#055 Special Feature - How to Speak AI: Learn the Lingo, Commonly Used Terms and Essential Concepts.
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AI BYTE # 1 📢 : How to Speak AI: Learn the Lingo, Commonly Used Terms and Essential Concepts
⭐ AI is everywhere, but do you know what it really means?
Artificial Intelligence is a technology that aims to mimic human thinking, but it can be hard to understand the terms and concepts behind it.
That’s why I’ve created this guide to help you learn the basics of AI, from Natural Language Processing to Neural Networks.
AI is not a single thing, but a collection of techniques that let computers learn from data and perform tasks that normally require human intelligence.
Here are some of the most important concepts you should know:
Machine Learning: a branch of AI that relies on techniques that let computers learn from the data they process. For example, you can train a machine learning system to recognize cats and dogs by showing it millions of pictures labeled as such.
Machine learning systems can find patterns in data, but they are not good at reasoning or planning.
Natural Language Processing: a form of machine learning that can interpret and respond to human language. It powers voice assistants like Siri and Alexa. Natural language processing systems can understand the meaning and context of words, but they may struggle with ambiguity or sarcasm.
Neural Networks: a technique in machine learning that mimics the way neurons act in the human brain. In the brain, neurons can send and receive signals that power thoughts and emotions.
In Artificial Intelligence, groups of artificial neurons, or nodes, similarly send and receive information to one another. Neural networks can learn from their mistakes and improve over time, but they are not exactly like the human brain.
Deep Learning: a form of AI that employs neural networks and learns continuously. The “deep” in deep learning refers to the multiple layers of artificial neurons in a network.
Deep learning algorithms are capable of more complex processing than neural networks, but they also require more data and computing power.
Large Language Models: are deep learning algorithms capable of summarizing, creating, predicting, translating and synthesizing text and other content because they are trained on huge amounts of data.
A common starting point for programmers and data scientists is to train these models on open-source, publicly available data sets from the internet.
Large language models can generate realistic and diverse outputs, but they may also produce inaccurate or harmful content.
Generative AI: is a type of artificial intelligence that can create various types of content including text, images, video and audio. Generative AI is the result of a person feeding information or instructions, called prompts, into a foundation model, which produces an output based on the prompt it was given.
Foundation models are a class of models trained on vast, diverse quantities of data that can be used to develop more specialized applications, such as chatbots, code writing assistants, and design tools.
Hallucination: when a foundation model produces responses that are not grounded in fact or reality, but are presented as such. Hallucinations are one of the primary shortcomings of generative AI, prompting many experts to push for human oversight of foundation models and their outputs.
Artificial General Intelligence: a hypothetical form of artificial intelligence in which a machine can learn and think like a human. Artificial general intelligence would need self-awareness and consciousness so it could solve problems, adapt to its surroundings and perform a broader range of tasks.
Some companies like Google DeepMind are working toward the development of some form of artificial general intelligence, but it is still far from being achieved.
I hope this guide has helped you understand some of the basics of AI and how it works.
AI is a fascinating and powerful technology that has many applications and implications for our future.
If you want to learn more about AI or share your thoughts on it, feel free to connect with me or leave a comment below. Thanks for reading!
