LLMs Explained - Aggregate Intellect - AI.SCIENCE

LLMs Explained - Aggregate Intellect - AI.SCIENCE

Views:
816,922
Subscribers:
20,400
Videos:
723
Duration:
20:17:30:40
Canada
Canada

LLMs Explained - Aggregate Intellect - AI.SCIENCE is a Canadian YouTube channel which has roughly 20.4 thousand subscribers, with his content totaling around 816.92 thousand views views across 723 videos.

Created on ● Channel Link: https://www.youtube.com/@ai-science



Top 100 Videos With The Longest Duration by LLMs Explained - Aggregate Intellect - AI.SCIENCE


Video TitleDurationCategoryGame
1.2019 AI Squared Forum Paper Track | AISC3:46:07
2.Plug and Play Language Models: A Simple Approach to Controlled Text Generation | AISC2:36:38
3.AlphaStar explained: Grandmaster level in StarCraft II with multi-agent RL2:10:12Let's PlayStarCraft II
4.Single Headed Attention RNN: Stop Thinking With Your Head | AISC2:06:49
5.[Phoenics] A Bayesian Optimizer for Chemistry | AISC Author Speaking2:06:09
6.Recurrent Models of Visual Attention | TDLS2:02:47
7.The Messy Side of AI Products | AISC2:01:00
8.Learnability can be undecidable | AISC2:00:34
9.Top-K Off-Policy Correction for a REINFORCE Recommender System | AISC1:59:25
10.Tensor Field Networks | AISC1:57:10
11.[AI Product] How to build products people actually want to use | AISC1:52:48Guide
12.[RoBERT & ToBERT] Hierarchical Transformers for Long Document Classification | AISC1:51:37
13.[DOM-Q-NET] Grounded RL on Structured Language | AISC Author Speaking1:50:00
14.TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing | AISC1:49:47Guide
15.[RecSys 2018 Challenge winner] Two-stage Model for Automatic Playlist Continuation at Scale |TDLS1:47:16
16.A Survey of Singular Learning | AISC1:47:02
17.XLNet: Generalized Autoregressive Pretraining for Language Understanding | AISC1:45:12
18.Superposition of Many Models into One | AISC1:44:41
19.Code Review: Transformer - Attention Is All You Need | AISC1:44:14Review
20.Understanding the Origins of Bias in Word Embeddings1:43:21
21.Speech synthesis from neural decoding of spoken sentences | AISC1:41:10
22.Ernie 2.0: A Continual Pre-Training Framework for Language Understanding | AISC1:40:01
23.ACT: Adaptive Computation Time for Recurrent Neural Networks | AISC1:39:42
24.Principles of Riemannian Geometry in Neural Networks | TDLS1:38:03
25.CNN Architectures for Large-Scale Audio Classification | AISC1:37:00
26.Deep InfoMax: Learning deep representations by mutual information estimation and maximization | AISC1:36:53Guide
27.Making of a conversational agent platform | AISC1:35:46
28.Transformer XL | AISC Trending Papers1:35:02
29.Explainable Neural Networks based on Additive Index Models | TDLS1:34:47
30.Towards Interpretable Deep Neural Networks by Leveraging Adversarial Examples | AISC1:33:19
31.Computational prediction of diagnosis & feature selection on mesothelioma patient records | AISC1:33:18
32.The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words & Sentences From Natural Supervision1:32:28
33.Detecting and Correcting Unfairness in Machine Learning | AISC1:32:22
34.The Importance of Strategy in AI Product Management | AISC1:32:20
35.AISC Abstract Night June 20 20191:31:06
36.[GQN] Neural Scene Representation and Rendering | AISC1:30:57
37.Building products for Continous Delivery in Machine Learning | AISC1:30:12
38.Location Intelligence Products: Goals and Challenges | AISC1:30:01
39.[OpenAI GPT2] Language Models are Unsupervised Multitask Learners | TDLS Trending Paper1:29:32
40.Restricted Boltzmann Machines for Collaborative Filtering | AISC1:29:28
41.[Original attention] Neural Machine Translation by Jointly Learning to Align and Translate | AISC1:28:14
42.[LISA] Linguistically-Informed Self-Attention for Semantic Role Labeling | AISC1:28:00
43.[OpenAI] Solving Rubik's Cube with a Robot Hand | AISC1:27:59
44.[DDQN] Deep Reinforcement Learning with Double Q-learning | TDLS Foundational1:27:42
45.Sparse Transformers and MuseNet | AISC1:27:01
46.Deep Temporal Logistic Bag-of-Features For Forecasting High Frequency Limit Order Book Time Series1:26:26
47.[Original ResNet paper] Deep Residual Learning for Image Recognition | AISC1:26:19
48.Deep Neural Networks for YouTube Recommendation | AISC Foundational1:26:17
49.Identifying Big ML product opportunities inside Big organizations | AISC1:25:11
50.Deep Q-Learning paper explained: Human-level control through deep reinforcement learning (algorithm)1:24:30
51.Model Selection for Optimal Prediction in Statistical Learning - Part 2 / 2 | AISC1:24:26
52.[RecSys Challenge 2019 2nd Place] Robust Contextual Models for In-Session Personalization | AISC1:24:19
53.Reconstructing quantum states with generative models | TDLS Author Speaking1:24:17
54.Eve: A Gradient Based Optimization Method with Locally and Globally Adaptive Learning Rates | TDLS1:24:13
55.Junction Tree Variational Autoencoder for Molecular Graph Generation | TDLS1:23:23
56.Unsupervised Data Augmentation | AISC1:22:57
57.[ELMo] Deep Contextualized Word Representations | AISC1:22:15
58.Operationalizing AI in Business at Scale | AISC1:22:02
59.Content Tree Word Embedding for document representation | AISC1:21:24
60.Swim Stroke Analytic: Front Crawl Pulling Pose Classification | AISC1:21:10
61.ACAI: Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer1:20:31
62.Steve Brunton: Machine Learning for Fluid Dynamics1:20:15
63.[Variational Autoencoder] Auto-Encoding Variational Bayes | AISC Foundational1:19:50
64.Defending Against Fake Neural News | AISC1:19:36
65.Bayesian Deep Learning on a Quantum Computer | TDLS Author Speaking1:19:30
66.Flexible Neural Representation for Physics Prediction | AISC Trending Paper1:18:42
67.[StackGAN++] Realistic Image Synthesis with Stacked Generative Adversarial Networks | AISC1:17:55
68.An Introduction to Quantum Computing1:17:43
69.[AlphaGo Zero] Mastering the game of Go without human knowledge | TDLS1:17:39Let's Play
70.Model Selection for Optimal Prediction in Statistical Learning (Part 1: 7 Wheels of Stat Learning)1:17:27
71.Learning Discrete Structures for Graph Neural Networks | AISC1:15:54
72.Learning to Represent Programs with Graphs | TDLS1:15:49
73.[GAT] Graph Attention Networks | AISC Foundational1:15:38
74.You May Not Need Attention | TDLS Code Review1:14:49Review
75.[Original Style Transfer] A Neural Algorithm of Artistic Style | TDLS Foundational1:14:40
76.DeepStack: Expert-Level Artificial Intelligence in Heads-Up No-Limit Poker | AISC1:13:41
77.Science of science: Identifying Fundamental Drivers of Science | AISC1:13:15
78.A Hybrid GA-PSO Method for Evolving Architecture and Short Connections of Deep Convolutional Neural1:12:57
79.Comparative Document Summarisation via Classification | AISC1:12:41
80.Generating High Fidelity Images with Subscale Pixel Networks and Multidimensional Upscaling1:12:21
81.Program Language Translation Using a Grammar-Driven Tree-to-Tree Model | TDLS1:12:21
82.Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning |1:12:13
83.Deep learning enables rapid identification of potent DDR1 kinase inhibitors | AISC1:11:55
84.Compact Neural Representation Using Attentive Network Pruning | AISC1:11:37
85.Predicting compound activity from phenotypic profiles1:11:16
86.Support Vector Machine (original paper) | AISC Foundational1:10:53
87.Annotating Object Instances With a Polygon RNN | AISC1:10:50
88.Predicting translational progress in biomedical research | AISC1:10:37
89.Inverse design of nanoporous crystalline reticular materials with deep generative models | AISC1:10:37
90.Overview of Machine Learning in Marketing | AISC1:09:11
91.Automated Vulnerability Detection in Source Code Using Deep Learning (algorithm) | AISC1:08:46
92.The People, Politics, & Histories Behind Machine Learning Datasets | AISC1:08:36
93.Machine Learning in Mobile Cybersecurity: An Overview1:08:30
94.[WeightWatcher] Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory1:08:16
95.NRCan Workshops Session #21:08:09
96.Video Action Transformer Network | AISC1:08:07
97.TMLS2018 - Machine Learning in Production, Panel Discussion1:07:06Discussion
98.A Web-scale system for scientific knowledge exploration | AISC1:06:38
99.The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies1:06:37
100.Benchmarking and Survey of Explanation Methods for Black Box Models | AISC1:06:27