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Peter Ma was bored in his high school computer science class. So he decided to teach himself something new: how to use artificial intelligence to find alien life. That’s how he eventually became the lead author of a groundbreaking study published in Nature Astronomy. The study reveals how Ma and his co-authors used AI to …
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Tens of thousands of AWS customers use AWS machine learning (ML) services to accelerate their ML development with fully managed infrastructure and tools. For customers who have been developing ML models on premises, such as their local desktop, they want to migrate their legacy ML models to the AWS Cloud to fully take advantage of …
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As deep learning models become increasingly complex and datasets larger, distributed training is all but a necessity. Faster training makes for faster iteration to reach your modeling goals. But distributed training comes with its own set of challenges. On top of deciding what kind of distribution strategy you want to use and making changes to …
Read more “Optimize PyTorch training performance with Reduction Server on Vertex AI”
The Walking Oligomeric Robotic Mobility System, or WORMS, is a reconfigurable, modular, multiagent robotics architecture for extreme lunar terrain mobility. The system could be used to assemble autonomous worm-like parts into larger biomimetic robots that could explore lava tubes, steep slopes, and the moon’s permanently shadowed regions.
Pre-trained model representations have demonstrated state-of-the-art performance in speech recognition, natural language processing, and other applications. Speech models, such as Bidirectional Encoder Representations from Transformers (BERT) and Hidden units BERT (HuBERT), have enabled generating lexical and acoustic representations to benefit speech recognition applications. We investigated the use of pre-trained model representations for estimating dimensional emotions, …
We’ve created GPT-4, the latest milestone in OpenAI’s effort in scaling up deep learning. GPT-4 is a large multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks.
By Guru Tahasildar, Amir Ziai, Jonathan Solórzano-Hamilton, Kelli Griggs, Vi Iyengar Introduction Netflix leverages machine learning to create the best media for our members. Earlier we shared the details of one of these algorithms, introduced how our platform team is evolving the media-specific machine learning ecosystem, and discussed how data from these algorithms gets stored in …
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Posted by Ellery Wulczyn and Yun Liu, Google Research When a patient is diagnosed with cancer, one of the most important steps is examination of the tumor under a microscope by pathologists to determine the cancer stage and to characterize the tumor. This information is central to understanding clinical prognosis (i.e., likely patient outcomes) and …
Today, tens of thousands of customers are building, training, and deploying machine learning (ML) models using Amazon SageMaker to power applications that have the potential to reinvent their businesses and customer experiences. These ML models have been increasing in size and complexity over the last few years, which has led to state-of-the-art accuracies across a …
The future of artificial intelligence (AI) will be open. New and innovative capabilities in areas like generative AI will come from all corners of the technology ecosystem and from companies distributed around the globe — from early stage startups to cloud-native AI platforms to large, global enterprises. The momentum in this space is incredible. In …
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