LSM - Technology First

Introduction Generative AI, a subset of artificial intelligence that uses machine learning techniques to generate new content, has seen explosive growth in recent years. This technology has the potential to revolutionize various sectors, from business to art, and is already being used by a third of organizations surveyed in a recent McKinsey Global Survey. The Rise of Generative AI Generative AI models have evolved over the past decade, with deep learning and General Adversarial Network (GAN) approaches typically being used. However, the latest approach is transformers. These models can generate new text based on the input they receive. In 2023, generative AI had a breakout year. Despite its nascent public availability, experimentation with these tools is already relatively common. Seventy-nine percent of all respondents in the McKinsey survey said they’ve had at least some exposure to generative AI, either for work or outside of work. Impact on Business Generative AI has s...

In the rapidly evolving world of technology, staying updated with the latest trends is crucial. This article explores the current technology trends shaping our world and their impact on our daily lives.   1. Artificial Intelligence (AI)   Artificial Intelligence (AI) is becoming increasingly prevalent in our daily lives. From voice assistants like Siri and Alexa to recommendation algorithms on Netflix and Amazon, AI is changing the way we interact with technology. In 2023, no-code AI, with its easy drag-and-drop interfaces, will enable any business to leverage its power to create more intelligent products and services. AI is also expected to augment nearly every job in every business process across industries.   2. Robotics, Drones, and Vehicle Automation   The field of robotics is advancing at a rapid pace, with drones and automated vehicles becoming more commonplace. These technologies are revolutionizing industries like logistics, agriculture, and ...

Introduction: In today's rapidly evolving technological landscape, terms like Machine Learning (ML), Artificial Intelligence (AI), and Deep Learning (DL) are frequently used, often interchangeably. However, these terms represent distinct concepts and technologies, each with its own set of applications and capabilities. In this article, we will delve into the key differences between Machine Learning, Artificial Intelligence, and Deep Learning, shedding light on their unique characteristics and contributions to the field of technology. 1. Machine Learning (ML): Machine Learning is a subset of Artificial Intelligence that focuses on the development of algorithms and models that enable computers to learn from and make predictions or decisions based on data. The core idea behind ML is to design systems that can improve their performance on a specific task through experience, without being explicitly programmed. Here are some key characteristics of Machine Learning:    a. Data-drive...