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To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. How do artificial intelligence, machine learning, deep learning and neuralnetworks relate to each other? Machine learning is a subset of AI. What is artificial intelligence (AI)?
Despite achieving remarkable results in areas like computer vision and natural language processing , current AI systems are constrained by the quality and quantity of training data, predefined algorithms, and specific optimization objectives.
The “distance” between each pair of neighbors can be interpreted as a probability.When a question prompt arrives, run graph algorithms to traverse this probabilistic graph, then feed a ranked index of the collected chunks to LLM. One more embellishment is to use a graph neuralnetwork (GNN) trained on the documents.
Word2Vec pioneered the use of shallow neuralnetworks to learn embeddings by predicting neighboring words. Powerful approximate nearest neighbor algorithms like HNSW , LSH and PQ enable fast semantic search even with billions of documents. Responsible AI tooling remains an active area of innovation.
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