Announcing the latest open-source LLM releases from the Qiskit Code Assistant team, featuring Qiskit 2.0 compatibility, enhanced text understanding, and new models including Granite 3.3, Granite 3.2, and Qwen2.5-Coder series.
Exciting update: Qiskit Code Assistant service now exposes compatible endpoints with OpenAI Completions API. This enables seamless usage via existing libraries like OpenAI and LiteLLM, making it easy to infuse Qiskit knowledge into your LLM pipelines.
Released granite-8b-qiskit-rc-0.10, the latest revision of the LLMs that empower Qiskit Code Assistant. Trained on significantly expanded Qiskit synthetic dataset, this marks the final model using the current training approach as we pivot to newer Granite base models and cutting-edge techniques.
Shipped granite-8b-qiskit-rc-0.10, the latest revision of LLMs empowering Qiskit Code Assistant. Trained on significantly expanded Qiskit synthetic dataset, marking the end of an era as the final model using current training approach before pivoting to newer Granite base models.
Excited to participate in the Quantum Developer Conference 2024 at IBM Thomas J. Watson Research Center, networking with quantum computing professionals and showcasing new developments at the intersection of AI and quantum computing - featuring the Qiskit Code Assistant and AI-powered transpiler passes.
Published a comprehensive blog post summarizing what Qiskit Code Assistant is and how to start using it. Following the recent launch, users are actively leveraging the tool features, and the team is developing improved models with enhanced capabilities for open source release.
Attended IEEE Quantum Week 2024 highlighting four major IBM Quantum AI initiatives: Qiskit Transpiler Service with AI-powered optimization, first preview of Qiskit Code Assistant, unitary compilation research with David Kremer, and the Qiskit HumanEval benchmark presentation.
Announcing multiple major releases at the convergence of AI and quantum computing: beta version of Qiskit transpiler service (unveiled at THINK24), research paper on AI-powered transpiler passes, and Qiskit Code Assistant with LLMs and the Qiskit HumanEval benchmark. Both projects recognized through IBM Quantum Challenge.
Published research paper on training specialized LLMs for quantum computing code generation using Qiskit. Addresses unique challenges in quantum programming, including scarcity of quantum code examples and rapid field evolution. Our model outperforms existing state-of-the-art quantum computing models.
Extremely proud of the massive Qiskit SDK v1.0 release including two projects from my team: the Qiskit Transpiler with AI transpiling passes and the Qiskit Code Assistant. This full-stack software for quantum computing brings together cutting-edge AI and quantum technologies.