“Vector search” is a new way of searching for information based on meaning rather than keywords. It can handle vague or unclear queries and provides results that are more relevant by understanding the context and similarity in meaning.
AI uses a technique called “Embedding” to understand the meaning of words. This method converts information into numerical values and places items with similar meanings or characteristics close to each other. By doing so, it supports functions like search engines and recommendation systems that we use in our daily lives.
To communicate effectively with generative AI, it’s important to use prompts that are clear and specific. By doing so, you can receive more accurate and relevant responses. Crafting good prompts is a valuable skill, as it helps bring out the full potential of AI. A new concept called “prompt engineering” is gaining attention—this refers to the ability to design effective questions or instructions for AI. As AI becomes more integrated into our work and daily lives, this skill is expected to become increasingly important.
GAN, a technology that enables AI to generate realistic images, works through a competitive process between two AI models: a generator and a discriminator. The generator creates data that resembles the real thing, while the discriminator tries to determine whether it’s genuine or fake. This dynamic interaction involves a kind of back-and-forth that feels surprisingly human, as each model improves by challenging the other.
How does AI draw pictures? The mechanism behind image generation, known as a “diffusion model,” starts with noise and gradually transforms it into meaningful images. While this method can produce highly detailed and realistic results, it also comes with challenges such as requiring significant computational power and longer processing times.
AI-powered video generation technology, which creates videos based on written text, is rapidly evolving. It offers new ways of expression in fields like advertising and film production. At the same time, it also presents challenges, including ethical concerns and technical limitations.
Speech synthesis technology is a system that converts written text into human-like speech. Thanks to advances in deep learning, it has become possible to generate more natural and conversational voices, and the technology is now being used in a wide range of everyday situations.
Here’s the English translation of the article excerpt:
This article gently explains the technology behind image generation, which allows computers to create realistic images simply by entering text. We’ll explore how it works, where it’s being used, and the challenges it presents.
AI-generated text is a technology that enables computers to create natural-sounding sentences, much like those written by humans. This capability is increasingly being used in everyday life and business settings.
To help AI understand the meaning of a sentence, it’s essential to convey the “order of words” — and that’s where a technique called “positional encoding” comes in. Thanks to this method, AI can grasp the overall flow and meaning of a sentence.
