Building Greater AI for Enterprise and Hybrid Clouds with IBM’s WatsonX

Applications of AI


AI is a hot topic, and IBM puts it at the center of its hybrid cloud strategy at the annual IBM Think conference. Over the past few years, while other companies have focused on the consumer side of new AI applications, IBM has developed a new generation of models that can better serve enterprise customers.

IBM announces watsonx.ai, an AI development platform for hybrid cloud applications. IBM watsonx AI development services are in technology preview and are expected to be generally available in Q3 2023.

IBM blogIntroducing watsonx: The future of AI for business – IBM Blog

This new generation of AI is designed to be a critical business tool that enables a new era of productivity, creativity and value creation. But for enterprises, it’s not just cloud access to this new class of AI constructs, commonly referred to as Large Language Models (LLMs). LLM forms the basis of generative AI products such as ChatGPT, but enterprises have many issues to consider, including data sovereignty, privacy, security, reliability (no drift), accuracy, and bias.

An IBM survey of businesses found that between 30% and 40% see business value in AI, a doubling since 2017. One forecast referenced by IBM says AI will contribute $16 trillion to the global economy by 2030. While the study calculates AI-enabled productivity gains, just as no one could have predicted the unique future value of the early Internet, beyond productivity gains You can create your own value. By improving productivity, AI fills many of the gaps between enterprise skill requirements and the people with those skills.

Today, AI is already improving software programming by making it faster and more error-free. Red Hat makes writing code easier with IBM’s Watson Code Assistant, powered by watsonx, by predicting and suggesting the next code segment you’ll type. The application of this AI is highly efficient because it targets the specific programming model of Red Hat Ansible Automation Platform. The Ansible code assistant is 35x smaller than other more popular code assistants as it is more restricted and optimized.

Another example is SAP. SAP has incorporated Watson service processing to power the digital assistant in SAP Start. New AI capabilities in SAP Start help improve user productivity through both natural language capabilities and predictive insights using IBM Watson AI solutions. SAP has found that up to 94% of queries can be answered by AI.

Bringing Watson to Life

The IBM AI development stack has three parts: watsonx.ai, watsonx.data, and watsonx.governance. The watsonx components are designed to work together and can also work with third-party integrations such as HuggingFace’s open source AI models. And watsonx can run on multiple cloud services such as IBM Cloud, AWS, and Azure, as well as on-premises servers.

The watsonx platform is delivered as a service and supports hybrid cloud deployments. These tools enable data scientists to rapidly engineer and tune custom AI models. The model then becomes the critical engine for the company’s business processes.

The watsonx.data service allows you to connect data from multiple sources to the rest of watsonx using Open Table Store. Manage the lifecycle of data used to train Watsonx models.

The watsonx.governance service is used to manage the model lifecycle, applying active governance to models as they are trained and refined on new data.

The heart of the product is watsonx.ai, where the development work takes place. IBM itself is currently developing 20 base models (FMs) with different architectures, modalities and sizes. In addition to these, there is the HuggingFace open source model available on the watsonx platform. IBM expects some customers to develop their own applications, but IBM offers consulting to help select the right model, retrain on customer data, and accelerate development if needed. It offers.





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