HAREKETLİ GÖRÜNTÜ ÜRETİMİNDE YAPAY ZEKÂ TEKNOLOJİLERİNİN KULLANIMI ÜZERİNE UYGULAMALI BİR ARAŞTIRMA

Yıl 2024, , 1 - 26, 29.11.2024

Türker Söğütlüler

https://doi.org/10.47107/inifedergi.1512175

Öz

Öz
20. yüzyılın ortalarından itibaren temelleri atılmaya başlayan, kökenleri nörobilime ve sinir ağlarının keşfine dayanan yapay zekâ teknolojileri küresel ölçekte hızla büyüyen bir rekabet alanı oluşturmuştur. Yapay zeka teknolojisine dayanan sistemler bugün sağlık, finans, ticaret, eğitim, medya, endüstriyel üretim, enerji, siber güvenlik gibi birey ve toplumu etkileyen önemli alanlarda kullanılmaktadır. Dünyanın önde gelen şirketleri ve hükümetler tarafından yapay zekâ şirketleri fonlanmakta, büyük veriye dayalı makine öğrenimi giderek önem kazanmaktadır. Olumlu kullanımlarından doğan faydaların yanında olumsuz kullanımlarından doğan etik sorunların varlığı tartışma konusu olsa da yapay zekâ teknolojilerinin geleceği şekillendireceği gerçeği, alandan uzaklaşmak yerine uzlaşıyı gerektirmektedir. Araştırma söz konusu gerçekliği gözeterek yapay zekânın hareketli görüntü üretimindeki potansiyelini tartışmaya açmayı amaçlamıştır. “Makineler düşünebilir mi?” sorusuyla başlayan insanlığın yapay zekâ serüveninde bu araştırma, “Yapay zekâ profesyonel, hiper gerçekçi sahneler üretebilir mi?” sorusuna odaklanarak alanda faaliyet gösteren üç öne çıkan platformun çıktılarını incelemiştir. Araştırma kapsamında Runway, Luma Dream Machine ve Imagine Art platformlarından gerçekçi ve fütüristik iki senaryoyu içeren hareketli görüntü üretmeleri istenmiştir. Üretilen hareketli görüntüler içerik analizine tabi tutulmuş, belirlenen kategoriler ve alt kategoriler altında incelenmiştir. Bu incelemeler üretilen hareketli görüntülerde çeşitli hatalar olsa da yapay zekâ teknolojilerinin kısa süre içinde uzmanlık gerektiren dizi, film, içerik üretimini yeniden şekillendireceğini, sektördeki çeşitli uzmanlıkların yerini yapay zekânın alacağını göstermiştir.
Anahtar Kelimeler: İletişim Çalışmaları, Yapay Zekâ, Hareketli Görüntü

Anahtar Kelimeler

İletişim Çalışmaları, Yapay Zeka, Hareketli Görüntü

Etik Beyan

Araştırma bilimsel etik kurallarına uygun biçimde hazırlanmıştır.

Destekleyen Kurum

Destekleyen kurum-kuruluş bulunmamaktadır.

Teşekkür

Alana önemli katkılar sunan derginize teşekkür ediyor, çalışmalarınızda kolaylıklar diliyorum...

AN APPLIED RESEARCH ON THE USE OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN MOVING IMAGE PRODUCTION

Öz

Abstract
Since the mid-20th century, artificial intelligence technologies, which have their roots in neuroscience and the discovery of neural networks, have created a rapidly growing competitive field on a global scale. Systems based on artificial intelligence technology are used today in important areas affecting individuals and society such as health, finance, trade, education, media, industrial production, energy, cyber security. Artificial intelligence companies are funded by the world's leading companies and governments, and machine learning based on big data is becoming increasingly important. Although the existence of ethical problems arising from negative uses as well as the benefits arising from positive uses is a matter of debate, the fact that artificial intelligence technologies will shape the future requires consensus instead of moving away from the field. The research aims to discuss the potential of artificial intelligence in moving image production by considering this reality. In the journey of artificial intelligence that started with the question "Can machines think?", this research focuses on the question "Can artificial intelligence produce professional, hyper-realistic scenes?" and examines three important platforms operating in this field. Within the scope of the research, Runway, Luma Dream Machine and Imagine Art platforms were asked to produce moving images including two realistic and futuristic scenarios. The moving images produced were subjected to content analysis and analysed under the categories and subcategories determined. Although there are various errors in the moving images produced, these examinations have shown that artificial intelligence technologies will reshape the production of series, films and content that require expertise in a short time, and that artificial intelligence will replace various expertise in the sector.
Keywords: Communication Studies, Artificial Intelligence, Moving Image

Anahtar Kelimeler

Communication Studies, Artificial Intelligence, Moving Image

Kaynakça

• Agrawal, A., Gans, J., & Goldfarb, A. (2017). What to expect from artificial intelligence. MIT Sloan Menagement Review, 1-9. AI Business. (2023, June 29). Google, Nvidia back AI video lab Runway in $141M funding round. AI Business. Retrieved July 1, 2024, from https://aibusiness.com/ml/google-nvidia-back-ai-video-lab-runway-in-141m-funding-round
• Anadolu, B. (2020). Makineler Film Yapmayı Düşler mi?: Jan Bot Örneği. SineFilozofi, 5(10), 682-703. https://doi.org/10.31122/sinefilozofi.726799
• Aris, S., Aeini, B., & Nosrati, S. (2023). A digital aesthetics? artificial intelligence and the future of the art. Journal of Cyberspace Studies, 7(2), 219-236. https://doi.org/10.22059/jcss.2023.366256.1097
• Aslanyürek, Y. ve Aycan, E. (2024). Cinematic futures: The impact of ai on the cinematography.İNİF E- Dergi, 9(1), 75-94. https://doi.org/10.47107/inifedergi.1420488.
• Ashour, A. F., & Rashdan, W. (2024). Artificial Intelligence: Potentialities and Challenges in Art and Design. The International Journal of Design Management and Professional Practice, 18(2), 19.
• Aslan, T., & Aydın, K. (2023). Metinden Görüntü Üretme Potansiyeli Olan Yapay Zekâ Sistemleri Sanat ve Tasarım Performanslarının İncelenmesi. Ondokuz Mayis University Journal of Education Faculty, 42(2), 1049-1198. https://doi.org/10.7822/omuefd.1293657
• Avinç, G, M., (2024). Mimaride Biyofilik Tasarım için Metinden Görüntü Üretme Potansiyeli Olan Yapay Zeka Araçlarının Kullanımı. Black Sea Journal of Engineering and Science, 7(4), 641-648. https://doi.org/10.34248/bsengineering.1470411
• Aydemir, M., & Fetah, V. (2023). Yapay Zekanın Di̇ji̇tal Hi̇kayeleşti̇rme ve Senaryo Tasarımında Kullanımı: Kısa Fi̇lm Uygulamalı Bir Araştırma. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi(58), 255-275. https://doi.org/10.30794/pausbed.1
• Banafa, A. (2024). "9 Narrow AI vs. General AI vs. Super AI," in Transformative AI: Responsible, Transparent, and Trustworthy AI Systems , River Publishers, pp.55-60.
• Bastian, M. (2024, June 1). Sony Pictures wants to use generative AI to cut movie production costs. The Decoder. Retrieved June 8, 2024, from https://the-decoder.com/sony-pictures-wants-to-use-generative-ai-to-cut-movie-production-costs/
• Başer, E., & Söğütlüler, T. (2023). Değişen İzleme Eğilimleri Çerçevesinde Dijital Platformlar ve İçerik Reklamları Üzerine Bir İnceleme. Akdeniz İletişim, (41), 1-26. doi: 10.31123/akil.1303391.
• Benriyene, S., I, B. A., & Bakkali, S. (2023, October). Artificial Intelligence and Employability: A Literature Review of Engineer’s Competencies. In International Conference on Advanced Intelligent Systems for Sustainable Development (pp. 215-224). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-54318-0
• Bloomberg. (2023 June 29). AI video startup Runway raises $141 million from Google, Nvidia. https://www.bloomberg.com/news/articles/2023-06-29/ai-video-startup-runway-raises-141-million-from-google-nvidia
• Bloomberg. (2024, May 23). Alphabet, Meta offer millions to partner with Hollywood on AI. Bloomberg. https://www.bloomberg.com/news/articles/2024-05-23/alphabet-meta-offer-millions-to-partner-with-hollywood-on-ai
• Bostrom, N. (2016). The Control Problem. Excerpts fromSuperintelligence: Paths, Dangers, Strategies. Science Fiction and Philosophy, 308–330. doi:10.1002/9781118922590.ch23
• Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D., Wu, J., Winter, C., Hesse, C., Chen, M., Sigler, E., Litwin, M., Gray, S., Chess, B., Clark, J., Berner, C., McCandlish, S., Radford, A., Sutskever, I., & Amodei, D. (2020). Language models are few-shot learners. Advances in Neural Information Processing Systems, 33, 1877-1901.
• Cake, S. (2023) Artificial Intelligence as a Co-creative Tool for Writing Screenplays. In Australian Screen Production Education and Research Association (ASPERA) Conference, 2023-06-28 - 2023-06-30, Adelaide, Australia, AUS.
• Calo, R. (2017). Artificial Intelligence Policy: A Primer and Roadmap. UC Davis Law Review, 51, 399.https://doi.org/10.2139/ssrn.3015350
• Cath, C. (2018). Governing artificial intelligence: ethical, legal and technical opportunities and challenges. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376(2133), 20180080. https://doi.org/10.1098/rsta.2018.0080
• Cevher, E., & Aydın, Y. (2020). Yapay Zekanın Şafağında Sinema: Morgan Filmi Fragmanı Örneği. Gümüşhane Üniversitesi İletişim Fakültesi Elektronik Dergisi, 8(1), 614-642. https://doi.org/10.19145/e-gifder.559287
• Chow, P. S. (2020). Ghost in the (Hollywood) machine: Emergent applications of artificial intelligence in the film industry. NECSUS_European Journal of Media Studies, 9(1), 193-214. http://dx.doi.org/10.25969/mediarep/14307.
• Dash, B., Ansari, M. F., Sharma, P., & Ali, A. (2022). Threats and opportunities with AI-based cyber security intrusion detection: a review. International Journal of Software Engineering & Applications (IJSEA), 13(5). https://doi.org//ijsea.2022.13502
• Deranty, J. P., & Corbin, T. (2024). Artificial intelligence and work: a critical review of recent research from the social sciences. AI & Society, 39(2), 675-691.
• Diamond, G. F., & Lindberg, A. (2023). Implementation of AI tools in 3D game art. Stocholm University.
• Dong, C., Loy, C. C., He, K., & Tang, X. (2015). Image Super-Resolution Using Deep Convolutional Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(2), 295-307. https://doi.org/10.1109/TPAMI.2015.2439281
• Forsyth, D. A., & Ponce, J. (2002). Computer vision: a modern approach. Prentice Hall.
• Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation?. Technological forecasting and social change, 114, 254-280. https://doi.org/10.1016/j.techfore.2016.08.019 Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
• Güney, E., & Yavuz, H. (2020). Yapay zekâ ile sanatsal üretim pratiğinde sanatçının rolü ve değişen sanat olgusu. Sanat ve Tasarım Dergisi, (26), 415-439.
• Hernández-Lugo, M. D. L. C. (2024). Artificial Intelligence as a tool for analysis in Social Sciences: methods and applications. LatIA, 2, 11-11. https://doi.org/10.62486/latia202411
• Iftikhar, P., Kuijpers, M. V., Khayyat, A., Iftikhar, A., & De Sa, M. D. (2020). Artificial intelligence: a new paradigm in obstetrics and gynecology research and clinical practice. Cureus, 12(2). doi: 10.7759/cureus.7124
• ImagineArt AI. (2024). ImagineArt AI Art Generator. https://www.imagine.art/
• Jiang, H. H., Brown, L., Cheng, J., Khan, M., Gupta, A., Workman, D., ... & Gebru, T. (2023, August). AI Art and its Impact on Artists. In Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society (pp. 363-374). https://doi.org/10.1145/3600211.3604681
• Kaya, E, B. (2021). Yapay Zekânın Medya ve Yayıncılık Alanına Etkisi. TRT Akademi, 6(13), 896-903. https://doi.org/10.37679/trta.1002525
• Kiela et al. (2023) – With minor processing by Our World in Data, Retrieved July 4, 2024, from https://ourworldindata.org
• Koren, Y. (2009). The bellkor solution to the netflix grand prize. Netflix prize documentation, 81(2009), 1-10.
• Krippendorff, K. (2018). Content analysis: An introduction to its methodology. Sage. https://doi.org/10.4135/9781071878781
• Larson, D. B., Magnus, D. C., Lungren, M. P., Shah, N. H., & Langlotz, C. P. (2020). Ethics of using and sharing clinical imaging data for artificial intelligence: a proposed framework. Radiology, 295(3), 675-682. https://doi.org/10.1148/radiol.2020192536
• Le, Q., & Mikolov, T. (2014, June). Distributed representations of sentences and documents. In International conference on machine learning (pp. 1188-1196). PMLR.
• Letheren, K., Russell-Bennett, R., & Whittaker, L. (2020). Black, white or grey magic? Our future with artificial intelligence. Journal of Marketing Management, 36(3-4), 216-232. https://doi.org/10.1080/0267257X.2019.1706306
• Li, N., Ho, C. P., Xue, J., Lim, L. W., Chen, G., Fu, Y. H., & Lee, L. Y. T. (2022). A progress review on solid‐state LiDAR and nanophotonics‐based LiDAR sensors. Laser & Photonics Reviews, 16(11), 2100511. https://doi.org/10.1002/lpor.202100511
• Littman, M. L., Ajunwa, I., Berger, G., Boutilier, C., Currie, M., Doshi-Velez, F., Hadfield, G., Horowitz, M. C., Isbell, C., Kitano, H., Levy, K., Lyons, T., Mitchell, M., Shah, J., Sloman, S., Vallor, S., & Walsh, T. (2021). Gathering strength, gathering storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 study panel report. Stanford University, Stanford, CA. Retrieved June 1, 2024, from http://ai100.stanford.edu/2021-report
• Luma Labs. (2024). Luma Dream Machine. Retrieved July 1, 2024, from https://lumalabs.ai/dream-machine
• Mayer-Schönberger, V., & Cukier, K. (2013). Big data: A revolution that will transform how we live, work, and think. Houghton Mifflin Harcourt. https://doi.org/10.1093/aje/kwu085
• Mazzone, M., & Elgammal, A. (2019, February). Art, creativity, and the potential of artificial intelligence. In Arts (Vol. 8, No. 1, p. 26). MDPI.
• McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (1956). A proposal for the Dartmouth summer research project on artificial intelligence. In Dartmouth Conference on Artificial Intelligence. Dartmouth College, Hanover, NH.
• McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (2006). A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI magazine, 27(4), 12-12. https://doi.org/10.1609/aimag.v27i4.1904
• McCormack, J., Gifford, T., Hutchings, P. (2019). Autonomy, Authenticity, Authorship and Intention in Computer Generated Art. In: Ekárt, A., Liapis, A., Castro Pena, M.L. (eds) Computational Intelligence in Music, Sound, Art and Design. EvoMUSART 2019. Lecture Notes in Computer Science, vol 11453. Springer, Cham. https://doi.org/10.1007/978-3-030-16667-0_3
• McCulloch, W.S., Pitts, W. A. (1943). logical calculus of the ideas immanent in nervous activity. Bulletin of Mathematical Biophysics 5, 115–133. https://doi.org/10.1007/BF02478259
• Medium (2023, February 24). The future of art: AI-powered text-to-image generator. Medium. Retrieved June 8, 2024, from https://medium.com/art3k7/the-future-of-art-ai-powered-text-to-image-generator-447470aa4d02
• Miller, T. (2019). Explanation in artificial intelligence: Insights from the social sciences. Artificial intelligence, 267, 1-38. https://doi.org/10.1016/j.artint.2018.07.007
• Minsky, M., & Papert, S. (1969). Perceptrons: An Introduction to Computational Geometry. Cambridge, MA, USA: MIT Press.
• Mondal, B. (2020). Artificial Intelligence: State of the Art. In: Balas, V., Kumar, R., Srivastava, R. (eds) Recent Trends and Advances in Artificial Intelligence and Internet of Things. Intelligent Systems Reference Library, vol 172. Springer, Cham. https://doi.org/10.1007/978-3-030-32644-9_32
• Monser, M., & Fadel, E. (2023). A modern vision in the applications of artificial intelligence in the field of visual arts. International Journal of Multidisciplinary Studies in Art and Technology, 6(1), 73-104.
• Muratoğlu-Pehlivan, B. ve Türkgeldi, S. K. (2020). Post-modern dönemde senaristin ve izleyicinin rolü: Yapay zeka, interaktif drama ve sinemanın geleceğine dair bir öngörü. Manas Sosyal Araştırmalar Dergisi, 9(4), 26382652.
• Müller, V. C. (2020). Ethics of artificial intelligence and robotics. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Winter 2020 ed.). Stanford University.
• Netflix. (2024). Netflix in your neighbourhood: Privacy. https://www.netflixinyourneighbourhood.ca/privacy/ Netflix Research. (2024). Machine learning research. Netflix. https://research.netflix.com/research-area/machine-learning
• OpenAI. (2024). ChatGPT. https://www.openai.com/chatgpt
• Oxford English Dictionary. (2023, December). Artificial intelligence. In Oxford English Dictionary. Oxford University Press. https://doi.org/10.1093/OED/7359280480
• Perrigo, B. (2023, June 21). Runway. Time. Retrieved June 8, 2024, from https://time.com/collection/time100-companies-2023/6285166/runway/
• Pika Art (2024) Pika Labs AI. https://pika.art/
• Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., & Sutskever, I. (2019). Language models are unsupervised multitask learners. OpenAI blog, 1(8), 9.
• Runway AI, Inc. (2024). Runway - Advancing creativity with artificial intelligence. https://runwayml.com/
• RunwayML. (2024). Video Tools. https://app.runwayml.com/video-tools/teams/
• Russell, S. J., & Norvig, P. (2016). Artificial intelligence: a modern approach. Pearson.
• Schonberger, M, V., & Cukier, K. (2013). Big data: the essential guide to work, life and learning in the age of insight. Hachette UK.
• Steck, H., Baltrunas, L., Elahi, E., Liang, D., Raimond, Y., & Basilico, J. (2021). Deep learning for recommender systems: A Netflix case study. AI Magazine, 42(3), 7-18. https://doi.org/10.1609/aimag.v42i3.18140
• Szeliski, R. (2022). Computer vision: algorithms and applications. Springer Nature. https://doi.org/10.1007/978-3-030-34372-9
• The Walt Disney Company. (2024). Current privacy policy. https://privacy.thewaltdisneycompany.com/en/current-privacy-policy/
• Tribeca Enterprises. (2024, May 31). Tribeca Festival and OpenAI announce ‘Sora Shorts’. Tribeca. Retrieved May 18, 2024, from https://tribecafilm.com/press-center/festival/press-releases/tribeca-festival-and-open-ai-announce-sora-shorts
• Turing, A. M. (1950). I.—Computing Machinery And Intelligence. Mind, Lix(236), 433–460. doi:10.1093/mind/lix.236.433
• Türten, B. (2024): Yapay Zekâ Ve Sinema: Film Yapımında Olanaklar ve Fırsatlar. Anadolu Ve Balkan Araştırmaları Dergisi 7(14), 399-425. https://doi.org/10.32953/abad.1539736.
• Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., ... & Polosukhin, I. (2017). Attention is all you need. Advances in Neural Information Processing Systems. arXiv preprint arXiv:1706.03762. Vidgenie.ai. (2024). Vidgenie.ai. https://vidgenie.ai/gad_source=1&gclid=Cj0KCQjw_sq2BhCUARIsAIVqmQvBLc9Hwr9GnusOjcg7eMKIjfxMPHmCEFObZQwNgvjCvrrZS3GoZdcaAsJoEALw_wcB
• Voulodimos, A., Doulamis, N., Doulamis, A., & Protopapadakis, E. (2018). Deep Learning for Computer Vision: A Brief Review. Computational intelligence and neuroscience, 2018, 7068349. https://doi.org/10.1155/2018/7068349 Weber, R. (1990). Basic content analysis. Thousand Oaks, CA: Sage., https://doi.org/10.4135/9781412983488
• Yetkiner, B., & Özdemir, N. (2022). Sinemada transhümanizm ve yapay zekâ. AJIT-e: Academic Journal of Information Technology, 13(51), 262-286. https://doi.org/10.5824/ajite.2022.04.003.x
• Zengin, F. (2021). Yapay Zekâ ve Kişiselleştirilmiş Seyir Kültürü: Netflix Örneği Üzerinden Sanat Eserinin Hiper Kişiselleştirilmesi. TRT Akademi, 6(13), 700-727. https://doi.org/10.37679/trta.959576
• Zengin, F. (2022). Yapay Zeka ve Sinema: Yapay Zeka Çağında Sinema. Ferhat Zengin (Ed.). İstanbul: İstanbul Gelişim Üniversitesi Yayınları.