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2. I tried over 15 AI tools this year. These are the ones I ...

   www.aol.com/tried-over-15-ai-tools-183143435.html

   This year, I tried more than 15 AI tools and features ranging from chatbots to virtual shopping assistants and smart mirrors. The variety is an indication of just how widespread AI is becoming and ...

3. Generative artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Generative_artificial...

   Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 2 ] [ 3 ] [ 4 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 5 ] [ 6 ] based on ...

4. Automated journalism - Wikipedia

   en.wikipedia.org/wiki/Automated_journalism

   Automated journalism, also known as algorithmic journalism or robot journalism, [1] [2] [3] is a term that attempts to describe modern technological processes that have infiltrated the journalistic profession, such as news articles and videos generated by computer programs.

5. Open-source artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Open-source_artificial...

   Open-source artificial intelligence is an AI system that is freely available to use, study, modify, and share. [1] These attributes extend to each of the system's components, including datasets, code, and model parameters, promoting a collaborative and transparent approach to AI development. [ 1 ]

6. Wikipedia:Artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Wikipedia:Artificial...

   As with any machine-generated content, care must be used when employing AI at scale or in applying it where the community consensus is to exercise more caution. When exploring AI techniques and systems, the community consensus is to prefer human decisions over machine-generated outcomes until the implications are better understood.

7. Retrieval-augmented generation - Wikipedia

   en.wikipedia.org/wiki/Retrieval-augmented_generation

   Retrieval Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.