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Artificial Intelligence (AI)
Information processing systems can be analogous to human decision-making and problem-solving abilities.
Generative AI
Algorithms that can create high-quality text, image, audio and synthetic data content
Key tool: Deep learning
Deep learning with neural networks enables programs to recognize patterns, weigh options, and reach conclusions
Common Models
Generative adversarial networks (GANs)
Diffusion Models
Variational autoencoders (VAEs)
Large language models (LLMs)
Traditional AI
Analyze historical data to make future value predictions and decisions
Key tool: Machine learning
Use statistical algorithms to "process data", "make predictions", and "optimize over multiple iterations"
(Supervision) Common Models
- Support Vector Machine
- Decision Tree
- Random Forest
- Logical regression
- Simple Neural Network
( Non-supervisory ) Common Models
- Data Clustering
- Data Correlation
- Dimensionality reduction
- Simple Neural Network
Modality and Use Cases
Voice User Interface
Voice is a natural and intuitive interface for conversation.
Large Multimodal Models
Utilize more perceptual input modalities to better understand the world.
Video and 3D
Generate content to provide richer and more realistic experiences.
Capabilities and Key Performance Indicators (KPI)
Longer Context Window
Allows for deeper conversations.
Personalization
Customized fine-tuning models for consumers, businesses, or industries (e.g., LoRA).
Higher Resolution
Process higher fidelity images to improve accuracy.
Intelligent Agents
Autonomously execute multi-step tasks and reason to achieve goals.
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