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Favorite Amazon SageMaker Studio can help you build, train, debug, deploy, and monitor your models and manage your machine learning (ML) workflows. Amazon SageMaker Pipelines enables you to build a secure, scalable, and flexible MLOps platform within Studio. In this post, we explain how to run PySpark processing jobs within
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Shared by AWS Machine Learning April 11, 2023
Favorite Enterprise customers have multiple lines of businesses (LOBs) and groups and teams within them. These customers need to balance governance, security, and compliance against the need for machine learning (ML) teams to quickly access their data science environments in a secure manner. These enterprise customers that are starting to
Read More Shared by AWS Machine Learning April 11, 2023
Favorite Developing web interfaces to interact with a machine learning (ML) model is a tedious task. With Streamlit, developing demo applications for your ML solution is easy. Streamlit is an open-source Python library that makes it easy to create and share web apps for ML and data science. As a
Read More Shared by AWS Machine Learning April 11, 2023
Favorite Financial services, the gig economy, telco, healthcare, social networking, and other customers use face verification during online onboarding, step-up authentication, age-based access restriction, and bot detection. These customers verify user identity by matching the user’s face in a selfie captured by a device camera with a government-issued identity card
Read More Shared by AWS Machine Learning April 11, 2023
Favorite Posted by Sara Ahadi, Research Fellow, Applied Science, and Andrew Carroll, Product Lead, Genomics Aging is a process that is characterized by physiological and molecular changes that increase an individual’s risk of developing diseases and eventually dying. Being able to measure and estimate the biological signatures of aging can
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Shared by Google AI Technology April 11, 2023
Favorite A Google AI expert answers common questions about generative AI, large language models, machine learning and more. View Original Source (blog.google/technology/ai/) Here.
Favorite You don’t have to be an expert in machine learning (ML) to appreciate the value of large language models (LLMs). Better search results, image recognition for the visually impaired, creating novel designs from text, and intelligent chatbots are just some examples of how these models are facilitating various applications
Read More Shared by AWS Machine Learning April 10, 2023
Favorite In November 2022, we announced that AWS customers can generate images from text with Stable Diffusion models using Amazon SageMaker JumpStart. Today, we are excited to introduce a new feature that enables users to inpaint images with Stable Diffusion models. Inpainting refers to the process of replacing a portion
Read More Shared by AWS Machine Learning April 10, 2023
Favorite Posted by Thomas Lew, Research Intern, and Montserrat Gonzalez Arenas, Research Engineer, Google Research, Brain Team Over the past several years, the capabilities of robotic systems have improved dramatically. As the technology continues to improve and robotic agents are more routinely deployed in real-world environments, their capacity to assist
Read More Shared by Google AI Technology April 7, 2023
Favorite With the advent of high-speed 5G mobile networks, enterprises are more easily positioned than ever with the opportunity to harness the convergence of telecommunications networks and the cloud. As one of the most prominent use cases to date, machine learning (ML) at the edge has allowed enterprises to deploy
Read More Shared by AWS Machine Learning April 7, 2023