UMNAI Disrupting Machine Learning Dynamics with Neuro-symbolic AI

In the fourth article of his “Ethical AI Start-up Eco-system” series, Abhinav Raghunathan, the creator of the Ethical AI Database (EAIDB) and writing for the Montreal AI Ethics Institute, explores and reports on EAIDB’s “Targeted Solutions and Technologies” category of companies. In addition to the vertical focused companies, this category also includes start-ups like UMNAI who are fundamentally altering Machine Learning (ML) techniques used in practice.

“In general, the momentum is somewhat shifting away from traditional ML to some of these alternative methods due to their apparent advantages.”

“Alternative methods to traditional AI / ML are poised to disrupt today’s standards.”

The article explores how UMNAI’s Neuro-symbolic AI as well as Causal AI and Federated Learning provide tangible, clear, and impactful advantages over classical systems and methodologies. Aside from delving into disruptive technologies like UMNAI’s and the barriers to adoption they face, Abhinav also examines trends in funding and the general outlook for the industry.

Read the full article HERE.

Contact us if you have as application that could benefit from UMNAI’s technology or if you’d like to learn more about the benefits of our Hybrid Intelligence technology and Neuro-symbolic AI.

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