IBM’s new open Granite models are designed for agentic AI, combining reasoning, tool use, coding, instruction following, and speech capabilities.

A new research tool for expressing fermionic operators, circuits, and mappings—and for building efficient fermionic algorithms.

Modular approach to housing and cooling quantum processors clears a path for interconnected, fault-tolerant systems.

The lead researcher behind IBM’s popular document parser, Docling, explains why generative AI needs its own document standard.

Quantum advantage is here. The next question is where to apply it. New updates from the Quantum Optimization Working Group offer a glimpse at the path ahead.

GENCO is a neural solver that, alongside the GridFM Development Framework, unifies three core electrical grid analysis tasks.

New quantum algorithms could unlock faster ways to model the complex systems behind circuits, fluids, finance, and more.

Demonstration shows trusted quantum computation in regimes where classical methods fail.

Filesystems and sockets once looked like unnecessary layers of indirection; now they’re the foundation of modern systems. Cryptography is ready for the same shift — and with PQC on the horizon, the timing is right.

IBM is part of a global team trying to make AI benchmarking results easier to compare, replicate, and reuse.

Spin qubits are an important element of IBM’s recent HRL Laboratories acquisition.

Exploring the storied history of HRL Laboratories, from the invention of the laser to silicon spin qubits.

An IBM project was also selected to accelerate AI-driven quantum application discovery.

Filesystems and sockets once looked like unnecessary layers of indirection; now they’re the foundation of modern systems. Cryptography is ready for the same shift — and with PQC on the horizon, the timing is right.

Three key hardware metrics reveal the scale, quality, and speed of any quantum computer—factors that determine computational capability and cost efficiency.

Technical release summary for Qiskit SDK v2.5, including top new features and performance improvements.

Introducing CodeAlchemy, a synthetic data pipeline that has already produced nearly 1 trillion tokens of open-source code

This new approach, a practical and conceptual shift, points to lighter-weight generative AI models that perform competitively, and in many cases even better.