How to Use Podcasting for Generation
Posted: Sat Jan 18, 2025 9:12 am
The petition has over 30,000 signatories and cites large-scale societal risks as its founding goal. “ Systems with intelligence competitive with that of humans can pose profound risks to society and humanity, as demonstrated by extensive research and recognized by leading AI labs .” Progress will be unstoppable, but what about the dangerous potential of this technological advancement in the service of disinformation. Article The Atlantic: AI Is Like…Nuclear Weapons. March 2023 Where does generated content come from. In search of lost meaning We could summarize in a very reduced way that ChatGPT and Midjourney are gigantic autocompletion engines of all (or almost) our knowledge and creativity made available over the last twenty years on the Internet sharing space, restored in a gigantic puzzle using the most probable elements.
For its deep learning on huge text corpora, OpenAI is based on portugal phone number library neural networks, more precisely an RNN, "Recursive Neural Network" (invented in the 1940s), which can be considered as idealizations of the way our brains seem to work . We add to this the notion of ' Transformer ' - GPT meaning Generative Pre-trained Transformer. Transformer is a neural network architecture that facilitates parallel attention and allows learning (on its own) long-term dependencies. To understand our natural language, a paragraph is cut into pieces, sentences, words, into text vectors. Each piece is passed, several times if necessary, through the same function (recursive).
For its deep learning on huge text corpora, OpenAI is based on portugal phone number library neural networks, more precisely an RNN, "Recursive Neural Network" (invented in the 1940s), which can be considered as idealizations of the way our brains seem to work . We add to this the notion of ' Transformer ' - GPT meaning Generative Pre-trained Transformer. Transformer is a neural network architecture that facilitates parallel attention and allows learning (on its own) long-term dependencies. To understand our natural language, a paragraph is cut into pieces, sentences, words, into text vectors. Each piece is passed, several times if necessary, through the same function (recursive).