IBM Journey to AI blog

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

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Neural Network Deep Learning Machine Learning Artificial Intelligence 178

Unite.AI

FEBRUARY 10, 2025

That's when Sushant and I realized the future wasn't about choosing between local or cloud processingit was about creating an intelligent technology that could seamlessly adapt between local, cloud, or hybrid processing based on each specific inference request. But AI shouldn't be limited by which end-user device someone happens to use.

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Neural Network Hybrid AI AI Modeling Large Language Models 227

Unite.AI

JUNE 25, 2023

However, assimilating the understanding of physics into the realm of neural networks has proved challenging. In a significant breakthrough, the UCLA study intends to combine the deep understanding from data and the real-world know-how of physics, thereby creating a hybrid AI with augmented capabilities.

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Computer Vision Robotics Neural Network Hybrid AI 361

Unite.AI

FEBRUARY 16, 2024

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.

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Neural Network Machine Learning Algorithm Natural Language Processing 190

O'Reilly Media

NOVEMBER 19, 2024

One more embellishment is to use a graph neural network (GNN) trained on the documents. tend to dislike using an AI application as a “black box” solution, which magically handles work that may need human oversight. This latter approach with node embeddings can be more robust and potentially more efficient.

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LLM NLP Hybrid AI Large Language Models 125

Marktechpost

JUNE 29, 2024

Scientific AI requires handling specific scientific data characteristics, including incorporating known domain knowledge such as partial differential equations (PDEs). Scaling AI systems involves both model-based and data-based parallelism. Finally, interpretability and explainability in AI models must be considered.

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Neural Network ChatGPT Hybrid AI Machine Learning 108