Shubham Sharma is a technology reporter with a focus on data and AI. He has written for various publications including VentureBeat, Dainik Jagran, and Tech News Tube. Shubham's work has been featured in The Economic Times, CNN-News18, and other notable platforms.
Preston is the artificial intelligence that powers the Intelligent Relations PR platform. Meet Preston
Not enough data
Shubham Sharma's coverage mainly revolves around AI, data analytics, and technology. He often includes expert commentary and announcements in his articles. Based on this pattern of coverage, he is likely to be interested in receiving pitches related to the latest advancements or innovations in artificial intelligence, particularly generative AI and its applications.
When reaching out to Shubham Sharma with a pitch, consider offering insights from industry experts who can comment on the implications of these advancements or those involved directly in the development process. Additionally, given his focus on technological developments across various sectors such as software & SaaS and data & analytics, new product launches or platform adaptations tailored for specific industries could also be of interest to him.
As there is no specified geographic focus for Shubham Sharma's articles, it would be beneficial to approach him with global perspectives rather than region-specific content.
This information evolves through artificial intelligence and human feedback. Improve this profile .
By: Shubham Sharma
Pulmonary fibrosis is a chronic lung disease that affects millions of people worldwide. However, many are still unaware of what it is, how it affects those diagnosed, and what can be done to manage this condition. This article aims to provide a clearer understanding of pulmonary fibrosis, making it easier for the general population to grasp the disease and its management options.
By: Shubham Sharma
AI accelerators and chips can help enterprises support select low- to medium-intensive AI workloads with better total cost of ownership.
By: Shubham Sharma
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More
By: Shubham Sharma
photo of Mostly AI’s synthetic text tool can unlock enterprise emails and conversations for AI training image Mostly AI's synthetic text tool can generate question-and-answer pairs, enabling enterprises to train smarter customer service chatbots.Read More
By: Shubham Sharma
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More
By: Shubham Sharma
photo of PicsArt’s creative AI playbook: A vision for contextual intelligence, AI agents image Eventually, Mehrabyan says contextual intelligence will lead PicsArt to an agent-based ecosystem.Read More
By: Shubham Sharma
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More
By: Shubham Sharma
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More
By: Shubham Sharma, Sameer Jain, Harleen Dahiya
This study investigates the subleading twist generalized transverse momentum dependent distributions (GTMDs) of a proton within the light-front quark-diquark model framework. We solve the parametrization equations for the Dirac matrix structure, yielding explicit GTMD expressions for both scalar and vector diquark configurations, leading to expressions for active and quarks. This analysis addresses the multidimensional nature of GTMDs by exploring their dependencies on one or two variables while keeping others fixed. Additionally, we extract transverse momentum dependent form factors from GTMDs by integrating over the longitudinal momentum fraction. The study uses three-dimensional plots to illustrate the variation of transverse momentum dependent form factors with the quark’s transverse momentum and the transverse momentum transfer to the proton.
By: Manuela Veloso, Salim Ibrahim, Daniele Magazzeni, Emanuele Albini, Saumitra Mishra, Shubham Sharma, Mattia Jacopo Villani
ojs.aaai.org Polyhedral geometry can be used to shed light on the behaviour of piecewise linear neural networks, such as ReLU-based architectures.
(833) 317-6278 
