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发布时间:2026-09-16 | 浏览:3
Start exploring today’s artificial intelligence
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Your trusted source on AI
CNET has been covering AI for more than two decades. Now we’re bringing you a new wave of expert, unique and helpful insights, through in-depth explainers, hands-on product reviews, how-to posts and more, to help you see how AI fits into your life.
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Artificial intelligence is what happens when computers perform tasks beyond following rigid, rules-based logic, when they go deeper into analyzing data and making predictions. For example, there’s image recognition; a famous early example involved computers studying photos of cats to learn how to identify cats. There’s understanding natural language – that is, human syntax rather than computer code, which is how you can have a conversation with chatbot. And there are self-driving cars, which interpret their surrounds and can take action on their own. In other words, AI is simulating aspects of human intelligence, including learning, problem solving and autonomy.
A generative AI model “hallucinates” when it delivers false or misleading information. This happens because of how the models are trained, on massive amounts of data, like articles, books, code and social media posts. In creating its response to a prompt, the AI makes inferences about what words should come next, but it lacks contextual information so it may generate wording that seems plausible but isn’t true. Hallucinations can also result from improper training and/or biased or insufficient data, which leave the model unprepared to answer certain questions.
An LLM is a large language model – basically, a vast trove of data from written material that serves as the foundation for a generative AI tool like ChatGPT or Gemini. When you give an AI chatbot a prompt, it blazes through the LLM data looking for word patterns that match the topic. As it strings together words to craft a response, it’s constantly making predictions about what the next word in the sequence should be. For instance, in the sentence “The ingredients for chili include…” it might suggest “ground beef” or “beans” as the next word in the sequence. It doesn’t understand the words, just the statistical relationships among them.
AI agents – sometimes referred to as agentive AI – are the hot buzzword in generative AI, the anticipated next wave of AI advances for our phones and other devices. These would go beyond chatbots, which respond to your queries or prompts one at a time, to become bona fide AI assistants, like a supercharged Siri or Alexa. They would actively anticipate your needs and be able to handle complex requests, such as travel planning, by working across apps, accounts, data and web searches.
A program that communicates with humans through text that simulates human language.
Policies and restrictions placed on AI models to ensure data is handled responsibly and that the model doesn’t create disturbing content.
An aspect of AI that allows computers to learn and make better predictive outcomes without explicit programming. Can be coupled with training sets to generate new content.
Numerical values that give LLMs structure and behavior, enabling them to make predictions.
The datasets, often quite vast, used to help AI models learn, including text, images, code or data.
Our writers and editors know the subject cold. Here are CNET’s leading authorities on AI.
AI Atlas is 100% human-generated. For more, see CNET’s AI policy .
Managing Editor
“Generative AI is changing our lives in so many ways, including how we work, get health care and express ourselves. I’m exploring how AI could affect all of us, whether we use a chatbot or not.”
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Katelyn Chedraoui
“Generative AI should not replace human artists and creativity. As AI content fills our online spaces, we all need to understand the legal, ethical and technological consequences of creative AI services.”
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