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arXiv:2304.06035cs.OH

Choose Your Weapon: Survival Strategies for Depressed AI Academics

Julian Togelius, Georgios N. Yannakakis

Abstract

Are you an AI researcher at an academic institution? Are you anxious you are not coping with the current pace of AI advancements? Do you feel you have no (or very limited) access to the computational and human resources required for an AI research breakthrough? You are not alone; we feel the same way. A growing number of AI academics can no longer find the means and resources to compete at a global scale. This is a somewhat recent phenomenon, but an accelerating one, with private actors investing enormous compute resources into cutting edge AI research. Here, we discuss what you can do to stay competitive while remaining an academic. We also briefly discuss what universities and the private sector could do improve the situation, if they are so inclined. This is not an exhaustive list of strategies, and you may not agree with all of them, but it serves to start a discussion.

arXiv comments
Journal reference
Proceedings of the IEEE, 2024
DOI
Subjects
cs.OHOther Computer Science cs.CYComputers and Society cs.NENeural and Evolutionary Computing

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Linked by 3 identifiable commenters in 3 comments across 3 threads, from Apr 2023 to Jul 2024. Found in 2 HN submissions from Apr 2023 to Apr 2024. Open submission discussions.

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Discussed in comments3 threads

  1. How can I do my research as a GPU poor? 1 comment
  2. OpenAI’s CEO says the age of giant AI models is already over 1 comment

    • I strongly believe the next generation of models will be based upon spiking neural concepts wherein action potentials are lazily-evaluated throughout the network (i.e. event-driven). There are a few neuron models that can be modified (at some expense to fidelity) in order to…

      bob1029View on HNParent context

  3. Segment Anything Model and the hard problems of computer vision 1 comment

    • I tried to run the automatic_mask_generator notebook [1] but the results is more noisy then the everything mode on the demo website. Are the parameters used in the demo's website published anywhere? [1]: https://arxiv.org/abs/2304.06035

      thangngoc89View on HNParent context

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