Choose Your Weapon: Survival Strategies for Depressed AI Academics [Point of View]

Proceedings of the IEEE(2024)

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摘要
As someone who does artificial intelligence (AI) research in a university, you develop a complicated relationship with the corporate AI research powerhouses, such as Google DeepMind, OpenAI, and Meta AI. Whenever you see one of these papers that train some kind of gigantic neural net model to do something you were not even sure a neural network could do, unquestionably pushing the state-of-the-art and reconfiguring your ideas of what is possible, you get conflicting emotions. On the one hand, it is very impressive. Good on you for pushing AI forward. On the other hand, how could we possibly keep up? As an AI academic, leading a laboratory with a few Ph.D. students and (if you are lucky) some postdoctoral fellows, perhaps with a few dozen graphics processing units (GPUs) in your laboratory, this kind of research is simply not possible to do.
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Neural Network,Deep Learning,Start-up,Video Games,Graphics Processing Unit,Career Path,Kind Of Research,Postdoctoral Fellow,Big Companies,Artificial Intelligence Research,Tech Companies,Part Of The Journey,Comparative Advantage,Large-scale Projects,Funding Agencies,Applicability Domain,Domain Experts,National Science Foundation,Deep Reinforcement Learning,Obvious Problem
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