Mindtech Enables Automated Creation of Millions of ‘Synthetic Actors’ for Greater Diversity in AI – Jahanagahi
Categories
Artificial intelligence

Mindtech Enables Automated Creation of Millions of ‘Synthetic Actors’ for Greater Diversity in AI

Users of Mindtech’s synthetic data platform can now create millions of automated actors to train AI vision systems

Platform delivers greater data diversity – essential for reducing bias and improving accuracy in AI systems

SHEFFIELD, England, May 11, 2022–(BUSINESS WIRE)–Mindtech Global, developer of the world’s leading platform for the creation of synthetic data for training AI, has released a significant update to its Chameleon platform. The end-to-end platform now enables the automated creation of millions of individual ‘actors’, placed into virtual worlds, creating synthetic data for training AI visual systems addressing a wide range of markets, including retail, security, smart city and home. This news follows the recent announcement of $3.7 million investment round led by strategic partner Appen, the global leader in data for the AI ​​Lifecycle.

This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20220510006028/en/

Mindtech’s synthetic data platform Chameleon, featuring configurable actors (Photo: Business Wire)

Using Mindtech’s Chameleon platform to train AI systems lessens developers’ dependency on real-world datawhich is often scarce, time consuming to annotate and requires strict compliance to ever-changing data privacy regulations. Chameleon’s ‘no-code’, ‘self-serve’ platform allows AI developers and data scientists to quickly automate the creation of high-quality, precisely annotated and privacy-compliant synthetic data by building computer generated scenes and scenarios. Mindtech’s unique, behavioral-led, simulation platform leads to faster creation of relevant data, promoting an “intelligently engineered data” approach to training vision systems.

This latest platform release sees the introduction of configurable “actors” – automated photo-realistic avatars, who can act and interact within a given scene and scenario – and offers users a wide range of diversity options including clothing, hairstyles, glasses, face coverings, height, build, age, and skin tone. The synthetic data generated enables AI vision systems to recognize greater diversity, visualize crowds and detect individual actions more accurately.

View a video of actor configurations available on the Chameleon platform: https://vimeo.com/showcase/mindtechchameleon221

Chris Longstaff, Mindtech’s VP Product Management said, “This new Chameleon release was driven by customer demand for greater diversity in AI training datasets, to ensure robust solutions that better address corner cases and bias. The ability to rapidly create a dataset with required human diversity statistics, such as age, race, fashion and regional characteristics, is essential for creating bias-free AI systems that better understand how humans interact with each other and the world around them.”

Chameleon 22.1 is available for immediate licensing.

Mindtech is exhibiting at NexTech Week AI Expo Tokyo on booth 7-18 between 11th and 13th May.

Mindtech Global www.mindtech.global

Mindtech Global is the developer of the world’s leading end-to-end ‘synthetic’ data creation platform for the training of AI vision systems. The company’s Chameleon platform is a step change in the way AI vision systems are trained, helping computers understand and predict human interactions in applications ranging across retail, smart home, healthcare, and smart city.

Mindtech is headquartered in the UK, with operations across the US and Far East and is funded by investors including Mercia, Deeptech Labs, In-Q-Tel and Appen.

Interviews, media images and demos available on request.

View source version on businesswire.com: https://www.businesswire.com/news/home/20220510006028/en/

contacts

Cat Lenheim
[email protected]
+44 203 417 0717 / +44 7511 117587

Leave a Reply

Your email address will not be published. Required fields are marked *