LLMs Explained - Aggregate Intellect - AI.SCIENCE

LLMs Explained - Aggregate Intellect - AI.SCIENCE

Views:
843,134
Subscribers:
22,400
Videos:
711
Duration:
18:20:50:03
Canada
Canada

LLMs Explained - Aggregate Intellect - AI.SCIENCE is a Canadian YouTube content creator with roughly 22.4 thousand subscribers. He published 711 videos which altogether total roughly 843.13 thousand views.

Created on ● Channel Link: https://www.youtube.com/channel/UCfk3pS8cCPxOgoleriIufyg



Top 100 Videos With The Most Comments by LLMs Explained - Aggregate Intellect - AI.SCIENCE


Video TitleCommentsCategoryGame
1.Classification of sentiment reviews using n-gram machine learning approach171Review
2.Combining Satellite Imagery and machine learning to predict poverty52
3.[BERT] Pretranied Deep Bidirectional Transformers for Language Understanding (algorithm) | TDLS39
4.[Transformer] Attention Is All You Need | AISC Foundational38
5.Deep Neural Networks for YouTube Recommendation | AISC Foundational20
6.Connectionist Temporal Classification, Labelling Unsegmented Sequence Data with RNN | TDLS18
7.All-optical machine learning using diffractive deep neural networks | TDLS18
8.[Variational Autoencoder] Auto-Encoding Variational Bayes | AISC Foundational18
9.Can deep learning AI help with detecting COVID-19/coronavirus?17
10.[Original ResNet paper] Deep Residual Learning for Image Recognition | AISC16
11.[StyleGAN] A Style-Based Generator Architecture for GANs, part 1 (algorithm review) | TDLS16Review
12.AlphaStar explained: Grandmaster level in StarCraft II with multi-agent RL14Let's PlayStarCraft II
13.Introduction to the Conditional GAN - A General Framework for Pixel2Pixel Translation14
14.Convolutional Neural Networks for processing EEG signals12
15.Principles of Riemannian Geometry in Neural Networks | TDLS11
16.Junction Tree Variational Autoencoder for Molecular Graph Generation | TDLS11
17.[ELMo] Deep Contextualized Word Representations | AISC11
18.Recurrent Models of Visual Attention | TDLS11
19.[StackGAN++] Realistic Image Synthesis with Stacked Generative Adversarial Networks | AISC9
20.(Original Paper) Latent Dirichlet Allocation (algorithm) | AISC Foundational9
21.Introduction to NVIDIA NeMo - A Toolkit for Conversational AI | AISC8
22.[GAT] Graph Attention Networks | AISC Foundational8
23.A Literature Review on Graph Neural Networks8Review
24.[DDQN] Deep Reinforcement Learning with Double Q-learning | TDLS Foundational7
25.Supercharging AI with high performance distributed computing7
26.[Original attention] Neural Machine Translation by Jointly Learning to Align and Translate | AISC7
27.Lagrangian Neural Networks | AISC7
28.Mathematics of Deep Learning Overview | AISC Lunch & Learn6
29.Transformer XL | AISC Trending Papers6
30.TGN: Temporal Graph Networks for Deep Learning on Dynamic Graphs [Paper Explained by the Author]6
31.Why you should be part of AISC community!5
32.Revolutionary Deep Learning Method to Denoise EEG Brainwaves5
33.Paper Explained : PEGASUS, a SOTA abstractive summarization model by Google | AISC5
34.Genomics with Deep Learning: A Concise Overview | AISC5
35.AlphaFold 2, Is Protein Folding Solved? | AISC5Let's Play
36.Leaf Doctor: Plant Disease Detection Using Image Classification | Deep Learning Workshop Capstone5
37.Explainable AI, Session 5: Intro to SHAP5
38.XLNet: Generalized Autoregressive Pretraining for Language Understanding | AISC5
39.Sparse Transformers and MuseNet | AISC5
40.A Framework for Developing Deep Learning Classification Models5
41.Applications of Blockchain to IoT Security | AISC5
42.Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond | TDLS5
43.News Recommender System Considering Temporal Dynamics and News Taxonomy | AISC4
44.Deep InfoMax: Learning deep representations by mutual information estimation and maximization | AISC4Guide
45.Neural Ordinary Differential Equations - part 1 (algorithm review) | AISC4Review
46.What is Wrong with Explainable AI? | AISC4
47.Building AI Products; The Journey | Overview4
48.Explainable AI with Layer-wise Relevance Propagation (LRP)4
49.Investigating Anti-Muslim Bias in GPT-34
50.[StyleGAN] A Style-Based Generator Architecture for GANs, part2 (results and discussion) | TDLS4Discussion
51.Graph Neural Networks, Session 6: DeepWalk and Node2Vec4
52.Logeo: Automatically Transform 2D Designs to 3D4Vlog
53.BERT & NLP Explained4Let's Play
54.Modeling Dissolution of Compact Planetary Systems4
55.[AlphaGo Zero] Mastering the game of Go without human knowledge | TDLS4Let's Play
56.The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words & Sentences From Natural Supervision4
57.Pink Diamond - Data Driven Prediction of Venture Success | Workshop Capstone3
58.Machine Learning on Source Code - GitHub / Open AI Copilot3
59.Similarity of neural network representations revisited3
60.Meta-Graph: Few-Shot Link Prediction Using Meta-Learning | AISC3
61.An overview of task-oriented dialog systems | AISC3Vlog
62.Explainable AI for Time Series - Literature Review | AISC3Review
63.XAI for LLMs: looking under the hood of Large Language Models3
64.Review Nuggets - Mining Insight from Consumer Product Reviews | Workshop Capstone3Review
65.Why do large batch sized trainings perform poorly in SGD? - Generalization Gap Explained | AISC3
66.Reinforcement Learning in the Real World (with Professor Matthew Taylor)3
67.[FFJORD] Free-form Continuous Dynamics for Scalable Reversible Generative Models (Part 1) | AISC3
68.[OpenAI GPT2] Language Models are Unsupervised Multitask Learners | TDLS Trending Paper3
69.[Original Style Transfer] A Neural Algorithm of Artistic Style | TDLS Foundational3
70.Using unsupervised machine learning to uncover hidden scientific knowledge | AISC3
71.Visualizing and measuring the geometry of BERT | AISC3
72.Multi-agent LLMs Course #business #startup https://maven.com/forms/30a6833
73.Attention is not not explanation + Character Eyes: Seeing Language through Character-Level Taggers |3
74.Deep learning enables rapid identification of potent DDR1 kinase inhibitors | AISC3
75.Code Review: Transformer - Attention Is All You Need | AISC3Review
76.Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches |3
77.How do Aggregate Intellect Machine Learning Product Competitions work?2
78.Multi Type Mean Field Reinforcement Learning | AISC2
79.Women In AI Spring 2021 Showcase!!!2
80.Trusted Text Classification from Concept to Deployment | NLP Workshop Capstone2Let's Play
81.Graph Neural Networks, Session 2: Graph Definition2
82.Tobias Pfaff (DeepMind): Learning to Simulate Complex Physics with Graph Networks2
83.ChatGPT - the Chatbot that Follows Instructions - DRT S2E92Tutorial
84.Building (AI?) Products; Step by Step Guide | AISC2Guide
85.Learning Mesh-Based Simulation with Graph Networks - Tobias Pfaff (DeepMind)2
86.Plug and Play Language Models: A Simple Approach to Controlled Text Generation | AISC2
87.Building a Quantum Computer with Trapped Ions2
88.What is the right team composition in era of LLMs?2
89.[RecSys 2018 Challenge winner] Two-stage Model for Automatic Playlist Continuation at Scale |TDLS2
90.Machine Learning for Cyber Security - Session 192
91.Deep Learning in Healthcare and Its Practical Limitations2
92.Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT | AISC2
93.MLOps: MLflow Hands On, Session 2, part 22
94.Learning Discrete Structures for Graph Neural Networks | AISC2
95.Integrating Physics into Machine Learning Models for Scientific Discovery | AISC2
96.Top-K Off-Policy Correction for a REINFORCE Recommender System | AISC2
97.'Less Than One'-Shot Learning (author speaking)2
98.[hgraph2graph] Hierarchical Generation of Molecular Graphs using Structural Motifs | AISC Spotlight2
99.High Dimensional Inference in the Universe2
100.DeSci Labs: Creating A Backend For Scientific Papers - Deep Random Talks S2 E12