Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Raiman, Jonathan"'
Large Language Models (LLMs) show promise in code generation tasks. However, their code-writing abilities are often limited in scope: while they can successfully implement simple functions, they struggle with more complex tasks. A fundamental differe
Externí odkaz:
http://arxiv.org/abs/2407.19055
Autor:
Song, Jialin, Swope, Aidan, Kirby, Robert, Roy, Rajarshi, Godil, Saad, Raiman, Jonathan, Catanzaro, Bryan
Automatically designing fast and space-efficient digital circuits is challenging because circuits are discrete, must exactly implement the desired logic, and are costly to simulate. We address these challenges with CircuitVAE, a search algorithm that
Externí odkaz:
http://arxiv.org/abs/2406.09535
Autor:
Lee, Chankyu, Roy, Rajarshi, Xu, Mengyao, Raiman, Jonathan, Shoeybi, Mohammad, Catanzaro, Bryan, Ping, Wei
Decoder-only large language model (LLM)-based embedding models are beginning to outperform BERT or T5-based embedding models in general-purpose text embedding tasks, including dense vector-based retrieval. In this work, we introduce the NV-Embed mode
Externí odkaz:
http://arxiv.org/abs/2405.17428
Autor:
Ducru, Pablo, Raiman, Jonathan, Lemos, Ronaldo, Garner, Clay, He, George, Balcha, Hanna, Souto, Gabriel, Branco, Sergio, Bottino, Celina
This article investigates how AI-generated content can disrupt central revenue streams of the creative industries, in particular the collection of dividends from intellectual property (IP) rights. It reviews the IP and copyright questions related to
Externí odkaz:
http://arxiv.org/abs/2406.11857
Autor:
Liu, Mingjie, Ene, Teodor-Dumitru, Kirby, Robert, Cheng, Chris, Pinckney, Nathaniel, Liang, Rongjian, Alben, Jonah, Anand, Himyanshu, Banerjee, Sanmitra, Bayraktaroglu, Ismet, Bhaskaran, Bonita, Catanzaro, Bryan, Chaudhuri, Arjun, Clay, Sharon, Dally, Bill, Dang, Laura, Deshpande, Parikshit, Dhodhi, Siddhanth, Halepete, Sameer, Hill, Eric, Hu, Jiashang, Jain, Sumit, Jindal, Ankit, Khailany, Brucek, Kokai, George, Kunal, Kishor, Li, Xiaowei, Lind, Charley, Liu, Hao, Oberman, Stuart, Omar, Sujeet, Pasandi, Ghasem, Pratty, Sreedhar, Raiman, Jonathan, Sarkar, Ambar, Shao, Zhengjiang, Sun, Hanfei, Suthar, Pratik P, Tej, Varun, Turner, Walker, Xu, Kaizhe, Ren, Haoxing
ChipNeMo aims to explore the applications of large language models (LLMs) for industrial chip design. Instead of directly deploying off-the-shelf commercial or open-source LLMs, we instead adopt the following domain adaptation techniques: domain-adap
Externí odkaz:
http://arxiv.org/abs/2311.00176
Autor:
Roy, Rajarshi, Raiman, Jonathan, Kant, Neel, Elkin, Ilyas, Kirby, Robert, Siu, Michael, Oberman, Stuart, Godil, Saad, Catanzaro, Bryan
Publikováno v:
ACM/IEEE Design Automation Conference (DAC), 2021, pp. 853-858
In this work, we present a reinforcement learning (RL) based approach to designing parallel prefix circuits such as adders or priority encoders that are fundamental to high-performance digital design. Unlike prior methods, our approach designs soluti
Externí odkaz:
http://arxiv.org/abs/2205.07000
Autor:
Raiman, Jonathan
Knowledge distillation between machine learning models has opened many new avenues for parameter count reduction, performance improvements, or amortizing training time when changing architectures between the teacher and student network. In the case o
Externí odkaz:
http://arxiv.org/abs/2011.11472
Understanding how knowledge about the world is represented within model-free deep reinforcement learning methods is a major challenge given the black box nature of its learning process within high-dimensional observation and action spaces. AlphaStar
Externí odkaz:
http://arxiv.org/abs/1912.06721
Autor:
OpenAI, Berner, Christopher, Brockman, Greg, Chan, Brooke, Cheung, Vicki, Dębiak, Przemysław, Dennison, Christy, Farhi, David, Fischer, Quirin, Hashme, Shariq, Hesse, Chris, Józefowicz, Rafal, Gray, Scott, Olsson, Catherine, Pachocki, Jakub, Petrov, Michael, Pinto, Henrique P. d. O., Raiman, Jonathan, Salimans, Tim, Schlatter, Jeremy, Schneider, Jonas, Sidor, Szymon, Sutskever, Ilya, Tang, Jie, Wolski, Filip, Zhang, Susan
On April 13th, 2019, OpenAI Five became the first AI system to defeat the world champions at an esports game. The game of Dota 2 presents novel challenges for AI systems such as long time horizons, imperfect information, and complex, continuous state
Externí odkaz:
http://arxiv.org/abs/1912.06680
The cost to train machine learning models has been increasing exponentially, making exploration and research into the correct features and architecture a costly or intractable endeavor at scale. However, using a technique named "surgery" OpenAI Five
Externí odkaz:
http://arxiv.org/abs/1912.06719