ISSN:
ISBN: 978-1-68558-182-4

• Registered: with the Library of Congress of the United States of America (ISSN)
• Free Access: in ThinkMind Digital Library

GPTMB 2024 is colocated with the following events as part of DigiTech 2024 Congress:

• DIGITAL 2024, Advances on Societal Digital Transformation
• IoTAI 2024, The First International Conference on IoT-AI
• GPTMB 2024, The First International Conference on Generative Pre-trained Transformer Models and Beyond

GPTMB 2024 Steering Committee

		Petre Dini IARIA USA/EU			Isaac Caicedo-Castro University of Córdoba Colombia
		Tzung-Pei Hong National University of Kaohsiung Taiwan			Stephan Böhm RheinMain University of Applied Sciences - Wiesbaden Germany
		Alper Yaman Fraunhofer IPA Germany

GPTMB 2024 conference tracks:

Generative-AI basics
Generative Pre-trained Transformer Models
Combination of GPT models and Reinforcement learning models
Creativity and originality in GPT-based tools
Deep learning
Large Language Models (LLM)
Autoregressive language models
Accuracy and relevancy

Critical issues on Input Data
Datasets: accuracy, granularity, precision, false/true negative/positive
Visible vs invisible (private, personalized) data
Data extrapolation
Output biases and biased Datasets
Sensitivity and specificity of Datasets
Fake and incorrect information
Volatile data
Time sensitive data

Critical Issues on Processing
Process truthfulness
Explainability
Detect biases and incorrectness
Incorporate the interactive feedback
Incorporate corrections

Output quality
Output biases and biased Datasets
Sensitivity and specificity of Datasets
Context-aware output
Fine/Coarse text summarization
Quality of Data pre-evaluation (obsolete, incomplete, fake, noisy, etc.)
Validation of output
Detect biased and incorrect summarization before spreading it

Education and academic liability issues
User awareness on output trust-ability
Copyright infringements rules
Plagiarism and self-plagiarism tools
Ownership infringement
Mechanisms for reference verification
Dealing with hidden self-references

Regulations and limitations
Regulations (licensing, testing, compliance-threshold, decentralized/centralize innovations)
Mitigate societal risks of GPT models
Capturing emotion and sentience
Lack of personalized (individual) memory and memories (past facts)
Lack of instant personalized thinking (personalized summarization)
Risk of GPTM-based decisions
AI awareness
AI-induced deskilling  

Case studies with analysis and testing AI applications
Lesson learned with existing tools (ChatGPT, Bard AI, ChatSonic, etc.)
Predictive analytics in healthcare
Medical Diagnostics
Medical Imaging 
Pharmacology
AI-based therapy
AI-based finance
AI-based planning
AI-based decision
AI-based systems control
AI-based education
AI-based cyber security

Deadlines:

Deadlines differ for special tracks. Please consult the conference home page for special tracks Call for Papers (if any).