πŸš€ WELCOME TO METAMESH.BIZ +++ AI browser agents shipping with security holes you could drive a context window through (researchers shocked that giving LLMs control of your cookies might be problematic) +++ GPTQ quantization gets a geometry lesson that actually makes sense (someone finally drew the weight update on a napkin and it clicked) +++ THE FUTURE IS QUANTIZED, VULNERABLE, AND ASKING NICELY FOR YOUR BROWSER PERMISSIONS +++ πŸš€ β€’
πŸš€ WELCOME TO METAMESH.BIZ +++ AI browser agents shipping with security holes you could drive a context window through (researchers shocked that giving LLMs control of your cookies might be problematic) +++ GPTQ quantization gets a geometry lesson that actually makes sense (someone finally drew the weight update on a napkin and it clicked) +++ THE FUTURE IS QUANTIZED, VULNERABLE, AND ASKING NICELY FOR YOUR BROWSER PERMISSIONS +++ πŸš€ β€’
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πŸ“š HISTORICAL ARCHIVE - October 26, 2025
What was happening in AI on 2025-10-26
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πŸ”¬ RESEARCH

SynthID-Image: Invisibly Watermarking AI-Generated Imagery

πŸ› οΈ TOOLS

OpenArc 2.0: NPU, Multi-GPU Pipeline Parallell, CPU Tensor Parallell, kokoro, whisper, streaming tool use, openvino llama-bench and more. Apache 2.0

"Hello! Today I'm happy to announce OpenArc 2.0 is finally done!! 2.0 brings a full rewrite to support NPU, pipeline parallel for multi GPU, tensor parallel for dual socket CPU, tool use for LLM/VLM, and an **OpenVINO version of llama-bench** and m..."
πŸ”’ SECURITY

The glaring security risks with AI browser agents

πŸ€– AI MODELS

Are you the asshole? Of course not –quantifying LLMs' sycophancy problem

🧠 NEURAL NETWORKS

[R] A geometric interpretation of the weight update in GPTQ quantization algorithm and a novel solution

"GPTQ is a simplified modification of the OBQ method where the weights in a matrix are quantized in each row independently one at a time from left to right. After step `i` of quantization, the remaining unquantized weights are modified like so: `dW[i:] = H[i:,i] dW[i]/H[i,i]`. This expression is deri..."
πŸ€– AI MODELS

I built a β€œdialectical” training harness that lets a tiny GPT know what it doesn’t know

"Most LLMs are optimized to always be right β€” statistically. Their only goal is to predict the most likely next token, so they can’t ever tell you how wrong a nearby alternative might have been. That’s why they can’t give meaningful β€œpercentages of truth.” They’re blind to their own uncertainty. I’v..."
πŸ’¬ Reddit Discussion: 41 comments πŸ‘ LOWKEY SLAPS
🎯 Reproduction & refinement β€’ Overfitting & regularization β€’ AI vs human discussion
πŸ’¬ "If anyone wants to reproduce or refine the 'contradiction sensitivity' metric, I'd love feedback." β€’ "if the weight's too high it over fits, but tuned right it actually reduces overfitting by smoothing the distribution after each update"
πŸ› οΈ TOOLS

I built a tool to stop MCP servers from eating 40%+ of your context window on every Claude Code session

"After repeatedly hitting the 200K context window quickly after I would start coding, I built house-mcp-manager to fix MCP server token consumption. **The problem I kept hitting:** \- AI coding tools load ALL MCP servers on startup \- Canvas alone = 78K tokens (40% of my 200K budget) \- ..."
πŸ’¬ Reddit Discussion: 11 comments 😐 MID OR MIXED
🎯 MCP feature usage β€’ Scope and configuration β€’ Project management
πŸ’¬ "Isn't there anything in the mcp spec that allows the agent to request additional information about tools that seem relevant to the query?" β€’ "Is it possible you have project A with, for example, GitHub MCP turned off. But then you cd into project B that has its own scope with GitHub MCP turned on?"
πŸ› οΈ TOOLS

ExecuTorch 1.0

πŸ› οΈ TOOLS

Torchcomms: A modern PyTorch communications API

πŸ› οΈ TOOLS

Llama.cpp model conversion guide

"Since the open source community always benefits by having more people do stuff, I figured I would capitalize on my experiences with a few architectures I've done and add a guide for people who, like me, would like to gain practical experience by porting a model architecture. Feel free to propose an..."
πŸ’¬ Reddit Discussion: 5 comments 🐐 GOATED ENERGY
🎯 LLM Debugging β€’ Model Optimization β€’ Model Conversion
πŸ’¬ "Debugging is quite important" β€’ "How can I know whether I can convert a safetensor model"
πŸ› οΈ SHOW HN

Show HN: Create-LLM – Train your own LLM in 60 seconds

πŸ’¬ HackerNews Buzz: 10 comments 🐝 BUZZING
🎯 Technical questions β€’ Architecture discussion β€’ Project popularity
πŸ’¬ "The tool works on Mac/Linux/Windows, check the README for setup." β€’ "It follows standard scaffolding patterns (create-next-app, etc). TypeScript CLI generates Python projects."
πŸ› οΈ SHOW HN

Show HN: Project Journal – Give AI coding assistants persistent memory

πŸ€– AI MODELS

Poor GPU Club : Good Worthy Pruned models?

"Wanted to explore more on this after seeing recent threads( 3 , 2 , [1](https://www.reddit.com/r/Loca..."
πŸ’¬ Reddit Discussion: 7 comments 🐝 BUZZING
🎯 Pruning and compression β€’ Model performance β€’ Dataset selection
πŸ’¬ "Pruning dense has been tried and it's not very successful" β€’ "Seems to be working just as well as the unpruned on coding"
πŸ› οΈ TOOLS

[N] OpenEnv: Agentic Execution Environments for RL post training in PyTorch

"External link discussion - see full content at original source."
πŸ¦†
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