By AI Trends Staff
In the black box problem in machine learning, data goes in, suggested decisions come out, and how the model arrived at its suggestions may or may not be explainable. This problem intrigued Prof. Anupam Datta of Carnegie Mellon University, who in 2014 with his PhD student Shayak Sen began researching explainable AI. At the same time, Will Uppington was among the founders at Bloomreach, which was trying to make black box machine learning models into a commercial product, and was running into similar issues around visibility into how models produce their answers.
Meeting each other in 2018, they decided to form the startup Truera in early 2019 to address the challenge. The company offers a Model Intelligence Platform, using AI explainability to power it. CEO Uppington recently responded via email to queries from AI Trends about the startup.
AI Trends: What business problem are you trying to solve?
Will Uppington: Machine Learning (ML) is exploding, but ML has a big flaw: it’s a black box. That means even when models work, data scientists don’t necessarily know why. This hinders data scientists from building high quality ML applications quickly and efficiently. It also becomes a problem when non-data scientists, such as business operators, regulators, or consumers ask questions about a result or when models break once they go live.
The science behind what drives outputs of ML models is called AI Explainability. AI explainability is the breakthrough technology that can address these challenges but it’s not enough on its own. You need a new class of software that analysts are calling Model Intelligence Platforms that leverage AI explainability, to address these problems throughout the model lifecycle: development, evaluation/testing, and monitoring.
AI Trends: How does your solution address the problem?
Uppington: Truera’s model intelligence software removes the “black box” surrounding Machine Learning (ML) and provides intelligence and actionable insights throughout the ML model lifecycle—enabling companies to improve the quality and accuracy of their models, boost stakeholder collaboration, and address responsible AI concerns including explainability and bias. Truera’s technology builds on six years of AI Explainability research performed at Carnegie Mellon University (CMU), which pioneered many of the methods that are becoming the standard for explaining popular ML models such as Tree models and Neural Networks.
AI Trends: How are you getting to the market?
Uppington: Truera is helping enterprise customers across all industry verticals including financial services, insurance, healthcare, pharmaceutical, manufacturing, and retail. Headquartered in the US, Truera sells throug
Source - Continue Reading: https://www.aitrends.com/startups/startup-truera-raising-money-to-get-ai-explainability-solution-to-market/