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IFAI

Qwen3.5-0.8B

Product2 stories

  1. ResearchReach 59

    GPT-6 Astra rewrites neural network weights directly without training

    Researchers introduced Weight-Space Programming, showing OpenAI's GPT-6 Astra can natively interpret and tweak neural network weights without traditional gradient training. By altering just 0.016% of Qwen3.5-0.8B's weights, it fixed a reasoning loop and bumped math accuracy from 7.9% to 48.1%. Why it matters: Direct parameter steering hints at automated model patching, though current results rely heavily on external Python tools rather than pure weight intuition.

  2. Open sourceReach 48

    Alibaba drops Qwen3.5 small model family from 0.8B to 9B

    Alibaba's Qwen team just launched the Qwen3.5 Small Model Series, offering four compact sizes from 0.8B to 9B parameters along with base checkpoints. Built with native multimodal architecture and scaled reinforcement learning, the lineup aims to deliver snappy intelligence directly on edge devices and local agents.