Study explores the scaling of deep learning models for chemistry research

Deep neural networks (DNNs) have proved to be highly promising tools for analyzing large amounts of data, which could speed up research in various scientific fields. For instance, over the past few years, some computer scientists have trained models based on these networks to analyze chemical data and identify promising chemicals for various applications.

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Enabling large-scale health studies for the research community

Posted by Chintan Ghate, Software Engineer, and Diana Mincu, Research Engineer, Google Research As consumer technologies like fitness trackers and mobile phones become more widely used for health-related data collection, so does the opportunity to leverage these data pathways to study and advance our understanding of medical conditions. We have previously touched upon how our …

How to implement enterprise resource planning (ERP)

Once your business has decided to switch to an enterprise resource planning (ERP) software system, the next step is to implement ERP. For a business to see the benefits of an ERP adoption it must first be deployed properly and efficiently by a team that typically includes a project manager and department managers as well. …

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Enabling large-scale health studies for the research community

Posted by Chintan Ghate, Software Engineer, and Diana Mincu, Research Engineer, Google Research As consumer technologies like fitness trackers and mobile phones become more widely used for health-related data collection, so does the opportunity to leverage these data pathways to study and advance our understanding of medical conditions. We have previously touched upon how our …

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Build trust and safety for generative AI applications with Amazon Comprehend and LangChain

We are witnessing a rapid increase in the adoption of large language models (LLM) that power generative AI applications across industries. LLMs are capable of a variety of tasks, such as generating creative content, answering inquiries via chatbots, generating code, and more. Organizations looking to use LLMs to power their applications are increasingly wary about …

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Running AI and ML workloads with the Cloud HPC Toolkit

The convergence of high performance computing (HPC) systems and AI and machine learning workloads is transforming the way we solve complex problems. HPC systems are well-suited for AI and machine learning workloads because they offer the AI-enabled computing infrastructure and parallel processing capabilities needed to train ML workloads like large language models (LLMs) — AI …