# IBM Corp. Published articles for IBM Corp.. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## IBM, AMD and Oak Ridge join forces to launch quantum computing error-correction platform DevFeed: [IBM, AMD and Oak Ridge join forces to launch quantum computing error-correction platform]() Original publisher: [Read original article]() Author: Kyt Dotson Published: 2026-11-05T13:00:59Z Content type: news Language: en Sources: [SiliconANGLE]() Topics: [Quantum Computing](), [High-Performance Computing](), [ibm]() Tags: [accelerators](), [advanced-micro-devices](), [ai](), [algorithm](), [algorithms](), [amd](), [architectures](), [computing](), [emerging-tech](), [error-correction](), [high-performance-computing](), [ibm](), [ibm-corp](), [jay-gambetta](), [launch](), [nasdaq-amd](), [news](), [noise](), [nyse-ibm](), [oak-ridge-national-laboratory](), [platform](), [quantum](), [quantum-computers](), [quantum-computing](), [quantum-error-correction](), [the-latest](), [travis-humble]() ### AI overview IBM, AMD and Oak Ridge National Laboratory's Quantum Science Center announced a co-designed platform to study quantum error correction using IBM quantum computers, including the 120-qubit Nighthawk, connected to Oak Ridge's Umbra supercomputer with AMD Instinct MI355X GPUs and 5th Gen EPYC CPUs. The project targets a scaling challenge: physical qubits can err every few hundred operations, while complex algorithms may require billions of error-free operations. Researchers can measure qubits during calculations, respond in real time, control the timing of protective signals and inspect raw measurement data. IBM says Nighthawk's square-lattice connectivity supports fast testing and real-time control; the platform is intended to evaluate error-correction architectures, software and workflows at scale. The excerpt describes research capabilities and goals, not demonstrated error-correction performance. ### Source excerpt IBM Corp., Advanced Micro Devices Inc. and the Quantum Science Center at Oak Ridge National Laboratory today announced a new quantum error-correction platform that integrates quantum and high-performance computing. Gaining high performance and correctness in quantum computing requires protecting quantum information from noise. In many cases, researchers have paired quantum computers with classical computers to [...] The post IBM, AMD and Oak Ridge join forces to launch quantum computing error-correction platform appeared first on SiliconANGLE. ## IBM puts agentic workloads at the heart of its AI operating model DevFeed: [IBM puts agentic workloads at the heart of its AI operating model]() Original publisher: [Read original article]() Author: Victoria Gayton Published: 2026-11-03T16:45:43Z Content type: news Language: en Sources: [SiliconANGLE]() Topics: [Agentic AI](), [ibm](), [AI Integration Strategies](), [AI Strategy](), [ai evaluation](), [ai observability](), [Artificial Intelligence](), [AI Infrastructure]() Tags: [actions](), [agentic](), [agentic-workloads](), [ai](), [ai-agents](), [ai-operating-model](), [applications](), [artificial-intelligence](), [autonomous](), [autonomous-systems](), [cube-event-coverage](), [data](), [data-governance](), [dave-vellante](), [enterprise-ai](), [enterprise-operations](), [enterprises](), [hybrid-cloud](), [ibm](), [ibm-corp](), [ibm-s-ai-operating-model-2026](), [ibmaioperatingmodel](), [infra](), [infrastructure](), [john-furrier](), [model](), [news](), [nyse-ibm](), [organizations](), [production](), [ritika-gunnar](), [salesforce](), [sap](), [scaling](), [scaling-ai](), [siliconangle](), [thecube](), [video-exclusive]() ### AI overview IBM's proposed AI operating model combines four components for agentic workloads: enterprise data, applications and workflows, automation, and hybrid cloud. The article says they must work together and integrate with existing systems such as SAP and Salesforce; automation provides observability that can inform model and agent selection. IBM's Ritika Gunnar emphasizes governing data access while preserving context and provenance, and keeping people involved in essential systems where tacit employee knowledge or AI maturity calls for human judgment. Logs and prompts can feed evaluation loops that compare decisions for accuracy, timeliness, and cost against intended business outcomes. The excerpt presents these as IBM's approach, without detailing implementation or independently evaluating results. ### Source excerpt Agentic workloads present a new operating challenge for enterprises putting artificial intelligence into production. As autonomous systems take on ongoing responsibilities, organizations must support decisions and actions across their data, applications and infrastructure. IBM Corp.'s approach draws on the experiences of clients scaling AI across their organizations. That work helped identify the requirements underpinning its [...] The post IBM puts agentic workloads at the heart of its AI operating model appeared first on SiliconANGLE. ## IBM puts governed context at the center of production AI DevFeed: [IBM puts governed context at the center of production AI]() Original publisher: [Read original article]() Author: Victoria Gayton Published: 2026-10-22T16:35:31Z Content type: news Language: en Sources: [SiliconANGLE]() Topics: [AI-Ready Data](), [ai-governance](), [AI Strategy](), [Artificial Intelligence](), [AI Integration Strategies]() Tags: [agents](), [ai](), [ai-agents](), [artificial-intelligence](), [artificial-intelligence-agents](), [business](), [business-context](), [business-process](), [business-processes](), [context](), [cube-event-coverage](), [data](), [data-governance](), [dave-vellante](), [enterprise-operations](), [enterprises](), [governed-context](), [ibm](), [ibm-confluent](), [ibm-corp](), [ibm-s-ai-operating-model-2026](), [ibm-techxchange-2026](), [ibmaioperatingmodel](), [john-furrier](), [large-language-models](), [news](), [nyse-ibm](), [personal](), [production](), [production-ai](), [productivity-tools](), [shaun-clowes](), [siliconangle](), [streamhouse-architecture](), [systems](), [thecube]() ### AI overview IBM's proposed "streamhouse architecture" brings current business state from operational systems to AI agents, with governance and data preparation close to where information is produced rather than requiring centralization first. IBM Confluent combines streaming, connectivity, processing, governance and querying to support that approach. Agents also need task-specific definitions and governed metrics or datasets so models reason from context suited to each business process. The excerpt recommends starting with high-value tasks, improving specialized agents as they gain experience, and connecting relevant data sources so agents can access operational information continuously. These points are presented as IBM executive Shaun Clowes's approach; the excerpt does not provide independent performance evidence. ### Source excerpt Governed context is becoming a practical requirement for artificial intelligence agents expected to make decisions across a business. As enterprises move beyond personal productivity tools, those agents need information that reflects changing conditions across the systems they use. IBM Corp.'s approach connects that data foundation to the broader challenge of putting AI into production. A [...] The post IBM puts governed context at the center of production AI appeared first on SiliconANGLE. ## IBM-backed llm-d framework adds controls for running AI models in-house DevFeed: [IBM-backed llm-d framework adds controls for running AI models in-house]() Original publisher: [Read original article]() Author: Paul Gillin Published: 2026-10-20T12:00:23Z Content type: release Language: en Sources: [SiliconANGLE]() Topics: [Self Hosted AI Tools](), [LLM optimization](), [Large Language Model](), [vllm](), [llm-reasoning](), [sglang](), [Local AI]() Tags: [accelerators](), [advanced-micro-devices](), [agentic](), [agents](), [ai](), [ai-agents](), [ai-inference](), [ai-models](), [artificial-intelligence](), [cached-context](), [distributed](), [distributed-ai-inference-framework](), [enterprises](), [ibm](), [ibm-corp](), [ibm-research](), [inference](), [inference-costs](), [infrastructure](), [large](), [llm-d](), [model-routing](), [multi-tenant-quality-of-service](), [news](), [on-premises-ai](), [open-source](), [pytorch](), [pytorch-conference](), [red-hat](), [release](), [the-latest]() ### AI overview llm-d 1.0 adds Kubernetes-based operational controls for running distributed model inference on an organization's own infrastructure: multi-tenant quality of service, request flow control and prioritization, and upgrades without downtime. For agent workloads, it routes requests toward replicas with reusable cached context and can move cached information between GPU memory, CPU memory, and storage. The release integrates these capabilities with prompt/response separation, batch optimization, and distribution of mixture-of-experts models across accelerators. It works with inference engines such as vLLM and SGLang. IBM reported 97% cache reuse in an agentic coding test; IBM and Red Hat separately said a demonstration ran 3,000 coding agents at five to 10 times lower cost than a hosted service using the same open model. These are company-reported results. ### Source excerpt IBM Corp. and several other contributors to the open-source llm-d project are releasing version 1.0 of their distributed artificial intelligence inference framework, adding operational controls intended to help enterprises run large models reliably on their own infrastructure. The release, announced ahead of the PyTorch Conference North America in San Jose today and tomorrow, focuses on [...] The post IBM-backed llm-d framework adds controls for running AI models in-house appeared first on SiliconANGLE. ## IBM allows on-prem deployment of its Bob agentic development platform DevFeed: [IBM allows on-prem deployment of its Bob agentic development platform]() Original publisher: [Read original article]() Author: Paul Gillin Published: 2026-10-01T19:49:51Z Content type: news Language: en Sources: [SiliconANGLE]() Topics: [agentic-coding](), [on-prem](), [internal developer platform automation](), [AI Strategy](), [iac-security]() Tags: [agentic-software-development](), [ai](), [air-gapped](), [application-modernization](), [artificial-intelligence](), [ibm](), [ibm-bob](), [ibm-corp](), [ibm-institute-for-business-value](), [infrastructure](), [news](), [nvidia-nemotron](), [on-prem](), [poolside-laguna](), [private-cloud](), [self-hosted](), [sovereign-cloud](), [the-latest]() ### AI overview IBM announced a self-hosted option for IBM Bob, its agentic software development platform, for on-premises, private-cloud, sovereign-cloud and air-gapped environments. Organizations can run supported models locally or connect to external model services in hybrid configurations, choosing where processing occurs. IBM says the option keeps source code, development context and build artifacts in customer-managed environments when using a supported self-hosted model configuration. ### Source excerpt IBM Corp. today announced a self-hosted deployment option for IBM Bob, its agentic software development platform, allowing enterprises to use artificial intelligence to build and modernize applications within their own infrastructure.. The offering supports on-premises, private-cloud, sovereign-cloud and air-gapped environments. It targets organizations whose sensitive source code, regulated data or critical systems limit their ability [...] The post IBM allows on-prem deployment of its Bob agentic development platform appeared first on SiliconANGLE.