As a Stanford alum, I am excited to announce that IBM Research is the first founding corporate partner of the Stanford Institute for Human-Centered Artificial Intelligence (HAI). Building on decades of research collaboration across computer and materials science, IBM is committed to joining HAI to advance AI research, education, policy and practice that improve how we live, work, play and learn. In this new role, IBM will work closely with fellow AI thought leaders, researchers and innovators at Stanford and through participation on the HAI Corporate Advisory Committee. IBM researchers will also work alongside Stanford researchers as part of the Visiting Scholars program. Across departments and with other academic, industry and government leaders, IBM will work with HAI to collaborate to advance the state of the art in AI research and to understand the multi-dimensional impact of AI as it transforms economies, business, legal and political norms, societies and cultures. By developing this understanding, IBM and HAI will seek to provide insight that will enable society to shape the application of AI in ways that are inclusive and promote social good. IBM Research will work with HAI to initially focus its AI research on three key areas: Trustworthy artificial intelligence We work hard to earn the trust of society by ushering powerful new technologies into the world responsibly and with clear purpose. That is why, through IBM Research’s Trustworthy AI strategy, we are developing diverse approaches to wiring AI systems for trust through multiple dimensions including robustness, fairness, explainability, and transparency. Natural language processing (NLP) IBM is committed to exploring, creating and deploying technologies that make the world better, safer, and more prosperous for every single person. Unlocking the power of human language to connect, transform, inspire and organize holds the potential to deliver on that commitment. With NLP, parsing and semantic interpretation of text ultimately allows systems to learn, analyze, and understand human language. The resulting applications help humans better communicate with each other, and with machines, through spoken and written words. Neuro-symbolic computation While classical IT systems handle incredibly complex computations and data management with ease, context and abstract concepts allude them. Programmed computers can only process what is encoded for them by humans. While deep learning has made it possible to categorize and generate insights from massive labeled datasets, even the most sophisticated computer vision technology today falls short of generating inferences related to context or abstraction. The newly emerging field of neuro-symbolic computation applies logic and semantic reasoning to symbols characterized by a neural network in order to infer complex relationships between them. Transforming the future through academic partnerships IBM has been partnering with universities around the world to advance science and technology for decades. In the past year alone, IBM has partnered with dozens of leading universities to conduct exploratory scientific research in areas including quantum computing , AI and genomics . With a commitment to open research, IBM provides university partners with access to its scientists, infrastructure and knowledge base throughout its 19 global locations. Silicon Valley researchers at IBM Research - Almaden have worked to advance science and technology for years including with Stanford researchers in 2019 to develop a smart flow reactor that holds promise as a tool for accelerating the discovery, design and development of new medicines and materials. Artificial intelligence has moved from an experimental stage to one of profound transformation. As AI matures and becomes broadly applied, it is our responsibility to make sure it serves the needs of all humans through dialogue and action across academia, industry, government and society. Introducing the IBM Granite 4.1 family of models Release Mike Murphy 29 Apr 2026 AI Computer Vision Foundation Models Generative AI Speech Trustworthy AI

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