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Intelleger = انتليجر
The project management system is a web application designed to assist software managers in efficiently managing their projects, including websites, mobile apps, and other software initiatives. Utilizing artificial intelligence, the application streamlines project creation and management processes, offering significant benefits in terms of organization and accuracy. Managers can create projects by inputting essential details such as the name, scope, deadline, and tasks. The system generates AI-based functional and non-functional requirements tailored to the project scope using gpt2 model on Pure dataset. Managers can then review and edit these requirements as needed before finalizing the project. The application facilitates comprehensive task management by allowing managers to assign tasks to developers, edit task details, and ensure task deadlines align with project deadlines. Developers can log their start and end times automatically when they begin and complete tasks, providing accurate time tracking and performance analysis.also they can use code generation model to generate their task’s code using codebert model on concode and codesearchnet dataset Real-time notifications keep both managers and developers informed of task assignments, completions, and other critical updates.
Foundation models for natural language processing : pre-trained language models integrating media
Covers basic natural language processing models, pre-trained language models BERT, GPT, and sequence-to-sequence converters, as well as the concepts of self-attention and context-sensitive embedding. Various approaches to improving these models are then discussed, such as expanding the pre-training parameters, increasing the length of input texts, or incorporating additional knowledge. An overview of the best performing models is then provided for about twenty application areas, e.g., question answering, translation, story generation, dialogue systems, image generation from text, etc. For each application area, the strengths and weaknesses of existing models are discussed, and an overview of further developments is provided. In addition, links to freely available code are provided. The concluding chapter summarizes the economic opportunities, risk mitigation, and potential developments of AI.
Deepfake detection
The rise of large language models (LLMs) and the increasing sophistication of deepfake images have made detecting synthetic content a pressing challenge. Several approaches have been proposed to tackle this problem, including statistical analysis, and machine learning algorithms. In this project, A novel zero-shot approach is proposed that utilizes the power of LLMs to detect fake text. The pre-trained LLM is fine-tuned to enhance its ability to differentiate real and fake text. The approach uses the LLM to detect text by analyzing the log probabilities of the text. For detecting fake images, computer vision algorithms and neural networks are used to analyze facial features. The facial region is cropped and preprocessed and the neural network identifies patterns indicative of synthetic content.
Creative applications of artificial intelligence in education
Explores the synergy between AI and education, highlighting its potential impact on pedagogical practices. It navigates the evolving landscape of AI-powered educational technologies and suggests practical ways to personalise instruction, nurture human-AI co-creativity, and transform the learning experience. Spanning from primary to higher education, this short and engaging volume proposes concrete examples of how educational stakeholders can be empowered in their AI literacy to foster creativity, inspire critical thinking, and promote problem-solving by embracing AI as a tool for expansive learning. Structured in three parts, the book starts developing the creative engagement perspective for learning and teaching to then present practical applications of AI in K-12 and higher education, covering different fields (teacher education, professional education, business education) as well as different types of AI supported tools (games, chatbots, and AI assisted assessment).
