Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., ... & Amodei, D. (2020). Language models are few-shot learners. arXiv preprint arXiv:2005.14165. [Online]. Available: https://arxiv.org/abs/2005.14165
"GPT-3: Language Models and the Next Generation of AI" by Lex Fridman: In this podcast episode, Lex Fridman interviews Sam Altman, CEO of OpenAI, about GPT-3 and its implications. They discuss the potential of language models, ethical considerations, and the challenges of developing AI technologies. Link: https://www.youtube.com/watch?v=SY5PvZrJhLE
"ChatGPT: A Large-Scale Transformer-Based Language Model for Conversational Agents" by OpenAI: This blog post by OpenAI provides an overview of ChatGPT, its development, and the challenges faced in training a conversational language model. It explains the techniques used to improve the model's behavior and its potential applications. Link: https://openai.com/blog/chatgpt/
"Introduction to GPT-3: How It Works and Its Implications" by OpenAI: This video provides an overview of GPT-3, one of the most advanced AI language models. It discusses the training process, model architecture, and showcases some of its impressive capabilities. Link: https://www.youtube.com/watch?v=nxWginnMr14
Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., & Sutskever, I. (2019). Language models are unsupervised multitask learners. OpenAI Blog. [Online]. Available: https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitask_learners.pdf
Dodge, J., Bau, D., Bello, I., Gajewski, T., Groeneveld, C., Liu, V., ... & Wu, J. (2021). Fine-tuning language models from human feedback. arXiv preprint arXiv:2103.07405. [Online]. Available: https://arxiv.org/abs/2103.07405
"Transfer Learning in NLP with Transformers" by Hugging Face: This video explores transfer learning with Transformers, focusing on the use of pre-trained language models. It explains how to fine-tune these models on specific NLP tasks and showcases practical examples. Link: https://www.youtube.com/watch?v=U2YC-uI4jnE
"Social Biases in NLP Models as Barriers for Persons with Disabilities" by Maarten Sap et al. (2019): This research paper highlights the biases present in AI language models and their impact on people with disabilities. It sheds light on the ethical considerations and challenges involved in addressing biases in language models. Link: https://arxiv.org/abs/1903.04561
"The Limitations of AI Language Models" by OpenAI: This blog post by OpenAI explores the limitations and potential risks associated with large-scale AI language models. It discusses issues like bias, factual accuracy, and potential misuse, emphasizing the importance of responsible development and usage. Link: https://openai.com/blog/limitations-of-ai-language-models/
"The Dark Side of Language Models" by Janelle Shane: Janelle Shane's TED Talk explores the unintended biases and quirky behaviors that can arise in AI language models. It showcases some humorous and thought-provoking examples, highlighting the importance of careful model development. Link: https://www.ted.com/talks/janelle_shane_the_dark_side_of_language_models
"The Hidden Biases in Big Data" by Kate Crawford: This TED Talk by Kate Crawford delves into the biases embedded in AI systems and the data they are trained on. It raises awareness about the societal implications of biased data and the need for ethical considerations in AI development. Link: https://www.ted.com/talks/kate_crawford_the_hidden_biases_in_big_data