(AI) Artificial Intelligence Terms Every Beginner Should Know
Published on: March 01, 2024
Last updated: May 02, 2024 Read in fullscreen view
Last updated: May 02, 2024 Read in fullscreen view
Recommended for you
- 06 Mar 2026
Next-Generation AI Agents Explained: OpenClaw, NanoClaw, IronClaw and the Rise of Agent Architectures 397/458 - 02 Dec 2025 The Question That Shook Asia: What Happens When We Ask AI to Choose Between a Mother and a Wife? 209/288
- 29 Oct 2024 Top AI Tools and Frameworks You’ll Master in an Artificial Intelligence Course 204/624
- 05 Jun 2025 How AI-Driven Computer Vision Is Changing the Face of Retail Analytics 196/338
- 09 Jul 2024 What Is Artificial Intelligence and How Is It Used Today? 187/493
- 18 Oct 2020 How to use the "Knowns" and "Unknowns" technique to manage assumptions 182/1303
- 16 Oct 2025 AI Inference Explained Simply: What Developers Really Need to Know 181/224
- 23 Dec 2024 Garbage In, Megabytes Out (GIMO): How to Rise Above AI Slop and Create Real Signal 178/255
- 06 Dec 2025 Enterprise Operations 2.0: Why AI Agents Are Replacing Traditional Automation 176/227
- 23 Sep 2021 INFOGRAPHIC: Top 9 Software Outsourcing Mistakes 161/595
- 25 Nov 2025 How AI Agents Are Redefining Enterprise Automation and Decision-Making 151/215
- 25 Dec 2025 What Is Algorithmic Fairness? Who Determines the Value of Content: Humans or Algorithms? 150/208
- 18 Aug 2022 What are the consequences of poor requirements with software development projects? 137/413
- 01 Oct 2020 Fail fast, learn faster with Agile methodology 133/1227
- 11 Jan 2024 What are the Benefits and Limitations of Augmented Intelligence? 130/627
- 15 Apr 2024 Weights & Biases: The AI Developer Platform 130/324
- 17 Oct 2025 MLOps vs AIOps: What’s the Difference and Why It Matters 130/258
- 13 Dec 2020 Move fast, fail fast, fail-safe 127/495
- 06 Feb 2021 Why fail fast and learn fast? 124/614
- 14 Oct 2021 Advantages and Disadvantages of Time and Material Contract (T&M) 122/1052
- 01 Jul 2025 The Hidden Costs of Not Adopting AI Agents: Risk of Falling Behind 122/278
- 21 Aug 2024 What is Singularity and Its Impact on Businesses? 120/591
- 10 Nov 2025 Multi-Modal AI Agents: Merging Voice, Text, and Vision for Better CX 120/242
- 12 Jan 2026 Companies Developing Custom AI Models for Brand Creative: Market Landscape and Use Cases 116/164
- 21 Nov 2025 The Rise of AgentOps: How Enterprises Are Managing and Scaling AI Agents 113/180
- 27 Aug 2025 How AI Consulting Is Driving Smarter Diagnostics and Hospital Operations 112/219
- 14 Mar 2024 Why should you opt for software localization from a professional agency? 111/258
- 28 Dec 2021 8 types of pricing models in software development outsourcing 111/551
- 15 May 2025 AI Consulting for Small Businesses: How to Leverage AI for Growth & Efficiency 109/304
- 12 May 2024 The Pros and Cons of the Creator Economy in the Age of AI: Opportunities, Challenges, and the Gray Zone with the Gig Economy 108/397
- 24 Dec 2024 Artificial Intelligence and Cybersecurity: Building Trust in EFL Tutoring 108/282
- 17 Feb 2022 Prioritizing Software Requirements with Kano Analysis 107/425
- 19 Oct 2021 Is gold plating good or bad in project management? 107/952
- 07 Nov 2025 Online vs. Offline Machine Learning Courses in South Africa: Which One Should You Pick? 107/188
- 28 Nov 2025 How AI Will Transform Vendor Onboarding and Seller Management in 2026 104/241
- 24 Oct 2025 AI Agents in SaaS Platforms: Automating User Support and Onboarding 102/179
- 06 May 2025 How Machine Learning Is Transforming Data Analytics Workflows 100/317
- 22 Sep 2025 Why AI Is Critical for Accelerating Drug Discovery in Pharma 97/221
- 08 Oct 2022 KPI - The New Leadership 96/709
- 10 Nov 2022 Poor Code Indicators and How to Improve Your Code? 94/320
- 10 Dec 2023 Pain points of User Acceptance Testing (UAT) 92/560
- 04 Oct 2023 The Future of Work: Harnessing AI Solutions for Business Growth 88/375
- 01 Mar 2023 Bug Prioritization - What are the 5 levels of priority? 88/327
- 12 Mar 2024 How do you create FOMO in software prospects? 88/275
- 21 Apr 2025 Agent AI in Multimodal Interaction: Transforming Human-Computer Engagement 87/296
- 19 Apr 2021 7 Most Common Time-Wasters For Software Development 80/635
- 23 May 2024 Mastering AI: Sharpening the Axe in the Digital Age 79/370
- 05 Aug 2024 Affordable Tech: How Chatbots Enhance Value in Healthcare Software 75/325
- 31 Oct 2021 Tips to Fail Fast With Outsourcing 75/479
- 08 Jan 2024 Ask Experts: Explicitation/Implicitation and Elicitation; two commonly used but barely unraveled concepts 74/473
- 05 Jan 2024 Easy ASANA tips & tricks for you and your team 72/278
- 29 Aug 2025 How AI Is Transforming Modern Management Science 69/150
- 26 Dec 2023 Improving Meeting Effectiveness Through the Six Thinking Hats 63/348
- 06 Nov 2019 How to Access Software Project Size? 58/328
- 24 Mar 2026 AI for Financial Reconciliation: Automating Finance Operations in 2026 21/240
- 11 Aug 2026 Top Enterprise AI Custom Model Development Providers in the USA 19/61
- 06 Nov 2025 Top AI Development Companies in the USA to Watch in 2026 19/398
- 01 Sep 2026 How to Add AI Features to Existing Software Products 1/6
- 24 Aug 2026 AI Agent Development Services: A Complete Guide for Enterprises /12
Artificial intelligence (AI)
Artificial intelligence, or AI, is technology that enables computers and machines to simulate human intelligence and problem-solving capabilities.
Intelligence Amplification (IA)
Intelligence Amplification is the use of technology to support and amplify human intelligence. Virtual assistants, chatbots, and communications platforms all already use IA in some form.
Weak AI
Also called narrow AI, this is a model that has a set range of skills and focuses on one particular set of tasks. Most AI currently in use is weak AI, unable to learn or perform tasks outside of its specialist skill set.
AI agent
AI agents are entities designed to perceive their environment and take actions in order to achieve specific goals. These agents can be software-based or physical entities and are often built using artificial intelligence techniques. They perceive their environment through sensors, process the information using algorithms or models, and then take actions using actuators or other means.
AI Detector
A detection tool will flag AI-generated content in your text.
AI Humanize
AI rewriting tool to rewrite that sound genuine.
Cognitive computing
Cognitive computing is a subset of AI, focused on mimicking human-like cognition and natural learning versus programmed intelligence.
They may utilise some of the same technologies, but the difference lies in their respective applications and aims. In short, the purpose of AI is to think on its own and make decisions independently, whereas the purpose of Cognitive Computing is to simulate and assist human thinking and decision-making.
Corpus
A "corpus" is a data set used to train an AI system, varying based on the system's intended use, aiding in its domain-specific intelligence development.
Data corpus
A data corpus is a collection of genuine audio or text that is spoken or written by a native speaker. A corpus can be generated from numerous sources including social networks, like Facebook and WhatsApp, Google and Apple app stores, Amazon marketplaces, tweets, movies, television shows, newspapers, etc. This data is extremely useful in the natural language processing domain to model artificial intelligence and machine learning models. To support a specific problem in an identified domain, it is a must to have a bunch of data that represents the given domain, and the problem to be achieved with ML and NLP.
Machine learning
This subset of AI is particularly focused on developing algorithms that will help machines to learn and change in response to new data, without the help of a human being.
TensorFlow
TensorFlow is a free, end-to-end and open-source platform (a type of software library) for machine learning and artificial intelligence. It was created by Google and continues to own and maintain the framework.
Generative AI
Generative AI is a category of artificial intelligence that can create new text, images, video, audio, or code.
Generative AI can create customized learning materials, cater to individual learning styles, and provide real-time feedback. OpenAI's focus on fairness would ensure that such AI-powered learning tools are free from bias and promote equal educational opportunities.
Search Generative Experience (SGE)
Browse web pages with generative AI-powered tools. With Search Generative Experience (SGE) while browsing, user can:
- Quickly find the web page’s key points.
- Find questions answered on the web page and jump to the relevant section to learn more.
Explainable AI (XAI)
Explainable artificial intelligence (XAI) aims to explain what has been done, what is being done, and what will be done next, and to unveil which information these actions are based on. This makes it possible to confirm existing knowledge, challenge existing knowledge, and generate new assumptions. XAI often overlapping with Interpretable AI, or Explainable Machine Learning, either refers to an AI system over which it is possible for humans to retain intellectual oversight, or to the methods to achieve this.
Google-fu
Skill in using search engines (especially Google) to quickly find useful information on the Internet.
GPT
GPT (Generative Pre-trained Transformer) is a multimodal large language model created by OpenAI, and the fourth in its series of GPT foundation models. GPT-4 is more creative and collaborative than the previous versions. It can generate, edit, and iterate with users on creative and technical writing.
Large Language Models (LLM)
Large language models (LLM) are very large deep learning models that are pre-trained on vast amounts of data that can perform a variety of natural language processing (NLP) tasks.
GPT models are known for their proficiency in text generation, text completion, and a multitude of language-related tasks. In contrast, LLMs cover a range of architectures, including Transformers, RNNs, and CNNs, designed for scalability and adaptability.
Prompt
A prompt is an input that a user feeds to an AI system in order to get a desired result or output.
Prompt Engineering
Prompt engineering is the practice of designing, writing, refining and optimizing inputs for AI tools that will produce optimal and specific, high-quality outputs.
AI infusion
Infusing AI is about being able to apply AI across your enterprise, drawing on predictions, automation, and optimization to improve your business decisions/
Data Annotation
The process of labeling data to show the outcome you want your machine learning model to predict. You are marking - labeling, tagging, transcribing, or processing - a dataset with the features you want your machine learning system to learn to recognize.
Semantic annotation
Tagging different search queries or products with the goal of improving the relevance of a search engine.
Sentiment analysis
The process of identifying and categorizing opinions in a piece of text, often with the goal of determining the writer’s attitude towards something.
Predictive analytics
By combining data mining and machine learning, this type of analytics is built to forecast what will happen within a given timeframe based on historical data and trends.
Reinforcement learning (RL)
RL is a machine learning (ML) technique that trains software to make decisions to achieve the most optimal results. It mimics the trial-and-error learning process that humans use to achieve their goals.
Supervised machine learning
Supervised learning, also known as supervised machine learning, is a subcategory of machine learning and artificial intelligence. It uses labeled datasets to learn the relationship between input and output, then predict outcomes and recognize patterns.
Unsupervised machine learning
Unsupervised learning in artificial intelligence is a type of machine learning that learns from data without human supervision.
The biggest difference between supervised and unsupervised machine learning is the type of data used. Supervised learning uses labeled training data, and unsupervised learning does not. More simply, supervised learning models have a baseline understanding of what the correct output values should be.
AI ethics
AI ethics are the set of guiding principles that stakeholders (from engineers to government officials) use to ensure artificial intelligence technology is developed and used responsibly.
Guardrails
Guardrails refers to restrictions and rules placed on AI systems to make sure that they handle data appropriately and don't generate unethical content.
Predictive analytics
Predictive analytics is a type of analytics that uses technology to predict what will happen in a specific time frame based on historical data and patterns.
Prescriptive analytics
Prescriptive analytics is a type of analytics that uses technology to analyze data for factors such as possible situations and scenarios, past and present performance, and other resources to help organizations make better strategic decisions.
[{"displaySettingInfo":"[{\"isFullLayout\":false,\"layoutWidthRatio\":\"\",\"showBlogMetadata\":true,\"includeSuggestedAndRelatedBlogs\":true,\"enableLazyLoad\":true,\"quoteStyle\":\"1\",\"bigHeadingFontStyle\":\"1\",\"postPictureFrameStyle\":\"1\",\"isFaqLayout\":false,\"isIncludedCaption\":false,\"faqLayoutTheme\":\"1\",\"isSliderLayout\":false}]"},{"articleSourceInfo":"[{\"sourceName\":\"\",\"sourceValue\":\"\"}]"},{"privacyInfo":"[{\"isOutsideVietnam\":false}]"},{"tocInfo":"[{\"isEnabledTOC\":true,\"isAutoNumbering\":true,\"isShowKeyHeadingWithIcon\":false}]"}]
Via
{content}
Explore more on these topics
![Top 10 Vietnam IT Outsourcing Vendors [MOST UPDATED] - TIGO CONSULTING](/Uploads/Vietnam12012023111455_thumb.jpg "Best IT Outsourcing Companies in Vietnam with Reviews 2023")
Guest Blogging: The Definitive Guide
Top Trending Topics
Share This
Link copied!
Recently Updated News
thực chiến - Kiến tạo tương lai cho các nhà sáng tạo nội dung.