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.
Celebrating qiskit-ibm-transpiler recognition as the 4th most used quantum computing development tool globally in the 2024 Unitary Fund survey. A remarkable achievement for a project with just 1 year of public existence, combining Qiskit heuristic algorithms with novel AI 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.
Quantum programs are typically developed using quantum Software Development Kits (SDKs). The rapid advancement of quantum computing necessitates new tools to streamline this development process, and one such tool could be Generative Artificial …
Published research paper introducing Qiskit HumanEval dataset for evaluating Large Language Models capability to generate quantum computing code. The dataset comprises more than 100 quantum computing tasks with prompts, solutions, test cases, and difficulty ratings, establishing benchmarks for generative AI tools in quantum code development.
Code Large Language Models (Code LLMs) have emerged as powerful tools, revolutionizing the software development landscape by automating the coding process and reducing time and effort required to build applications. This paper focuses on training …
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.