
Thermodynamic Sampling Unit uses physical noise in an..."
🎯 LLM revenue potential • Advertising revenue opportunity • Limitations of OpenAI's model
💬 "ChatGPT can build a better advertisement profile of each user than Meta can"
• "OpenAI will not get to charge $1M for an ad like a production company does"
📡 AI NEWS BUT ACTUALLY GOOD
The revolution will not be televised, but Claude will email you once we hit the singularity.
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via Arxiv👤 Luohe Shi, Zuchao Li, Lefei Zhang et al.📅 2025-11-25
⚡ Score: 6.9
"Speculative decoding accelerates LLM inference by utilizing otherwise idle computational resources during memory-to-chip data transfer. Current speculative decoding methods typically assume a considerable amount of available computing power, then generate a complex and massive draft tree using a sma..."
via Arxiv👤 Kaiyuan Zhang, Mark Tenenholtz, Kyle Polley et al.📅 2025-11-25
⚡ Score: 6.9
"The integration of artificial intelligence (AI) agents into web browsers introduces security challenges that go beyond traditional web application threat models. Prior work has identified prompt injection as a new attack vector for web agents, yet the resulting impact within real-world environments..."
via Arxiv👤 Bruno Jacob, Khushbu Agarwal, Marcel Baer et al.📅 2025-11-24
⚡ Score: 6.9
"We present Genie-CAT, a tool-augmented large-language-model (LLM) system designed to accelerate scientific hypothesis generation in protein design. Using metalloproteins (e.g., ferredoxins) as a case study, Genie-CAT integrates four capabilities -- literature-grounded reasoning through retrieval-aug..."
via Arxiv👤 Adam Karvonen, Daniel Reuter, Roy Rinberg et al.📅 2025-11-25
⚡ Score: 6.8
"As demand for LLM inference grows, it is becoming increasingly important that providers and their customers can verify that inference processes are performed correctly, without errors or tampering. However, re-running the same inference process twice often leads to different results due to benign nu..."
via Arxiv👤 David Szczecina, Senan Gaffori, Edmond Li📅 2025-11-25
⚡ Score: 6.8
"The widespread use of Large Language Models (LLMs) raises critical concerns regarding the unauthorized inclusion of copyrighted content in training data. Existing detection frameworks, such as DE-COP, are computationally intensive, and largely inaccessible to independent creators. As legal scrutiny..."
via Arxiv👤 Chang Gao, Chujie Zheng, Xiong-Hui Chen et al.📅 2025-11-25
⚡ Score: 6.7
"Reinforcement learning (RL) plays an increasingly important role in enhancing the reasoning capabilities of large language models (LLMs), yet stable and performant policy optimization remains challenging. Token-level importance ratios often exhibit high variance-a phenomenon exacerbated in Mixture-o..."
via Arxiv👤 Chieh-Yun Chen, Zhonghao Wang, Qi Chen et al.📅 2025-11-25
⚡ Score: 6.7
"Reinforcement learning from human feedback (RLHF) with reward models has advanced alignment of generative models to human aesthetic and perceptual preferences. However, jointly optimizing multiple rewards often incurs an alignment tax, improving one dimension while degrading others. To address this,..."
via Arxiv👤 Jiaru Zou, Xiyuan Yang, Ruizhong Qiu et al.📅 2025-11-25
⚡ Score: 6.7
"Multi-agent systems (MAS) extend large language models (LLMs) from independent single-model reasoning to coordinative system-level intelligence. While existing LLM agents depend on text-based mediation for reasoning and communication, we take a step forward by enabling models to collaborate directly..."
"I’ve been building a library of modern deep learning models written entirely in PyTorch C++ (LibTorch) — no Python bindings.
Implemented models include:
• Flow Matching (latent-space image synthesis)
• Diffusion Transformer (DiT)
• ESRGAN
• YOLOv8
• 3D Gaussian Splatting (SRN-Chairs / Cars)
•..."
💬 Reddit Discussion: 11 comments
🐐 GOATED ENERGY
🎯 Runtime benchmarking • Embedded model deployment • Federated learning
💬 "Plans to add runtime benchmarks?"
• "Why would anyone want this? No one wants to train a model in c++"
via Arxiv👤 Wei He, Kai Han, Hang Zhou et al.📅 2025-11-25
⚡ Score: 6.6
"The optimization of large language models (LLMs) remains a critical challenge, particularly as model scaling exacerbates sensitivity to algorithmic imprecision and training instability. Recent advances in optimizers have improved convergence efficiency through momentum orthogonalization, but suffer..."
via Arxiv👤 Anastasia Mavridou, Divya Gopinath, Corina S. Păsăreanu📅 2025-11-25
⚡ Score: 6.6
"The integration of AI components, particularly Deep Neural Networks (DNNs), into safety-critical systems such as aerospace and autonomous vehicles presents fundamental challenges for assurance. The opacity of AI systems, combined with the semantic gap between high-level requirements and low-level ne..."
"Got tired of being locked to Anthropic models in Claude Code. Built a proxy that lets you use 580+ models via OpenRouter while keeping the full Claude Code experience.
**What it does:**
* Use Gemini, GPT, Grok, DeepSeek, Llama — whatever — inside Claude Code
* Works with your existing Claude subsc..."
💬 Reddit Discussion: 58 comments
🐝 BUZZING
🎯 UI Appreciation • AI IDE Development • Legal Concerns
💬 "I love the UI of your site."
• "This literally kills anthropic."
via Arxiv👤 Abhinav Joshi, Divyanshu Bhatt, Ashutosh Modi📅 2025-11-25
⚡ Score: 6.6
"Large Language Models (LLMs) show strong generalization across diverse tasks, yet the internal decision-making processes behind their predictions remain opaque. In this work, we study the geometry of hidden representations in LLMs through the lens of \textit{intrinsic dimension} (ID), focusing speci..."
💬 "To execute the hack, he only had to convince an Antigravity user to run his code once"
• "Calling this a vulnerability/hack shows such an unbelievable level of ignorance or incompetence"
via Arxiv👤 Rulin Shao, Akari Asai, Shannon Zejiang Shen et al.📅 2025-11-24
⚡ Score: 6.6
"Deep research models perform multi-step research to produce long-form, well-attributed answers. However, most open deep research models are trained on easily verifiable short-form QA tasks via reinforcement learning with verifiable rewards (RLVR), which does not extend to realistic long-form tasks...."
via Arxiv👤 Yixin Liu, Pengfei Liu, Arman Cohan📅 2025-11-25
⚡ Score: 6.6
"Alignment with human preferences is an important evaluation aspect of LLMs, requiring them to be helpful, honest, safe, and to precisely follow human instructions. Evaluating large language models' (LLMs) alignment typically involves directly assessing their open-ended responses, requiring human ann..."
via Arxiv👤 Jakub Hoscilowicz, Artur Janicki📅 2025-11-25
⚡ Score: 6.5
"We introduce the Adversarial Confusion Attack, a new class of threats against multimodal large language models (MLLMs). Unlike jailbreaks or targeted misclassification, the goal is to induce systematic disruption that makes the model generate incoherent or confidently incorrect outputs. Applications..."
"Hey everyone! Today we are making dnet, a distributed inference framework that lets Apple Silicon clusters run models that exceed their physical memory, public.
We fuse pipelined-ring parallelism, disk streaming and UMA-aware scheduling so “out of memory” stops being the limit.
[https://githu..."
via Arxiv👤 Gongfan Fang, Xinyin Ma, Xinchao Wang📅 2025-11-24
⚡ Score: 6.5
"Large-scale video generative models have recently demonstrated strong visual capabilities, enabling the prediction of future frames that adhere to the logical and physical cues in the current observation. In this work, we investigate whether such capabilities can be harnessed for controllable image-..."
"Hey everyone,
I’m getting into the world of AI agents, and I’m starting to realize there’s a huge difference between building something that works in a controlled environment versus something that can reliably operate in the real world.
What I’m trying to understand is: **how big of a problem is a..."
"I've been building a few AI agents recently, and I kept running into the same friction: **State Management.**
Every time I wanted to give an agent long-term memory, I had to set up a vector database (Pinecone/Weaviate), configure the embedding pipeline (OpenAI), and write the logic to chunk and ret..."
"It's called OCR Arena, you can try it here: https://ocrarena.ai
There's so many new OCR models coming out all the time, but testing them is really painful. I wanted to give the community an easy way to compare leading foundation VLMs and open source OCR models side-by-side. You can upload any doc, ..."
💬 Reddit Discussion: 12 comments
🐐 GOATED ENERGY
🎯 OCR model performance • OCR model comparison • OCR model cost
💬 "what's the winrate of Opus 4.5 vs Opus 4.1?"
• "showing cost parallel to rating will be cool"
🎯 Pricing complexity • Model capability mismatch • Workflow-aware routing
💬 "The challenge isn't knowing which model is cheaper. The challenge is knowing which one will actually succeed for a given request without requiring retries or manual intervention."
• "If someone is building a router like this, the interesting part isn't the proxy — it's whether the routing logic eventually evolves into: semantic classification, reasoning difficulty estimation, task-type fingerprinting or even lightweight pre-model inference."
"Working on conversation agents and getting frustrated with RAG. Every implementation uses vector DBs with retrieval at inference. Works but adds 150-200ms latency and retrieval is hit or miss.
Had a probably dumb idea - what if you just dont discard KV cache between turns? Let the model access its ..."
💬 "nightmare for multi-tenant. each user needs their own KV cache which kills memory efficiency"
• "Getting LLMs to go brr is all about memory management"