Cloudera announced several new Accelerators for ML Projects (AMPs), designed to reduce time-to-value for enterprise AI use cases. The new additions focus on providing enterprises with cutting-edge AI techniques and examples within Cloudera that can assist AI integration and drive more impactful results.
AMPs are end-to-end machine learning (ML) based projects that can be deployed with a single-click directly from the Cloudera platform. Each AMP encapsulates industry-leading practices for tackling complex ML challenges with workflows that facilitate seamless transitions, no matter where enterprises are running examples or deploying data.
With its collection of AMPs, Cloudera is committed to making AI more accessible so businesses can accelerate adoption and maximize the value of both their own data and the generated AI outputs. The latest AMPs and updates include:
● Fine-Tuning Studio – Provides users with an all-encompassing application and “ecosystem” for managing, fine tuning, and evaluating LLMs.
● RAG with Knowledge Graph – A demonstration of how to power a RAG (retrieval augmented generation) application with a knowledge graph to capture relationships and context not easily accessible by vector stores alone.
● PromptBrew – Offers AI-powered assistance to create high-performing and reliable prompts via a simple user interface.
● Chat with Your Documents – Building upon the previous LLM Chatbot Augmented with Enterprise Data AMP, this accelerator enhances the responses of the LLM using context from an internal knowledge base created from the documents uploaded by the user.
In addition to accelerating AI projects, Cloudera AMPs are fully open source and include deployment instructions for any environment, serving as further testament of Cloudera’s commitment to the open source community.
“While almost every business is experimenting with Generative AI, the technology is still so new that there are very few best practices for enterprises,” said The Futurum Group’s Chief Technology Advisor, Steven Dickens. “As a result, it’s common practice for data scientists and AI engineers to build on existing examples when starting new AI projects. However, there are many drawbacks with this approach, including added security and legal risks. AMPs remove this ambiguity by providing fully built, end-to-end solutions that give data scientists a ready-to-go MVP for various AI use cases that are proven to be effective and able to quickly drive value.”
“In today’s environment, enterprises are constrained with time and resources to get AI projects off the ground,” said Dipto Chakravarty, Chief Product Officer at Cloudera. “Our AMPs are catalysts to fast-track AI projects from concept to reality with pre-built solutions and working examples, ensuring that use cases are dependable and cost effective, while reducing development time. This enables enterprises to swiftly experience the productivity gains and efficiencies that come from AI initiatives.”
