AI is a popular topic now these days. Understand these 20 buzzwords, it will make you sound like an expert in AI while talking with your friends.
1. AI (Artificial Intelligence)
There are two types of AI, depending on its aim. Suppose the goal is to get the system working but not simulate human behavior. In that case, we are talking about “Weak AI.” Weak AI is used to perform a specific task. However, if the system aims to simulate human behavior and “think as humans think,” then it is called “Strong AI,” or artificial general intelligence.
2. NFT (Non-fungible token)
NFT probably isn’t exactly a term in the artificial intelligence sector, but it is a popular tech term now. And many people associate this term with AI because it’s so new and cool. By definition from Investopedia – “NFTs are unique cryptographic tokens that exist on a blockchain and cannot be replicated.” To make it simple, NFT is like a digital certificate to show your ownership of a specific digital item. It’s like a deed that shows your home ownership. NFT shows your ownership of things like a picture or a piece of music.
Metaverse is a 3D virtual world service offered by large tech companies like Facebook and Apple. Facebook even changed its corporate name from Facebook to Meta to promote the metaverse. All the most recent technologies were involved, such as AI, VR, AR, etc. And to experience the metaverse, it’s suggested to have a VR helmet like Oculus Quest or Apple Vision Pro. The goal of a metaverse is to let people have a second and new life in a virtual world, but the metaverse is still in its early stages. It’s still a video game to most people when you first enter it.
4. Big data
- the large volume of data in many environments;
- the wide variety of data types frequently stored in big data systems; and
- the velocity at which much data is generated, collected, and processed.
5. Machine learning (ML)
Machine learning is a set of algorithms that teach computers to learn new things and perform specific tasks by themselves. Machine learning and its evolved version, deep learning, is widely used in many applications, such as visual recognition, speech-to-text, data filtering, complex data analytics, etc. And the famous AlphaGo is also an application based on machine learning and deep learning.
Since machine learning became popular and a hot topic, Andrew Ng, one of the top AI influencers, launched a few online courses. This is a great class for newcomers to AI, machine learning and deep learning.
6. Neutral network
In the AI sector, the neural network is more than the biological processes in the human brain. It’s a mathematical method that sets algorithms to teach computers to mimic the human brain’s function. Neutral networks allow the computer to find more insight and relationships among different data. The neutral network can help people solve complex real-life problems like facial recognition, disease diagnosis, or winning a chess game!
7. Cluster analysis
Clustering is a method being used in machine learning to categorize data into different groups. Data in the same cluster are more similar than those in another cluster. Cluster analysis is to compare and analyze the data in groups. When there is a large volume of data, it’s impossible to read and analyze the data in Excel. Cluster analysis will help to discover and understand more insights about the data.
8. Cloud Computing
There are three types of cloud: public, private, and hybrid. Most of us use a public cloud. This type of cloud is open to public use and can be free. A private cloud, on the other hand, is used for only one organization or company and can be hosted internally or externally. Finally, a hybrid cloud is a combination of the two.
A Chatbot is a service powered by specific rules that you can interact with using a chat interface. It is the most common application of artificial intelligence. Natural language recognition is widely used in powering a chatbot to allow the chatbot to talk to you like a human. You may have used a chatbot if you ever talked to customer service on e-commerce websites or telecom providers.
10. Data Mining
For enterprises, data mining tools are essential in predicting future industry or market trends. It is sometimes called “Knowledge Discovery in Data” (KDD).
A typical personal computer works with Gigabytes (GB). That’s 1 billion bytes. That’s a lot, but basically nothing compared to a Yottabyte (YB), which is 1 septillion bytes, or 1000000000000000000000000 bytes (10^24 Bytes). Regarding memory size, Yottabyte is the largest unit for measuring data. By the way, You may not be familiar with Yottabyte as a tech term, but Yottabyte is well-known as an energetic song by Martin Garrix.
12. NLP (Natural Language Processing)
Natural language processing technology allows developers to organize and structure knowledge and perform various tasks, including translation, speech recognition, topic segmentation, named entity recognition, automatic summarization, sentiment analysis, and relationship extraction.
13. AWS (Amazon Web Services)
AWS includes Amazon Elastic Compute Cloud (EC2) and Amazon Simple Storage Service (S3). Regarding market share, AWS is the largest public cloud provider, followed by Microsoft Azure, Google Cloud, and IBM Cloud.
14. IoT (Internet of Things)
Every IoT device needs to be connected with others of its kind and applications to send and receive information using Internet Transfer Protocols (ITP). An IoT Platform works as a bridge between data networks and sensors.
15. IBM Watson
IBM Watson was initially a natural language understanding-powered question-answer system created by IBM. Watson was named after IBM’s founder and first CEO, industrialist Thomas J. Watson. With the development of AI technology and surging demand for AI applications, IBM made Watson a cloud-based AI platform that allows you to build and manage different AI applications and tools on the Watson platform.
The supercomputer is a class of compelling computers. The fastest supercomputer is the Fugaku, which is in Kobe, Japan. It has 7.3 million cores and a speed of 415.5 petaFLOPS.
17. Computer Vision
Computer vision is a use case of artificial intelligence that teaches computers to understand images and videos. The most common use of computer vision is “facial recognition.” So, computer vision is also be seen as facial recognition. When you look at your phone, the phone will automatically recognize that it’s you are using the phone. This is based on computer vision.
18. Autonomous vehicles
Autonomous vehicles are also known as self-driving cars. According to the Society of Automotive Engineers (SAE), there are 6 levels of driving automation ranging from Level 0 (fully manual) to Level 5 (fully autonomous). Tesla, Uber, and Google Waymo are all developing and testing self-driving cars. And Waymo claimed that their driverless taxi service already reached Level 4.
19. Chat GPT
What is Chat GPT? This is the answer from Chat GPT:
Chatbot GPT (Generative Pre-trained Transformer) is an advanced conversational AI model developed by OpenAI. It is part of the GPT series, which stands for "Generative Pre-trained Transformer." GPT models are designed to generate human-like text based on the input they receive.
ChatGPT uses deep learning techniques and a massive amount of text data to learn the statistical patterns and relationships in language. It is trained on a diverse range of internet text, including books, articles, websites, and other sources. By analyzing this data, the model learns to generate coherent and contextually relevant responses to user inputs.
Python is a modern computer programming language first appeared in 1991. Compared with other traditional programming languages like C++ or Java, Python is more straightforward with a simplified syntax and more accessible for beginners. Python is now the top programming language for machine learning tasks like data mining and training. If you’d like to try to code any software in AI, Python is a must-learn and foundation knowledge.