AI News 2025-04-03

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  • OpenAI pushed an update to their 4o model. This has significantly improved its ranking (e.g. now best non-reasoning model on coding benchmark).
  • An interesting test of GPT-4o in-context image generation: it is unable to generate an image of a maze with a valid solution; at lest when the maze is a square. However, if you ask it to make an image of a diamond orientation maze (45° rotated square), it succeeds to have a valid solution. We can rationalize this based on the sequential order of autoregressive generation. By generating first from the start of the maze (and only its local neighborhood), and similarly finishing with this sort of locality, the model can more correctly build a valid solution. (Conversely, the usual square orientation requires longer-range reasoning across image patches.)
    • At first, this might seem like just another silly oddity. But it shows how recasting a problem, just by changing the generation order, can massively change model performance. This sheds light on how they “think” and suggests that alternate generation strategies could perhaps unlock capabilities.
      • For instance, one could imagine an LLM with different branches (like MoE?) where each branch is trained on a different autoregression strategy (left-to-right, right-to-left, block diffusion, random, etc.) such that the overall LLM can invoke/combine different kinds of thinking modes.
    • Another trick is to ask it to generate an image of a maze with the solution identified, and then update the image to remove the solution. This is a visual analog of “think step-by-step” and other inference-time-compute strategies. This implies that current models have untapped visual reasoning capabilities that could be unlocked by allowing them to visually iterate on problems.
  • Anthropic announces Claude for Education, which provides a university-wide solution tailored to education.

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