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Protect your privacy with Surfshark! Enter the ATILA coupon code for another 4 months free at https://surfshark.com/atila Script and presentation: Atila Iamarino - Twitter @oatila Instagram @oatila Direction and Production: Paloma Sato Image Composition, Editing, Animation and Thumb: Giulia Donadio: Instagram: @giulia_donadio The book I quote: Merchant, B. (2023). Blood in the Machine: The Origins of the Rebellion Against Big Tech. Hachette UK. - https://amzn.to/407gCf0 Sources: Investor reports: https://www.bloomberg.com/news/articl... https://www.goldmansachs.com/images/m... Loss that OpenAI should still have: https://www.theinformation.com/articl... https://www.theinformation.com/articl... Power usage: https://www.bbc.com/portuguese/ articl... https://exame.com/tecnologia/big-tech... Zhou, L., Schellaert, W., Martínez-Plumed, F., Moros-Daval, Y., Ferri, C., & Hernández-Orallo, J. (2024). Broader, more instructive language models become less reliable. Nature, 1-8. Cappelli, P., Tambe, P. S., & Yakubovich, V. (2024). Will Large Language Models Really Change How Work Is Done?. Companion Article Package, 19. Mirzadeh, I., Alizadeh, K., Shahrokhi, H., Tuzel, O., Bengio, S., & Farajtabar, M. (2024). GSM-Symbol: Understanding the Limitations of Mathematical Reasoning in Large Language Models. arXiv preprint arXiv:2410.05229. Svanberg, M., Li, W., Fleming, M., Goehring, B., & Thompson, N. (2024). Beyond AI Exposure: Which Tasks are Cost-Effective to Automate with Computer Vision?. Available at SSRN 4700751.