AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
Category
1,774 papers
This work presents two board games intended to serve as an engaging introduction to growth hacking for students and helps spark interest in growth hacking among the academia.
Cyber Physical Systems (CPS) development approaches tend to start from the physical (hardware) perspective, and the software is the final element in the process. However, this approach is unfit for the more software-intensive world that is increasingly iterative, connected, and constantly online. Many constraints preve...
This investigation revealed different types of AI systems and different AI development approaches, but it is common that business opportunities involving with AI systems are not validated and there is lack of business-driven metrics that guide the development ofAI systems.
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Reach audiences
Advertise in front of researchers, engineers, and readers.
A unified platform that utilizes multiple artificial intelligence agents to automate the process of transforming user requirements into well-organized deliverables, including user stories, prioritization, and UML sequence diagrams, along with the modular approach to APIs, unit tests, and end-to-end tests.
A web-based software tool is introduced that employs an LLM-based agent and prompt engineering to automate the generation of test case scenarios against user requirements and crafting test case scenarios based on these stories.
A web-based software tool utilizing AI agents and prompt engineering to automate task prioritization and apply diverse prioritization techniques, aimed at enhancing project management within the agile framework is introduced.
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Results corroborate the effectiveness of LLMs in improving and streamlining RE phases by analyzing the semantic similarity and API performance of different models, as well as their effectiveness and efficiency in requirements analysis.
A novel multi-agent AI model is introduced that aims to assess and compare the performance of various LLMs, and initial results indicate that the GPT-3.5 Turbo model's performance is comparatively better than the other models.
The results indicate that if the OpenAPI specification is kept small and focused, LLM-based multi-agent systems are capable of generating complete functional code with business logic that aligns to the specification.
This work proposes and develops a multi-model unified platform to generate and execute code based on natural language prompts and presents practitioners feedback and insights into the use of LLMs in software development, including their strengths and weaknesses, key aspects overlooked by benchmarks and metrics.
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
Genie 4: our new world model unlocking unprecedented realism in real-time simulation.
Generative AI
General Science
A Blog post by NVIDIA on Hugging Face
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
