By Jenny Kay Pollock, Cofounder of Women And AI
Artificial Intelligence has become an integral part of our daily lives, revolutionizing industries and reshaping the way we interact with technology. As we continue to make AI a bigger part of our world, it's essential to understand the fundamentals and various types of AI that are driving innovation.
Often times generative AI (Chat GPT, Claude, Perplexity etc.) is thought of as the entirety of AI. In reality it's a small subset of the field of AI that is powered by Large Language models. You can see the relationship between different pieces of the AI landscape in the circles below.
Let's explore each of these terms in detail:
Artificial Intelligence (AI)
Artificial Intelligence refers to the development of computer systems capable of performing tasks that typically require human intelligence. Including learning, reasoning, problem-solving, perception, and language understanding. AI systems are designed to analyze vast amounts of data, identify patterns, and make decisions or predictions based on that information.
Types of AI
Machine Learning (ML)
Machine learning is a subset of AI that focuses on training algorithms to learn from data and improve their performance over time. This approach allows AI systems to adapt and make predictions or decisions without being explicitly programmed. Machine learning has numerous applications, from recommendation systems on streaming platforms to fraud detection in financial services.
AI disclosure: this image was created with Napkin AI.
Natural Language Processing (NLP)
Natural Language Processing enables machines to understand, interpret, and generate human language. This technology powers virtual assistants like Siri and Alexa, as well as language translation services. NLP has made significant advances in recent years, allowing for more natural and context-aware interactions between humans and machines.
AI disclosure: this image was created with Napkin AI.
Deep Learning
Deep learning is a subset of machine learning that uses artificial neural networks with multiple layers to process and learn from large amounts of data. This approach has led to significant breakthroughs in areas such as image and speech recognition, natural language processing, and autonomous systems. Deep learning models can identify complex patterns and make highly accurate predictions, often surpassing human-level performance in specific tasks.
AI disclosure: this image was created with Napkin AI.
Generative AI
Generative AI is an advanced artificial intelligence technology capable of creating original content across various formats, including text, images, audio, and synthetic data. Unlike traditional AI systems, generative AI can autonomously produce new and unique outputs based on user prompts.
AI disclosure: this image was created with Napkin AI.
Large Language Models (LLMs)
Large Language Models are sophisticated AI systems trained on massive amounts of text data to understand and generate human-like text. These models, such as GPT, can perform complex language tasks like writing, code generation, and content creation. LLMs represent a breakthrough in AI, enabling more natural and contextually aware interactions.
AI disclosure: this image was created with Napkin AI.
The future of AI is bright, and having a strong foundation of the pieces of the AI landscape will take you far.
By leveraging this knowledge of the different pieces of the AI landscape, we can further contribute to the development of innovative AI solutions.
I appreciate your acknowledgement of what everything thinks AI is. And showing how it's possible to understand this tremendous new sub-field of computer science even if you're not a techie. You covered it so clearly. 🤩
I loved this post. It explains the different types of AI in such a clear and engaging way. The examples made everything easy to understand, and I feel like I learned a lot. It’s clear that a lot of effort went into breaking down a complex topic. Great job!