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  • Shannon Harney

Synthetic Data is solving AI’s biggest problem

Artificial intelligence has the potential to change the way people interact with computer — ushering in a new era, improving quality of life, and enhancing productivity. But that future is not inevitable.


While AI performance is improving steadily, the most important part of creating an AI system — the data — hasn’t been improved in years.


There’s not yet a solution for the incredible time and energy AI engineers spend cultivating and labeling training data — the data used to teach AI. This means the AI industry is focused on incremental improvements to AI architectures, while the raw materials that comprise AI are still living in the last decade. Lexset has the solution — better raw material for AI.


Enter Synthetic Data.


Lexset generates synthetic data algorithmically, to a creator’s exact specifications. As a result, data is obtained quickly, engineered to combat model bias, and comes with complete and exact annotations. Creating similar datasets using traditional approaches is at best expensive and time consuming, and sometimes outright impossible.


And while the processes used to create synthetic couldn’t be more different than collecting real world data, synthetic data is just like real-world data in that it has the same mathematical and statistical properties. You can use it to reflect the real world in AI systems, letting them train in a completely virtual world without the built-in problems of the real world.


Problems with training data don’t stop at acquisition and labeling


One of the biggest problems that pops up in AI data — the one that you’ve probably read the most about — is bias. When data isn’t labeled perfectly, or isn’t annotated well enough, it can lead to systemic discrimination. It’s something that we talked about earlier this month, which is already pervasive in existing datasets — and unfortunately, it’s not getting much better.


Privacy issues have already caused existing datasets major problems, leading to deletion of millions of training images and redaction in others, making it harder and harder for an AI to learn from effectively.


Synthetic data doesn’t inherently have these problems. Which is why, according to Forrester Research, synthetic data could lead to “AI 2.0,” making radical changes to improve AI.

With Lexset’s synthetic data, you receive pixel-perfect annotation in images, effectively eliminating bias. Your AI will learn exactly what it’s supposed to, and won’t be misguided by broken metadata, mislabeled or unlabeled data points.


And since the data is all artificial, there are no privacy concerns to contend with. Your AI won’t have to try to learn around redacted or edited real-world images.


And maybe best of all, it’s faster and cheaper to generate synthetic data than it is to compile thousands and thousands of real-world annotated images.


That's how Lexset can help.


We’re leading the industry in synthetic data generation. Our data is always unbiased, completely accurate, and built to exactly what you need. Better still, it’s the easiest data in the industry to access with users making their own datasets with Lexset tools.


Lexset allows you to rapidly iterate on your models, building dramatically improved accuracy in your AI.


Putting it simply, using Lexset’s synthetic data, you can make sure your AI is doing the right thing, every time.


Reach out to us to get your company started with our synthetic data!

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