Call For Proposals (CFP)

Foundations, Frameworks and Tools for Machine Learning

• Unlocking Interoperability: A Deep Dive into ONNX and PMML
• Seamless Pipelines: Strategies for Bridging Multiple ML Frameworks
• Graph Neural Networks: Applications and Challenges
• Differentiable Programming: A New Horizon in ML Applications
• Future-Proofing ML Deployments: Emerging Tools for Interoperable Models
• The Role of APIs in Machine Learning Interoperability

MLOps, GenOps and DataOps

• GitOps for Machine Learning: Version Control for ML Models
• AIOps: AI for IT Operations
• Scaling Kubernetes Clusters for Generative Models
• GenOps: End-to-end Workflows for LLMs and Generative Models
• End-to-End MLOps with MLFlow and KubeFlow
• AI in Continuous Testing and Validation
• Data Lineage in Machine Learning Pipelines
• Model Compression Techniques for Efficient Deployment
• Effectively Scaling Machine Learning Models
• Model Observability and Monitoring in Production 
• Interoperability in the Cloud: MLOps Strategies for Multi-Cloud Deployments

Generative AI and Creative Computing

Autonomous AI and Reinforcement Learning

• Imitation Learning: Teaching Agents to Mimic Human Actions in Videos
• AI Safety in Autonomous Systems
• Evolutionary Algorithms for Game Playing Agents
• Multi-Agent Systems and Competitive Learning
• Autonomous Agents for the Enterprise: Automated the Workplace
• Using Larging Language Models for Autonomous Agent Behaviors
• Open Source Simulations: Leveraging O3DE for Robotics Training
• Reinforcement Learning from Human Feedback: Improving Agent Performance Through Human Preferences

Natural Language Processing and Computer Vision

• Emotional Intelligence in AI: Sentiment and Beyond
• Cross-Lingual Natural Language Processing
• Automatic Speech Recognition: Challenges and Solutions
• Subword Algorithms and Language Models
• Building and Operating Your Own Tokenizer
• AI-Driven Content Summarization and Aggregation
• 3D Vision and Depth Estimation: Applications in Robotics and AR/VR
• Image-to-Image Translation: Techniques and Applications in Style Transfer
• Human Pose Estimation: From Gaming to Healthcare
• Real-Time Object Detection: Challenges and Solutions

Edge and Distributed AI

• Federated Learning: Navigating the Landscape of Decentralized, Privacy-Preserving AI
• Resource Constraints in Edge AI: Optimizing for CPU, Memory, and Power
• Distributed Deep Learning: Horovod, Parameter Servers, and Beyond
• AI in Network Edge Computing
• Real-Time Decision Making in Edge AI

Data Engineering and Management

• Real-Time Analytics and Stream Processing
• Vector Stores, Similarity Search and Retrieval-Augmented Generation
• Data Imputation Techniques in AI
• Meta-Learning for Data Augmentation
• Data Marketplaces and Data Exchanges
• The Role of Data Mesh in Decentralized Data Architecture

Community and Ecosystem Building

• Collaborative Open Source AI Projects: Case Studies
• The Role of Hackathons and Competitions in AI Education
• The Impact of AI in Emerging Economies
• Public-Private Partnerships in AI Research and Development
• AI Literacy: Education and Outreach Programs
• Shepherding Responsible Legislation for Open-Source AI

Responsible AI: Ethics, Security, and Governance in AI

• Defining a Standard Responsible AI Framework
• XAI: eXplainable AI: Understanding How Models Function
• Human in the Loop: Controllable AI
• Adversarial Methods: Human and Model-Derived Adversarial Prompting for LLMs
• Fairness-Aware Machine Learning
• Responsible Data Collection and Usage in AI
• Synthetic Media and Deepfakes: Ethical Implications
• Algorithmic Accountability: Legal Frameworks and Policies
• Data Security and Privacy: Encryption, Leakage Control and Privacy-Preserving Techniques
• Untested Waters: The Legal Implications of Generative AI