Edan Meyer Courses

Steps to AGI

1 rating

Explore DeepMind Alberta's plan for achieving AGI through reinforcement learning, continual learning, and meta-learning in complex environments, with a focus on key steps and core concepts.

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

GPT-4 - What, Why, How?

Explore GPT-4's advancements, capabilities, and potential impacts. Learn about its features, evaluations, multilingual support, and image processing, with demos and insights on access and applications.

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

Sparks of AGI - What to Know

Explore GPT-4's capabilities and limitations in this analysis of Microsoft's "Sparks of AGI" paper, discussing experiments, tool usage, and the potential for artificial general intelligence.

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

This Embodied LLM is...

Explore Google's PaLM-E, an embodied multimodal LLM showing positive transfer across robotics tasks. Learn its workings, applications, results, and implications for AI advancement.

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

Learning From Passive Data Explained

Explore reinforcement learning algorithm using passive data to learn without direct interaction, based on successor features. Covers offline RL, algorithm details, results, and critical analysis.

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

Agent Learns to Do Reinforcement Learning

Explore DeepMind's innovative approach to Reinforcement Learning using behavior cloning and Transformers, discussing its potential impact on AI learning algorithms and efficiency.

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

Stable Diffusion - What, Why, How?

Explore Stable Diffusion's text-to-image generation, compare it to DALL-E 2, and learn advanced techniques like custom pipelines, video creation, and image-to-image transformation.

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

This AI Learns from YouTube

Explore OpenAI's innovative approach to training AI agents using YouTube videos, focusing on Minecraft gameplay and combining imitation learning with reinforcement learning techniques.

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

Chinchilla Explained - Compute-Optimal Massive Language Models

Explore DeepMind's Chinchilla, a compute-optimal language model outperforming larger models with fewer parameters. Learn about its development, performance, and implications for AI scaling.

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

Learning Forever, Backprop Is Insufficient

Explores continual learning in machine learning, discussing plasticity decay and proposing Continual Backpropagation as a solution to overcome limitations of traditional backpropagation in non-stationary environments.

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

Learning Fast with No Goals - VISR Explained

Explore rapid generalization in Reinforcement Learning with VISR, focusing on successor features and goal-conditioned policies for efficient task adaptation without rewards.

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

AlphaCode Explained - AI Code Generation

Explore DeepMind's AlphaCode, a powerful AI model for code generation. Learn its workings, competitive programming applications, and key insights from recent research.

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

Reinforcement Learning in RTS Games

Explore reinforcement learning in RTS games, examining recent breakthroughs and key factors driving success in AI models like OpenAI Five and AlphaStar.

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

Can OpenAI Codex Compete in an ML Competition?

Explore OpenAI Codex's capabilities in ML competitions, examining its LSTM approach for a Kaggle challenge and assessing its performance against human competitors.

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

A New Theory for How the Brain Learns

Explore a novel theory on brain learning, focusing on neuronal burst firing for feedback signaling and solving the credit assignment problem in hierarchical circuits.

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