In the business world, generative AI has brought the ability to automate content generation such as text, images and even code, increasing operational efficiency and saving time and resources for businesses. However, the generative AI confidence gap has also emerged as a pivotal concern, casting a spotlight on the reliability and quality of AI-generated content.
This gap rose from various factors, including the absence of a definitive "ground truth," language ambiguity, and the presence of biases and ethical concerns, all of which have contributed to a growing sense of uncertainty among users. In turn, this highlights the pressing need for ongoing research and development to refine AI models and to enable them to better grasp context and nuance, reduce biases and provide mechanisms for users to gauge and control the confidence levels associated with AI-generated content.
To close that gap, DataRobot, has announced new end-to-end functionality that also accelerates AI solutions from prototype to production and drives real-world value.
For context, DataRobot is an AI company that helps organizations implement AI solutions to drive business impacts. They offer an open AI platform that supports the AI lifecycle, which enables secure and efficient AI development and deployment. (And they're trusted by organizations worldwide to address AI challenges.)
So, the new functionality announced by DataRobot brings enterprise-grade governance and observability to generative and predictive AI in the DataRobot AI Platform.
The 360-degree Observability Console provides a full-360-degree view observability for DataRobot and third-party models across cloud providers, on-premises or at the edge. The console acts as a command and control center with comprehensive insights into the performance, behavior and health of AI systems and models, allowing for immediate detection of issues or anomalies.
The LLM Cost and Performance Monitoring feature allows organizations to observe and manage their generative AI solutions and costs in real-time with customizable metrics designed for high performance and on-target budgets. This means that organizations can see cost per prediction and total spend by generative AI solution, set their own alerts to avoid exceeding thresholds, and make cost-performance tradeoff decisions.
Generative AI Guard Models allows organizations to assess critical attributes like toxicity, sentiment, PII leaks, prompt injection and correctness for generative AI models in production, as well as capture user feedback on the quality of generated responses to improve models over time.
The Unified AI Registry is a single system of record to govern all generative and predictive AI assets, including models from different systems. The new centralized registry helps organizations track what matters while unifying disparate projects, processes and multi-cloud environments for seamless cross-team visibility and collaboration across the organization.
Multi-Provider LLM Playground is a visual interface with built-in access to GCP Vertex (News - Alert) AI, Azure OpenAI and AWS BedRock to easily compare and experiment different recipes with any combination of foundation model, vector databases and prompting strategies.
Generative AI Accelerators are designed to quickly accomplish common tasks for accelerating generative AI deployment, such as building and hosting a Retrieval Augmented Generation application, adding custom metrics, monitoring external models and integrating with business applications like Slack and Microsoft (News - Alert) Teams.
Enhancements to the DataRobot AI Platform will allow organizations to better operate with correctness and control, govern with full transparency and build with speed and optionality.
“The demands around generative AI are broad, complex and evolving in real-time,” said Venky Veeraraghavan, Chief Product Officer, DataRobot. “With this latest launch, we've designed a suite of production-ready capabilities to address the challenges unique to generative AI and instill the confidence required to bring transformative solutions into practice.”
Be part of the discussion about the latest trends and developments in the Generative AI space at Generative AI Expo, taking place February 13-15, 2024, in Fort Lauderdale, Florida. Generative AI Expo discusses the evolution of GenAI and feature conversations focused on the potential for GenAI across industries and how the technology is already being used to create new opportunities for businesses to improve operations, enhance customer experiences, and create new growth opportunities.
Edited by
Alex Passett
