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AI language models

Sascha Block2025-02-05T13:55:57+01:00Tags: AGI, AI ethics, AI for companies, AI Governance, AI in everyday life, AI in research, AI language models, AI Research, AI safety, AI-supported creativity, Alexa, Algorithmic Bias, Artificial intelligence, Attention mechanism, Autoencoding, Autoregressive models, BERT, Bias in AI, bidirectional models, Chatbots, CLIP, Cloud computing, Computational linguistics, Computing power, Conversational AI, DALL-E, Data ethics, Deep learning, DeepMind, digital assistants, Embeddings, Energy-efficient AI, Explainability, Fairness in AI, Few-Shot Learning, Few-Shot Prompting, Fine tuning, GDPR, generative AI, generative language models, GitHub Copilot, GloVe, Google AI, Google Assistant, GPT, GPT-2, GPT-3, GPT-4, GPUs, Hallucinations in AI, Hugging Face, Information retrieval, Interpretability, Knowledge Graphs, Language processing, Large Language Models, LLM, LSTM, machine learning, machine translation, Masked Language Modeling, Meta AI, Model compression, multimodal AI, multimodal models, Named Entity Recognition, natural language processing, neural networks, NLP, Open source AI, OpenAI, OpenAI Codex, Perplexity, Privacy, Prompt Engineering, Prompt Tuning, Regulation, Reinforcement Learning, Responsible AI, Retrieval-Augmented Generation, RNN, Scalability, Self-Attention, Sentiment analysis, Siri, Supervised Learning, synthetic data, T5, Text classification, Text generation, Tokenizer, TPUs, Training data, Transfer Learning, Transformer, Unsupervised Learning, Voice assistants, Word2Vec, Zero-shot learning|

AI language models - what's behind them? Artificial intelligence is changing the way we interact with machines. Language models enable machines not only to understand language, but also to generate meaningful, human-like responses. Find out more now...

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Generative pretrained transformer (GPT) – AI tech & AI learning models

Sascha Block2024-04-01T22:39:39+02:00Tags: AI, AI, Alan Turing, AlexNet, Backpropagation, Context limitations, Dartmouth Conference, Deep Blue, Deep learning, Distortions, Embeddings, Fine tuning, Generative Pretrained Transformer, GPT, GPT-2, GPT-3, ImageNet, machine learning, neural networks, neural networks, OpenAI, Positional Encoding, Self-Attention, Text generation, Tokenization, Top-k Sampling, Transformer architecture, Turing test, unsupervised learning, Unsupervised Learning|

What is a generative pretrained transformer (GPT)? A Generative Pre-Trained Transform - GPT for short - is an advanced machine learning AI model based on the Transformer architecture. This AI technology was developed by OpenAI and is known for its ability to generate high-quality texts that are similar to those of a human being. The core of GPT technology lies in the use of large amounts of data to pre-train the model before it is fine-tuned for specific tasks.

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