Rohan Varma
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Articles by Rohan Varma
The AI Product Operating Model
Marty Cagan made the product operating model famous. But if you look at how the top AI companies are operating, it is quite different: Anthropic engineers prototype hundreds of solutions and ship without ever consulting a product manager or designer. OpenAI’s new hot product Codex started with just two PMs, one designer, and about 40 engineers, collectively responsible for 10 to 12 distinct product surfaces.
Learning a Deep Language Model for Microbiomes: The Power of Large Scale Unlabeled Microbiome Data
Quintin Pope, Rohan Varma, Christine Tataru, Maude M David, Xiaoli Fern. Abstract We use open source human gut microbiome data to learn a microbial “language” model by adapting techniques from Natural Language Processing (NLP). Our microbial “language” model is trained in a self-supervised fashion (i.e., without additional external labels) to capture the interactions among different microbial taxa and the common compositional patterns in microbial communities.
Learning a deep language model for microbiomes: The power of large scale unlabeled microbiome data
Citation: Pope Q, Varma R, Tataru C, David MM, Fern X (2025) Learning a deep language model for microbiomes: The power of large scale unlabeled microbiome data. PLoS Comput Biol 21(5): e1011353. https://doi.org/10.1371/journal.pcbi.1011353 Editor: Stacey D. Finley, University of Southern California, UNITED STATES OF AMERICA Received: July 25, 2023; Accepted: March 24, 2025; Published: May 7, 2025 Copyright: © 2025 Pope et al.
Scaling your LLM inference workloads: multi-node deployment with TensorRT-LLM and Triton on Amazon EKS | Amazon Web Services
This post was contributed by Aman Shanbhag from, and Kshitiz Gupta, Jiahong Liu, Rohan Varma, and Wenhan Tan from NVIDIA. In the ever-evolving landscape of Artificial Intelligence, Large Language Models (LLMs) have been growing exponentially in size and capability.
Tips for Efficient Task Management
In modern web applications, it's crucial to handle time-consuming tasks efficiently. Whether it's sending emails, processing uploaded files, or generating reports, Laravel's powerful queue system can help you manage these tasks asynchronously, improving your application's performance and user experience. In this blog, we'll dive deep into mastering Laravel queues and jobs for efficient task handling. Table of Contents 1.
Learning a deep language model for microbiomes: the power of large scale unlabeled microbiome data
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Discover the Best 10 Node.js IDEs for Building Modern Applications in 2023
Discover the Best 10 Node.js IDEs for Building Modern Applications in 2023 Building modern applications with Node.js requires the right tools and resources. One essential tool for developers is an Integrated Development Environment (IDE) that provides a feature-rich environment for efficient coding. In this blog, we will explore the top 10 Node.js IDEs that empower developers to create robust and innovative applications.
Top Features in React to Boost Your Web Development You Need to Know in 2023
Top New Features in React to Boost Your Web Development You Need to Know in 2023 React is an ever-evolving technology that has been revolutionizing web development since its release. In this blog, we will explore some of the top new features in React to boost your web development, along with some useful resources to help you stay up-to-date with the latest developments in React. One of the significant new features in React is automatic code splitting.
5 Key Changes in Node.js 20 You Need to Know in 2023
Node.js 20 was launched on April 1st, 2023, and it includes a number of new updates that aim to enhance the overall developer experience. It's critical to comprehend these changes and how they may affect your projects whether you are an experienced Node.js developer or are just getting started with the platform.
Scaling Multimodal Foundation Models in TorchMultimodal with Pytorch Distributed
Introduction In recent years, scaling model sizes has become a promising area of research. In the field of NLP, language models have gone from hundreds of millions of parameters (BERT) to hundreds of billions of parameters (GPT-3) demonstrating significant improvements on downstream tasks. The scaling laws for large scale language models have also been studied extensively in the industry.
Introducing PyTorch Fully Sharded Data Parallel (FSDP) API
Recent studies have shown that large model training will be beneficial for improving model quality. During the last 3 years, model size grew 10,000 times from BERT with 110M parameters to Megatron-2 with one trillion. However, training large AI models is not easy—aside from the need for large amounts of computing resources, software engineering complexity is also challenging. PyTorch has been working on building tools and infrastructure to make it easier.
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