Our approach to AI safety
Ensuring that AI systems are built, deployed, and used safely is critical to our mission.
Implement unified text and image search with a CLIP model using Amazon SageMaker and Amazon OpenSearch Service
The rise of text and semantic search engines has made ecommerce and retail businesses search easier for its consumers. Search engines powered by unified text and image can provide extra flexibility in search solutions. You can use both text and images as queries. For example, you have a folder of hundreds of family pictures in …
Google’s Cloud TPU v4 provides exaFLOPS-scale ML with industry-leading efficiency
Editor’s note: Today, two legendary Google engineers describe the “secret sauce” that has made TPU v4 a platform of choice for the world’s leading AI researchers and developers for training machine learning models at scale. Norm Jouppi is the chief architect for all Google’s TPUs, from TPU v1 to TPU v4. He is a Google …
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NVIDIA Takes Inference to New Heights Across MLPerf Tests
MLPerf remains the definitive measurement for AI performance as an independent, third-party benchmark. NVIDIA’s AI platform has consistently shown leadership across both training and inference since the inception of MLPerf, including the MLPerf Inference 3.0 benchmarks released today. “Three years ago when we introduced A100, the AI world was dominated by computer vision. Generative AI …
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AI progress is scaring people
TL;DR The Future of Life Institute calls for a 6-month AI moratorium. Image Credit Pause Giant AI Experiments: An Open Letter … We call on all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4. — Future of Life Institute The Future of Life Institute …
Automate and implement version control for Amazon Kendra FAQs
Amazon Kendra is an intelligent search service powered by machine learning (ML). Amazon Kendra reimagines enterprise search for your websites and applications so your employees and customers can easily find the content they’re looking for, even when it’s scattered across multiple locations and content repositories within your organization. Amazon Kendra FAQs allow users to upload …
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Meet the Data Champions: How Goodcall is bringing the power of AI to Main Street Businesses
In our new blog series, “Meet our Data Champions,” we showcase the exciting work Google Cloud customers are doing with data and AI/ML. In this edition, we talk to Bob Summers, CEO and founder of Goodcall, a company whose phone AI service leverages Google Cloud Speech AI technologies to bring the power of AI to …
TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation
Denoising Diffusion models have demonstrated their proficiency for generative sampling. However, generating good samples often requires many iterations. Consequently, techniques such as binary time-distillation (BTD) have been proposed to reduce the number of network calls for a fixed architecture. In this paper, we introduce TRAnsitive Closure Time-distillation (TRACT), a new method that extends BTD. For …
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Generate a counterfactual analysis of corn response to nitrogen with Amazon SageMaker JumpStart solutions
In his book The Book of Why, Judea Pearl advocates for teaching cause and effect principles to machines in order to enhance their intelligence. The accomplishments of deep learning are essentially just a type of curve fitting, whereas causality could be used to uncover interactions between the systems of the world under various constraints without …
How you can automate ML experiment tracking with Vertex AI Experiments autologging
Practical machine learning (ML) is a trial and error process. ML practitioners compare different performance metrics by running ML experiments till you find the best model with a given set of parameters. Because of the experimental nature of ML, there are many reasons for tracking ML experiments and making them reproducible including debugging and compliance. …
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