A demonstration of the RvS policy we learn with just supervised learning and a depth-two MLP. It uses no TD learning, advantage reweighting, or Transformers! Offline reinforcement learning (RL) is conventionally approached using value-based methods based on temporal difference (TD) learning. However, many recent algorithms reframe RL as a supervised learning problem. These algorithms learn…
Humans may be one of the biggest roadblocks keeping fully autonomous vehicles off city streets. If a robot is going to navigate a vehicle safely through downtown Boston, it must be able to predict what nearby drivers, cyclists, and pedestrians are going to do next. Behavior prediction is a tough problem, however, and current artificial…
Posted by Chen-Yu Lee and Chun-Liang Li, Research Scientists, Google Research, Cloud AI Team Form-based document understanding is a growing research topic because of its practical potential for automatically converting unstructured text data into structured information to gain insight about a document’s contents. Recent sequence modeling, which is a self-attention mechanism that directly models relationships…
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. How the AI industry profits from catastrophe It was meant to be a temporary side job—a way to earn some extra money. Oskarina Fuentes Anaya signed up for Appen, an AI data-labeling platform,…
It was meant to be a temporary side job—a way to earn some extra money. Oskarina Fuentes Anaya signed up for Appen, an AI data-labeling platform, when she was still in college studying to land a well-paid position in the oil industry. But then the economy tanked in Venezuela. Inflation skyrocketed, and a stable job,…
Posted by Zifeng Wang, Student Researcher, and Zizhao Zhang, Software Engineer, Google Research Supervised learning is a common approach to machine learning (ML) in which the model is trained using data that is labeled appropriately for the task at hand. Ordinary supervised learning trains on independent and identically distributed (IID) data, where all training examples…
My husband and I love to eat and to learn about history. So shortly after we married, we chose to honeymoon along the southern coast of Spain. The region, historically ruled by Greeks, Romans, Muslims, and Christians in turn, is famed for its stunning architecture and rich fusion of cuisines. Little did I know how…
The economy is being transformed by digital technologies, especially in artificial intelligence, that are rapidly changing how we live and work. But this transformation poses a troubling puzzle: these technologies haven’t done much to grow the economy, even as income inequality worsens. Productivity growth, which economists consider essential to improving living standards, has largely been…
Students in the MIT course 6.036 (Introduction to Machine Learning) study the principles behind powerful models that help physicians diagnose disease or aid recruiters in screening job candidates. Now, thanks to the Social and Ethical Responsibilities of Computing (SERC) framework, these students will also stop to ponder the implications of these artificial intelligence tools, which…
Posted by Andreas Steiner and Basil Mustafa, Research Software Engineers at Google Research, Brain team The ability to classify images into categories has been transformed by deep learning. It has also been significantly accelerated by transfer learning, whereby models are first pre-trained on large datasets, like ImageNet, to learn visual representations that are then transferred…