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ARMONK, N.Y., June 18, 2025 /PRNewswire/ — Today, as enterprises scale AI agents across their organizations, IBM (NYSE: IBM) is announcing the industry’s first software to bring AI security and AI governance teams together and provide a unified view of enterprises’ risk posture.

The new capabilities enhance and integrate watsonx.governance and Guardium AI Security to help clients keep their AI systems, including agents, secured and responsible at scale. Watsonx.governance is IBM’s end-to-end AI governance tool and Guardium AI Security is IBM’s tool for securing AI models, data, and usage.

“AI agents are set to revolutionize enterprise productivity, but the very benefits of AI agents can also present a challenge,” said Ritika Gunnar, General Manager, Data and AI, IBM. “When these autonomous systems aren’t properly governed or secured, they can carry steep consequences.”

Today’s new offerings include:

Integrating and Automating Agentic AI Security 

IBM is enhancing the integration of IBM Guardium AI Security and watsonx.governance, providing enterprises with the first unified solution to manage security and governance risks associated with AI use cases. The integration supports users’ processes to validate compliance standards against 12 different frameworks, including the EU AI Act and ISO 42001.

IBM is also introducing new capabilities to Guardium AI Security through a collaboration with AllTrue.ai, including the ability to detect new AI use cases in cloud environments, code repositories, and embedded systems –providing broad visibility and protection in an increasingly decentralized AI ecosystem. Once identified, IBM Guardium AI Security can automatically trigger appropriate governance workflows from watsonx.governance.

Recent updates to IBM Guardium AI Security also include automated red teaming to help enterprises detect and fix vulnerabilities and misconfigurations across AI use cases. And to help mitigate risks such as code injection, sensitive data exposure, and data leakage, the tool enables users to define custom security policies that analyze both input and output prompts. These features are available now in IBM Guardium AI Security, and their integration with watsonx.governance will roll out throughout the remainder of the year.

“The future of AI depends on how well we secure it today. Embedding security from the start is essential to protecting data, supporting compliance obligations, and building lasting trust,” said Suja Viswesan, Vice President, Security and Runtime Products, IBM.

“One of the biggest challenges for security teams is translating incidents and compliance violations into quantifiable business risk. The rapid adoption of AI and agentic AI amplifies this issue,” said Jennifer Glenn, Research Director for the IDC Security and Trust Group. “Unifying AI governance with AI security gives organizations the necessary context to find and prioritize risks, as well as the information to clearly communicate the consequences of not addressing them.”

Enhanced Agentic AI Evaluation and Lifecycle Governance

IBM watsonx.governance can now monitor and manage AI agents across their entire lifecycle, from development to deployment. Evaluation nodes can be built directly into agents, allowing users to carefully monitor metrics like answer relevance, context relevance, and faithfulness – and help identify the root cause of poor performance. Planned future capabilities also include agent onboarding risk assessment, agent audit trails, and an agentic tool catalogue, which are expected to be available June 27.

Off-the-Shelf Compliance Capabilities 

IBM watsonx.governance Compliance Accelerators provide select pre-loaded regulations, standards, and frameworks from around the globe, enabling users to identify relevant obligations and map them onto their own AI use cases. Content covers key regulations like the EU AI Act, the U.S. Federal Reserve’s SR 11-7, and New York City Local Law 144, along with global standards like ISO/IEC 42001 and frameworks like the NIST AI RMF. Watsonx.governance Compliance Accelerators is available now as an add-on.

Expertise to Scale AI Responsibly

To help clients scale AI responsibly, IBM Consulting Cybersecurity Services is introducing a new set of services that brings together data security platforms, like IBM Guardium AI Security, with deep AI technology and domain consulting. The new services will support organizations through their AI transformation journey: from discovering AI deployments and potential vulnerabilities, to implementing secure-by-design practices across AI layers, to governance guidance for a constantly evolving regulatory landscape. The new services build on IBM Consulting’s experience helping hundreds of clients worldwide on AI strategy and governance, including Nationwide Building Society and e&.

To provide AWS clients with increased value and convenience, watsonx.governance is now also available on AWS data center in India with enhanced model monitoring capabilities.

Today’s new capabilities and integrations give businesses the comprehensive governance and security they need to thrive in the agentic AI era. The innovations also dovetail with IBM’s broader suite of IBM watsonx AI solutions, built to help companies accelerate the impact of generative AI, responsibly and securely.

• IBM Quantum roadmap, processors, and infrastructure outline clear path to IBM Quantum Starling, expected to be first large-scale, fault-tolerant quantum computer 
• Breakthrough research defines key elements for an efficient fault-tolerant architecture — charting the first viable path toward a system projected to run 20,000 times more operations than today’s quantum computers
• Representing the computational state of IBM Starling would require the memory of more than a quindecillion (10⁴⁸) of the world’s most powerful supercomputers

YORKTOWN HEIGHTS, N.Y., June 10, 2025/PRNewswire/ — IBM (NYSE: IBM) unveiled its path to build the world’s first large-scale, fault-tolerant quantum computer, setting the stage for practical and scalable quantum computing.

Delivered by 2029, IBM Quantum Starling will be built in a new IBM Quantum Data Center in Poughkeepsie, New York and is expected to perform 20,000 times more operations than today’s quantum computers. To represent the computational state of an IBM Starling would require the memory of more than a quindecillion (10⁴⁸) of the world’s most powerful supercomputers. With Starling, users will be able to fully explore the complexity of its quantum states, which are beyond the limited properties able to be accessed by current quantum computers.

IBM, which already operates a large, global fleet of quantum computers, is releasing a new Quantum Roadmap that outlines its plans to build out a practical, fault-tolerant quantum computer.

“IBM is charting the next frontier in quantum computing,” said Arvind Krishna, Chairman and CEO, IBM. “Our expertise across mathematics, physics, and engineering is paving the way for a large-scale, fault-tolerant quantum computer — one that will solve real-world challenges and unlock immense possibilities for business.”

A large-scale, fault-tolerant quantum computer with hundreds or thousands of logical qubits could run hundreds of millions to billions of operations, which could accelerate time and cost efficiencies in fields such as drug development, materials discovery, chemistry, and optimization.

Starling will be able to access the computational power required for these problems by running 100 million quantum operations using 200 logical qubits. It will be the foundation for IBM Quantum Blue Jay, which will be capable of executing 1 billion quantum operations over 2,000 logical qubits.

A logical qubit is a unit of an error-corrected quantum computer tasked with storing one qubit’s worth of quantum information. It is made from multiple physical qubits working together to store this information and monitor each other for errors.

Like classical computers, quantum computers need to be error corrected to run large workloads without faults. To do so, clusters of physical qubits are used to create a smaller number of logical qubits with lower error rates than the underlying physical qubits. Logical qubit error rates are suppressed exponentially with the size of the cluster, enabling them to run greater numbers of operations.

Creating increasing numbers of logical qubits capable of executing quantum circuits, with as few physical qubits as possible, is critical to quantum computing at scale. Until today, a clear path to building such a fault-tolerant system without unrealistic engineering overhead has not been published.

The Path to Large-Scale Fault Tolerance

The success of executing an efficient fault-tolerant architecture is dependent on the choice of its error-correcting code, and how the system is designed and built to enable this code to scale.

Alternative and previous gold-standard, error-correcting codes present fundamental engineering challenges. To scale, they would require an unfeasible number of physical qubits to create enough logical qubits to perform complex operations – necessitating impractical amounts of infrastructure and control electronics. This renders them unlikely to be able to be implemented beyond small-scale experiments and devices.

A practical, large-scale, fault-tolerant quantum computer requires an architecture that is:

• Fault-tolerant to suppress enough errors for useful algorithms to succeed.
• Able to prepare and measure logical qubits through computation.
• Capable of applying universal instructions to these logical qubits.
• Able to decode measurements from logical qubits in real-time and can alter subsequent instructions.
• Modular to scale to hundreds or thousands of logical qubits to run more complex algorithms.
• Efficient enough to execute meaningful algorithms with realistic physical resources, such as energy and infrastructure.

Today, IBM is introducing two new technical papers that detail how it will solve the above criteria to build a large-scale, fault-tolerant architecture.

The first paper unveils how such a system will process instructions and run operations effectively with qLDPC codes. This work builds on a groundbreaking approach to error correction featured on the cover of Nature that introduced quantum low-density parity check (qLDPC) codes. This code drastically reduces the number of physical qubits needed for error correction and cuts required overhead by approximately 90 percent, compared to other leading codes. Additionally, it lays out the resources required to reliably run large-scale quantum programs to prove the efficiency of such an architecture over others.

The second paper describes how to efficiently decode the information from the physical qubits and charts a path to identify and correct errors in real-time with conventional computing resources.

From Roadmap to Reality

The new IBM Quantum Roadmap outlines the key technology milestones that will demonstrate and execute the criteria for fault tolerance. Each new processor in the roadmap addresses specific challenges to build quantum computers that are modular, scalable, and error-corrected:

• IBM Quantum Loon, expected in 2025, is designed to test architecture components for the qLDPC code, including “C-couplers” that connect qubits over longer distances within the same chip.
• IBM Quantum Kookaburra, expected in 2026, will be IBM’s first modular processor designed to store and process encoded information. It will combine quantum memory with logic operations — the basic building block for scaling fault-tolerant systems beyond a single chip.
• IBM Quantum Cockatoo, expected in 2027, will entangle two Kookaburra modules using “L-couplers.” This architecture will link quantum chips together like nodes in a larger system, avoiding the need to build impractically large chips.

Together, these advancements are being designed to culminate in Starling in 2029.

NEW YORK, June 2, 2025 /PRNewswire/ — IBM (NYSE: IBM) today announced watsonx AI Labs, a new, developer-first innovation hub in New York City, designed to supercharge AI builders and accelerate AI adoption at scale. watsonx AI Labs connects IBM’s enterprise resources and expertise with the next generation of AI developers in order to build breakthrough AI applications for business.

Located in the heart of Manhattan at IBM’s new offices at One Madison, watsonx AI Labs extends IBM’s global network of engineering labs, bringing together IBM researchers and engineers in a collaborative hub dedicated to co-creating and advancing meaningful, agentic AI solutions. The lab will work side-by-side with startups, scale-ups, and the world’s largest enterprises to help clients unlock real-world value from their AI.

The lab benefits from – and helps fuel – New York City’s status as a global AI hub. New York City has more than 2,000 AI startups, and its AI workforce grew by nearly 25% from 2022 to 2023, according to Tech:NYC. Since 2019, more than 1,000 AI-related companies in New York City have raised $27 billion in funding.

Also today, continuing its commitment to the local startup ecosystem, IBM announced it will acquire expertise and license technology from Seek AI, the New York City-based startup building AI agents to harness enterprise data. Seek AI helps businesses leverage agentic AI to mine value from enterprise data, and their expertise will serve as a foundational part of watsonx AI Labs.

“This isn’t your typical corporate lab. watsonx AI Labs is where the best AI developers gain access to world-class engineers and resources and build new businesses and applications that will reshape AI for the enterprise,” said Ritika Gunnar, General Manager, Data & AI, IBM. “By anchoring this mission in New York City, we are investing in a diverse, world‑class talent pool and a vibrant community whose innovations have long shaped the tech landscape.”

“IBM’s launch of watsonx AI Labs signals a transformative investment in New York’s innovation ecosystem. By bringing together world-class engineering talent, emerging startups, and deep enterprise expertise right here in the heart of the city, this initiative strengthens New York’s position as a global hub for responsible and cutting-edge AI development,” said Julie Samuels, President and CEO of Tech:NYC. “It’s a win for our tech sector, communities, workforce, and economy. We’re thrilled to see IBM betting big on the extraordinary talent and entrepreneurial spirit that make this city so unique.”

The lab seeks to tap into New York City’s rich technology landscape by attracting local talent, pursuing collaborations with local universities and research institutions, and supporting local entrepreneurs. Consistent with IBM’s long-standing investment in New York State, over the next five years, local startups that successfully launch AI enterprise solutions at the lab will have access to technical experts, mentorship and amplification, as well as potential investment from IBM Ventures and its global $500M Enterprise AI Venture Fund.

“Building a foundational part of watsonx AI Labs allows us to pair our expertise building data agents with IBM’s engineering depth to solve clients’ toughest AI challenges,” said Sarah Nagy, CEO of Seek AI. “We’re excited to tackle these challenges here in New York City, where Seek AI was founded and the AI talent and innovation ecosystem is thriving.”

watsonx AI Labs will focus on co-creation of domain‑specific AI solutions to solve enterprises’ most complex challenges – from customer service and supply‑chain optimization to cybersecurity, responsible AI governance, and open-source AI.

To learn more about participating in the watsonx AI Labs, visit www.ibm.com/products/watsonx-ai-labs.