This is an effort to get some discussion going.

I remember starting grad school and coming across reddit posts with themes like, “What research area will be hot in the next 10 years?”, etc. In retrospect, the comments there were not very informed (talk of graphical models and bayesian non-parametrics). But, the heart of these posts is talking about a research area that you find exciting.

So, tell us what research area is currently exciting to you. Are you starting a new job, project, or graduate program to work on it?

  • @[email protected]English
    2•1 year ago

    I had the pleasure of conducting research into self-supervised learning (SSL) for computer vision.

    What stood out to me was the simplicity of the SSL algorithms combined with the astonishing performance of the self-supervisedly trained models after supervised fine-tuning.

    Also the fact that SSL works across tasks and domains, e.g., text generation, image generation, semantic segmentation…

    • @MachinaDoctrinaEnglish
      1•1 year ago

      I too believe that SSL (and to some extent Unsupervised Learning) is by far the best way to frame learning problems in DL, it has shown to avoid the pesky mode collapse and improves out of distribution inference performance.