Artificial Intelligence Ibm Research

Bonisiwe Shabane

-Dec 27, 2025, 4:22 PM

Enjoy transformative outcomes with AI that integrates and unifies your data across applications IBM helps you build a competitive edge by enabling you to use AI to automate workflows and tasks in critical areas such as customer service, supply chain management, HR tasks, IT and more. Partnering with leading innovators like AWS, Microsoft and SAP, we can deliver AI solutions tailored to your needs. No matter where you are on your AI journey, IBM is here to help you move forward. Discover our portfolio of AI products that accelerate generative AI into core workflows, driving automation and productivity. Find data and AI tools to build, scale and govern your custom solutions across the AI lifecycle.

Create personalized AI assistants and AI agents to automate repetitive tasks, simplify complex processes and accelerate your work. IBM (NYSE: IBM) and Pearson (FTSE: PSON.L), the world’s lifelong learning company, today announced a global partnership to build new personalized learning products powered by AI for businesses, public organizations, and educational institutions. IBM (NYSE: IBM) and Confluent, Inc. (NASDAQ:CFLT), the data streaming pioneer, today announced they have entered into a definitive agreement under which IBM will acquire all of the issued and outstanding common shares of Confluent for $31 per share, representing... Confluent provides a leading open-source enterprise data streaming platform that connects, processes and governs reusable and reliable data and events in real time, foundational for the deployment of AI. At IBM Think Riyadh 2025, IBM (NYSE: IBM) and Riyadh Air announced a major milestone in their collaboration, unveiling Riyadh Air as the world’s first AI-native airline.

Designed from the ground up without legacy patch work, these AI-driven operations provide the foundation to transform guest and employee experiences and set a new benchmark for innovation in the aviation industry. Enterprises are entering a new chapter of digital transformation focused on scaling Agentic AI solutions across their operations. But moving from pilot to production isn’t easy. Many are... IBM (NYSE: IBM) and the University of Dayton today announced an agreement for the joint research and development of next-generation semiconductor technologies and materials. The collaboration aims to advance critical technologies for the age of AI including AI hardware, advanced packaging, and photonics.

ALBANY, N.Y. (Nov. 18, 2024) — The University at Albany and IBM Research on Monday announced seed funding for five new joint artificial intelligence (AI) research projects. These projects will explore the use of AI for designing complex circuits more efficiently, optimizing large language models for use in mental health applications, improving next-generation wireless signal processing, developing advanced mathematical applications and... The projects are the first five funded through the Center for Emerging Artificial Intelligence Systems (CEAIS), a $20 million UAlbany-IBM research collaboration announced last year by Gov. Kathy Hochul that included the installation of state-of-the-art prototype IBM AI hardware at UAlbany.

With the founding of CEAIS, UAlbany became the first university in the world to receive a cluster of IBM Artificial Intelligence Unit (AIU) chips designed to support AI computing with greater speed and energy... The projects funded will make use of the AIU cluster, containing prototype IBM Spyre chips, among other resources. “CEAIS was conceived as a research incubator that would pair creative minds at UAlbany and IBM on innovative approaches to AI software, hardware and applications, while leveraging the latest technology coming out of the... “I am so excited to see this first round of projects, in areas with tremendous social impact, take flight and eager to see the new knowledge and techniques that these explorations yield.” “We applaud UAlbany for being at the forefront of AI research by supporting advances in both hardware and software technology,” said Mukesh Khare, general manager of IBM Semiconductors and vice president, Hybrid Cloud Research... “These new projects reveal how AI models could help solve some of today’s most pressing challenges, while running on state-of-the-art IBM Research prototype chips designed from the ground up for AI workloads.”

A new way to increase the capabilities of large language models Nuno Loureiro, professor and director of MIT’s Plasma Science and Fusion Center, dies at 47 Enabling small language models to solve complex reasoning tasks MIT affiliates named 2025 Schmidt Sciences AI2050 Fellows A smarter way for large language models to think about hard problems The Artificial Intelligence Research Collaboration (AIRC) is a multiyear, joint effort between Rensselaer and IBM that involves multiple graduate students, postdocs, research scientists, and faculty working closely with IBM researchers to push the frontiers...

The AIRC is part of the AI Horizons Network, which brings together IBM researchers, world-class faculty, and top graduate students to collaborate on a series of advanced research projects and experiments designed to accelerate... Projects are designed to apply the technologies to some of the world’s most enduring challenges, ranging from disease and the environment, to transportation and education. The AI Horizons Network addresses the entire AI stack, from analyzing the unstructured and structured data required to train these systems, to building the new computing infrastructures needed to optimize the new data-intensive workloads... At Rensselaer, graduate students who have been selected as Artificial Intelligence Horizons Network Scholars are working on a series of projects designed to accelerate the application of artificial intelligence, machine learning, natural language processing,... This article was featured in the Think newsletter. Get it in your inbox.

In 2026, the smartest AI models may not be the biggest ones. That is the bet now being placed by labs, investors and researchers who spent the past year watching their assumptions collapse. The coming 12 months will be defined not by the race to build larger systems, but by the scramble to develop wiser ones, models that think before they speak, that do more with less. “You can get a small language model performing at the same level, or even better, than much larger models,” Kush Varshney, an IBM Fellow, told IBM Think in an interview. A year ago, that would have sounded like heresy. For a decade, AI had operated according to a brutally simple catechism: more data, more parameters, more computing power, more intelligence.

Labs competed to announce parameter counts like bodybuilders flexing in a mirror. Training runs consumed the electrical output of small cities. The whole enterprise had the feeling of a land rush, except the territory being claimed was measured in teraflops. Artificial intelligence (AI) is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy. Applications and devices equipped with AI can see and identify objects. They can understand and respond to human language.

They can learn from new information and experience. They can make detailed recommendations to users and experts. They can act independently, replacing the need for human intelligence or intervention (a classic example being a self-driving car). But in 2024, most AI researchers, practitioners and most AI-related headlines are focused on breakthroughs in generative AI (gen AI), a technology that can create original text, images, video and other content. To fully understand generative AI, it’s important to first understand the technologies on which generative AI tools are built: machine learning (ML) and deep learning. Stay up to date on the most important—and intriguing—industry trends on AI, automation, data and beyond with the Think newsletter.

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Artificial Intelligence Ibm Research

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