A selection of the most important recent news, articles, and papers about Coding with and for AI and Quantum Computing.
General News, Articles, and Analyses
The Walrus Operator: Python’s Assignment Expressions – Real Python
https://realpython.com/python-walrus-operator/
Author: Geir Arne Hjelle
(Wednesday, August 14, 2024) “In this tutorial, you’ll learn about assignment expressions and the walrus operator. The biggest change back in Python 3.8 was the inclusion of the := operator, which you can use to assign variables in the middle of expressions. You’ll see several examples of how to take advantage of this feature.”
News and Articles about Coding with AI or Coding for AI
AI in Context: First Test of Several Generative AI Code Generators – The Futurum Group
https://futurumgroup.com/insights/ai-in-context-first-test-of-several-generative-ai-code-generators/
Author: Dr. Bob Sutor
(Tuesday, April 16, 2024) “Generative AI has many applications, including code generation. I usually program in Python, so I tested five code generators to see how they performed on an HTML file search operation. I restricted myself to browser-based generators. I did not test all such generators, but the results show an interesting range in quality and completeness.”
CodeRabbit Secures $16 Million in Series A Funding to Revolutionize AI Code Reviews
https://coderabbit.ai/newsroom/series-a-funding-by-crv
(Wednesday, August 14, 2024) “CodeRabbit‘s platform automates code reviews by utilizing advanced AI reasoning, which comprehends the intent behind the code and delivers actionable, “human-like’ feedback. Traditional static analysis tools and linters are rule-based and often generate high false-positive rates, while peer reviews are time-consuming and subjective. The company’s AI-first approach improves code quality and significantly reduces the manual effort required in the code review process.”
Open source Dracarys models ignite generative AI fired coding | VentureBeat
https://venturebeat.com/ai/open-source-dracarys-models-ignite-generative-ai-fired-coding/
Author: Sean Michael Kerner
(Friday, August 23, 2024) “Abacus.ai is bringing new fire to the open source LLM world with fine tuned models optimized for coding with its Dracarys recipe.”
Business Reporter – AI & Automation – AI-generated code in software development
Author: Patrick Carey
(Friday, August 23, 2024) “AI-enabled code development is the new normal. By leveraging the practices used for human-developed software, organisations can capitalise on its potential”
News and Articles about Coding for Quantum Computers
Generative AI Revolutionizes Quantum Computer Programming
https://scitechdaily.com/generative-ai-revolutionizes-quantum-computer-programming/
(Thursday, May 23, 2024) “Researchers have developed a machine learning model that generates quantum circuits from text descriptions, similar to how models like Stable Diffusion create images. This method, improves the efficiency and adaptability of quantum computing.”
Release news: Qiskit SDK v1.2 is here! | IBM Quantum Computing Blog
https://www.ibm.com/quantum/blog/qiskit-1-2-release-summary
(Wednesday, August 21, 2024) “The Qiskit SDK is more performant than ever with its new v1.2 release.”
Qiskit SDK 1.2 release notes | IBM Quantum Documentation
https://docs.quantum.ibm.com/api/qiskit/release-notes/1.2
(Wednesday, August 21, 2024) “Changes made in Qiskit SDK 1.2”
Quantum Open Source Foundation
“The Quantum Open Source Foundation, herein after referred to as QOSF, is charged to expand the role of open source software in quantum computing and improve the standardization and quality thereof. The main focus of the QOSF will be on software intended for the use with current and near-term quantum computing technologies also often referred to as noisy intermediate scale quantum (NISQ) technologies.”
Technical Papers, Articles, and Preprints
Quantum circuit synthesis with diffusion models | Nature Machine Intelligence
https://www.nature.com/articles/s42256-024-00831-9
Authors: Fürrutter, Florian; Muñoz-Gil, Gorka; and Briegel, Hans J.
(Monday, May 20, 2024) “Achieving the promised advantages of quantum computing relies on translating quantum operations into physical realizations. Fürrutter and colleagues use diffusion models to create quantum circuits that are based on user specifications and tailored to experimental constraints.”
