Why did editing 0.016% of AI weights increase math performance by 6x? The mechanics and configuration secrets of the MIT study

Conclusion: The 0.016% weight edit fixed "premature termination due to thinking loops," and even unedited models can reach an ...
kingy.ai

Weight-Space Programming: How GPT-6 Astra Raised Qwen’s MATH-500 Score Sixfold

GPT-6 Astra edited Qwen’s weights and raised MATH-500 from 7.9% to 48.1% in author-run tests. How weight-space programming works—and its limits.
shattered.io

Bedrock vs Microsoft Foundry vs Vertex AI: Pricing [2026]

Three companies now sell the same basic product: on-demand access to frontier AI models through a cloud API. Amazon Bedrock, Microsoft Foundry, and Google’s Vertex AI all promise the same pitch: pick ...
GitHub

README.md

Contribute to Favouratem/Database_portfolio- development by creating an account on GitHub.

A CPU running inside an LLM running on a GPU? ...I know it sounds crazy, but here is what I learned and didn't learn from replicating Qwenputer

A model was released on Hugging Face that claims to have a 32-bit RISC-V CPU compiled and embedded within the weights of ...
xenospectrum

MIT Shows an LLM Can Read and Edit Another Neural Network's Weights Directly

MIT CSAIL's "weight-space programming" has a frontier LLM read and edit neural network weights directly, with no gradient descent. Surgical edits ended Qwen's reasoning loops, but the results come ...