Synthetic Data Is Transforming Artificial Intelligence

Introduction

Artificial intelligence (AI) is rapidly transforming the world around us, from the way we work to the way we live. But to build truly powerful and intelligent AI systems, we need access to vast amounts of high-quality data. Data is the essential ingredient for AI. But real data can be hard to get. Synthetic data offers a virtual solution - better than real data.

Data: The Essential Ingredient for AI

AI models are trained on data, and the quality and quantity of that data has a direct impact on the model's performance. If the training data is biased, inaccurate, or incomplete, the model will learn to make biased, inaccurate, or incomplete predictions - junk in, junk out. But data can be expensive and time-consuming to collect, curate, and manage.

Why Real Data is Hard

However, collecting and annotating real-world data can be difficult, expensive (even millions), and time-consuming. For example, to train a self-driving car, you would need to collect millions of miles of driving data, annotated with information about the road, traffic, and other objects.

Not to mention, for all weather conditions, road hazards, and rare events.

Synthetic Data: A Virtual Solution

Synthetic data offers a solution to these challenges. Synthetic data is data that is artificially generated, rather than collected from the real world. It can be used to create virtual worlds that are identical to the real world, or even more complex and challenging.

Labeled data has brought AI to where we are today, imagine for a moment what synthetic data will bring in the next decade - nothing short of spectacular.

Building Better AI with Synthetic Data

Synthetic data is a powerful tool for building robust and scalable AI systems. By using synthetic data to train AI models on a wide range of scenarios, we can create AI systems that can handle the real world with confidence. It has the potential to revolutionize the way we build and deploy AI systems. By generating high-quality synthetic data at scale, we can train AI models to perform tasks that were once thought to be impossible.

The Power of Synthetic Data

Synthetic data is already being used to train AI models in a wide range of applications, including self-driving cars, medical diagnosis, and robot navigation. Early self-driving cars like Waymo started with massive amounts of data, today no investor will fund you for data collection, but new self-driving car startups are still popping up, why? Because their models are trained in simulation - a vastly synthetic environment with some real data. This space has grown exponentially with unicorns providing Simulators. Beyond self-driving cars synthetic data is used in diverse applications like Amex Fraud detection and medical images.

Source: Gartner, “Maverick Research: Forget about Your Real Data – Synthetic Data Is the Future of AI” – 24 June 2021

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