Hey guys, what is up? In today’s video, we’re going to show you the basic terms that all chat DVD users should know. Are you looking for a guide on all the basic terms that you should know if you use stat CPT? Stay tuned because this video is for you.
Alright, so Chad GBT, the AI chatbot from OpenAI, which has an uncanny ability to answer any question, was likely your first introduction to AI. From writing poems, resumes, and fusion recipes, the power of GPT has been compared to autocomplete on steroids. But AI chatbots are only one part of the AI landscape. How does GPT help you with your homework or create fascinating images or even completely reshape economies? Let’s dive into some important AI terms you should know.
The first term is Artificial General Intelligence or AGI. It suggests a more advanced version of AI than we know today, one that can perform tasks much better than humans while also teaching and advancing its own capabilities. AI safety is an interdisciplinary field concerned with the long-term impact of AI and how to prevent harm to humans. It involves determining how AI systems should collect data and deal with bias.
Algorithm is a series of instructions that allows a computer program to learn and analyze data in a particular way, such as recognizing patterns. AI chatbots use algorithms to learn from data and accomplish tasks on their own. Alignment refers to tweaking an AI to better produce a desired outcome, such as moderating content or maintaining positive interactions with humans.
When humans tend to give non-human objects human-like characteristics in AI, it is called anthropomorphism. This could include believing a chatbot is more human-like and aware than it actually is. Artificial Intelligence or AI is the use of technology to simulate human intelligence in computer programs or robotics.
Bias in AI refers to errors resulting from the training data, which can lead to falsely attributing certain characteristics to certain races or groups based on stereotypes. A chatbot is a program that communicates with humans through text and simulates human language. GPT is an AI chatbot developed by OpenAI that uses large language models.
Cognitive Computing is another term for artificial intelligence. Data augmentation is the process of remixing existing data or adding a more diverse set of data to train AI models. Deep learning is a method of AI that uses multiple parameters to recognize complex patterns in pictures, sound, and text. Diffusion is a method of machine learning that adds random noise to existing data.
Emergent behavior occurs when an AI model exhibits unintended abilities. End-to-end learning is a deep learning process in which a model is instructed to perform a task from start to finish. Ethical considerations involve being aware of the ethical implications of AI and issues related to privacy, data usage, fairness, and misuse.
Boom, also known as fast takeoff or hard takeoff, is the concept that if someone builds an AGI, it might already be too late to save humanity. Generator is a generative AI model that creates new content, while discriminator checks if it’s authentic. Generative AI is a technology that uses AI to create text, video, computer code, or images.
Google Bard is an AI chatbot by Google that functions similarly to GPT but pulls information from the current web. Guardrails are policies and restrictions placed on AI models to ensure responsible data handling and prevent the creation of disturbing content. Hallucination refers to incorrect responses from AI, which can include generative AI producing answers that are incorrect but stated with confidence.
Large Language Model or LLM is a model trained on massive amounts of text data to understand language and generate novel content. Machine learning is a component of AI that allows computers to learn and make better predictions without explicit programming. Microsoft Bing is a search engine that can now use AI technology powered by GPT to provide powerful search results.
Multi-model AI is a type of AI that can process multiple types of inputs, including text, images, videos, and speech. Natural Language Processing is a branch of AI that uses machine learning and deep learning to give computers the ability to understand human language. Neural network is a computational model that resembles the human brain structure and is used to recognize patterns in data.
Overfitting is an error in machine learning where the model closely follows the training data but may not perform well on new data. Parameters are numerical values that give LLM structure and behavior, enabling it to make predictions. Chaining is the ability of AI to use information from previous interactions to influence future responses.
Stochastic Parrot is an analogy of LLMs that illustrates that the software doesn’t have a larger understanding of the meaning behind languages or the world around it. Style transfer is the ability to adapt the style of one image to the content of another. Temperature parameters control how random the language model’s output is.
Text-image generation is the process of creating images based on textual descriptions. Training data is the data sets used to help AI models learn, including text, images, and code. Transformer is a neural network architecture and deep learning model that learns context by tracking relationships in data. That’s it for this video. Hope you liked it! Don’t forget to like, comment, share, subscribe, and ring that Bell icon. We’ll see you on the next one!
