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Boosting developer productivity: How Deloitte uses Amazon SageMaker Canvas for no-code/low-code machine learning

Favorite The ability to quickly build and deploy machine learning (ML) models is becoming increasingly important in today’s data-driven world. However, building ML models requires significant time, effort, and specialized expertise. From data collection and cleaning to feature engineering, model building, tuning, and deployment, ML projects often take months for

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Shared by AWS Machine Learning December 2, 2023

Unsupervised speech-to-speech translation from monolingual data

Favorite Posted by Eliya Nachmani, Research Scientist, and Michelle Tadmor Ramanovich, Software Engineer, Google Research Speech-to-speech translation (S2ST) is a type of machine translation that converts spoken language from one language to another. This technology has the potential to break down language barriers and facilitate communication between people from different

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Shared by Google AI Technology December 1, 2023

Evaluate large language models for quality and responsibility

Favorite The risks associated with generative AI have been well-publicized. Toxicity, bias, escaped PII, and hallucinations negatively impact an organization’s reputation and damage customer trust. Research shows that not only do risks for bias and toxicity transfer from pre-trained foundation models (FM) to task-specific generative AI services, but that tuning

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Shared by AWS Machine Learning December 1, 2023

Easily build semantic image search using Amazon Titan

Favorite Digital publishers are continuously looking for ways to streamline and automate their media workflows to generate and publish new content as rapidly as they can, but without foregoing quality. Adding images to capture the essence of text can improve the reading experience. Machine learning techniques can help you discover

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Shared by AWS Machine Learning December 1, 2023

Build and evaluate machine learning models with advanced configurations using the SageMaker Canvas model leaderboard

Favorite Amazon SageMaker Canvas is a no-code workspace that enables analysts and citizen data scientists to generate accurate machine learning (ML) predictions for their business needs. Starting today, SageMaker Canvas supports advanced model build configurations such as selecting a training method (ensemble or hyperparameter optimization) and algorithms, customizing the training

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Shared by AWS Machine Learning December 1, 2023

Scale foundation model inference to hundreds of models with Amazon SageMaker – Part 1

Favorite As democratization of foundation models (FMs) becomes more prevalent and demand for AI-augmented services increases, software as a service (SaaS) providers are looking to use machine learning (ML) platforms that support multiple tenants—for data scientists internal to their organization and external customers. More and more companies are realizing the

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Shared by AWS Machine Learning December 1, 2023