Knowledge catalogue
IBM has released Granite 4.2, an open‑source agentic AI model that adds native reasoning, tool use, coding instruction following and speech capabilities to enterprise agents. The suite of pre‑built mo
IBM has introduced **DocLang**, a new markup language specifically designed for large‑language models (LLMs). Developed by lead researcher Peter Staar and IBM’s document‑parsing team, DocLang aims to
GENCO is an AI‑driven neural solver released by IBM Research and partners that unifies three core electrical‑grid analysis tasks within the GridFM Development Framework. It runs on Linux Foundation En
IBM, as part of a global effort, is developing tools to streamline AI benchmarking by making results easier to compare, validate, and reuse. The initiative is detailed in a blog post titled 'All of AI
CoFrGeNets are a novel architecture proposed by IBM Research that replaces the core structural components ('bones') of transformer-based models with a more efficient design. This approach aims to impr
This IBM Research article examines how training environments and conditions can inadvertently cause AI models to develop undesirable behaviors or fail to learn intended objectives. The piece likely ex
IBM Quantum's Q2 2026 updates likely showcase advancements in quantum computing hardware, software, or services, including new processor capabilities, improved error correction, expanded cloud access,
IBM Research explores the application of quantum computing to model the chemical behavior of molten salts used in fusion reactor materials and cooling systems. The work addresses the computational com
IBM's July 2026 Ponder This Challenge likely presents a mathematical or logic puzzle with a superhero theme, continuing IBM Research's monthly series of recreational problem-solving challenges. The pu
The IBM Quantum Developer Conference 2026 is accepting applications from developers interested in quantum computing. This conference, organized by IBM Research, provides an opportunity for quantum dev
IBM announced the development of sub-1 nanometer computer chips, representing a significant advancement in semiconductor miniaturization beyond previous technological limits. This breakthrough in chip
Qiskit Paulice is a quantum error correction technique developed by IBM Research that uses postselection to improve the reliability of quantum computations. The method selectively retains quantum meas
IBM's nanostack is a chip architecture that stacks multiple layers of transistors vertically to increase transistor density and computing power within a smaller physical footprint. This 3D approach en
IBM Research presents a framework for benchmarking quantum optimization algorithms, addressing the need for standardized methods to evaluate quantum computing performance on optimization problems. The
This IBM Research article discusses optimizing AI inference performance and costs by leveraging mixed hardware configurations, combining different types of processors and accelerators rather than rely
IBM Quantum Credits is a program that provides researchers and developers with access to IBM's quantum computing systems to explore and develop advanced quantum algorithms. The initiative enables user
SQL Data Insights Pro is an IBM tool that applies semantic AI capabilities to IBM DB2 databases, enhancing data analysis and insights generation. The solution leverages advanced AI techniques to help
The Fast Fourier Transform (FFT) is a computationally efficient algorithm that converts time-domain signals into their frequency-domain representation, reducing computational complexity from O(n²) to
IBM Research introduced Granite Libraries and Project Granite Switch, which are tools and initiatives designed to improve software development and system integration. These offerings likely focus on p
IBM Research highlighted quantum computing developments and applications at NY Tech Week, showcasing the technology's potential impact on industry and research. The event featured discussions on quant
Qiskit Fall Fest 2026 is an event organized by IBM that focuses on quantum computing education and community engagement through the open-source Qiskit framework. The event likely provides opportunitie
IBM announced a $10 billion investment in quantum computing to advance the development and commercialization of quantum technologies. The investment aims to accelerate quantum hardware improvements, e
IBM Research's June 2026 Ponder This Challenge presents a mathematical or logical puzzle involving superhero team movies. The challenge likely requires solvers to work through constraints and combinat
Renowned mathematician Subhash Khot has joined IBM Research, bringing his expertise to the organization's research initiatives. Khot is known for his work in theoretical computer science and computati
IBM has introduced new classroom accounts that provide educators with expanded access to quantum computing resources for teaching and research purposes. These accounts are designed to make quantum tec
Qiskit Global Summer School 2026 is an educational program offered by IBM that focuses on quantum computing and the Qiskit framework, with registration now available for interested participants. The s
IBM researchers have achieved a record-breaking quantum circuit by advancing quantum computing benchmarking and performance capabilities. The work likely demonstrates progress in quantum algorithm imp
MIT and IBM have renewed their long-standing research collaboration, focusing on advancing computing research and technology development. The partnership brings together expertise from both institutio
IBM is exploring the application of quantum computing to simulate and model complex physical systems and phenomena in the universe. This research represents efforts to leverage quantum computers' uniq
Sample-based quantum diagonalization is a quantum algorithm technique that estimates the eigenvalues and eigenvectors of matrices using measurements from quantum hardware, rather than requiring full q
IBM researchers demonstrated a quantum-centric supercomputing approach that successfully simulated a protein containing 12,635 atoms in collaboration with Cleveland Clinic and RIKEN, combining classic
IBM Research reflects on ten years of quantum computing development and deployment through cloud-based platforms, documenting the evolution from early experimental systems to more practical quantum pr
This IBM Research challenge problem likely involves analyzing mathematical properties of binary matrices (matrices containing only 0s and 1s), potentially exploring topics such as matrix operations, e
IBM Research describes how artificial intelligence and accelerated computing are being applied to high-speed racing design, likely through collaboration with racing teams or manufacturers like Dallara
IBM Research’s recent blog post highlights new collaborations with MIT, ETH Zurich, and the University of Illinois aimed at advancing next‑generation artificial‑intelligence and quantum‑computing algo
IBM Granite 4.1 is a family of foundation models released by IBM Research designed for enterprise AI applications. The models likely offer improvements in performance, efficiency, and capabilities com
IBM Research has developed an AI model designed to analyze and predict the behavior of fusion plasma, advancing computational capabilities for nuclear fusion research. The model likely leverages machi
IBM and the University of Illinois Urbana-Champaign (UIUC) have established a partnership focusing on quantum computing and related algorithmic research. The agreement, discussed by IBM researcher Han
Qiskit v2.4 represents the latest release of IBM's open-source quantum computing framework, introducing new features and improvements to the software development kit for quantum programming. The relea
IBM Quantum's Q1 2026 updates likely cover recent advances in quantum computing hardware, software, and applications, including announcements about processor improvements, new quantum algorithms, or e
IBM Quantum is leveraging quantum computing technology to advance healthcare and biology research, with the company highlighting selected finalists in their quantum-for-biology (Q4Bio) initiative. The
IBM Research has demonstrated that mid-training — a dedicated training phase between initial pre-training and fine-tuning — is essential for improving reasoning capabilities in large language models (
IBM Research demonstrated the capability to store and search across a database of 100 billion vectors, showcasing extreme-scale vector storage for AI applications. This work addresses the growing need