Posit released Positron on Amazon SageMaker AI, saying it enables data scientists to run their integrated development environment (IDE) within a unified platform. It is the company's first major update since its initial launch as a data science tool.
Posit reported a 2.03 percent default rate in the synthetic 50,000-loan portfolio, measured during data profiling in Amazon Athena. That compares with an earlier 12.3 percent observed default rate in the highest-risk decile during model evaluation.
Positron is built on Amazon SageMaker AI and targets data science workflows that require governed data access, R analysis, Python model development, and real-time deployment. Availability begins with a synthetic dataset, initially for data science teams using Amazon SageMaker Studio.
"You can run multiple Spaces at once for independent projects, and use a shared Space so several people collaborate in the same Positron application," said Posit’s product team. The tool allows teams to reserve capacity with SageMaker AI training plans so compute is available for scheduled training.
The announcement follows the release of the Positron container image definition, which is built on the Amazon SageMaker Distribution image. Posit said the integration streamlines data science workflows by combining data access, analysis, and deployment into one environment.
Posit did not say how the tool will perform with larger datasets, and raised the question of how the cache efficiency and cost estimates will scale with different models and providers. The tool is now available for use in the Amazon SageMaker Studio domain.
Source: awsml
