With the advent of Generative AI, the world is on the cusp of another revolution that has the potential to alter the way we work radically. We have already witnessed the promise of generative AI and large language models. At Think 2024, IBM claimed that they have been working on a myriad of methods, models, and projects to automate every aspect of business, from front-office processes to back-office processes and physical infrastructure, like manufacturing plants. 

These areas can be enhanced with various generative AI language and code technologies, spanning a breadth of technical domains. This includes breakthroughs in content extraction, code generation, retrieval-augmented generation (RAG), summarization, multi-turn conversational AI, APIs, planning, and more. These features are all powered by IBM’s Granite language and code models, which were showcased in detail at the Think 2024 conference.  

IBM’s official statement mentioned that the team across IBM is using the emerging tools to build systems that save businesses time, money, and heaps of stress. 

Reimagining how the world codes 

IBM has open-sourced its Granite code models, available to anyone for tasks like fixing code, explaining, or translating code between languages. These models are a step towards supporting legacy systems and future applications. IBM announced that Watsonx Code Assistant for Enterprise Java Applications could summarize existing Java code, make recommendations, execute code upgrades, detail code changes, and generate unit tests. The automated test generator framework increases testing coverage by up to 50%, spanning benchmarks for IBM Granite and other models. 

Identifying and addressing IT issues as they happen 

IBM Research is automating the collection and analysis of IT health data to help engineers identify and fix problems in complex systems. The company is also introducing AI and generative updates to its IT automation portfolio, including intelligent remediation for Instana, GPU optimization for Turbonomic, and cloud cost management tools (FinOps) for Turbonomic and Apptio. These technologies can summarize IT issues, identify probable causes, and recommend actions, with some resulting in over 2,500 deflected calls per year. 

IBM Research is working with several companies to turn these concepts into working solutions for their systems. AI systems can also help monitor resource allocations using Turbonomic, with IBM testing how GPUs are apportioned on its own systems. 

The future of manufacturing 

AI is revolutionizing the way we build and supply everything. IBM’s Maximo Application Suite has introduced automated work order intelligence based on its Granite model, which can predict work order failure codes. This software saves 10,000 hours of productivity annually.  

Generative AI is allowing businesses to access vast amounts of information and insights, allowing for more efficient plant management. IBM’s open-source Granite time-series models, particularly the tiny time mixer (TTM) model, outperform other forecasting models and enable better timely monitoring of assets and processes. 

Automating the time-consuming tasks 

IBM’s Orchestrate product has revolutionized business processes by making tasks of varying complexity easy. Generative AI offers the potential to make this automation more flexible and tailored to specific users.  

IBM’s Watsonx Orchestrate Assistant Builder helps businesses build assistants with underlying skills that fit specific tasks, such as human resources, sales, and procurement. These skills and open API specifications can be quickly built, enhanced, and validated, transforming the build experience.  

IBM Research is also developing generative interfaces for automation tasks that users can create on the fly, allowing them to write in plain English. These systems can invoke APIs, sequence multiple APIs, query databases with natural language, and summarize retrieved content using IBM’s Granite LLM. 

Source: IBM Research

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