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Rethinking Reproducibility As the New Frontier in AI Research

Unite.AI

In the domain of Artificial Intelligence (AI) , where algorithms and models play a significant role, reproducibility becomes paramount. Moreover, the interdisciplinary nature of AI research, involving collaboration between computer scientists, statisticians, and domain experts, emphasizes the need for clear and well-documented methodologies.

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The Intersection of AI and Quantum Computing

Pickl AI

Introduction In recent years, two technological fields have emerged as frontrunners in shaping the future: Artificial Intelligence (AI) and Quantum Computing. A study demonstrated that quantum algorithms could accelerate the discovery of new materials by up to 100 times compared to classical methods.

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Data science vs. machine learning: What’s the difference?

IBM Journey to AI blog

Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention. IBM computer scientist Arthur Samuel coined the phrase “machine learning” in 1952. This led to the theory and development of AI.

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Boston Children’s Researchers, in Joint Effort, Deploy AI Across Their Hip Clinic to Support Patients, Doctors

NVIDIA

A team of 10 researchers are working on the project, funded in part by an NVIDIA Academic Hardware Grant , including engineers, computer scientists, orthopedic surgeons, radiologists and software developers.

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Getting ready for artificial general intelligence with examples

IBM Journey to AI blog

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Achieving these feats is accomplished through a combination of sophisticated algorithms, natural language processing (NLP) and computer science principles.

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MLOps and the evolution of data science

IBM Journey to AI blog

The advancement of computing power over recent decades has led to an explosion of digital data, from traffic cameras monitoring commuter habits to smart refrigerators revealing how and when the average family eats. Both computer scientists and business leaders have taken note of the potential of the data. What is MLOps?

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This AI newsletter is all you need #34

Towards AI

Understanding Large Language Models — A Transformative Reading List In just five years, large language models (transformers) have revolutionized the field of natural language processing. Scientists from MIT, Google Research, and Stanford University are working to unravel this mystery.