San Francisco-based company Synthesis AI, a frontrunner in the field of synthetic data technologies, unveiled its latest project, Synthesis Labs, on April 18, 2023. This initiative focuses on introducing new generative AI capabilities, with an emphasis on text-to-3D technologies for digital humans. These advancements mark a milestone in the company's journey to support advanced AI applications, making Synthesis AI the first ever to demonstrate text-to-3D digital human synthesis at high-resolution cinematic quality. By merging generative AI with cinematic VFX pipelines, the Synthesis AI platform generates perfectly labeled synthetic data, which can be utilized to train machine learning models. The newest text-to-3D offerings, featured in Synthesis Labs, allow users to experience prompt-based input and editing, making no-code 3D generative AI capabilities accessible to a wide range of users – from computer vision and machine learning experts to non-technical users.

You're at the wheel of your car but you're exhausted. Your shoulders start to sag, your neck begins to droop, your eyelids slide down. As your head pitches forward, you swerve off the road and speed through a field, crashing into a tree. But what if your car's monitoring system recognised the tell-tale signs of drowsiness and prompted you to pull off the road and park instead? The European Commission has legislated that from this year, new vehicles be fitted with systems to catch distracted and sleepy drivers to help avert accidents.

Companies are building software that uses AI to monitor people's behavior and interpret their emotions and body language in real life, virtually and even in the metaverse. But to develop that AI, they need fake data, and startups are stepping in to supply it. Synthetic data companies are providing millions of images, videos and sometimes audio data samples that have been generated for the sole purpose of training or improving AI models that could become part of our everyday lives in controversial forms of AI such as facial recognition, emotion AI and other algorithmic systems used to keep track of people's behavior. While in the past companies building computer vision-based AI often relied on publicly available datasets, now AI developers are looking to customized synthetic data to "address more and more domain-specific problems that have zero data you can actually access," said Ofir Zuk, co-founder and CEO of synthetic data company Datagen. Synthetic data companies including Datagen, Mindtech and Synthesis AI represent a corner of an increasingly compartmentalized AI industry.

Synthesis AI enables the world's most advanced AI companies to build more powerful and ethical computer vision. The company's synthetic data and simulation platform was recently recognized as a Top 10 Breakthrough Technology by MIT Tech Review and ranked #4 on Fast Company's Global List of Most Innovative Small Companies. Synthesis AI is an ambitious team of technologists, researchers, creatives, and product designers driving a paradigm change in AI. Through a proprietary combination of generative neural networks and cinematic CGI pipelines, Synthesis' on-demand platform creates vast amounts of perfectly-labeled image data to train AI models at orders of magnitude increased speed and reduced cost. Current customers include Fortune 10 companies, top smartphone manufacturers, global technology enterprises, and leading AR/VR/metaverse companies.

Synthetic datasets are increasingly being used to train AI models. These promise greater privacy and less bias, but are not without their drawbacks. Synthetic datasets are becoming increasingly popular for training artificial intelligence models. Proponents of this computer-generated data say it protects personal information and reduces the chances of bias emerging in AI systems. But for many, concerns over privacy and accuracy remain.

AI has the potential to change the world in many amazing ways. But like every revolution, it requires fuel. It's long been said that "data is the oil of the information age," and that's certainly true in many ways. But while data is a less finite resource than actual oil, it does come with some challenges. People are (rightly) protective of their personal data, and there are compliance and regulatory responsibilities that must be upheld if we're using that personal data (often the most valuable kind of data) to power AI and generate predictions.

Founded in 2019, San Francisco-based Synthesis AI has developed technology that generates vast quantities of photorealistic images and pixel-perfect labels to optimize computer vision training. "The world is exploding with cameras," says Synthesis AI CEO Yashar Behzadi. This is great news for AI startups that specialize in computer vision, a field of AI that trains computers to interpret elements from digital images and videos. Up to now, computer vision has relied heavily on supervised learning, in which humans label key attributes in an image and then teach computers to do the same. But to Behzadi, this method has some pretty major setbacks.