The Workplace Glossary: Guide to Modern Technology Talk

Posted on Thursday 8 June 2023.

AI terms

We’re back with the second edition of our blog series, The Workplace Glossary.” In this blog, we’re bringing you a list of popular phrases and concepts to help you understand the new branches of AI. Whether you’re a tech guru or a curious novice, we’ve got you covered with some popular AI terms you need to know to stay on top of the ever-evolving tech landscape. Get ready to level up your tech game!

From Analytical AI, Artificial General Intelligence (AGI), and Generative AI, to Conversational AI there are many distinct branches or aspects of artificial intelligence, each with its own focus and objectives.

Let’s break down their meanings and differences!

AI infographic

Analytical AI – It’s also known as Analytic Artificial Intelligence and refers to a branch of artificial intelligence that focuses on using algorithms and techniques to analyse complex data sets and extract meaningful insights. It includes tasks like data mining, machine learning, and statistical analysis to understand the data and draw conclusions.

Artificial general intelligence (AGI) – AGI aims to mimic human cognitive abilities, including reasoning, learning, problem-solving, and application of knowledge to various fields. Essentially, it refers to a hypothetical intelligent agent who can understand or learn any intellectual task that humans are capable of.

AIOps (Artificial Intelligence for IT Operations) – AIOps refers to the use of AI and machine learning algorithms to automate and optimise IT operations processes, including incident management, event correlation, and problem resolution.

AI-as-a-Service (AIaaS) – Refers to a cloud-based model that allows businesses to harness the power of AI without investing in extensive infrastructure. These platforms offer a range of services like machine learning, and natural language processing, that can enhance app functionality.

Auto-GPT – It’s an open-source Python application that uses GPT-4 as its basis and allows the AI to act “autonomously” without the need for the user to prompt every action.

Automated Machine Learning (AutoML) – AutoML is designed to automate the selection, tuning, and optimization of machine learning models for specific datasets, thereby reducing the amount of time required for model training. Its applications are diverse and can be found in sectors such as healthcare, finance, and retail, where it streamlines processes and enhances efficiency.

Bard Chatbot – It’s an AI-enabled chatbot that uses Google’s own model, called LaMDA, and it tends to provide concise responses that are not too text-heavy.

Bias – Refers to error that can occur in a larger language model when its output is influenced by the training data that it has been exposed to.

Bing Chatbots – It’s an AI-enabled chatbot that uses the same GPT-4 tech as ChatGPT, it can do more than just generate text, as it can produce images as well.

ChatGPT – It’s a conversational AI language model developed by OpenAI. It can generate human-like text based on input from a user and can be used in a variety of applications, such as customer service, content generation, and language translation.

Conversational AI – Refers to the branch of artificial intelligence that deals with creating intelligent systems capable of engaging in natural and interactive conversations with humans. It combines natural language processing (NLP) with machine learning. It includes technologies such as chatbots, virtual assistants, voice interfaces, and customer support systems.

Ethical AI – Ethical AI solutions will be introduced to address user concerns and build trust. These solutions will prioritise transparency, providing explanations for system decisions and reinforcing cybersecurity measures. Additionally, Ethical AI will combat bias in automated decision-making systems, promoting fairness and eliminating discrimination.

Generative AI – Refers to a field of artificial intelligence focused on creating original content that resembles human creations. Generative AI is an exciting field of AI that allows machines to create original content based on existing data. It’s expanding the limits of what can be achieved in generating images, videos, texts, sounds, and computer codes. There are many examples, including ChatGPT for text and DALL-E and Midjourney for images.

Generative Pre-trained Transformer (GPT) – It’s an advanced deep learning model that has been trained on a vast dataset to create text that resembles human writing.

Hybrid AI – Hybrid AI refers to the utilization of multiple AI methodologies in artificial intelligence technology.

Intelligent Automation – Intelligent automation refers to the integration of artificial intelligence and machine learning algorithms into automation processes to enhance their accuracy, efficiency, and ability to adapt and learn over time.

Natural language processing (NLP) – It’s a branch of AI that focuses on enabling computers to understand, interpret, and generate human language.

So, in the broad scope of artificial intelligence, each area has unique objectives and applications. Analytical AI deals with data analysis and decision-making, AGI aims to replicate human-level intelligence, Generative AI is designed to create new content, and Conversational AI aims to facilitate seamless communication between humans and machines using natural language.

And with the emergence of new technologies and the continued evolution of AI, the field of AI will expand, introducing many new terminologies, acronyms, and phrases that we will become familiar with.

Antonija Bozickovic

Antonija Bozickovic

Content Creator at SDI



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