🦈 생성형 인공지능은 통계적 '따라쟁이'일 뿐이다 (게티어 문제 2편)

[영상 순서] 00:00 들어가며 01:00 창작과 학습의 환상 02:03 의미를 숫자로 바꾸는 마법, 그리고 한계 03:53 프레게의 통찰, 기계 속에서 부활하다 05:42 환각의 탄생 07:27 마치며 - 📌매주 금요일 업로드 예정 - #생각 #마음 #인문학 #철학 #수리철학 #논리학 #언어철학 #AI - 영상 제작을 위해 참고한 문헌은 다음과 같습니다. (1) Gettier, E. L. (1963). Is justified true belief knowledge? Analysis, 23(6), 121–123. (2) Frege, G. (1884). Die Grundlagen der Arithmetik: Eine logisch-mathematische Untersuchung über den Begriff der Zahl. Breslau: W. Koebner. (3) Frege, G. (1892). Über Sinn und Bedeutung. Zeitschrift für Philosophie und philosophische Kritik, 100, 25–50. (4) Gödel, K. (1931). Über formal unentscheidbare Sätze der Principia Mathematica und verwandter Systeme I. Monatshefte für Mathematik und Physik, 38(1), 173–198. (5) Searle, J. R. (1980). Minds, brains, and programs. Behavioral and Brain Sciences, 3(3), 417–457. (6) Bender, E. M., Gebru, T., McMillan-Major, A., & Mitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’21) (pp. 610–623). (7) Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., & Polosukhin, I. (2017). Attention is all you need. Advances in Neural Information Processing Systems, 30, 5998–6008. (8) Plato. (c. 369 BCE). Theaetetus (B. Jowett, Trans.). In The dialogues of Plato (Vol. 3). Oxford University Press. (Original work published ca. 369 BCE) (9) Williamson, T. (2000). Knowledge and its limits. Oxford: Oxford University Press. (10) Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., ... & Amodei, D. (2020). Language models are few-shot learners. Advances in Neural Information Processing Systems, 33, 1877–1901. (11) Kaplan, J., McCandlish, S., Henighan, T., Brown, T. B., Chess, B., Child, R., ... & Amodei, D. (2020). Scaling laws for neural language models. arXiv preprint arXiv:2001.08361. (12) Ji, Z., Lee, N., Frieske, R., Yu, T., Su, D., Xu, Y., ... & Fung, P. (2023). Survey of hallucination in natural language generation. ACM Computing Surveys, 55(12), 1–38. (13) Maynez, J., Narayan, S., Bohnet, B., & McDonald, R. (2020). On faithfulness and factuality in abstractive summarization. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (pp. 1906–1919). (14) Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., ... & Liang, P. (2021). On the opportunities and risks of foundation models. arXiv preprint arXiv:2108.07258. (15) Weidinger, L., Mellor, J., Rauh, M., Griffin, C., Uesato, J., Huang, P.-S., ... & Gabriel, I. (2022). Taxonomy of risks posed by language models. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’22) (pp. 214–229). (16) OpenAI. (2023). GPT-4 technical report. arXiv preprint arXiv:2303.08774. (17) Buckner, C. (2021). Deep learning: A philosophical introduction. Philosophy Compass, 16(9), e12744. (18) Floridi, L., & Chiriatti, M. (2020). GPT-3: Its nature, scope, limits, and consequences. Minds and Machines, 30(4), 681–694. - 이 콘텐츠는 인공지능 가상 연기자 서비스, 타입캐스트를 활용하여 제작되었습니다. 출연진: 이나 https://typecast.ai/kr This content was produced with Typecast, an AI virtual actor service. Characters casted: 이나 https://typecast.ai - 에드먼드 게티어(사진=https://cdn.thecollector.com/wp-conte...) 쿠르트 괴델(사진=https://i0.wp.com/1000wordphilosophy....) 존 설(사진=https://static.religiondigital.org/cl...)