Discover AI Courses

Topological Message Passing: From Graph Neural Networks to Simplicial Complexes on CW Networks

Delve into advanced Graph Neural Network concepts, exploring topological message passing, simplicial complexes, and high-dimensional interactions for computational graph networks and molecular design applications.

• YouTube
• 25 minutes
• On-Demand
• Free Video

SETFIT Hyperparameter Optimization for SBERT Text Classification - Part 45

Master SETFIT hyperparameter optimization techniques for efficient text classification using Sentence Transformers, focusing on contrastive training and automated parameter tuning for optimal performance.

• YouTube
• 22 minutes
• On-Demand
• Free Video

SetFit with SBERT for Few-Shot Text Classification - Multi-Class and Multi-Label

Master SetFit and SBERT techniques for efficient few-shot text classification, exploring contrastive training, dense embeddings, and classification head implementation for both multi-class and multi-label scenarios.

• YouTube
• 28 minutes
• On-Demand
• Free Video

Graph Inspired Veracity Extrapolation (GIVE) - Integrating LLMs with Knowledge Graphs

Discover how GIVE framework enhances LLM reasoning by combining knowledge graphs with internal model knowledge, enabling more accurate responses through structured, step-by-step logical inference processes.

• YouTube
• 19 minutes
• On-Demand
• Free Video

Qwen 2.5 Math and Vision Models - Latest Open Source Developments

Explore the latest advancements in Qwen2.5-72B models, featuring specialized mathematics capabilities and enhanced vision processing with M-RoPE technology for improved AI performance and versatility.

• YouTube
• 18 minutes
• On-Demand
• Free Video

Reasoning and Tools Framework for AI Forecasting - A New Approach

Discover how advanced AI forecasting combines reasoning capabilities with real-time data through the RTF framework, enabling precise predictions across finance, weather, and material science domains.

• YouTube
• 20 minutes
• On-Demand
• Free Video

Adapting Image-based Reinforcement Learning Policies via Predicted Reward Fine-Tuning

Explore groundbreaking research on Predicted Reward Fine-Tuning (PRFT), a novel approach solving domain shift challenges in image-based reinforcement learning and sim-to-real AI transfer.

• YouTube
• 16 minutes
• On-Demand
• Free Video

Role-Playing Language Agents with MindEcho - Creating Personal AI Clones

Explore groundbreaking Chinese AI research on creating virtual KOL clones through Role-Playing Language Agents, examining technical implementation and ethical considerations.

• YouTube
• 20 minutes
• On-Demand
• Free Video

Text-to-Graph with Large Generative Graph Models

Explore cutting-edge research on large generative graph models and their applications in biomedicine and cybersecurity through diffusion-based technology and text-to-graph conversion.

• YouTube
• 12 minutes
• On-Demand
• Free Video

Fine-tuning Vision Language Models with PaLiGemma-3B - A Practical Guide

Master fine-tuning techniques for Vision Language Models using PyTorch and JAX FLAX, with practical examples for PaliGemma-3B implementation on free compute platforms like Google Colab and Vertex AI.

• YouTube
• 14 minutes
• On-Demand
• Free Video

Testing and Development Tools for Autonomous AI Agents - Performance Analysis and Frameworks

Explore the latest developments in autonomous AI agents, testing frameworks, and RAG systems through Webarena, Microsoft's Geckopt, and Cohere's open-source toolkit.

• YouTube
• 13 minutes
• On-Demand
• Free Video

Building RAG Systems: From Vector Embeddings to Self-Reflective CRAG - 5 Python Notebooks

Explore practical RAG implementations through 5 Python notebooks, from basic text embeddings to advanced self-reflective systems using LlamaIndex, Ollama, and ReAct Agent frameworks.

• YouTube
• 19 minutes
• On-Demand
• Free Video

LLM2LLM: Synthetic Data Generation for Fine-Tuning AI Models

Explore how large language models can generate synthetic data to teach and fine-tune other LLMs, with insights into performance metrics and applications for edge devices.

• YouTube
• 14 minutes
• On-Demand
• Free Video

LLM Reasoning Limitations: Understanding Linear Order and Logical Hallucinations

Delve into groundbreaking research from Stanford and DeepMind revealing LLMs' limitations in causal reasoning, premise ordering, and mathematical logic, highlighting key challenges in AI development.

• YouTube
• 16 minutes
• On-Demand
• Free Video

Phase Transitions in Dot-Product Attention Layer Learning - New AI Discovery

Explore groundbreaking research on phase transitions in LLM attention mechanisms, revealing key insights into semantic learning and potential breakthroughs in AI model efficiency.

• YouTube
• 12 minutes
• On-Demand
• Free Video