How ChatGPT is Trained - Model and Training Explained
Delve into the technical foundations and training methodology behind ChatGPT, exploring its model architecture, reinforcement learning principles, and step-by-step training process.
How to Create an Effective Prompt - A No-Code Guide for Custom LLM Applications
Learn to craft effective AI prompts tailored to your needs with a practical, template-free approach that works across different LLM platforms and specific use cases.
Evaluating LLMs as AI Reasoning Agents - A Performance Comparison Study
Explore how different LLMs perform as AI agents in real-world tasks, comparing their effectiveness in database interactions, web bookings, and online product comparisons.
Fine-tuning ChatGPT with Synthetic GPT-4 Datasets - A Python Implementation
Master fine-tuning ChatGPT using Python and synthetic GPT-4 datasets through hands-on implementation of multi-GPT system interactions and advanced prompt engineering techniques.
Tool LLM for API Calls - Understanding Fine-Tuned Language Models for API Performance
Explore how Tool LLama, a fine-tuned LLM, leverages API capabilities through ToolBench dataset to achieve ChatGPT-level performance in handling API interactions.
ChatGPT Prompt Engineering with In-Context Learning - 7 Examples
Master prompt engineering techniques through 7 practical examples, from zero-shot prompting to reverse Turing tests, while exploring innovation theory and strategic AI applications.
ChatGPT Prompt Engineering with In-Context Learning Using OpenAI API
Master prompt engineering techniques for ChatGPT with hands-on practice using In-Context Learning and OpenAI API integration in Python through a practical COLAB environment.
Generative AI and LLM Technologies - A Comprehensive Tutorial
Explore essential concepts and technologies behind generative AI systems, from pre-training and fine-tuning to prompt engineering and advanced data structures for LLMs.
ChatGPT vs Flan-T5: Comparing Proprietary and Free LLMs with Performance Tuning
Explore the differences between ChatGPT and Flan-T5 LLM models, comparing their capabilities, accessibility, and performance optimization through practical demonstrations and hyperparameter tuning techniques.
Domain-Specific AI Models - Creating Customized BERT and SBERT Models for Business Applications
Discover how to effectively train and fine-tune BERT and SBERT models for specialized domains, focusing on medical and biochemical terminology, with practical solutions for business applications.
Sparrow - Google's Second Generation Conversational AI After BARD
Explore Google's Sparrow AI system, its architecture, and comparison with ChatGPT, featuring demonstrations and insights into next-generation conversational search technology and language models.
Fine-tuning ChatGPT with In-Context Learning - Chain of Thought, AMA, and ReAct Reasoning
Master advanced in-context learning techniques like Chain-of-Thought and ReAct to optimize ChatGPT's performance without expensive fine-tuning, based on latest research insights and practical applications.
Deep Learning: RLHF, ChatGPT, and Alignment in LLMs - Lecture 14
Dive into advanced concepts of RLHF, ChatGPT training, and LLM alignment, exploring efficient transformers and the technical foundations behind modern language models.
AI, Large Language Models and University Education
Explore the impact of AI and large language models on university education through expert insights from Prof. Ioannis Pitas in this thought-provoking lecture.
Visualizing Data Integration Between ChatGPT and Enterprise Systems
Discover how to integrate enterprise data with ChatGPT through OpenAI plugins, vector stores, and semantic search capabilities, focusing on GPT-4's dynamic data flow and PostgreSQL integration.
From Documents to Vectors: Understanding ChatGPT's Technical Architecture with OpenAI Plugins
Dive into the technical architecture of ChatGPT plugins, exploring vector databases, API endpoints, and real-time data retrieval methods for enhanced AI capabilities.
Connecting Multiple ChatGPT Sessions with Dynamic Instruction Prompt Templates
Master advanced prompt design techniques to connect and optimize multiple ChatGPT sessions using Dynamic Instruction Prompt Templates (DIPT), enabling continuous learning and improved effectiveness across conversations.
LangChain - Integrating External Documents and SQL with GPT-4
Dive into LangChain's capabilities for integrating external documents and SQL with GPT-4, learning to chain multiple data sources and leverage advanced language models effectively.
The ALPACA Code: Self-Instruct Fine-Tuning of Large Language Models
Dive into the technical implementation of self-instruct fine-tuning for Large Language Models using ALPACA, covering synthetic dataset generation and parallel task optimization.
Creating Self-Instruct Data Sets for LLM Fine-Tuning with ChatGPT
Master the creation of synthetic instruction datasets using ChatGPT and GPT-4 for fine-tuning language models, covering data generation, multi-task training, and task decomposition techniques.
Self-Instruct Fine-Tuning of Large Language Models - Introduction to Alpaca
Master self-instruct fine-tuning techniques for LLMs, focusing on synthetic data generation using ChatGPT/GPT-4 to enhance model performance in specific tasks like summarization and translation.