IBM (IBM), on Tuesday, at its annual Think conference, unveiled the Watsonx platform, an AI and data platform designed to enable businesses to scale and accelerate the impact of advanced AI using trusted data. IBM’s Watsonx platform offers a complete technology stack for training, tuning, and deploying AI models, including foundation models and machine learning capabilities. It allows organizations to deploy AI models with trusted data, speed, and governance. Furthermore, Watsonx is designed to run seamlessly across any cloud environment.
At the Think conference, IBM announced additional developments, such as a GPU-as-a-service infrastructure that can support AI-intensive workloads. Additionally, an AI-powered dashboard to monitor cloud carbon emissions will be introduced, along with a new consulting practice for Watsonx and generative AI, which will aid in clients’ AI deployment.
IBM’s Watsonx provides an AI development studio that offers businesses access to IBM’s pre-trained foundation models and open-source models, as well as a data store for gathering and cleaning training and tuning data. The platform includes a governance toolkit, which enables businesses to seamlessly integrate AI workflows and scale AI adoption with ease.
Arvind Krishna, the CEO and Chairman of IBM, stated that foundation models have made AI for business more powerful than ever before. He said that the Watsonx platform was built to address the needs of enterprises, allowing them to become AI-empowered rather than just users. Watsonx empowers businesses to efficiently train and deploy custom AI capabilities across their entire organization while retaining data control. The platform provides clients with toolsets, technology, infrastructure, and consulting expertise to build or adapt AI models on their own data and deploy them at scale in a trusted and transparent environment. By doing so, businesses can derive competitive differentiation and unique business value from how adaptable an AI model is to their unique data and domain knowledge.
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