Dinesh Nirmal of IBM Software
IBM has announced plans for recent generative artificial intelligence (GenAI) foundation models and enhancements coming to watsonx its artificial intelligence (AI) and data platform with a set of AI capabilities designed to help enterprises scale and accelerate impact of AI. These enhancements include a technical preview for watsonx.governance, recent generative AI data services coming to watsonx.data and planned integration of watsonx.ai foundation models across select software and infrastructure products.
Developers will be able to get their hands on many of these capabilities and models September 11-14 at TechXchange, IBM’s technical learning event in Las Vegas.
The recent IBM and third-party generative AI models coming to watsonx.ai include:
- Granite series models: IBM plans to introduce its Granite series models later this month. The Granite models use “Decoder” architecture, which underpins ability of today’s large language models (LLMs) to predict word in a sequence, and can support enterprise NLP tasks, such as summarisation, content generation and insight extraction. IBM plans to provide a list of sources of data as well as a description of data processing and filtering steps that were performed to produce training data for Granite series of models.
- Third-party models: IBM is now offering Meta’s Llama 2-chat 70 billion parameter model and StarCoder LLM for code generation in watsonx.ai on IBM Cloud.
IBM has established a training process for its foundation models centered on principles of trust and transparency that starts with rigorous data collection and ends in control points for enabling responsible deployments of models and applications for governance, risk assessment, privacy concerns, bias mitigation, and compliance.
IBM is also announcing plans to introduce capabilities across watsonx platform.
Watsonx.ai:
- Tuning studio: IBM plans to release initial iteration of its tuning studio, which will include prompt tuning a productive, low cost way for clients to adapt foundation models to their downstream tasks with their own enterprise data.
- Synthetic data generator: IBM introduced synthetic data generator to assist users in creating artificial tabular data sets from custom data schemas or internal data sets. This will allow users to extract insights for AI model training with reduced risk, thereby augmenting decision making and accelerating time to market.
Watsonx.data:
- Generative AI: IBM plans to infuse watsonx.ai generative AI capabilities in watsonx.data to help users discover, augment, visualise, and refine data for AI through a self-service experience powered by a conversational, natural language interface.
- Vector database capability: IBM plans to integrate a vector database capability into watsonx.data to support watsonx.ai retrieval augmented generation use cases.
Watsonx.governance:
- Model risk governance for generative AI: IBM is introducing a tech preview for watsonx.governance. Clients in tech preview will be able to explore capabilities for automated collection and documentation of foundation model details and model risk governance capabilities that allow stakeholders to view relevant metrics in dashboards of their enterprise-wide AI workflows with approvals’ so humans are engaged at right times.
“As demonstrated by the ongoing rollout of the watsonx platform within just a few months since launch, we are here to support clients through the entire AI lifecycle. As a transformation partner, IBM is collaborating with clients to help them scale AI in a trustworthy way from helping to institute foundational elements of their data strategies to tuning models for their specific business uses cases to helping them govern models beyond that.” says Dinesh Nirmal, senior vice president, products, IBM Software.
The IBM watsonx AI and data platform will be complemented by a set of AI assistants designed to help clients scale and accelerate impact of AI with their trusted data across key enterprise use cases, such as:
- Application modernisation: IBM watsonx Code Assistant products, coming later this year, will use tailored foundation models to change and generate code recommendations for developers. Recently, IBM announced two upcoming AI assisted code products watsonx Code Assistant for Z to enhance developer productivity and accelerate COBOL (common business oriented language) application modernisation and watsonx Code assistant for red hat ansible lightspeed to help developers of all levels write ansible playbooks.
- Customer care: IBM watsonx assistant will help deliver consistent and intelligent customer service solutions with conversational AI. For instance, IBM Support Insights Pro, which is expected to be available later this month, will use watsonx Assistant to help clients find insights in their multivendor IT (information technology) infrastructures to proactively assess support patterns and remediate risks, resulting in higher availability and security.
- HR (human resources) and talent: IBM watsonx orchestrate will help HR professionals automate repetitive, high-friction tasks and back-office processes such as interview scheduling or posting open jobs, through a conversational interface.
IBM is also planning to embed watsonx.ai creations across its hybrid cloud software and infrastructure products, including:
- Intelligent IT automation: Entering tech preview next week, IT Automation products instana and AIOps insights will include intelligent remediation, which embeds watsonx.ai generative AI foundation models to assist IT Ops (operations) practitioners with summarisation of incident details, as well as provide prescriptive workflow suggestions to help engineers quickly implement solutions.
- Developer services for watsonx: To help simplify and accelerate developers’ ability to bring watsonx capabilities closer to their companies’ data on IBM Power for SAP workloads, SAP ABAP SDK for watsonx is expected to add to ways clients can use AI to inference near their data on Power systems and deploy AI algorithms on their sensitive data and transactions.
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