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

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

Symbolic AI , a classical approach using logic and symbols for knowledge representation and manipulation, excels in abstract and structured problems like mathematics and chess but needs help scaling and integrating sensory and motor data.

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Neural Network Machine Learning Algorithm Natural Language Processing 193

Unite.AI

AUGUST 22, 2023

We wrote developed custom rules (later more complex neural networks) to predict which customers we should approach with which products at which times to maximize the likelihood of a salesperson’s time resulting in revenue uplift. You’ve described Algolia as being the most scalable hybrid AI search engine in the world.

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Big Data Neural Network Natural Language Processing Hybrid AI 246

NVIDIA

MAY 29, 2024

As the capabilities and use cases for generative AI continue to grow, so does the demand for compute to support it. Hybrid AI combines the onboard AI acceleration of NVIDIA RTX with scalable, cloud-based GPUs to effectively and efficiently meet the demands of AI workloads.

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Generative AI Hybrid AI Data Scientist Neural Network 92

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. One critical aspect of AI4S is accommodating the specific characteristics of scientific data.

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Neural Network ChatGPT Hybrid AI Machine Learning 104

Unite.AI

JANUARY 23, 2024

Word2Vec pioneered the use of shallow neural networks to learn embeddings by predicting neighboring words. LLMs utilize embeddings to understand word context. Techniques like Word2Vec and BERT create embedding models which can be reused. Recent research has evolved embeddings to capture more semantic relationships.

Large Language Models 100

Large Language Models Prompt Engineer Prompt Engineering LLM 100