At the start of the summer, I walked into G2’s corporate headquarters in Chicago feeling both excited and nervous about my internship in the tech industry. Little did I know, I had a lot to learn, especially about the impact of artificial intelligence (AI) on the corporate world. Here’s what I wish I had known before starting my internship.
Artificial intelligence, or AI, has been around for many years, but it has only recently gained significant momentum. You might be wondering what all the fuss is about and why AI matters to everyone, regardless of their field. Let’s start with some basic definitions.
AI is defined as the science of creating machines that can think like humans and perform smart tasks. Unlike humans, AI technology can process large amounts of data and make decisions based on patterns and judgments. To achieve this, AI requires a vast amount of data.
Machine learning (ML) is a subset of AI that focuses on computer systems learning and creating new algorithms independently. ML allows computers to adapt and learn new processes on the go. For example, a self-driving car’s system is trained to make decisions based on real-time learning rather than mapping out every possible scenario in advance.
A chatbot is a computer program designed to simulate human-like conversations. It uses AI to predict and engage in conversational dialogue. Examples of well-known AI chatbots include ChatGPT, Bard, and AI Bing.
Large language models (LLMs) are predictive AI programs that learn through data input/output sets. They can process massive amounts of data, providing accurate responses based on the information they’ve learned. However, there is a concern about bias or inaccuracies in the data used to train LLMs.
Natural language processing (NLP) refers to the ability of computers to understand and process spoken words like humans. NLP is used in voice-operated GPS systems, text-to-speech options, chatbots, and more, to improve business processes and provide faster and accurate results to customers.
Deep learning (DL) is a subset of ML that tackles larger-scale problems, running multiple computations simultaneously for faster results. DL programs can generate new algorithms without human guidance, expanding their knowledge across various domains.
The origin of AI can be traced back to the 1950s with Alan Turing’s concept of machines using stored information to solve problems. However, at that time, computers were limited in capability and memory. Over the years, as computers became more powerful and affordable, AI started gaining traction.
In recent years, AI has seen significant growth and adoption. OpenAI’s ChatGPT, an AI chatbot focusing on NLP, gained remarkable popularity, surpassing one million users in just four days. Major companies across industries are incorporating AI to streamline their processes. Microsoft, for example, invested $10 billion in AI research and development after partnering with OpenAI.
In the tech industry, AI is seen as a powerful tool to gain a competitive edge. It can enhance business efficiency, customize solutions, and streamline business models cost-effectively. G2, for instance, developed its own AI chatbot called Monty to assist software researchers in finding suitable services quickly.
AI is not something limited to a specific industry or field; it has the potential to revolutionize various aspects of our lives. By effectively utilizing AI, we can boost productivity and output, leading to a new generation built on streamlined processes and the collaboration between humans and machines.