ITBench-AA: A New Benchmark for Evaluating AI in Enterprise IT Tasks

IBM and Artificial Analysis unveil ITBench-AA, marking a significant step in assessing AI performance in Site Reliability Engineering tasks, with frontier models scoring below 50%.

IBM and Artificial Analysis unveil ITBench-AA, marking a significant step in assessing AI performance in Site Reliability Engineering tasks, with frontier models scoring below 50%.

IBM has introduced two new multilingual embedding models, significantly enhancing retrieval capabilities across over 200 languages while maintaining a compact size.

The MIT-IBM Computing Research Lab has been established to explore the intersection of artificial intelligence and quantum computing, building on a decade-long collaboration between the two institutions.

IBM's ALTK-Evolve introduces a long-term memory system for AI agents, enabling them to learn from past interactions and improve their performance in complex tasks.

IBM and Arm are joining forces to enable Arm software on IBM's enterprise systems, targeting AI and data-intensive workloads.

IBM unveils Granite 4.0 3B Vision, a sophisticated vision-language model tailored for extracting information from complex enterprise documents.

The MIT-IBM Watson AI Lab is fostering the growth of early-career faculty by providing essential resources and collaborative opportunities, shaping the future of AI research.

IBM unveils Granite 4.0 1B Speech, a streamlined speech-language model designed for enterprise use, enhancing multilingual automatic speech recognition and translation capabilities.

A collaboration between IBM Research and UC Berkeley has led to significant insights into the failures of agentic systems in IT automation, utilizing the ITBench benchmark and the MAST taxonomy.

IBM's CEO has called out major tech companies like Google, Amazon, and Microsoft, questioning their approach to AI and its implications for the industry.