Do not get Too Excited. You Might not be Done With Deepseek China Ai
페이지 정보
작성자 Alexander 작성일25-03-15 11:33 조회1회 댓글0건본문
Thoppilan, Romal; De Freitas, Daniel; Hall, Jamie; Shazeer, Noam; Kulshreshtha, Apoorv; Cheng, Heng-Tze; Jin, Alicia; Bos, Taylor; Baker, Leslie; Du, Yu; Li, YaGuang; Lee, Hongrae; Zheng, Huaixiu Steven; Ghafouri, Amin; Menegali, Marcelo (2022-01-01). "LaMDA: Language Models for Dialog Applications". Cheng, Heng-Tze; Thoppilan, Romal (January 21, 2022). "LaMDA: Towards Safe, Grounded, and High-Quality Dialog Models for Everything". Yang, Zhilin; Dai, Zihang; Yang, Yiming; Carbonell, Jaime; Salakhutdinov, Ruslan; Le, Quoc V. (2 January 2020). "XLNet: Generalized Autoregressive Pretraining for Language Understanding". Gao, Leo; Biderman, Stella; Black, Sid; Golding, Laurence; Hoppe, Travis; Foster, Charles; Phang, Jason; He, Horace; Thite, Anish; Nabeshima, Noa; Presser, Shawn; Leahy, Connor (31 December 2020). "The Pile: An 800GB Dataset of Diverse Text for Language Modeling". Black, Sidney; Biderman, Stella; Hallahan, Eric; et al. Table D.1 in Brown, Tom B.; Mann, Benjamin; Ryder, Nick; Subbiah, Melanie; Kaplan, Jared; Dhariwal, Prafulla; Neelakantan, Arvind; Shyam, Pranav; Sastry, Girish; Askell, Amanda; Agarwal, Sandhini; Herbert-Voss, Ariel; Krueger, Gretchen; Henighan, Tom; Child, Rewon; Ramesh, Aditya; Ziegler, Daniel M.; Wu, Jeffrey; Winter, Clemens; Hesse, Christopher; Chen, Mark; Sigler, Eric; Litwin, Mateusz; Gray, Scott; Chess, Benjamin; Clark, Jack; Berner, Christopher; McCandlish, Sam; Radford, Alec; Sutskever, Ilya; Amodei, Dario (May 28, 2020). "Language Models are Few-Shot Learners".
Askell, Amanda; Bai, Yuntao; Chen, Anna; et al. Wang, Shuohuan; Sun, Yu; Xiang, Yang; Wu, Zhihua; Ding, Siyu; Gong, Weibao; Feng, Shikun; Shang, Junyuan; Zhao, Yanbin; Pang, Chao; Liu, Jiaxiang; Chen, Xuyi; Lu, Yuxiang; Liu, Weixin; Wang, Xi; Bai, Yangfan; Chen, Qiuliang; Zhao, Li; Li, Shiyong; Sun, Peng; Yu, Dianhai; Ma, Yanjun; Tian, Hao; Wu, Hua; Wu, Tian; Zeng, Wei; Li, Ge; Gao, Wen; Wang, Haifeng (December 23, 2021). "ERNIE 3.0 Titan: Exploring Larger-scale Knowledge Enhanced Pre-coaching for Language Understanding and Generation". Lewkowycz, Aitor; Andreassen, Anders; Dohan, David; Dyer, Ethan; Michalewski, Henryk; Ramasesh, Vinay; Slone, Ambrose; Anil, Cem; Schlag, Imanol; Gutman-Solo, Theo; Wu, Yuhuai; Neyshabur, Behnam; Gur-Ari, Guy; Misra, Vedant (30 June 2022). "Solving Quantitative Reasoning Problems with Language Models". Wu, Shijie; Irsoy, Ozan; Lu, Steven; Dabravolski, Vadim; Dredze, Mark; Gehrmann, Sebastian; Kambadur, Prabhanjan; Rosenberg, David; Mann, Gideon (March 30, 2023). "BloombergGPT: A large Language Model for Finance". March 15, 2023. Archived from the original on March 12, 2023. Retrieved March 12, 2023 - by way of GitHub. GitHub. Archived from the original on August 23, 2024. Retrieved August 29, 2024. The staff that has been maintaining Gym since 2021 has moved all future growth to Gymnasium, a drop in replacement for Gym (import gymnasium as gym), and Gym is not going to be receiving any future updates.
3 August 2022). "AlexaTM 20B: Few-Shot Learning Using a big-Scale Multilingual Seq2Seq Model". 29 March 2022). "Training Compute-Optimal Large Language Models". Ananthaswamy, Anil (8 March 2023). "In AI, is bigger at all times higher?". Dey, Nolan (March 28, 2023). "Cerebras-GPT: A Family of Open, Compute-environment friendly, Large Language Models". Ren, Xiaozhe; Zhou, Pingyi; Meng, Xinfan; Huang, Xinjing; Wang, Yadao; Wang, Weichao; Li, Pengfei; Zhang, Xiaoda; Podolskiy, Alexander; Arshinov, Grigory; Bout, Andrey; Piontkovskaya, Irina; Wei, Jiansheng; Jiang, Xin; Su, Teng; Liu, Qun; Yao, Jun (March 19, 2023). "PanGu-Σ: Towards Trillion Parameter Language Model with Sparse Heterogeneous Computing". Raffel, Colin; Shazeer, Noam; Roberts, Adam; Lee, Katherine; Narang, Sharan; Matena, Michael; Zhou, Yanqi; Li, Wei; Liu, Peter J. (2020). "Exploring the bounds of Transfer Learning with a Unified Text-to-Text Transformer". Patel, Ajay; Li, Bryan; Rasooli, Mohammad Sadegh; Constant, Noah; Raffel, Colin; Callison-Burch, Chris (2022). "Bidirectional Language Models Are Also Few-shot Learners". Taylor, Ross; Kardas, Marcin; Cucurull, Guillem; Scialom, Thomas; Hartshorn, Anthony; Saravia, Elvis; Poulton, Andrew; Kerkez, Viktor; Stojnic, Robert (sixteen November 2022). "Galactica: A big Language Model for Science".
Manning, Christopher D. (2022). "Human Language Understanding & Reasoning". Hoffmann, Jordan; Borgeaud, Sebastian; Mensch, Arthur; Sifre, Laurent (12 April 2022). "An empirical analysis of compute-optimal massive language model coaching". Hoffmann, Jordan; Borgeaud, Sebastian; Mensch, Arthur; et al. The buying and selling rely is listed as 102 trades, however in actuality, there were 103 trades. And there isn't any such factor as US democracy. The smaller fashions including 66B are publicly accessible, whereas the 175B mannequin is offered on request. In case you are like me, after studying about something new - often by way of social media - my subsequent action is to search the net for extra information. DeepSeek: In contrast, DeepSeek strives for accuracy and reliability, especially in specific sectors like medication, regulation, and research. Well, mostly as a result of American AI corporations spent a decade or so, and hundreds of billions of dollars to develop their models using a whole lot of thousands of the latest and most powerful Graphic Processing chips (GPUs) (at $40,000 every), whereas DeepSeek v3 was built in only two months, for lower than $6 million and with much much less-powerful GPUs than the US corporations used. A state-of-the-art AI information middle might have as many as 100,000 Nvidia GPUs inside and value billions of dollars.
Here is more info in regards to deepseek français have a look at our own website.
댓글목록
등록된 댓글이 없습니다.