Yannic Kilcher Courses

LLaMA- Open and Efficient Foundation Language Models - Paper Explained

2 ratings

Detailed explanation of Meta's LLaMA language models, covering training data, architecture, implementation, and performance. Explores how smaller models can outperform larger ones with optimized training.

• YouTube
• 41 minutes
• Self-Paced
• Free Video

GLIDE- Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

1 rating

Explore GLIDE, a text-guided diffusion model for photorealistic image generation and editing. Learn about diffusion models, conditional generation, and guided diffusion techniques for high-quality image synthesis.

• YouTube
• 42 minutes
• Self-Paced
• Free Video

Reinforced Self-Training for Language Modeling - Paper Explained

Explores Reinforced Self-Training, a novel approach for improving language models using offline reinforcement learning, offering efficiency advantages over traditional online methods.

• YouTube
• 53 minutes
• Self-Paced
• Free Video

Text Embeddings Reveal Almost As Much As Text - Iterative Embedding Inversion

Explore how text embeddings can potentially reconstruct original text, discussing methods, implications, and prevention strategies for this emerging privacy concern in natural language processing.

• YouTube
• 37 minutes
• Self-Paced
• Free Video

Google's Gemini Video Controversy - Analysis and Implications

Analysis of Google's Gemini marketing video, examining its portrayal of AI capabilities and raising questions about authenticity and potential misrepresentation of the model's true abilities.

• YouTube
• 16 minutes
• Self-Paced
• Free Video

Scalable Extraction of Training Data from Language Models

Explore techniques to extract training data from language models, revealing vulnerabilities in data privacy and model security. Learn about new attacks and their implications for AI alignment and memorization.

• YouTube
• 48 minutes
• Self-Paced
• Free Video

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Explore Mamba, a novel linear-time sequence modeling architecture using selective state spaces. Learn about its advantages over Transformers and its applications in language, audio, and genomics.

• YouTube
• 41 minutes
• Self-Paced
• Free Video

NeurIPS 2023 Poster Session 4 - Highlights in Machine Learning Research

Explore cutting-edge machine learning research in temporal action segmentation, test-time adaptation, recurrent neural networks, dictionary learning, equivariant adaptation, cross-task generalization, and adversarial learning.

• YouTube
• 58 minutes
• Self-Paced
• Free Video

Q-Learning: From Basics to Deep Q-Networks

Explore Q-Learning fundamentals, from Markov Decision Processes to Deep Q-Networks, in this comprehensive overview of reinforcement learning concepts and applications.

• YouTube
• 46 minutes
• Self-Paced
• Free Video

NeurIPS 2023 Poster Session 1 - Adversarial Patches, Continual Learning, and Reinforcement Learning

Explore cutting-edge AI research from NeurIPS 2023, covering adversarial patches, continual learning, neural network inference, and offline reinforcement learning.

• YouTube
• 19 minutes
• Self-Paced
• Free Video

NeurIPS 2023 Research Highlights - Circuits, Collaborative Filtering, Clustering, and Privacy

Overview of NeurIPS 2023 poster presentations covering graph neural networks, collaborative filtering, semi-supervised learning, and privacy assessment in image reconstruction, with insights on cutting-edge machine learning research.

• YouTube
• 34 minutes
• Self-Paced
• Free Video

NeurIPS 2023 Research Highlights - Poster Session 2

Explore cutting-edge AI research from NeurIPS 2023, covering topics like RNN training, image editing, language models, transformers, geo-localization, and hardware resilience in image classifiers.

• YouTube
• 44 minutes
• Self-Paced
• Free Video

Mixtral of Experts - Paper Explained

Explore Mixtral 8x7B, a Sparse Mixture of Experts language model outperforming larger models. Learn about its architecture, expert routing, parallelism, and impressive benchmark results.

• YouTube
• 35 minutes
• Self-Paced
• Free Video

Efficient Streaming Language Models with Attention Sinks - Paper Explained

Explore efficient streaming language models using attention sinks, enabling infinite sequence lengths without fine-tuning. Learn about the phenomenon, experimental evidence, and practical applications in AI.

• YouTube
• 32 minutes
• Self-Paced
• Free Video

Building a CPU Using GPT for Every Instruction

Explore building a CPU using GPT for every instruction, compiling C code to LLVM-IR. Learn about compilers, virtual machines, and innovative applications of language models in computing.

• YouTube
• 22 minutes
• Self-Paced
• Free Video