IBM, at its annual Think conference, has announced IBM watsonx – a new AI and data platform to be released that will enable enterprises to scale and accelerate the impact of the most advanced AI with trusted data. Enterprises turning to AI today need access to a full technology stack that enables them to train, tune and deploy AI models, including foundation models and machine learning capabilities, across their organization with trusted data, speed, and governance – all in one place and to run across any cloud environment.

With watsonx, IBM is offering an AI development studio with access to IBM-curated and trained foundation models and open-source models, access to a data store to enable the gathering and cleansing of training and tuning data, and a toolkit for governance of AI into the hands of businesses that will provide a seamless end-to-end AI workflow that will make AI easier to adapt and scale.

“With the development of foundation models, AI for business is more powerful than ever,” said Arvind Krishna, IBM Chairman and CEO. “Foundation models make deploying AI significantly more scalable, affordable, and efficient. We built IBM watsonx for the needs of enterprises, so that clients can be more than just users, they can become AI advantaged. With IBM watsonx, clients can quickly train and deploy custom AI capabilities across their entire business, all while retaining full control of their data.”

Clients will have access to the toolset, technology, infrastructure, and consulting expertise to build their own — or fine-tune and adapt available AI models — on their own data and deploy them at scale in a more trustworthy and open environment to drive business success. Competitive differentiation and unique business value will be able to be increasingly derived from how adaptable an AI model can be to an enterprise’s unique data and domain knowledge.

The IBM watsonx platform consists of three unique product sets to address these needs:

IBM watsonx.ai: A next generation enterprise studio, expected to be generally available in July 2023, for AI builders to train, test, tune, and deploy both traditional machine learning and new generative AI capabilities powered by foundation models through an open and intuitive user interface.

• The AI studio provides a range of foundation models, training and tuning tools, and cost-effective infrastructure that facilitate the entire data and AI lifecycle, from data preparation to model development, deployment, and monitoring.
• The studio also includes a foundation model library that gives users easy access to IBM curated and trained foundation models. The IBM foundation models use a large, curated set of enterprise data backed by a robust filtering and cleansing process and auditable data lineage. These models are being trained not just on language, but on a variety of modalities, including code, time-series data, tabular data, geospatial data, and IT events data. An initial set of foundation models will be made available in beta tech preview to select clients. Examples of model categories include:
  • code: Models built to automatically generate code for developers through a natural-language interface to boost developer productivity and enable the automation of many IT tasks.
  • NLP: A collection of large language models (LLMs) for specific or industry-specific domains that utilize curated data where bias can be mitigated more easily and can be quickly customized using client data.
  • geospatial: Model built on climate and remote sensing data to help organizations understand and plan for changes in natural disaster patterns, biodiversity, land use, and other geophysical processes that could impact their businesses.
• As part of a new collaboration between IBM and Hugging Face, the watsonx.ai studio will build upon Hugging Face’s open-source libraries and offer thousands of Hugging Face open models and datasets. This is part of IBM’s commitment to delivering to clients an open ecosystem approach that allows them to leverage the best models and architecture for their unique business needs.

IBM watsonx.data: A fit-for-purpose data store built on open lakehouse architecture that is optimized for governed data and AI workloads, supported by querying, governance, and open data formats to access and share data. The solution is expected to be generally available in July 2023 and:

• The solution can manage workloads both on-premise and across multi-cloud environments.
• Through workload optimization, with this solution, an organization can reduce data warehouse costs by up to 50 percent.1
• data will allow users to access their increasingly robust data through a single point of entry while applying multiple fit-for-purpose query engines to uncover valuable insights.
• It will also provide built-in governance tools, automation and integrations with an organization’s existing databases and tools to simplify set-up and user experience.

IBM watsonx.governance: An AI governance toolkit to enable trusted AI workflows. The solution, expected to be generally available later this year:

• Operationalizes governance to help mitigate the risk, time and cost associated with manual processes and provides the documentation necessary to drive transparent and explainable outcomes.
• Provides the mechanisms to protect customer privacy, proactively detect model bias and drift, and help organizations meet their ethics standards.

With the watsonx platform, clients are enabled to meet the needs of their organization in five key areas of their business: interacting and conversing with customers and employees; automating business workflows and internal processes; automating IT processes; protecting against threats; and tackling sustainability goals.

IBM also plans to infuse watsonx.ai foundation models throughout all its major software products going forward, for example:

• Watson Code Assistant: A solution, expected later this year, that taps generative AI to allow developers to generate code with a straightforward English language command.
• AIOps Insights: AI Operations (AIOps) capabilities enhanced with foundation models expected for code and NLP to provide greater visibility into performance across IT environments, helping IT operations (ITOps) managers and Site Reliability Engineers (SREs) resolve incidents in a more expedient and cost-efficient way.
• Watson Assistant and Watson Orchestrate: IBM’s digital labor products are expected to be combined with an NLP foundation model to enable enhanced employee productivity and customer service experiences.

Environmental Intelligence Suite: IBM EIS Builder Edition is planned to be enabled by the geospatial foundation model and available in preview later this year, allowing organizations to create tailored solutions that address and mitigate environmental risks based on their unique goals and needs.