The infrastructure powering IBM's Gen AI model development

Autor: Gershon, Talia, Seelam, Seetharami, Belgodere, Brian, Bonilla, Milton, Hoang, Lan, Barnett, Danny, Chung, I-Hsin, Mohan, Apoorve, Chen, Ming-Hung, Luo, Lixiang, Walkup, Robert, Evangelinos, Constantinos, Salaria, Shweta, Dombrowa, Marc, Park, Yoonho, Kayi, Apo, Schour, Liran, Alim, Alim, Sydney, Ali, Maniotis, Pavlos, Schares, Laurent, Metzler, Bernard, Karacali-Akyamac, Bengi, Wen, Sophia, Chiba, Tatsuhiro, Choochotkaew, Sunyanan, Yoshimura, Takeshi, Misale, Claudia, Elengikal, Tonia, Connor, Kevin O, Liu, Zhuoran, Molina, Richard, Schneidenbach, Lars, Caden, James, Laibinis, Christopher, Fonseca, Carlos, Tarasov, Vasily, Sundararaman, Swaminathan, Schmuck, Frank, Guthridge, Scott, Cohn, Jeremy, Eshel, Marc, Muench, Paul, Liu, Runyu, Pointer, William, Wyskida, Drew, Krull, Bob, Rose, Ray, Wolfe, Brent, Cornejo, William, Walter, John, Malone, Colm, Perucci, Clifford, Franco, Frank, Hinds, Nigel, Calio, Bob, Druyan, Pavel, Kilduff, Robert, Kienle, John, McStay, Connor, Figueroa, Andrew, Connolly, Matthew, Fost, Edie, Roma, Gina, Fonseca, Jake, Levy, Ido, Payne, Michele, Schenkel, Ryan, Malki, Amir, Schneider, Lion, Narkhede, Aniruddha, Moshref, Shekeba, Kisin, Alexandra, Dodin, Olga, Rippon, Bill, Wrieth, Henry, Ganci, John, Colino, Johnny, Habeger-Rose, Donna, Pandey, Rakesh, Gidh, Aditya, Gaur, Aditya, Patterson, Dennis, Salmani, Samsuddin, Varma, Rambilas, Rumana, Rumana, Sharma, Shubham, Mishra, Mayank, Panda, Rameswar, Prasad, Aditya, Stallone, Matt, Zhang, Gaoyuan, Shen, Yikang, Cox, David, Puri, Ruchir, Agrawal, Dakshi, Thorstensen, Drew, Belog, Joel, Tang, Brent, Gupta, Saurabh Kumar, Biswas, Amitabha, Maheshwari, Anup, Gampel, Eran, Van Patten, Jason, Runion, Matthew, Kaki, Sai, Bogin, Yigal, Reitz, Brian, Pritko, Steve, Najam, Shahan, Nambala, Surya, Chirra, Radhika, Welp, Rick, DiMitri, Frank, Telles, Felipe, Arvelo, Amilcar, Chu, King, Seminaro, Ed, Schram, Andrew, Eickhoff, Felix, Hanson, William, Mckeever, Eric, Joseph, Dinakaran, Chaudhary, Piyush, Shivam, Piyush, Chaudhary, Puneet, Jones, Wesley, Guthrie, Robert, Bostic, Chris, Islam, Rezaul, Duersch, Steve, Sawdon, Wayne, Lewars, John, Klos, Matthew, Spriggs, Michael, McMillan, Bill, Gao, George, Kamra, Ashish, Singh, Gaurav, Curry, Marc, Katarki, Tushar, Talerico, Joe, Shi, Zenghui, Malleni, Sai Sindhur, Gallen, Erwan

AI Infrastructure plays a key role in the speed and cost-competitiveness of developing and deploying advanced AI models. The current demand for powerful AI infrastructure for model training is driven by the emergence of generative AI and foundational

Externí odkaz: http://arxiv.org/abs/2407.05467

Projective Integral Updates for High-Dimensional Variational Inference

Autor: Duersch, Jed A.

Variational inference is an approximation framework for Bayesian inference that seeks to improve quantified uncertainty in predictions by optimizing a simplified distribution over parameters to stand in for the full posterior. Capturing model variati

Externí odkaz: http://arxiv.org/abs/2301.08374

Variational Kalman Filtering with Hinf-Based Correction for Robust Bayesian Learning in High Dimensions

Autor: Das, Niladri, Duersch, Jed A., Catanach, Thomas A.

In this paper, we address the problem of convergence of sequential variational inference filter (VIF) through the application of a robust variational objective and Hinf-norm based correction for a linear Gaussian system. As the dimension of state or

Externí odkaz: http://arxiv.org/abs/2204.13089

A Qualitative Investigation of Factors Influencing the Integration of Complementary and Integrative Healthcare Recommendations in the Daily Lives of Patients with Cancer

Autor: Helena Dürsch BSc, Ursula Boltenhagen MSc, RN, Cornelia Mahler Professor, PhD, MA, RN, Stefanie Joos Professor,MD, Szecsenyi Joachim Professor, MD, MSc, Dipl-Soz, Nadja Klafke PhD, MA

Publikováno v: Integrative Cancer Therapies, Vol 23 (2024)

Background: Many patients diagnosed with cancer use complementary and integrative healthcare (CIH) approaches to manage their cancer- and treatment-related symptoms and improve their well-being. Evidence suggests that counseling on CIH can improve he

Externí odkaz: https://doaj.org/article/11733a9346584b819eb6211409c28cee

Parsimonious Inference

Autor: Duersch, Jed A., Catanach, Thomas A.

Bayesian inference provides a uniquely rigorous approach to obtain principled justification for uncertainty in predictions, yet it is difficult to articulate suitably general prior belief in the machine learning context, where computational architect

Externí odkaz: http://arxiv.org/abs/2103.02165