Artificial General Intelligence (AGI): AGI is achieved when an AI system can perform better than humans across a wide range of cognitive tasks. The sources suggest that AI is getting close to AGI.
Attention: A key concept in “Transformer” technology where more importance (“attention”) is given to certain parts of the training data, improving efficiency.
Chains of Thought (CoT): A technique using multiple queries and comparisons to improve the reliability of an AI’s responses, allowing for problem-solving through inference chains.
Generative Pre-trained Transformer (GPT): The underlying technology behind ChatGPT.
GPUs: Graphics Processing Units. Originally designed for tasks like gaming and cryptocurrency mining, they are now crucial for the parallel processing needed in AI, especially for neural networks.
Hallucinations: Instances where an AI generates inaccurate or made-up information.
Inference Chains: A series of reasoned conclusions or deductions made by an AI, enabling it to solve problems using its stored knowledge.
Large Language Models (LLMs): AI systems trained on vast amounts of text data, capable of understanding and generating human-like text. The creation of LLMs was made possible by “Transformers” technology.
Neural Network: A computing system inspired by the structure of the human brain. It “learns” from data by adjusting the weights of connections between its artificial neurons.
Post-Training Computation: Computations performed after the initial training of an LLM. This technique enhances the reliability and problem-solving capabilities of LLMs.
Pre-training: The initial, intensive process of training a neural network by feeding it massive amounts of data and adjusting its parameters until it can generate accurate outputs.
Test-time (Inference-time): The stage where a trained neural network is used to make predictions or generate outputs based on new input data.
“Transformers”: A groundbreaking technology that significantly accelerated the training of neural networks, paving the way for the development of LLMs.
Leave a Reply
You must be logged in to post a comment.