IBM’s new benchmark puts industrial agents to the test
Research
Kim Martineau
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195 results for Research
Advancing quantum algorithms for large-scale simulations of quantum spin chains
ResearchSimone Cantori, Marcel Pfaffhauser, Fabio Scafirimuto, and Robert DavisNew algorithms open possibilities for training AI models on analog chips
ResearchPeter HessFor LLMs, IBM’s NorthPole chip overcomes the tradeoff between speed and efficiency
ResearchPeter HessHow memory augmentation can improve large language model efficiency and flexibility
ResearchPeter HessTeaching AI models to improve themselves
ResearchPeter HessDetecting health and science misinformation with AI
ResearchPeter HessSimulating the universe’s most extreme environments with utility-scale quantum computation
ResearchRoland C. Farrell, Marc Illa, Anthony N. Ciavarella, Martin J. Savage, and Robert DavisLandmark IBM error correction paper published on the cover of Nature
ResearchRafi LetzterA faster, systematic way to train large language models for enterprise
ResearchKim MartineauQiskit tools help researchers probe the noisy dynamics of graph-state stabilizers
ResearchHaggai Landa, Liran Shirizly, and Robert DavisComputing with error-corrected quantum computers
ResearchGuanyu Zhu, Andrew Cross, Ben Brown, and Ryan MandelbaumLogical gates with magic state distillation
ResearchAn AI model trained on data that looks real but won’t leak personal information
ResearchKim MartineauThe latest AI safety method is a throwback to our maritime past
ResearchKim MartineauYou need 100 qubits to accelerate discovery with quantum
ResearchRyan Mandelbaum, Robert Davis, Jennifer Janechek, and Rafi LetzterCan quantum computers bring an end to corrosion?
ResearchRobert Davis
