Overview: Clear problem definitions prevent wasted effort and keep machine learning work focused.Clean, well-understood data ...

AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a specific approach to reach the same goal.

This article was co-written with my colleague and fellow YEC member, Nirman Dave, CEO at Obviously AI. Back in March of this year, MIT Sloan Management Review made a sobering discovery: The majority ...

Businesses are generating data at a faster pace than ever: 90% of the world’s data was generated within the last two years. The increased data volume is rapidly outpacing our ability to consume it.

Researchers have explained how large language models like GPT-3 are able to learn new tasks without updating their parameters, despite not being trained to perform those tasks. They found that these ...

ML is a subset of artificial intelligence (AI) that allows computers to learn without being explicitly programmed. In simple terms, machine learning (ML) is a subset of artificial intelligence (AI) ...

Machine learning and deep learning are both parts of artificial intelligence, but they work in different ways — like a smart student versus a super-specialised ...

From SOCs to smart cameras, AI-driven systems are transforming security from a reactive to a predictive approach. This ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

Automating through machine learning (ML) allowed Amazon.com to predict future demand for millions of products globally in seconds. Leaders at the multinational tech giant successfully reinvented their ...