Favorite 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
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Shared by Google AI Technology February 24, 2023
Favorite 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
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Shared by AWS Machine Learning February 24, 2023
Favorite 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
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Shared by Google AI Technology February 23, 2023
Favorite Posted by Greg Corrado, Distinguished Scientist, and Yossi Matias, VP Engineering and Research, Google Research (This is Part 8 in our series of posts covering different topical areas of research at Google. You can find other posts in the series here.) Google’s focus on AI stems from the conviction
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Shared by Google AI Technology February 23, 2023
Favorite This post is co-written with Swagata Ashwani, Senior Data Scientist at Boomi. Boomi is an enterprise-level software as a service (SaaS) independent software vendor (ISV) that creates developer enablement tooling for software engineers. These tools integrate via API into Boomi’s core service offering. In this post, we discuss how
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Shared by AWS Machine Learning February 23, 2023
Favorite Posted by Hartmut Neven, VP of Engineering, and Julian Kelly, Director of Quantum Hardware, on behalf of the Google Quantum AI Team Many years from today, scientists will be able to use fault-tolerant quantum computers for large-scale computations with applications across science and industry. These quantum computers will be
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Shared by Google AI Technology February 22, 2023
Favorite For the first time ever, our Quantum AI researchers have experimentally demonstrated it’s possible to reduce errors by increasing the number of qubits. View Original Source (blog.google/technology/ai/) Here.
Favorite We’re thrilled to announce an expanded collaboration between AWS and Hugging Face to accelerate the training, fine-tuning, and deployment of large language and vision models used to create generative AI applications. Generative AI applications can perform a variety of tasks, including text summarization, answering questions, code generation, image creation,
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Shared by AWS Machine Learning February 22, 2023
Favorite After you build, train, and evaluate your machine learning (ML) model to ensure it’s solving the intended business problem proposed, you want to deploy that model to enable decision-making in business operations. Models that support business-critical functions are deployed to a production environment where a model release strategy is
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Shared by AWS Machine Learning February 22, 2023
Favorite Posted by John Platt, Distinguished Scientist, Google Research (This is Part 7 in our series of posts covering different topical areas of research at Google. You can find other posts in the series here.) It’s an incredibly exciting time to be a scientist. With the amazing advances in machine
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Shared by Google AI Technology February 21, 2023
Shared by Google AI Technology February 24, 2023
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