AI / ML

Amazon Quick introduces two new capabilities to accelerate dashboard creation. Users can now generate individual sheets within existing analyses using natural language prompts, which automatically selects visuals, adds filters, and calculates fields like year-over-year growth. Additionally, the tool can recreate an editable analysis from an image of an existing dashboard, supporting inputs from other BI tools.

• Generate Sheet allows natural language prompting to add visuals and calculated fields to existing analyses without manual build steps.
• Image-to-analysis feature reconstructs editable dashboards from screenshots, including those from third-party BI platforms.
• Automated inclusion of filter controls and comparisons (e.g., month-over-month) reduces manual configuration overhead.
• Accelerates iteration cycles by removing the need to build each visual component from scratch.

Amazon SageMaker AI now allows users to submit prioritized lists of acceptable instance types for training and processing workloads. Previously, jobs required a single specific instance type, often leading to unpredictable waits during high-demand periods. This new feature automates capacity selection across multiple options, eliminating the need for complex custom retry logic or concurrent job submissions.

• Submit prioritized lists of instance types instead of a single fixed option to reduce wait times.
• Eliminate custom retry logic or concurrent job submissions previously needed for capacity finding.
• Beneficial for workloads like fine-tuning that perform comparably across various instance sizes.
• Automates selection process to find the first available compute capacity in the preference list.