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Machine Learning (ML): Techniques enabling computers to learn from data, making predictions or decisions, useful for customer segmentation and sales forecasting.
Natural Language Processing (NLP): Technologies that allow computers to understand and interact using human language, crucial for customer service automation and sentiment analysis.
Artificial Neural Networks (ANNs): Systems inspired by the human brain, used to recognize patterns and solve complex problems, beneficial for processing customer feedback and behavior.
Deep Learning: A subset of machine learning with multi-layered neural networks, driving advancements in voice and image recognition technologies, enhancing personalized customer experiences.
Generative AI (GenAI): A subset of AI technology that focuses on creating content or generating data autonomously. Unlike traditional AI systems that rely on predefined rules or patterns, GenAI utilizes advanced algorithms, often based on deep learning techniques, to produce new and original content, such as images, text, video and more.
Human-in-the-Loop (HITL): Human input that guides or validates machine processes, improving accuracy and adaptability.
Predictive Analytics: Utilizing historical data to forecast future trends, aiding demand forecasting and risk management.
Robotic Process Automation (RPA): Automating repetitive tasks with software robots, streamlining operations like billing and data entry.
Data Science: The study of extracting meaningful insights from data, supporting data-driven decisions for market trends and operational optimization.
Hallucination: When AI models generate incorrect or nonsensical outputs. It is crucial to recognize this for businesses using AI for content creation or data analysis.
ChatGPT: An AI model trained by OpenAI for generating human-like text. It’s useful for automating customer service, creating content, and answering queries, helping businesses save time and improve customer engagement.
Custom GPT: A variation of GPT (Generative Pre-trained Transformer) models that can be customized for specific industries or applications. Small businesses can use CustomGPT to tailor chatbots, content generation, or data analysis tools specifically to their needs, enhancing relevance and efficiency.
Diffusion Models: A type of generative model that starts with a random pattern of noise and gradually refines it into an image, text, or another output based on the training data. This process is useful for creating unique content, such as marketing materials or product designs, by guiding the model toward desired outcomes.
Midjourney: An independent research lab’s generative AI tool, often used for creating highly detailed and imaginative visual content. Small businesses can leverage Midjourney for branding, product visualization, and marketing campaigns to captivate audiences with novel imagery.
DALL-E: An AI program by OpenAI known for generating images from textual descriptions. It’s particularly beneficial for businesses needing custom graphics, advertising visuals, or social media content, offering a fast and cost-effective way to produce high-quality, creative imagery.
LLM: Large Language Models (LLMs) are advanced AI systems capable of understanding, generating, and interacting with human language at a vast scale. They are trained on extensive text datasets, enabling them to perform various language-based tasks, such as writing, translating, summarizing, and answering questions. LLMs leverage deep learning techniques to process and produce text in a way that can mimic human writing styles and comprehend complex language nuances, making them valuable for applications in content creation, customer service, and beyond.
API: Application Programming Interface (API) is a set of rules, protocols, and tools for building software and applications. An API specifies how software components should interact, allowing different programs to communicate with each other. It enables developers to use certain technologies or services without building them from scratch, facilitating integration and enabling functionality between different software products or services.
On its own, AI is a pretty terrible writer. It’s overly effusive, reliant on flowery adverbs, mixes metaphors (oh how it loves metaphors) and wouldn’t understand pacing if its participle were dangling in front of it. As more and more people are just pasting straight out of ChatGPT or Gemini, we’re being subjected to awful emails, marketing blurbs, blogs and social posts.