LLMs are everywhere: what other thoughts can we come up with? This post is the list of alternative sources to read about LLMs and what changes they have brought: * Choose Your Weapon: Survival Strategies for Depressed AI Academics 🙃 "what should we do know when ChatGPT is here?" has asked probably every student/researcher in NLP academia. This statement paper can provide you several ideas why not to continue😉 * Closed AI Models Make Bad Baselines: We will see how many papers mentioning ChatGPT will appear this ACL. However, Closed models is not the way to do benchmarking in research. * Towards Climate Awareness in NLP Research: together with the raise of data bases and size of models, our responsibility to the environment also increases. To do modern research, it is nice to report how much of computational time/resource/CO2 emissions were used. * Step by Step Towards Sustainable AI: if you want to finalize your reading about responsible AI, I really recommend this issue of AlgorithmWatch issue. Professionals from HuggingFace and several German institutions are sharing their thoughts about at what key points we should pay attention to deploy AI safely to humanity and nature.