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.”
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.
“Alternative methods to traditional AI / ML are poised to disrupt today’s standards.”
Read the full article HERE.
Contact us if you have an 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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The Montreal AI Ethics Institute is an international non-profit organization democratizing AI ethics literacy. We equip citizens concerned about artificial intelligence to take action because we believe that civic competence is the foundation of change. You are our best shot at a future where humans and algorithms bring out the best in each other.
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