Runpod offers a cloud-based platform designed for running AI workloads, focusing on providing scalable, on-demand GPU resources to accelerate machine learning (ML) model training and inference. With its diverse selection of powerful GPUs like the NVIDIA A100, RTX 3090, and H100, Runpod supports a wide range of AI applications, from deep learning to data processing. The platform is designed to minimize startup time, providing near-instant access to GPU pods, and ensures scalability with autoscaling capabilities for real-time AI model deployment. Runpod also offers serverless functionality, job queuing, and real-time analytics, making it an ideal solution for businesses needing flexible, cost-effective GPU resources without the hassle of managing infrastructure.
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Planview AdaptiveWork is a project and portfolio management product for organizations managing complex execution across multiple portfolios and delivery models. It supports IT PPM, Professional Services Automation, Product Development and R&D, and business project and program management use cases, with Planview Anvi available as an embedded AI add-on for insights and automation.
Governed Workflow Automation
-Low-code workflow automation for any step in the portfolio and project management process
-Changes ripple automatically across hundreds or thousands of projects
-Admins create and manage workflow changes without code
-Waterfall, agile, stage-gate, and hybrid delivery supported in one governed system
Resource and Capacity Planning
-Time-phased planning and allocation across thousands of resources by month, quarter, or year
-Planning horizon extends years forward and back without restructuring the system
-Supports employees, contractors, equipment, and other non-labor resources
Financial and Portfolio Reporting
-Bidirectional reporting: top-down portfolio to project, and bottom-up project to portfolio
-Time-phased financial planning, forecasting, and tracking, including when funds are committed or earned
-Role-based and executive-ready reporting dashboards
-Native data export on any data object, including custom fields, for ALM, PLM, ERP, and BI systems
Extensible Data Model
-Every standard object, custom field, and custom object automatically generates API endpoints
-Custom objects support hundreds of configurable fields, each API-enabled by design
-Data model can be extended without breaking integrations or requiring middleware
Embedded AI with Planview Anvi
-Natural language questions answered about any project, program, or portfolio using live data
-Scheduled agents automate recurring status reports on a defined schedule
-Risk identification agent surfaces risks at project initiation from scope, timeline, and resource profile
-Work plan agent surfaces recommendations based on delivery patterns across the organization
-Sentiment analysis across project text fields and an in-app text assistant for tone, grammar, and translation
-Customer data is not used to train AI models
AdaptiveWork is designed for upper mid-market to large organizations, including departments within larger enterprises, that need governance and reporting to scale without adding administrative overhead.
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Amazon Rekognition
Amazon Rekognition makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology that requires no machine learning expertise to use. With Amazon Rekognition, you can identify objects, people, text, scenes, and activities in images and videos, as well as detect any inappropriate content. Amazon Rekognition also provides highly accurate facial analysis and facial search capabilities that you can use to detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases.
With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs. For example, you can build a model to classify specific machine parts on your assembly line or to detect unhealthy plants. Amazon Rekognition Custom Labels takes care of the heavy lifting of model development for you, so no machine learning experience is required.
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