Tech giant IBM allows developers and AI builders to expedite their AI development process using watsonx.ai. IBM watsonx.ai™ is an enterprise-grade AI studio for developing and deploying AI services into your applications.
Combining Gen AI with traditional machine learning techniques, IBM watsonx.ai provides builders with a one-stop AI developer studio to innovate with all the APIs, tools, models, and runtimes to simplify and scale AI application development and deployment.
Let’s explore how IBM watsonx.ai can help streamline the AI application development process.
Offering Enterprise-ready AI Toolkit
IBM Watsonx.ai provides developers with the tool to scale their AI development and adoption of specific AI use cases. “ With IBM watsonx.ai, we’re providing AI developers and model builders an intuitive and collaborative development experience,” the company said.
“Automation capabilities with prebuilt patterns, access to third-party AI frameworks, models and integrations with the broader IT stack helps accelerate time to value for real business impact and returns. We provide developers with tools to begin building valuable generative AI applications for your business today.”
Selecting Enterprise-grade Foundation Models
IBM watsonx™ offers developers a selection of cost-effective, enterprise-ready foundation models, including the Granite™ model series built by IBM Research, open-source models, and models sourced from third-party providers.
All the models can be used for a variety of AI applications, including agents and RAG-based solutions. Through API connections or IBM’s low-code or no-code visual interface, developers can start building with these models.
Learn to choose the right AI foundation model.
watsonx.ai for RAG
IBM watsonx.ai allows AI builders to build powerful RAG applications with a comprehensive toolkit. By using the RAG pattern, developers can employ foundation models in Watsonx.ai to provide factually correct output based on data from a knowledge base.
Choosing watsonx.ai for RAG provides flexibility and enterprise-grade tools while allowing rapid deployment.
What’s More?
By fine-tuning an LLM to understand a certain field of knowledge or skills, developers can also help in enhancing the efficiency of RAG applications. However, this process often requires significant collections of human-generated data.
To address the data challenge, IBM Research and Red Hat developed the Large-Scale Alignment (LAB) method. This represents an innovative approach that enables efficient fine-tuning of pretrained-base models to specific business needs. InstructLab is an example of an alignment tuning method.
According to the company, IBM watsonx.ai plans to make available improved InstructLab experience to watsonx.ai in the future.
IBM Watsonx.ai is focused on offering seamless integration with many open source frameworks, including LangChain and Crew AI, by fully supporting industry-standard APIs. With this, developers can easily power these frameworks with multiple models hosted in watsonx.ai.
IBM has also open-sourced its own experimental agentic framework Bee, which supports various models and offers tools through which application developers can accelerate the next wave of AI adoption in the enterprise.
Developers must explore the IBM watsonxai and streamline and accelerate their AI development process.
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