Google’s 4-Hour AI Course for Beginners - Distilled into 10 Minutes
Introduction to AI and Its Subfields
- Artificial Intelligence (AI): Entire field of study, like physics.
- Machine Learning (ML): Subfield of AI, analogous to thermodynamics in physics.
- Deep Learning (DL): Subset of ML.
- Discriminative Models: Subset of DL focusing on classification.
- Generative Models: Subset of DL focusing on generating new data.
- Large Language Models (LLMs): Subset of DL, intersection of Generative Models and DL (e.g., ChatGPT, Google Bard).
Machine Learning (ML)
- Definition: Programs that use input data to train models that make predictions on unseen data.
- Types of ML Models:
- Supervised Learning: Uses labeled data (e.g., predicting tips based on the bill amount and delivery status).
- Unsupervised Learning: Uses unlabeled data (e.g., grouping employees by tenure and income).
- Pro Tip: After making a prediction, supervised models compare it to training data and try to close any gap. Unsupervised models do not.
Deep Learning (DL)
- Definition: Type of ML using artificial neural networks.
- Artificial Neural Networks: Inspired by the human brain, composed of layers of nodes/neurons.
- Semi-Supervised Learning: Uses small labeled and large unlabeled dataset (e.g., fraud detection in banking).
Discriminative vs. Generative Models
- Discriminative Models: Classify data points based on learned relationships (e.g., distinguishing between cats and dogs).
- Generative Models: Learn patterns and generate new data (e.g., creating a new dog image based on learned patterns).
- Simple Determination: If the output is a number, classification, or probability—it’s not generative AI. Generative AI generates text, speech, images, or audio.
Types of Generative AI Models
- Text-to-Text Models: e.g., ChatGPT, Google Bard.
- Text-to-Image Models: e.g., MidJourney, DALL-E, Stable Diffusion.
- Text-to-Video Models: e.g., Imagen Video, Cog Video.
- Text-to-3D Models: Used for creating game assets (e.g., OpenAI’s Shape-E).
- Text-to-Task Models: Perform specific tasks (e.g., summarizing unread emails in Gmail).
Large Language Models (LLMs)
- Definition: Subset of DL, generally pre-trained with large datasets and fine-tuned for specific purposes.
- Training Example: Pre-trained dog vs. fine-tuned guide/police dog.
- Real-World Scenario: Hospitals fine-tuning pre-trained LLMs with medical data for diagnostic purposes.
- Business Model: Big tech companies develop general LLMs and sell to smaller institutions for domain-specific fine-tuning.
Course Details
- Modules: Five total, badges awarded for each.
- Pro Tip: Right-click video player to copy video URL at the current time for easy navigation.
- Recommendation: Follow-up with a video on mastering prompting.
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