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Inching towards AGI: How reasoning and deep research are expanding AI from statistical prediction to structured problem-solving

Flipboard

Back in 2017, my firm launched an AI Center of Excellence. AI was certainly getting better at predictive analytics and many machine learning (ML) algorithms were being used for voice recognition, spam detection, spell ch… Read More GUEST: AI has evolved at an astonishing pace.

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From Concept to Code: Unveiling the ChatGPT Algorithm

Towards AI

Nevertheless, when I started familiarizing myself with the algorithm of LLMs the so-called transformer I had to go through many different sources to feel like I really understood the topic.In How does the algorithm conclude which token to output next? this article, I want to summarize my understanding of Large Language Models.

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Understanding and coding Neural Networks From Scratch in Python and R

Analytics Vidhya

Note: This article was originally published on May 29, 2017, and updated on July 24, 2020 Overview Neural Networks is one of the most. The post Understanding and coding Neural Networks From Scratch in Python and R appeared first on Analytics Vidhya.

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DeepMind Introduces JEST Algorithm: Making AI Model Training Faster, Cheaper, Greener

Unite.AI

The learning algorithms need significant computational power to train generative AI models with large datasets, which leads to high energy consumption and a notable carbon footprint. Google's recently introduced JEST algorithm is pioneering research toward making training algorithms smarter.

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Using KNIME for Data Driven Decision Making

Analytics Vidhya

Introduction In 2017, The Economist declared that “the world’s most valuable resource is no longer oil, but data.” Companies like Google, Amazon, and Microsoft gather large bytes of data, harvest it, and create complex tracking algorithms. This article was published as a part of the Data Science Blogathon.

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Sepsis ImmunoScore: The First FDA-Authorized AI Tool for Early Sepsis Detection and Risk Assessment

Marktechpost

The study conducted a prospective, multicenter observational study to develop and evaluate an ML algorithm, the Sepsis ImmunoScore, designed to identify sepsis within 24 hours and assess critical illness outcomes such as mortality and ICU admission. hospitals between April 2017 and July 2022.

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Are AI Models Becoming Commodities?

Unite.AI

AI researcher Andrew Ng as early as 2017 likened AIs potential to the new electricity, suggesting that just as electricity became a ubiquitous commodity underpinning modern life, AI models could become fundamental utilities available from many providers. This is the crux of the commoditization debate. OpenAIs own strategy reflects this shift.