IBM watsonx.ai
IBM Software
IBM watsonx.ai
IBM Software
IBM watsonx.ai
IBM Software
A next generation enterprise studio for AI builders to train, validate, tune and deploy AI models
IBM watsonx.ai is the next-generation enterprise studio for all AI builders to build, train, validate, tune and deploy AI models. It brings traditional machine learning and new generative AI capabilities powered by foundation models into a powerful studio that spans the AI lifecycle. IBM's open, hybrid, full stack approach includes a collection of foundation models including IBM-developed models that combine best-of-breed architectures with a rigorous focus on data acquisition, provenance, and quality, to serve enterprise needs. The collection also includes third-party and select open-source foundation models from Hugging Face. watsonx.ai also features a Prompt Lab and API to experiment with foundation models and build prompts for various use cases. The studio also includes a data science toolset to build machine learning models with code or with auto AI capabilities, as well as a collection of powerful capabilities such as visual data pipelines and flows, synthetic data generation and more - all running on a scalable, open and trusted, hybrid AI infrastructure. Clients can immediately get started with watsonx.ai and co-create with IBM Consulting, Client Engineering, Expert Labs or IBM's extensive partner ecosystem to accelerate the value of AI for their business.
AI builders can work with foundation models and build prompts using prompt engineering. Within the Prompt Lab, users can experiment with zero-shot, one-shot, or few-shot prompting to support a range of Natural Language Processing (NLP) type tasks.
Prompt-tune foundation models as part of our Tuning Studio to help tune your foundation models with labeled data for better performance and accuracy.
Data science and MLOps toolset: All the tools, pipelines and runtimes powered by foundation models, a data scientist would need to support building machine learning models automatically.