Applied Generative AI and Software Safety Workshop by Tonex
This 2-day workshop is designed to provide participants with a comprehensive understanding of how generative AI can be applied to enhance software safety. Through interactive sessions, hands-on exercises, and collaborative discussions, attendees will explore AI-driven solutions for ensuring software safety, compliance, fault tolerance, and risk management. The workshop aims to equip software engineers, developers, and safety professionals with the skills and knowledge to leverage AI technologies for achieving higher safety standards in software systems.
Learning Objectives
- Understand Generative AI in Software Safety: Gain a comprehensive understanding of generative AI technologies and their applications in enhancing software safety.
- AI-driven Safety Assurance: Learn how to use AI tools for improving software safety and compliance.
- Fault Tolerance and Risk Management: Explore AI techniques for fault detection, isolation, recovery, and risk management in software systems.
- Enhanced Development Practices: Improve software engineering workflows using AI-driven insights and tools for safety.
- Practical Implementation: Engage in hands-on exercises to apply AI tools in real-world software safety scenarios.
Audience
This workshop is ideal for:
- Software engineers and developers looking to integrate AI into their safety practices.
- IT professionals and data scientists involved in software safety and compliance.
- Project managers and team leaders overseeing safety-critical software development projects.
- Researchers and academics interested in the intersection of AI and software safety.
- Anyone with a background in software development seeking to enhance their understanding of AI applications in safety.
Program Details
Day 1:
- Introduction to Generative AI and Software Safety
- Overview of generative AI technologies
- Introduction to software safety principles and practices
- Synergy between AI and software safety
- AI-Driven Safety Assurance and Compliance
- Techniques for AI integration in software safety assurance
- Case studies of AI-enhanced safety compliance
- Tools and frameworks for AI-driven safety assurance
- Hands-on Session: Generative AI Tools for Software Safety
- Practical exercises using AI tools for software safety improvement
- Creating and evaluating AI models for safety-critical applications
- Optimizing software safety and performance using AI
- Case Study Analysis: Real-world Applications
- In-depth analysis of successful AI implementations in software safety
- Discussion of challenges and solutions
- Extracting best practices and lessons learned
Day 2:
- Advanced Techniques for AI-Enhanced Fault Tolerance and Risk Management
- AI methodologies for fault detection and isolation
- Application of machine learning in fault recovery and risk management
- Real-time monitoring and predictive maintenance using AI
- Lifecycle Management with AI
- Role of AI in the lifecycle management of safety-critical software systems
- Predictive analytics for lifecycle planning
- AI in maintenance and sustainability of safety-critical software projects
- Interactive Q&A Session
- Open floor discussion with AI and software safety experts
- Addressing specific participant questions and scenarios
- Collaborative problem-solving and idea exchange
- Ethical and Responsible AI Use in Software Safety
- Understanding AI ethics in safety-critical software contexts
- Strategies for mitigating biases and ensuring ethical AI deployment
- Governance frameworks for responsible AI use
- Future Trends in Generative AI and Software Safety
- Exploring upcoming advancements in AI technologies
- Preparing for future AI innovations in software safety
- Strategic planning for long-term AI integration
- Final Project: AI-Enhanced Software Safety Plan
- Developing a comprehensive plan for integrating AI in software safety practices
- Group presentations and peer feedback
- Actionable steps for post-workshop implementation