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#Attention Mechanisms

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Stanford University

How I Learned to Stop Worrying and Love the Transformer - Stanford CS25 Lecture

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Explore the Transformer's evolution and future directions with Ashish Vaswani, co-author of "Attention is All You Need". Gain insights into motivations, developments, and promising research areas in AI and NLP.
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1 Lesons
1 hour 21 minutes
On-Demand
Free-Video
Stanford University

Overview of Transformers - Stanford CS25: Lecture 1

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Comprehensive introduction to NLP, Transformers, and AI agents, covering history, functionality, recent breakthroughs, applications, and challenges in the field of artificial intelligence.
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1 Lesons
1 hour 17 minutes
On-Demand
Free-Video
University of Central Florida

AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks

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Explore fine-grained text-to-image generation using attentional GANs, covering architecture, experiments, and novel scenarios in this technical deep dive.
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16 Lesons
46 minutes
On-Demand
Free-Video
University of Central Florida

Video Action Transformer Network: Implementation and Experiments

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Learn about Video Action Transformer Networks, exploring their architecture, implementation, and experimental results for advanced video understanding and action recognition.
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16 Lesons
21 minutes
On-Demand
Free-Video
University of Central Florida

Video Content Understanding Using Text

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Explore video content understanding using text, covering challenges, algorithms, and techniques for video representation, scoring, optimization, and inaccuracy detection.
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42 Lesons
44 minutes
On-Demand
Free-Video
University of Central Florida

Textual Explanation for Self-Driving Vehicles

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Explore self-driving vehicle technology through an explainable driving model, focusing on network architecture, preprocessing, and evaluation of vehicle control and explanation generation.
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18 Lesons
28 minutes
On-Demand
Free-Video
Cloud Security Alliance

Demystifying LLMs and Their Security Implications - A Business-Friendly Overview

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Explore GenAI and LLMs, understanding their operations, security implications, and deployment scenarios. Learn to manage risks, prevent data leakage, and implement practical strategies for safe AI integration.
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31 Lesons
1 hour 7 minutes
On-Demand
Free-Video
Simons Institute

Exact Solutions to the Geometric Dynamics of Signal Propagation Through Transformers

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Explore exact solutions to geometric dynamics of signal propagation in transformers, predicting their behavior as computational models.
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1 Lesons
44 minutes
On-Demand
Free-Video
Simons Institute

Limitations of Attention Mechanism in Transformers - Implications for Generalization and Optimization

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Explore Transformer's reasoning capabilities and limitations in sequential tasks, examining optimization challenges and out-of-distribution generalization issues compared to RNNs.
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1 Lesons
48 minutes
On-Demand
Free-Video
Simons Institute

Transformers as a Computational Model

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Explore Transformers as a computational model with Misha Belkin, delving into their architecture, capabilities, and implications for AI research and applications.
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1 Lesons
53 minutes
On-Demand
Free-Video
Simons Institute

Introduction to Transformers

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Dive into the fundamentals of Transformers, exploring their architecture and applications in large language models with expert insights from Columbia University.
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1 Lesons
1 hour 10 minutes
On-Demand
Free-Video
Alexander Amini

MIT 6.S191 - Recurrent Neural Networks

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Explore recurrent neural networks, LSTMs, and attention mechanisms for sequence modeling. Learn backpropagation through time, gradient issues, and practical applications in deep learning.
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11 Lesons
45 minutes
On-Demand
Free-Video
Alexander Amini

MIT: Recurrent Neural Networks

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Explore deep sequence modeling with recurrent neural networks, including LSTMs and attention mechanisms. Learn to tackle challenges like vanishing gradients and long-term dependencies in sequence tasks.
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33 Lesons
37 minutes
On-Demand
Free-Video
Institute for Advanced Study

Modularity, Attention and Credit Assignment Computations - Anirudh Goyal

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Explore modularity, attention, and credit assignment in computational models, focusing on complex generalization, independent mechanisms, and selective activation for improved learning and problem-solving.
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27 Lesons
1 hour 2 minutes
On-Demand
Free-Video
Institute for Advanced Study

Priors for Semantic Variables - Yoshua Bengio

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Explore semantic variables, learning theory, and cognitive processes with Yoshua Bengio. Delve into attention mechanisms, causality, and modular recurrent networks for advanced machine learning insights.
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19 Lesons
1 hour 32 minutes
On-Demand
Free-Video
Simons Institute

How Do Transformers Work? - A Deep Dive into Neural Network Architecture

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Dive into the fundamental mechanics and architecture of transformer models, exploring their key components and operational principles through expert insights from MIT's research.
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1 Lesons
1 hour 16 minutes
On-Demand
Free-Video
AI Institute at UofSC - #AIISC

Transformers in Time Series: A Survey

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Explore the application of Transformer models in time series analysis, covering recent advancements and potential future directions in this rapidly evolving field.
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1 Lesons
43 minutes
On-Demand
Free-Video
Serrano.Academy

The Math Behind Attention Mechanisms

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Demystify attention mechanisms in Transformer models through visuals, examples, and mathematical explanations, focusing on embeddings, similarity, and key-query-value matrices.
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7 Lesons
38 minutes
On-Demand
Free-Video
StatQuest with Josh Starmer

Essential Matrix Algebra for Neural Networks

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Learn essential matrix algebra for neural networks, covering linear transformations, matrix operations, and their application in PyTorch and Attention mechanisms.
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11 Lesons
30 minutes
On-Demand
Free-Video
Centre International de Rencontres Mathématiques

The Linear Algebra of Large Language Models

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Explorez les fondements mathématiques des modèles de langage à grande échelle et leur lien avec l'algèbre linéaire avancée.
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1 Lesons
30 minutes
On-Demand
Free-Video
Scalable Parallel Computing Lab, SPCL @ ETH Zurich

HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers

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Explore higher-order dynamic graph representation learning with efficient Transformers for improved link prediction in rapidly changing graphs. Learn about HOT model's architecture and performance.
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9 Lesons
20 minutes
On-Demand
Free-Video
DataLearning@ICL

Autoregressive Long-Context Music Generation with Perceiver AR

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Explore autoregressive long-context music generation using Perceiver AR, presented by DeepMind's Cătălina Cangea. Gain insights into cutting-edge AI techniques for creating music.
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1 Lesons
1 hour
On-Demand
Free-Video
Data Science Conference

From RNNs to Transformers - A Journey Through Language Modeling

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Explore the evolution of language models from RNNs to Transformers, understanding attention mechanisms and investigating the minimal requirements for coherent language generation in AI systems.
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1 Lesons
1 hour 26 minutes
On-Demand
Free-Video
Data Science Conference

Revealing the Unseen: Visualizing Attention in Transformer Models

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Dive into the visualization techniques of attention mechanisms in Transformer models, understanding their inner workings and practical applications through expert insights.
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1 Lesons
24 minutes
On-Demand
Free-Video
AI Bites

Making LLMs Fully Utilize Context - A Data-Driven Approach

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Discover how to enhance LLM context utilization through Microsoft's data-driven approach, exploring information-intensive training methods and practical solutions for improved context awareness and reasoning capabilities.
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14 Lesons
14 minutes
On-Demand
Free-Video
Discover AI

LongRoPE and Theta Scaling for Extended Context Length in LLMs - Part 2

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Delve into advanced techniques for extending LLM context lengths through LongRoPE and Theta Scaling, exploring methods to enhance model performance from 8K to 4M tokens.
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1 Lesons
59 minutes
On-Demand
Free-Video
Discover AI

Understanding Retrieval Heads in Large Language Models - From Discovery to Applications

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Discover groundbreaking research on retrieval heads in transformer architecture, exploring their impact on RAG systems, long-context processing, and chain-of-thought reasoning for enhanced AI capabilities.
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10 Lesons
31 minutes
On-Demand
Free-Video
Discover AI

RecurrentGemma: Moving Past Transformers with Griffin Architecture for Long Context Length

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Explore Google's RecurrentGemma-2B architecture, featuring Griffin's innovative approach to language modeling that surpasses traditional transformers with enhanced efficiency and long-context processing capabilities.
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12 Lesons
31 minutes
On-Demand
Free-Video
Discover AI

TransformerFAM and BSWA: Understanding Feedback Attention Memory and Block Sliding Window Attention

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Dive into Google's revolutionary TransformerFAM architecture, exploring how feedback attention mechanisms and working memory enhance AI's ability to process indefinite sequence lengths with improved efficiency and context awareness.
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9 Lesons
25 minutes
On-Demand
Free-Video
Discover AI

INFINI Attention: Efficient Infinite Context Transformers with 1 Million Token Context Length

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Explore Google's Infini-attention transformer mechanism, featuring compressive memory integration for handling million-token sequences and efficient long-term information processing.
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11 Lesons
21 minutes
On-Demand
Free-Video
Discover AI

Ring Attention and Blockwise Transformers for Extended Context Length in Language Models

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Dive into the technical mechanics of Ring Attention, exploring how it achieves million-token context lengths in large language models through blockwise parallel transformers and efficient implementation.
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9 Lesons
25 minutes
On-Demand
Free-Video
Discover AI

StreamingLLM: Enabling Infinite Sequence Length in Large Language Models

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Dive into StreamingLLM's framework for extending LLM attention windows to handle infinite sequences, featuring practical implementation insights and code analysis.
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1 Lesons
38 minutes
On-Demand
Free-Video
AI Bites

LongNet: Understanding Transformer Scaling to 1 Billion Tokens - A Technical Overview

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Dive into Microsoft's LongNet transformer architecture, exploring how dilated attention mechanisms enable processing of billion-token sequences and advance the field towards artificial general intelligence.
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8 Lesons
12 minutes
On-Demand
Free-Video
UofU Data Science

Pairwise Feature Importance and Effective Attention in Self-Attention Networks

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Dive into advanced concepts of attention mechanisms, exploring effective attention computation, norm-based analysis, and practical applications in neural networks.
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5 Lesons
36 minutes
On-Demand
Free-Video
Discover AI

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

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Explore groundbreaking research on phase transitions in LLM attention mechanisms, revealing key insights into semantic learning and potential breakthroughs in AI model efficiency.
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3 Lesons
12 minutes
On-Demand
Free-Video
Data Science Courses

Deep Learning: Transformers and Encoder-Decoder Architecture - Lecture 10

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Dive into transformer architectures, exploring encoder-decoder mechanisms and positional embeddings for advanced deep learning applications.
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1 Lesons
1 hour 10 minutes
On-Demand
Free-Video
Data Science Courses

Attention Mechanism and Self-Attention in Deep Learning - Lecture 9

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Dive into attention mechanisms and self-attention concepts in deep learning, exploring their revolutionary impact on NLP and discovering practical applications in sequence models.
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1 Lesons
1 hour 18 minutes
On-Demand
Free-Video
UofU Data Science

Transformer Types and Practical Considerations

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Explore different transformer architectures and key implementation factors for building effective natural language processing models and applications.
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1 Lesons
1 hour 21 minutes
On-Demand
Free-Video
UofU Data Science

Attention and Transformer Encoder Architecture

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Master the inner workings of Transformer encoders and attention mechanisms in deep learning, exploring their architecture, self-attention calculations, and practical applications in modern AI.
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1 Lesons
1 hour 17 minutes
On-Demand
Free-Video
UofU Data Science

Transformer Decoder - Pretraining and Finetuning

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Master transformer decoder architecture fundamentals, exploring pretraining methods and effective finetuning techniques for advanced natural language processing applications.
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1 Lesons
1 hour 19 minutes
On-Demand
Free-Video
The Full Stack

Transfer Learning and Transformers - Full Stack Deep Learning - Spring 2021

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Explore transfer learning's evolution from computer vision to NLP, diving into embeddings, language models, and the revolutionary Transformer architecture. Gain insights into various models and their applications.
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9 Lesons
49 minutes
On-Demand
Free-Video
The Full Stack

Recurrent Neural Networks - Full Stack Deep Learning - Spring 2021

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Explore Recurrent Neural Networks: architecture, challenges, solutions, and applications. Dive into LSTMs, bidirectionality, attention mechanisms, CTC loss, and non-recurrent sequence models like WaveNet.
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9 Lesons
1 hour 6 minutes
On-Demand
Free-Video
Valerio Velardo - The Sound of AI

Transformers for Generative Music AI - Part 2: Decoder and Music Generation

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Explore transformer architecture for music AI, focusing on decoder components, masked attention, and practical tips for generating music. Dive into future research and neuro-symbolic integration for robust music generation.
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20 Lesons
1 hour 4 minutes
On-Demand
Free-Video
Aladdin Persson

Pytorch Transformers from Scratch - Attention Is All You Need

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Implement Pytorch Transformers from scratch, exploring the "Attention is all you need" paper. Learn attention mechanisms, encoder-decoder architecture, and practical application.
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11 Lesons
57 minutes
On-Demand
Free-Video
Aleksa Gordić - The AI Epiphany

The Sensory Neuron as a Transformer - Permutation-Invariant Neural Networks for Reinforcement Learning - Paper Explained

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Explore Google Brain's "Attention Neuron" model for reinforcement learning, featuring permutation-invariant neural networks and their application in various experiments and visualizations.
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9 Lesons
33 minutes
On-Demand
Free-Video
Edan Meyer

Recreate Google Translate - Model Training

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Explore model training and testing for Neural Machine Translation, recreating Google Translate using mT5 and Hugging Face. Practical implementation and demo of multilingual translations.
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6 Lesons
21 minutes
On-Demand
Free-Video
Aleksa Gordić - The AI Epiphany

Non-Parametric Transformers - Paper Explained

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Explore non-parametric transformers: innovative AI model for tabular data, relational reasoning, and causal mechanisms. Learn architecture, loss function, and connections to other neural networks.
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15 Lesons
46 minutes
On-Demand
Free-Video
Yannic Kilcher

Rethinking Attention with Performers

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Explore a novel approach to efficient attention mechanisms in Transformers using random positive orthogonal features, enabling linear-time approximation of attention matrices for scalable deep learning architectures.
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14 Lesons
55 minutes
On-Demand
Free-Video
Yannic Kilcher

LambdaNetworks- Modeling Long-Range Interactions Without Attention

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Explore LambdaNetworks, a novel approach to modeling long-range interactions in AI without traditional attention mechanisms, offering improved efficiency and performance in computer vision tasks.
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8 Lesons
1 hour
On-Demand
Free-Video
Yannic Kilcher

Hopfield Networks Is All You Need - Paper Explained

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Explores the connection between Hopfield networks and transformer attention, analyzing BERT through this lens and applying Hopfield attention to immune repertoire classification.
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9 Lesons
1 hour 5 minutes
On-Demand
Free-Video
Yannic Kilcher

Avoiding Catastrophe - Active Dendrites Enable Multi-Task Learning in Dynamic Environments

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Explore how active dendrites in neural networks mitigate catastrophic forgetting, enabling multi-task learning and adaptation in dynamic environments through context-sensitive gating and sparse representations.
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12 Lesons
1 hour 5 minutes
On-Demand
Free-Video
Yannic Kilcher

Train Short, Test Long - Attention With Linear Biases Enables Input Length Extrapolation

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ALiBi: A novel attention mechanism enabling transformers to process longer sequences than trained on. Uses linear biases instead of position encodings, improving efficiency and extrapolation capabilities.
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7 Lesons
31 minutes
On-Demand
Free-Video
Yannic Kilcher

Not All Memories Are Created Equal - Learning to Forget by Expiring

0 rewiews
Explore Facebook AI's Expire-Span, a Transformer XL variant that dynamically assigns expiration dates to signals, enabling efficient handling of long sequences while maintaining performance and reducing resource consumption.
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9 Lesons
42 minutes
On-Demand
Free-Video
Yannic Kilcher

Emerging Properties in Self-Supervised Vision Transformers - Facebook AI Research Explained

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Explore Facebook AI's DINO system, combining self-supervised learning with Vision Transformers for impressive image analysis without labels. Learn about its architecture, methodology, and groundbreaking results in computer vision.
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10 Lesons
39 minutes
On-Demand
Free-Video
rupert ai

Hugging Face Transformers - The Basics - Practical Coding Guides - NLP Models (BERT/RoBERTa)

0 rewiews
Learn the basics of Hugging Face Transformers library, including installation, pre-defined pipelines, and implementing models in PyTorch. Explore tokenization, attention masks, and model outputs in this practical coding guide.
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10 Lesons
30 minutes
On-Demand
Free-Video
James Briggs

Vision Transformers Explained + Fine-Tuning in Python

0 rewiews
Explore Vision Transformers (ViT) for image classification, from theory to implementation. Learn about attention mechanisms, patch embeddings, and fine-tuning using Hugging Face in Python.
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19 Lesons
30 minutes
On-Demand
Free-Video
HuggingFace

A Gentle Visual Intro to Transformer Models

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Explore key concepts of Transformer models, including encoder, decoder, and attention, through a visual and accessible explanation by ML expert Jay Alammar.
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10 Lesons
29 minutes
On-Demand
Free-Video
Launchpad

DF-GAN: Deep Fusion Generative Adversarial Networks for Text-to-Image Synthesis

0 rewiews
Learn about DF-GAN, a deep fusion architecture for text-to-image synthesis. Explore its simplified backbone, gradient penalty, and deep fusion block, with quantitative and qualitative results.
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17 Lesons
38 minutes
On-Demand
Free-Video
Graham Neubig

Neural Nets for NLP 2019 - Attention

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Explore attention mechanisms in neural networks for NLP, covering basic concepts, improvements, specialized varieties, and a case study on the Transformer model.
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18 Lesons
1 hour 19 minutes
On-Demand
Free-Video
Graham Neubig

Neural Nets for NLP 2017 - Attention

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Comprehensive exploration of attention mechanisms in neural networks for NLP, covering various types, improvements, and applications, with a focus on the Transformer model.
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22 Lesons
1 hour 3 minutes
On-Demand
Free-Video
Graham Neubig

Neural Nets for NLP 2021 - Attention

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Explore attention mechanisms in neural networks for NLP, covering key concepts, improvements, and specialized varieties with practical examples and applications.
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18 Lesons
38 minutes
On-Demand
Free-Video
Graham Neubig

CMU Multilingual NLP - Machine Translation-Sequence-to-Sequence Models

0 rewiews
Explore conditional language modeling, sequence-to-sequence models, generation methods, attention mechanisms, and transformers in multilingual natural language processing.
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26 Lesons
44 minutes
On-Demand
Free-Video
Graham Neubig

Neural Nets for NLP 2020 - Attention

0 rewiews
Explore attention mechanisms in neural networks for NLP, covering types, improvements, and specialized varieties. Dive into the "Attention is All You Need" paper and its impact on the field.
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18 Lesons
1 hour 5 minutes
On-Demand
Free-Video
Runway

GPT-2 and Transformers

0 rewiews
Explore text-based AI models, focusing on GPT-2 and Transformers. Learn about their architecture, capabilities, and potential applications in natural language processing.
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6 Lesons
13 minutes
On-Demand
Free-Video
Alexander Amini

Recurrent Neural Networks, Transformers, and Attention

0 rewiews
Explore recurrent neural networks, transformers, and attention mechanisms in deep learning. Learn design principles, applications, and advanced concepts like LSTM and backpropagation through time.
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19 Lesons
1 hour 3 minutes
On-Demand
Free-Video
Aladdin Persson

Pytorch Seq2Seq with Attention for Machine Translation

0 rewiews
Build a Seq2Seq model with Attention in PyTorch for German-to-English machine translation, applying it to the Multi30k dataset and learning from scratch.
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1 Lesons
25 minutes
On-Demand
Free-Video
Simons Institute

On Localization in Language Models

0 rewiews
Explore the role of individual components in language models, their characterization, and how analyzing internal structures can elucidate behavior in memorization, gender bias, and factual recall.
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1 Lesons
1 hour 1 minute
On-Demand
Free-Video
Aleksa Gordić - The AI Epiphany

Flash Attention 2.0 with Tri Dao - Discord Server Talks

0 rewiews
Explore Flash Attention 2.0 with author Tri Dao, covering its motivation, improvements, and future directions. Gain insights into memory bottlenecks and IO awareness in attention mechanisms for long sequences.
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9 Lesons
1 hour
On-Demand
Free-Video
CodeEmporium

Transformer Encoder in 100 Lines of Code

0 rewiews
Learn to implement a Transformer Encoder from scratch in Python. Explore key concepts like attention mechanisms, layer normalization, and feed-forward networks through hands-on coding.
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25 Lesons
50 minutes
On-Demand
Free-Video
Yannic Kilcher

Attention Is All You Need

0 rewiews
Explore the groundbreaking Transformer architecture, revolutionizing sequence transduction with attention mechanisms. Learn its superior performance in machine translation and generalization to other NLP tasks.
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11 Lesons
27 minutes
On-Demand
Free-Video
Alan Turing Institute

Recurrent Neural Networks and Models of Computation - Edward Grefenstette, DeepMind

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Exploring recurrent neural networks and memory-enhanced architectures, analyzing their computational capabilities and efficiency in relation to traditional models of computation.
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16 Lesons
39 minutes
On-Demand
Free-Video
Alfredo Canziani

Parameter Sharing - Recurrent and Convolutional Nets

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Explore parameter sharing in recurrent and convolutional neural networks, covering hypernetworks, RNNs, LSTMs, attention mechanisms, and ConvNets, with insights on architecture, training, and biological inspiration.
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29 Lesons
2 hours
On-Demand
Free-Video
Alfredo Canziani

Attention and the Transformer

0 rewiews
Explore self-attention, key-value stores, and transformer architecture in deep learning. Learn to implement attention mechanisms and understand encoder-decoder paradigms for advanced neural network design.
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5 Lesons
1 hour 18 minutes
On-Demand
Free-Video
Alfredo Canziani

CNN Applications, RNN, and Attention

0 rewiews
Explore CNN applications in digit recognition, object detection, and semantic segmentation. Dive into RNNs, addressing their challenges with attention mechanisms, GRUs, LSTMs, and Seq2Seq models.
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7 Lesons
1 hour 29 minutes
On-Demand
Free-Video
Pascal Poupart

Memory Augmented Networks

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Learn about memory augmented networks, including architecture, attention mechanisms, and applications in machine translation, with a focus on improving generalization in deep learning models.
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9 Lesons
47 minutes
On-Demand
Free-Video
Pascal Poupart

CS480-680 Lecture 19 - Attention and Transformer Networks

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Explore attention mechanisms, transformer networks, and their applications in machine learning, including multihead attention and normalization techniques.
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10 Lesons
1 hour 23 minutes
On-Demand
Free-Video
Launchpad

MAST - A Memory-Augmented Self-Supervised Tracker

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Learn about MAST, a novel memory-augmented self-supervised tracker that enhances video tracking and segmentation using attention mechanisms and innovative algorithms.
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15 Lesons
23 minutes
On-Demand
Free-Video
Applied Algebraic Topology Network

Graph Representation Learning and Its Applications to Biomedicine

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Graph representation learning techniques for biomedical applications, focusing on SubGNN for disentangled subgraph embeddings and their use in predicting disease treatments and safe drug combinations.
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24 Lesons
1 hour
On-Demand
Free-Video
MITCBMM

Question Answering for Language and Vision

0 rewiews
Explore advanced techniques in question answering for language and vision, including joint models, multitask learning, and neural networks with Richard Socher from MetaMind.
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15 Lesons
40 minutes
On-Demand
Free-Video
Andreas Geiger

Driving with Attention

0 rewiews
Explore innovative sensor fusion techniques for autonomous driving, focusing on TransFuser and NEAT models that leverage attention mechanisms to improve perception and decision-making in complex traffic scenarios.
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20 Lesons
33 minutes
On-Demand
Free-Video
Simons Institute

Fast Attention Requires Bounded Entries

0 rewiews
Explore the relationship between fast attention mechanisms and bounded entries in machine learning, with insights from Josh Alman's research on sketching and algorithm design.
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1 Lesons
46 minutes
On-Demand
Free-Video
1littlecoder

AI News: Open Source Advancements and Recent Developments

0 rewiews
Explore latest AI advancements: new models, papers, and tools. Learn about HyperAttention, MemGPT, Self-RAG, PaLI-3, Fuyu-8B, MistralLite, and more. Stay updated on AI developments in various domains.
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19 Lesons
24 minutes
On-Demand
Free-Video
StatQuest with Josh Starmer

Coding a ChatGPT-Like Transformer From Scratch in PyTorch

0 rewiews
Step-by-step tutorial on building a ChatGPT-like Transformer from scratch in PyTorch, covering data preparation, position encoding, attention mechanisms, and model training for natural language processing.
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8 Lesons
31 minutes
On-Demand
Free-Video
Serrano.Academy

Transformer Models: Understanding Their Architecture and Functionality - Part 3

0 rewiews
Demystifying Transformer models with visuals and examples, covering key concepts like attention mechanism, tokenization, embeddings, and fine-tuning for various NLP tasks.
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13 Lesons
44 minutes
On-Demand
Free-Video
TEDx

Navigating Forgetfulness and Intelligence in AI

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Explore AI's memory dynamics, learning challenges, and the interplay between forgetfulness and intelligence. Gain insights into how AI systems remember, forget, and process information over time.
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1 Lesons
15 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

Fast Multipole Attention: A Divide-and-Conquer Attention Mechanism for Long Sequences

0 rewiews
Innovative divide-and-conquer strategy for efficient attention in long sequences, reducing complexity while maintaining global receptive field. Potential to enhance large language models with extended context processing.
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1 Lesons
42 minutes
On-Demand
Free-Video
Yannic Kilcher

Scalable MatMul-free Language Modeling - Paper Explained

0 rewiews
Explore innovative MatMul-free language modeling techniques using quantization and recurrence, achieving comparable performance to traditional models while significantly reducing computational costs and memory usage.
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8 Lesons
50 minutes
On-Demand
Free-Video
Center for Language & Speech Processing(CLSP), JHU

The NLP Task Effectiveness of Long-Range Transformers

0 rewiews
Explore the effectiveness of long-range Transformer variants on NLP tasks, comparing their performance and analyzing attention behaviors to uncover strengths and limitations.
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1 Lesons
12 minutes
On-Demand
Free-Video
Simons Institute

Long-context Attention in Near-Linear Time

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Explores HyperAttention, an innovative approach to tackle computational challenges in long-context LLMs, offering significant speed improvements while maintaining performance across various datasets.
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1 Lesons
41 minutes
On-Demand
Free-Video
Simons Institute

Sub-Linear Algorithms Meets Large Language Models

0 rewiews
Explore emerging ideas and successful trends in sub-linear algorithms for future LLMs, addressing compute, memory, and energy challenges in training and inference.
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1 Lesons
41 minutes
On-Demand
Free-Video
GOTO Conferences

Hello Deep Learning

0 rewiews
Explore deep learning from scratch, building an OCR solution for handwritten letters. Learn the fundamentals of machine learning and gain insights into the world of AI and neural networks.
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16 Lesons
44 minutes
On-Demand
Free-Video
Conference GSI

Chan Vese Attention U-Net - An Attention Mechanism for Robust Segmentation

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Explore an innovative attention mechanism for robust image segmentation using Chan Vese Attention U-Net, enhancing segmentation accuracy and efficiency.
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1 Lesons
20 minutes
On-Demand
Free-Video
The Julia Programming Language

Raising the Ki of a SciML Model - Enhancing GOKU-nets for Scientific Machine Learning

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Explore advanced SciML techniques with GOKU-UI, enhancing Latent ODEs through attention mechanisms and multiple shooting. Learn to improve model performance and data efficiency for complex system modeling.
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1 Lesons
11 minutes
On-Demand
Free-Video
Google Cloud Tech

Transformer Models and BERT Model: Overview

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Explore Transformer architecture and BERT model, understanding key components and applications in text classification, question answering, and natural language inference.
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1 Lesons
12 minutes
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Free-Video
Google Cloud Tech

Creating Image Captioning Models: Overview and Components

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Learn to build deep learning image captioning models, exploring encoder-decoder architecture, training techniques, and evaluation methods for accurate visual descriptions.
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5 Lesons
12 minutes
On-Demand
Free-Video
USENIX

Cost-Efficient Large Language Model Serving for Multi-turn Conversations with CachedAttention

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Innovative attention mechanism for efficient LLM serving in multi-turn conversations, reducing computation costs and improving performance through hierarchical KV caching and optimized cache management.
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1 Lesons
22 minutes
On-Demand
Free-Video
CodeEmporium

Informer Encoder Architecture Explained

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Explore the Informer Encoder architecture, its key components, and implementation details for advanced time series forecasting and sequence modeling tasks.
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1 Lesons
26 minutes
On-Demand
Free-Video
Yannic Kilcher

Transformers Are RNNs- Fast Autoregressive Transformers With Linear Attention

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Explore a novel approach to transformers using linear attention, reducing computational complexity and revealing connections to RNNs. Gain insights into faster, more efficient deep learning models for long sequences.
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11 Lesons
48 minutes
On-Demand
Free-Video
Yannic Kilcher

BERTology Meets Biology - Interpreting Attention in Protein Language Models

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Explores how BERT models trained on protein sequences learn biological properties, revealing insights into protein structure, binding sites, and biophysical characteristics through attention mechanism analysis.
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10 Lesons
37 minutes
On-Demand
Free-Video
Yannic Kilcher

Object-Centric Learning with Slot Attention

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Explanation of a novel deep learning module for object-centric visual scene understanding. Covers architecture, algorithm, experiments, and implications of Slot Attention for improved object recognition and reasoning.
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9 Lesons
43 minutes
On-Demand
Free-Video