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AI-basis
20 artikelen
AI-basis
What is generative AI?
Generative AI creates new content based on a prompt: text, images, music, video, 3D or code. What happens during the generation process, and how do you turn an interesting result into something useful for your work?
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What is text generation using AI?
Text generation is the process of creating text using a language model. From draft emails and summaries to structured responses: the task and the available information determine the output.
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What is image generation?
Image generation, or ‘beeldgeneratie’, enables AI to create new images or modify existing ones. A description or reference provides guidance; the model constructs the visual output.
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What is music generation?
Music generation is the process of creating music using AI based on, for example, style, atmosphere, instruments or a sound clip. The model generates a musical composition which you can then listen to and edit.
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What is speech and audio generation?
With AI, you can convert text to speech and generate other sounds. How do text-to-speech, sound effects and transcription differ, and where do they fit into a practical workflow?
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What is AI-powered video generation?
Video generation creates moving images from a description, an image or an existing clip. The model must not only produce attractive images, but also maintain continuity between successive frames.
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What is 3D generation using AI?
3D generation creates a digital spatial representation based on text or images. From concept object to textured model: the output is only usable when it is compatible with your design software and application.
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How does generation work with diffusion models?
Many generative image models construct an image through successive steps starting from noise. What roles do the model, the prompt and the settings play during that process?
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What are frontier models?
Frontier models are at the cutting edge of what AI is currently capable of. What does that say about quality, and when do you really need such a model?
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What are tokens in AI?
A language model works with tokens: small building blocks of input and output. They help determine how much context fits, how long a response takes and what an API request costs.
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What are AI hallucinations?
AI can provide a convincing answer that is factually incorrect. Learn how to recognise fabricated information and build applications that handle uncertainty more effectively.
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What is ablation in language models?
Abliteration adjusts a model’s internal properties to reduce learned rejection behaviour. What does this change, and what does it not tell us about the quality?
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What are the weights of an AI model?
Weights are the trained numbers that determine how a model processes information. Find out how model weights, parameters and a downloadable model file are related.
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What is a vector in AI?
A vector is an ordered sequence of numbers. In AI, such a sequence helps to represent, compare and retrieve information — for example, when searching by meaning.
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What is inference in an LLM?
Inference is the process of using a trained model to produce an outcome. In the case of an LLM, this involves processing input and then constructing a response.
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What is a vision model?
A vision model processes visual information, such as photographs and document images. A vision-language model combines this with language to answer questions about an image.
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What is an LLM?
An LLM is a large language model that can understand, predict and generate text. It often seems intelligent, but the quality of the result depends heavily on context, model choice and how you use it.
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What is context in AI?
Context is all the additional information you provide to a model so that it better understands what you mean. Good context makes the difference between a generic answer and something that really suits your task, organisation or document.
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What is a context window?
The context window is the maximum amount of information a model can process in a single interaction. This determines how much text, chat history or document fragments can be used at any one time.
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What is prompt engineering?
Prompt engineering is the deliberate formulation of instructions to ensure a model produces useful output. It is not about tricks, but about clarity regarding the objective, context, tone, preconditions and desired format.
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