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Will Large Language Models End Programming?

Unite.AI

The simplicity of user interfaces and the ability to generate code through straightforward commands like “Build me a website to do X” is revolutionizing the process. AI's influence in programming is already huge. The rapid advancements in AI, are not limitd to text/code generation.

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Rethinking Reproducibility As the New Frontier in AI Research

Unite.AI

Recent advancements in AI emphasize the need for improved reproducibility due to the rapid pace of innovation and the complexity of AI models. Multiple factors contribute to the reproducibility crisis in AI research.

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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. DGX enabled advanced computations on more than 20 years’ worth of historical data for our fine-tuned clinical AI model.”

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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. LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language.

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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. MLOps and IBM Watsonx.ai

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

IBM Journey to AI blog

This led to the theory and development of AI. IBM computer scientist Arthur Samuel coined the phrase “machine learning” in 1952. In 1962, a checkers master played against the machine learning program on an IBM 7094 computer, and the computer won. He wrote a checkers-playing program that same year.

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This AI newsletter is all you need #34

Towards AI

Announcing the launch of the Medical AI Research Center (MedARC) Medical AI Research Center (MedARC) announced a new open and collaborative research center dedicated to advancing the field of AI in healthcare. This article delves into the details of these emerging approaches and their potential impact on AI development.