(An English-language version of this post can be read here.) Nota del editor: Este es el cuarto post de Explicando Palantir, una serie que explora una selección de temas, incluyendo nuestro enfoque hacia la privacidad, la protección, y la seguridad de la IA/ML, entre otros. Las entradas anteriores exploran nuestro modelo de negocio, los controles de …
Read more “Confianza en los Datos (Explicando Palantir, #4)”
Model tuning is the experimental process of finding the optimal parameters and configurations for a machine learning (ML) model that result in the best possible desired outcome with a validation dataset. Single objective optimization with a performance metric is the most common approach for tuning ML models. However, in addition to predictive performance, there may …
Communication Service providers (CSPs) are facing a new dynamic where they have a digitally savvy customer base and market competition is higher than ever before. Understanding customers and being able to present them with relevant products and services in a contextual manner has become the focus of CSPs. Digitization and hyper-personalization will be powering the …
Our mission is to ensure that artificial general intelligence—AI systems that are generally smarter than humans—benefits all of humanity. If AGI is successfully created, this technology could help us elevate humanity by increasing abundance, turbocharging the global economy, and aiding in the discovery of new scientific knowledge that changes the limits of possibility. AGI has …
Posted by Yang Li, Research Scientist, and Gang Li, Software Engineer, Google Research The computational understanding of user interfaces (UI) is a key step towards achieving intelligent UI behaviors. Previously, we investigated various UI modeling tasks, including widget captioning, screen summarization, and command grounding, that address diverse interaction scenarios such as automation and accessibility. We …
Read more “A vision-language approach for foundational UI understanding”
In recent years, advances in computer vision have enabled researchers, first responders, and governments to tackle the challenging problem of processing global satellite imagery to understand our planet and our impact on it. AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers …
Advancements in whole genome sequencing have ignited a revolution in digital biology. Genomics programs across the world are gaining momentum as the cost of high-throughput, next-generation sequencing has declined. Whether used for sequencing critical-care patients with rare diseases or in population-scale genetics research, whole genome sequencing is becoming a fundamental step in clinical workflows and …
Hey there, We are planning something and wanted to give you a sneak peek. Yes, it’s about ChatGPT and the Chatbot Conference. We are working on bringing you an event that will blow your mind. We can’t say too much right now, but trust us, you won’t want to miss this. We have big plans …
Posted by Aviral Kumar, Student Researcher, and Sergey Levine, Research Scientist, Google Research Reinforcement learning (RL) algorithms can learn skills to solve decision-making tasks like playing games, enabling robots to pick up objects, or even optimizing microchip designs. However, running RL algorithms in the real world requires expensive active data collection. Pre-training on diverse datasets …
Read more “Pre-training generalist agents using offline reinforcement learning”
Over the last 10 years, a number of players have developed autonomous vehicle (AV) systems using deep neural networks (DNNs). These systems have evolved from simple rule-based systems to Advanced Driver Assistance Systems (ADAS) and fully autonomous vehicles. These systems require petabytes of data and thousands of compute units (vCPUs and GPUs) to train. This …
Read more “Modular functions design for Advanced Driver Assistance Systems (ADAS) on AWS”