RealityEngines.AI Rebrands To Abacus.AI, Secures $13 Million In Series A Funding

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  • It is also open-sourcing three techniques to de-bias algorithms and is introducing a new model showcase service
  • Abacus.AI is going to use the funds to scale the service, gain early customers, and grow its research team

Abacus.AI, formerly RealityEngines.AI has announced the general availability of first fully autonomous AI service. The company also announced $13 million in series A funding led by Index Ventures. It is also open-sourcing three techniques to de-bias algorithms and is introducing a new model showcase service.

The company said that this will allow developers and data scientists to share and compare deep learning models and metrics. It will enable businesses and enterprises to build cutting-edge real-time deep learning systems that can make a 5-15 per cent impact to the bottom line as per the company. Abacus.AI is going to use the funds to scale the service, gain early customers, and grow its research team

Total funding to $18.25 million

This funding brings the total funding to $18.25 million. It was led by Mike Volpi from Index Ventures, with participation from Eric Schmidt, Ram Shriram, Decibel Ventures, and Jerry Yang. Following the investment, Mike Volpi and Ram Shriram will be joining the company’s Board of Directors. .Mariam Naficy, Erica Shultz, Neha Narkhede, Xuezhao Lan, and Jeannette Furstenberg also joined in the round.

Mike Volpi, partner at Index Ventures said, “We are excited to announce our Series A investment in Abacus.AI. As we’ve spent the last few months working with them, we are even more convinced that their vision of democratizing AI is spot on, and that they are going after a massive opportunity. Bindu Reddy, Arvind Sudararajan, Siddartha Naidu, along with their extraordinary team, are the right people to pull this off and the entire Index team is honored to be supporting their journey.”

Best neural architecture given a particular dataset

Abacus.AI helps organisations plug and play state-of-the-art deep learning systems into their existing customer experiences and business processes. It said that its research team has invented a technique that finds the best neural architecture given a particular dataset and use-case. Once the neural architecture is identified, the system trains the neural net model and provides a simple prediction API that customers can use to embed predictions into their apps or websites.

The company said that during the beta phase, Abacus.AI worked with 1500 beta testers and tested hundreds of datasets to refine the accuracy of the deep-learning models created by their AI engine. The company is also launching a model showcase feature where users of Abacus.AI services can share their models with the rest of the AI and data science community. It has also published 20 models trained on public datasets. Accuracy metrics on these models are comparable to those from models that have been hand-crafted by data scientists said the company.

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