The advent of Large Language Models (LLMs) can democratize access to AI and advance enterprise adoption of AI technology. In this time of discovery and experimentation, the governed use of AI is more critical than ever. That’s why IBM® and Anaconda are collaborating to provide an enterprise-grade Generative AI solution. Natively built within IBM watsonx.ai™, Anaconda allows data scientists to use Python and open source to unleash innovation with AI.

IBM watsonx.ai users can access Anaconda’s natively built open-source Python repository. Anaconda Distribution provides users with Python open-source package management. Watsonx.ai can also integrate with Anaconda Repository on-premises for Python security vulnerability management and license management.

Python continues to be the leading language for data science and Generative AI workloads in 2024, and Anaconda is the gateway to the open-source Python community, providing curated access to the packages powering enterprise AI. Through this collaboration, watsonx.ai brings Generative AI models to clients, and Anaconda brings enterprise-grade Python to enhance enterprise AI.

Python and LLMs in 2024: How data scientists can leverage watsonx.ai and Anaconda

To help advance enterprise AI initiatives, Anaconda Distribution has been updated to include key Generative AI packages like huggingface_hub, transformers and safetensors. These packages leverage open-source development to expedite time to value for deploying LLMs and other models in the enterprise.

Anaconda’s clear mission and dedication to innovation has led to its core open-source package management system being used in AI frameworks at Meta, NVIDIA, PyTorch, OpenAI and now IBM watsonx.ai.

For clients building with watsonx.ai, they will have access to enterprise-ready open-source Python packages directly within watsonx.ai. This means users can use Anaconda Repositoryto access the latest stable OSS Python packages in one place to train, validate, tune and deploy AI models.

This will help provide scaling and broad enterprise usage while mitigating security vulnerability risk. This powerful combination is engineered to allow AI builders to:

  • Build AI applications, choosing from the latest stable and OSS Python packages and AI frameworks; and
  • Tune the enterprise AI software supply chain with the Anaconda Repository, which provides additional security with vulnerability analysis, channel management and open-source security best practices.

IBM’s expertise in AI, combined with Anaconda’s distribution of open-source packages, creates a dynamic collaboration designed to allow clients to advance their AI journey.

Start building with IBM watsonx.ai and Anaconda today

More from Data and Analytics

Breaking Boundaries: PostgreSQL 16 is now available on IBM Cloud

2 min read - PostgreSQL Version 16 is now available on IBM Cloud®. The latest version of IBM Cloud® Databases for PostgreSQL includes critical features that offer unmatched reliability and scalability for clients' data storage needs. Advanced features like enhanced parallel query performance and accelerated indexing provide significant performance gains to your applications. With IBM Cloud's robust ecosystem of extensions and plugins, PostgreSQL v16 empowers customers to build and manage sophisticated, high-performance applications easily while continuing to improve data management at scale. In addition, customers can continue to access powerful IBM…

IBM and TechD partner to securely share data and power insights with gen AI

3 min read - As technology expands, at TechD, we know that the quality of generative AI (gen AI) depends on accurate data sourcing. A reliable and trustworthy data source is essential for sharing information across departments. Through the implementation of generative AI we are able to expand our knowledge to many individuals easily, quickly and efficiently becoming a resource. In today's rapidly evolving digital world, immediate responses are crucial for delivering outstanding user experiences. Our partnership with IBM facilitates the delivery of scalable…

Data virtualization unifies data for seamless AI and analytics

5 min read - Data integration stands as a critical first step in constructing any artificial intelligence (AI) application. While various methods exist for starting this process, organizations accelerate the application development and deployment process through data virtualization. Data virtualization empowers businesses to unlock the hidden potential of their data, delivering real-time AI insights for cutting-edge applications like predictive maintenance, fraud detection and demand forecasting. Despite heavy investments in databases and technology, many companies struggle to extract further value from their data. Data virtualization…

IBM Newsletters

Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters