AI Platform for Business
IBM Research pursues an open and integrated “AI first” approach to enterprise operations. Our cross-disciplinary research teams rethink enterprise architecture and transform business processes by combining AI algorithms, distributed systems, human computer interaction, and software engineering. We apply AI methodologies to accelerate the development of AI solutions from data acquisition, through model generation, to application delivery and continuous update. These include automated machine learning, continuous learning, flexible and dynamic composition, semi-automated model generation, visual analytics, human-AI interaction, and novel quality metrics.
The successful adoption of AI relies on the trust of end users, which means AI systems must be safe and adhere to ethical norms. We focus on delivering tools and techniques to identify and mitigate risks and violations, to help understand trust-related implications for and challenges of AI models, and to assist developers and data scientists in easily building trusted, safe, and explainable AI systems.
To let data scientists focus on models and data, we are innovating to create an AI platform that handles computation speed, scale, hardware selection, and placement. Advances in deep learning as a service, novel programming languages and programming models for AI, and elastic resilient deep learning at scale are examples of AI-optimized programming models and runtimes.