alternative title：Synthetaic claims that AI data is comparable to real data

  • Synthetaic raised $15 million in a Series B round co-led by Lupa Systems and TitletownTech.
  • The amount of image data generated is growing exponentially, which highlights the growing need for advanced AI solutions.
  • Synthetaic’s technology provides a transformative approach to AI model training and creation that addresses a critical need for technology decision makers.

The leading Synthetaic

China’s “spy” balloon incident in 2023 proved difficult for civilians to trace to its origin, and only artificial intelligence companies such as Synthetaic can do so using satellite imagery. The balloon incident provided Synthetaic with a powerful product demonstration opportunity that attracted the attention of investors including defense contractor Booz Allen Hamilton.

“The exponential growth in the amount of image data generated highlights the growing need for advanced AI solutions to manage and analyze this vast repository of information.”

Corey Jaskolski，Synthetaic CEO

“We’ve seen that gaining insights from these massive amounts of data remains a significant pain point and priority for many industries, such as defense, geospatial, video security, or drone surveillance.” Synthetaic’s AI solutions for unsupervised learning and data analysis put us in a strategic position in a growing technology field”， Jaskolski said.

AI need human help

Jaskolski is a graduate of the Massachusetts Institute of Technology (MIT) and former director of technology at National Geographic. He has dived in icebergs in Antarctica, dived 12,500 feet below sea level to explore the wreck of the Titanic, led a helicopter to map the Neapolitan side of Mount Everest, ventured deep into flooded caves, cataloged victims of Mayan sacrifices and ice age bear bone frames.

So what led a globetraveller like Jasolsky to create a synthetic battery despite his own mortality? It was simple: he realized that AI had the potential to help classify the world’s information, but its development was hampered by the need to annotate data manually.

“Human tagging is the standard for AI training,” Jaskolski said. “As AI models get bigger, they get better, but they need more data to train because they have more and more internal tunable parameters.
Synthetaic, launched in 2019, provides a tool – Fast Automatic Image Classification (RAIC for short) – that aims to automatically analyze large datasets, namely satellite images and videos that do not contain labels.Many AI models are trained by labeling data. For example, a model given a large number of images and annotations for each breed of cat will eventually “learn” to distinguish between a bobtail and a shorthair. In contrast, the user provides RAIC with a single image, and RAIC locates that image elsewhere in the dataset.
“RAIC means being able to handle scarce or complex datasets, accelerate the development of artificial intelligence, and improve predictive modeling without being limited by the quantity or quality of the data,” Jaskolski said. “This makes RAIC a strategic asset to drive innovation, operational efficiency and competitive advantage, especially in use cases where data is a bottleneck for AI adoption and implementation.”

Also read: Is big data the future of AI?