[1] Microsoft guidance: A guidance language for controlling large language models. https://github.com/microsoft/guidance.2023.
[2] OpenAI API completions reference. https://platform.openai.com/docs/api-reference/completions.2023.
[3] Only Connect. Television show, 2008-2020. Created by Presentable, RDF Television and Parasol, Presented by Victoria Coren Mitchell.
[4] A. Akbik, T. Bergmann, D. Blythe, K. Rasul, S. Schweter, and R. Vollgraf. FLAIR: An easy-to-use framework for state-of-the-art NLP. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations), pages 54-59, Minneapolis, Minnesota, 2019. Association for Computational Linguistics. doi: 10.18653/v1/N19-4010.
[5] S. Altman. Planning for AGI and beyond. OpenAI Blog, February, 2023.
[6] C. Anotado, T. Ruddle, and J. Halbur. The Only Connect Database.
[7] S. Basu, I. Davidson, and K. Wagstaff. Constrained clustering: Advances in algorithms, theory, and applications. CRC Press, 2008.
[8] Z. Beda and S. M. Smith. Chasing red herring: Memory of distractors causes fixation in creative problem solving. Memory & Cognition, 46:671-684, 2018.
[9] M. Benedek and A. C. Neubauer. Revisiting Mednick's model on creativity-related differences in associative hierarchies. Evidence for a common path to uncommon thought. The Journal of creative behavior, 47(4):273-289, 2013.
[10] R. Bommasani, D. A. Hudson, E. Adeli, R. Altman, S. Arora, S. von Arx, M. S. Bernstein, J. Bohg, A. Bosselut, E. Brunskill, et al. On the opportunities and risks of foundation models. *ArXiv preprint*, abs/2108.07258, 2021.
[11] S. Borgeaud, A. Mensch, J. Hoffmann, T. Cai, E. Rutherford, K. Millican, G. van den Driessche, J. Lespiau, B. Damoc, A. Clark, D. de Las Casas, A. Guy, J. Menick, R. Ring, T. Hennigan, S. Huang, L. Maggiore, C. Jones, A. Cassirer, A. Brock, M. Paganini, G. Irving, O. Vinyals, S. Osindero, K. Simonyan, J. W. Rae, E. Elsen, and L. Sifre. Improving language models by retrieving from trillions of tokens. In K. Chaudhuri, S. Jegelka, L. Song, C. Szepesváři, G. Niu, and S. Sabato, editors, International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, volume 162 of Proceedings of Machine Learning Research, pages 2206-2240. PMLR, 2022.
[12] P. S. Bradley, K. P. Bennett, and A. Demiriz. Constrained k-means clustering. Microsoft Research, Redmond, 20(0):0, 2000.
[13] T. B. Brown, B. Mann, N. Ryder, M. Subbiah, J. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, S. Agarwal, A. Herbert-Voss, G. Krueger, T. Henighan, R. Child, A. Ramesh, D. M. Ziegler, J. Wu, C. Winter, C. Hesse, M. Chen, E. Sigler, M. Litwin, S. Gray, B. Chess, J. Clark, C. Berner, S. McCandlish, A. Radford, I. Sutskever, and D. Amodei. Language models are few-shot learners. In H. Larochelle, M. Ranzato, R. Hadsell, M. Balcan, and H. Lin, editors, Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020.
[14] S. Bubeck, V. Chandrasekaran, R. Eldan, J. Gehrke, E. Horvitz, E. Kamar, P. Lee, Y. T. Lee, Y. Li, S. Lundberg, et al. Sparks of artificial general intelligence: Early experiments with GPT-4. ArXiv preprint, abs/2303.12712, 2023.
[15] M. Chen, J. Tworek, H. Jun, Q. Yuan, H. P. d. O. Pinto, J. Kaplan, H. Edwards, Y. Burda, N. Joseph, G. Brockman, et al. Evaluating large language models trained on code. ArXiv preprint, abs/2107.03374, 2021.