Tag: ai/ml

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 …

Read more “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 …

Read more “Enabling large-scale health studies for the research community”

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 …

Read more “Build trust and safety for generative AI applications with Amazon Comprehend and LangChain”

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 …

Read more “Running AI and ML workloads with the Cloud HPC Toolkit”

Posted by Katherine Heller, Research Scientist, Google Research, on behalf of the CAIR Team Artificial intelligence (AI) and related machine learning (ML) technologies are increasingly influential in the world around us, making it imperative that we consider the potential impacts on society and individuals in all aspects of the technology that we create. To these …

Read more “Responsible AI at Google Research: Context in AI Research (CAIR)”

Posted by Katherine Heller, Research Scientist, Google Research, on behalf of the CAIR Team Artificial intelligence (AI) and related machine learning (ML) technologies are increasingly influential in the world around us, making it imperative that we consider the potential impacts on society and individuals in all aspects of the technology that we create. To these …

Read more “Responsible AI at Google Research: Context in AI Research (CAIR)”

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is essential for seamlessly bridging the gap between data science experimentation and deployment while meeting the requirements around model performance, security, and compliance. In order to fulfill regulatory and compliance requirements, the …

Read more “Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD”