Artificial intelligence (AI) Archive - Page 2 of 2 - Rock the Prototype

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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GTP Store – What does the Chat GPT App Store offer?

Sascha Block2024-01-12T12:14:35+01:00Tags: AI app, AI apps, App, App Store, App Stores, Apps, GPT Apps|

What is the GPT Store? The GPT Store is a marketplace for innovative AI solutions based on ChatGPT. As a specialized chat GPT AppStore, it offers countless apps in the field of artificial intelligence. We present the current TOP 10 GPT apps in the GPT Store. Our 10 tips: How do I find my perfect AI app in the App Store? help you step by step to find your perfect AI app...

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LLAMA3 – AI model for natural language processing

Sascha Block2024-04-23T14:35:46+02:00Tags: AI model, Algorithm development, Chatbots, Efficiency, LLAMA3, machine translation, natural language processing, NLP, Open Source, Scalability, Training data, Transformer architecture|

What is LLAMA3? LLAMA3 is a state-of-the-art artificial intelligence (AI) model for natural language processing. As an AI model, it is known for its ability to understand and generate human-like speech. LLAMA3 differs from its predecessors by its open-source availability and its efficient structure, which makes it possible to achieve high-quality performance with a smaller number of parameters.

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Machine Learning

Sascha Block2023-12-10T19:11:37+01:00Tags: Alan Turing, Algorithms, Artificial intelligence, Artificial intelligence programs, artificial neural networks, Automation, Backpropagation, Big Data, Chess program, continuous learning, Convolutional Neural Networks (CNNs), Data, Decision making, Deep learning, Efficiency, Image processing, Logic Theorist, machine learning, Models, natural language processing, Pattern recognition, Perceptron, personalized recommendations, Predictions, Recurrent Neural Networks (RNNs), Turing machine|

Machine learning is a branch of artificial intelligence (AI) that deals with the development of algorithms and models that enable computers to learn from experience and data, recognize patterns and make predictions without being explicitly programmed. The aim of machine learning is to enable computers to learn independently from data and extract information in order to master complex tasks. We explain which concepts are used to do this and how predictions can be made by adapting models to existing data.

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Natural Language Processing (NLP)

Sascha Block2025-01-24T15:57:08+01:00Tags: AllenNLP, API integration, Artificial intelligence, Attention mechanism, Azure Text Analytics, BERT, Bias reduction, bidirectional models, Chatbot development, Computational linguistics, computational semantics, Constituent parsing, Context-aware models, Contextual embeddings, Conversational AI, Corpus analysis, Data preprocessing, Deep learning, Dependency parsing, Dialog systems, ethical AI, Fairness in AI, Gated Recurrent Unit (GRU), GloVe, Google Cloud NLP, GPT, Handling sensitive data, Hugging Face, IBM Watson, Information retrieval, Language comprehension, Language models, Lemmatization, Long Short-Term Memory (LSTM), machine learning, morphological analysis, Multilingual NLP, Named Entity Recognition (NER), natural language processing, neural networks, NLP, NLTK, NLU (Natural Language Understanding), OpenNLP, Parsing algorithms, Privacy, PyTorch, Question answer, recurrent neural networks (RNN), Self-Attention, semantic analysis, Sentiment analysis, Sentiment classification, Sequence modeling, spaCy, Speech recognition, Speech-to-text, Stemming, syntactic analysis, TensorFlow, Text analysis, Text classification, Text generation, Text mining, Text parsing, Text summary, Text-to-speech, Tokenization, Transformer models, virtual assistants, Word embeddings, Word type tagging, Word2Vec|

Natural Language Processing (NLP) - a highly specialized subfield of artificial intelligence (AI) How do machines understand human language? Natural Language Processing is the key to bridging the gap between humans and machines

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Reinforcement Learning

Sascha Block2025-01-26T18:51:25+01:00Tags: Actor-Critic Models, algorithmic trading, AlphaGo, autonomous vehicles, computational complexity, Deep Q-Networks, DQN, energy optimization, ethics in AI, Exploration vs. exploitation, Google Dopamine, Markov Decision Process, MDP, OpenAI Five, OpenAI Gym, overfitting, Policy-Based Methods, Portfolio Optimization, PyTorch, Q-Learning, Reinforcement Learning, Reward Design, reward maximization, RL, RLlib, Robotics, safety in AI, Scalability, Smart grids, sparse rewards, Stable baselines, Supervised Learning, TensorFlow, Unsupervised Learning|

Reinforcement learning is a branch of machine learning that trains agents to make optimal decisions by interacting with their environment. Reinforcement learning is used in autonomous vehicles, robotics, games such as AlphaGo and AlphaZero and the optimization of resources in energy systems.

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Retrieval Augmented Generation (RAG) – using AI models effectively

Sascha Block2024-03-30T10:36:37+01:00Tags: Advanced RAG, AI language models, AI technology, Artificial intelligence, Data processing, Dialog systems, FAQ, Language models, Modular RAG, multimodal applications, Naive RAG, Question and answer systems, RAG Systems|

What is Retrieval Augmented Generation (RAG)? Retrieval-Augmented Generation (RAG) is an advanced AI technique in AI language modeling based on the integration of external information sources to improve and augment answer generation. A RAG system combines the comprehensive knowledge capacities of a Large Language Model (LLM) with the ability to obtain specific information from an external knowledge repository. This AI method allows the model to generate answers based not only on its internally trained knowledge, but also on current, specific and extensive external data. Find out more now!

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Artificial intelligence (AI)

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

GTP Store – What does the Chat GPT App Store offer?

LLAMA3 – AI model for natural language processing

Machine Learning

Natural Language Processing (NLP)

Reinforcement Learning

Retrieval Augmented Generation (RAG) – using AI models effectively

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