AI News, Synthetic biology artificial intelligence

Synthetic Data Platforms for Training AI Algos Cheaply

This synthetic data, he adds, “assists in teaching a computer how to react to certain situations or criteria, replacing real-world-captured training data.” Bernard Marr, a futurist and self-proclaimed tech influencer, writes for Forbes that one way to create synthetic data is simply to anonymize real-world data by stripping out private information like names, addresses, and social security numbers. Other methods to generate synthetic data include using different AI techniques, computer games, virtual reality, and other types of software.

Conversely, machines can be used to create realistic representations of the objects, which can then be “manipulated virtually to create endless variations that reflect different characteristics in size, shape, and color of a hundred similar products.” Says Neuromation CEO Yashar Behzadi, “Thanks to synthetic data, companies only need 50% of their original, authentic training data to finish the formal training of their algorithms.

Neuromation is still developing its synthetic data generation platform and recently released its third-quarter report about its latest efforts: In one use case, the company is creating digital images containing simulated pigs for a client that wants to train an algorithm to track livestock, according to the story in Wired.

The company is also focused on churning out synthetic data for AI in healthcare. With offices in San Francisco, Europe, and Israel, Neuromation is helping enterprises across the world to build better AI models.  Founded in 2015, Berlin-based TwentyBN has raised $12.5 million, including a $10 million Series A in September.

At this time, the company isn’t using synthetic generation but actually employing crowdsourced workers to record short video clips for specific descriptions, such as a person doing a thumbs-down gesture.

While the company’s crowd actors aren’t out of a job just yet, the experiment showed that “synthetic data can be a useful complement to real data.” Founded in 2017, New Yawk-based AI Reverie took in an undisclosed amount of Seed funding in May, which included Vulcan Capital, the multi-billion dollar investment arm of Microsoft co-founder Paul Allen, who passed away in October, so hopefully, the startup already cashed the check.

(Too soon?) The young company builds photorealistic virtual worlds to closely mimic any real location for its clients, many of whom appear to be on an African safari, based on the video below: The virtual worlds replicate everything from weather to weather people, with fully annotated video.

Reinforcement learning is a form of deep learning that encourages a machine to find the best way forward to maximize a reward, though we’re not exactly sure how you reward a machine outside of 3D printed sexbots.

For example, the company can quickly create thousands of training images of an object in a specific physical environment by using an augmented reality app to produce hybrid images of virtual objects in real-world settings.

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