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IBM released a new benchmark for evaluating enterprise agents on multi-hop multi-source reasoning, called VAKRA 🙌🏻 Interesting to see gpt-oss-120b is second in the benchmark after Gemini-3-Flash topping the leaderboard 👏 pretty cool how they consistently release enterprise agentic work (that no other lab does!) get started in their demo → https://lnkd.in/dc_jVuW4
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IBM just released Granite 4.0 1B Speech, a compact and efficient speech-language model, designed for multilingual speech recognition and bidirectional speech translation. New #1 on the OpenASR leaderboard! It can even run in your browser on WebGPU, thanks to 🤗 Transformers.js
Gabe Goodhart built a local AI coding assistant using Granite 4, Ollama, VS Code, and Continue. In this tutorial, he breaks down the full workflow — including the architecture behind it and how to do it locally: https://ibm.co/6041EHOHB
Qiskit, the open-source quantum software developer stack, guides you from high-level problem design to hardware execution: ✨ Build, run, and visualize quantum experiments ⚡️ Connect quantum hardware with existing classical systems 🧰 Use pre-built templates, algorithms, and add-ons to design new applications Explore Qiskit and the broader quantum computing ecosystem: https://ibm.co/6046EHDuq
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Our new Granite 4 Speech model just dropped, and it has taken the #1 spot on the Open ASR (Automated Speech Recognition) Leaderboard! Even more exciting, at 1B parameters, it is our fastest and lightest Granite Speech to date, a fraction of the size of competitors. Granite 4 1B Speech: 🏆 Best in class word error rates on the Open ASR Leaderboard. ⚡️ Lightning fast 1B parameter form factor built on a Granite 4 foundation 💬 Support for English, French, German, Spanish, Portuguese, and Japanese 💪 Built for business. Open, commercial-friendly Apache 2.0 license, Industry-leading transparency. 🔗 Link below in the replies:
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Most conversations about AI coding tools still focus on speed. I think the more interesting question is control. In enterprise software, faster output can also mean: - more review pressure - more hidden assumptions - more architectural drift - more expensive mistakes later The better pattern is simple: - Humans define intent. - Systems enforce guardrails. - Agents execute bounded work. - Verification protects trust. That’s the thinking behind this carousel and a big part of how I think about Bob for software engineering teams and enterprise development workflows. Code got cheaper. Judgment got more valuable. #Bob #AI #Java #SoftwareEngineering #EnterpriseArchitecture #IBM IBM IBM Developer #IBMBob
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Watch my new video on IBM Bob YouTube channel: "IBM Bob for IBM watsonx Orchestrate: Create MCP Tools and Agents". See Bob in action, taking a plain-English prompt all the way from design and architecture to deployment in watsonx Orchestrate. Bob plans the project, builds an MCP server with two tools, writes unit tests, validates everything end-to-end with an MCP client with error handling, then imports the tools and creates a working agent in watsonx Orchestrate. I highly encourage you to subscribe to Bob YouTube channel for more videos from Bob friends, including Alex Soto, Maximilian Jesch, and Tim Rowe, showcasing how Bob helps across DevSecOps, observability, security, application modernization, and IBM i transformation. A big thank you to Maximilian Jesch and Martin Keen for your contributions and guidance on editing the video, and thank you to Neel Sundaresan for your overall support and encouragement. https://lnkd.in/dnYP-gEp
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𝗪𝗵𝗮𝘁 𝗶𝗳 𝘁𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗴𝗮𝗽 𝗶𝗻 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝗶𝘀𝗻’𝘁 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲, 𝗶𝘁’𝘀 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲? That’s why we’ve partnered with the 𝗜𝗕𝗠 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝗟𝗮𝗯. The problem is clear: - 𝟴𝟬%+ 𝗼𝗳 𝗔𝗜 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝗳𝗮𝗶𝗹 - Only 𝟱% 𝗼𝗳 𝗚𝗲𝗻𝗔𝗜 pilots reach real business impact Why? Because most frameworks focus on the Brain (reasoning) while ignoring the Body (UI + enterprise connectivity) and Guardrails (governance, safety, human‑in‑the‑loop). 𝗢𝘂𝗿 𝗮𝗻𝘀𝘄𝗲𝗿: 𝗙𝘂𝗹𝗹‑𝗦𝘁𝗮𝗰𝗸 𝗔𝗴𝗲𝗻𝘁 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲. 🧠 𝗜𝗕𝗠 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝗟𝗮𝗯 - 𝗖𝗨𝗚𝗔 • Enterprise‑ready generalist open‑source agent, trusted for policy adherence, safety, auditability, and reliability • #1 on AppWorld 🏗️ 𝗞𝗮𝘁𝗼𝗻𝗶𝗰 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 – 𝗔𝗚‑𝗨𝗜 & 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗨𝗜 • Enterprise‑ready interaction layer • Seamless deployment on your infrastructure 🛡️ 𝗝𝗼𝗶𝗻𝘁 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 • Completion Under Policy metric for enterprise‑grade agent evaluation • Safety benchmarks • Human‑in‑the‑loop workflows 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝘁𝗵𝗮𝘁 𝘁𝗵𝗶𝗻𝗸, 𝗮𝗰𝘁, 𝗮𝗻𝗱 𝘀𝗵𝗼𝘄. CUGA is live on Katonic today. The #1 ranked agent, running on your infrastructure with full data sovereignty. “𝗪𝗲 𝗳𝗼𝗰𝘂𝘀 𝗼𝗻 𝗵𝗼𝘄 𝗮𝗴𝗲𝗻𝘁𝘀 𝘁𝗵𝗶𝗻𝗸 𝗶𝗻 𝗮 𝘀𝗮𝗳𝗲 𝗮𝗻𝗱 𝘁𝗿𝘂𝘀𝘁𝗲𝗱 𝗺𝗮𝗻𝗻𝗲𝗿. 𝗞𝗮𝘁𝗼𝗻𝗶𝗰 𝗳𝗼𝗰𝘂𝘀𝗲𝘀 𝗼𝗻 𝗵𝗼𝘄 𝗮𝗴𝗲𝗻𝘁𝘀 𝗶𝗻𝘁𝗲𝗿𝗮𝗰𝘁 𝘄𝗶𝘁𝗵 𝗵𝘂𝗺𝗮𝗻𝘀 𝗮𝗻𝗱 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲𝘀. 𝗬𝗼𝘂 𝗻𝗲𝗲𝗱 𝗯𝗼𝘁𝗵.” - Asaf Adi, Senior Manager, AI Agents, IBM Software Innovation Lab 𝗪𝗵𝗮𝘁’𝘀 𝗻𝗲𝘅𝘁: → Katonic contributing to CUGA open‑source → Joint whitepaper (coming soon) → Live webinar (dates announced shortly) 𝗧𝗵𝗶𝘀 𝗶𝘀 𝗖𝗵𝗮𝗽𝘁𝗲𝗿 𝟭. 👉 https://lnkd.in/gmVw8JCR Asaf Adi Ayhan Sebin Nir Mashkif Avi Yaeli Sami Marreed Prem Naraindas Mohan K #AIResearch #AIAgents #FullStackAgents #IBMSoftwareInnovationLab #KatonicAI #CUGA
Langflow 1.7 focuses on production-ready agent workflows—adding streamable MCP over HTTP, new agent components, and improved security. See what’s included → https://ibm.co/6049DIYFB
There’s a lot of noise around AI IDEs. Maximilian Jesch walks through how IBM Bob works with real-world Java codebases, analyzing dependencies and supporting modernization at scale. ⬇️