Jeff Bezos Is Funding a Wild Hunt for the Brain’s ‘Core Algorithm’

With $500 million in funding and a reported $2.5 billion valuation, Flourish wants to reinvent AI by putting real neurons ...
Investopedia

Predictive Modeling: Techniques, Uses, and Key Takeaways

Investopedia contributors come from a range of backgrounds, and over 25 years there have been thousands of expert writers and editors who have contributed. Jared Ecker is a researcher and fact-checker ...
Analytics Insight

Most Important AI Algorithms for Beginners in 2025

As we progress into 2025, Artificial Intelligence (AI) continues to reshape industries and revolutionize how we interact with technology. For those starting their journey in AI, it’s essential to ...
eWeek

Types of AI Models: A Deep Dive into AI Architecture

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...
IEEE

Regression Decision Trees Used With An Interferometric Sensor for Improved Temperature Measurement

Abstract: Nowadays, machine learning techniques are used in classification and regression tasks. In this work, the decision tree method, which is a basic supervised learning algorithm, was used to ...
Analytics Insight

What is the space complexity of various machine learning algorithms?

Space complexity of machine learning algorithms is the amount of memory or storage an algorithm requires for its successful execution. This becomes one of the important metrics of concern since it ...
Ars Technica

The real research behind the wild rumors about OpenAI’s Q* project

On November 22, a few days after OpenAI fired (and then re-hired) CEO Sam Altman, The Information reported that OpenAI had made a technical breakthrough that would allow it to “develop far more ...
InfoWorld

The engines of AI: Machine learning algorithms explained

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...
IEEE

Analysis of Learning Behavior Characteristics and Prediction of Learning Effect for Improving College Students’ Information Literacy Based on Machine Learning

Abstract: Information literacy is a basic ability for college students to adapt to social needs at present, and it is also a necessary quality for self-learning and lifelong learning. It is an ...
Frontiers

Discrimination of psychrophilic enzymes using machine learning algorithms with amino acid composition descriptor

Psychrophilic enzymes are a class of macromolecules with high catalytic activity at low temperatures. Cold-active enzymes possessing eco-friendly and cost-effective properties, are of huge potential ...
Frontiers

A framework for identification and classification of liver diseases based on machine learning algorithms

Hepatocellular carcinoma (HCC) is one of the most commonly seen liver disease. Most of HCC patients are diagnosed as Hepatitis B related cirrhosis simultaneously, especially in Asian countries. HCC is ...