Why a decades old architecture decision is impeding the power of AI computing
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Peter Hess
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AI agents have the potential to revolutionize work — and now you can measure if they actually are
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Mike Murphy
Melting magnets with utility-scale quantum simulation: Researchers explore condensed-matter physics phenomena
ResearchEdward H. Chen and Robert DavisExploring the potential for quantum advantage in mathematical optimization
ResearchStefan Woerner, Ryan Mandelbaum, and Robert DavisThe 2024 IBM Research annual letter
Deep DiveSriram Raghavan, Mukesh Khare, and Jay GambettaHow analog in-memory computing could power the AI models of tomorrow
ResearchPeter HessA benchmark for evaluating conversational RAG
ResearchKim MartineauHow John Knickerbocker spent a career cultivating new technologies
Deep DivePeter HessUsing dynamic circuits to efficiently implement quantum states with long-range entanglement
ResearchSimone Cantori, Marcel Pfaffhauser, Elisa Bäumer, Fabio Scafirimuto, and Robert DavisHow low-precision computing boosts efficiency — without hurting accuracy
ExplainerPeter HessA year of simplifying quantum software development tools with Qiskit
Technical noteBlake Johnson, Ismael Faro, Sanket Panda, Abby Mitchell, and Robert DavisInside the lab testing some of the world’s most capable AI chips
Deep DiveMike Murphy
