explainable ai

AI is a somewhat underspecified term and can mean many things to different audiences. However, in business, boardroom execs today are still seeking answers to what AI will truly deliver to their business. Many have spent millions of dollars, yet few have seen significant real-world impact and ROI. One exec recently remarked “In the current […]

Are you ready? Governments and regulators now have well established regulations in place for managing data including the security and privacy implications associated with these.  However, as AI is now being regularly deployed within organisations, countries around the world are looking at how it should be regulated.  Some regulation builds upon (or is inherent within) […]

Today more than ever enterprises are seeking immediate value from AI investments. Most enterprises have made significant AI investments yet continue to struggle with real world implementation of “why did the machine make its decision” and next best action. In order to deliver real-world AI, the fundamental and critical phases of ideation, experimentation, engineering and […]

When looking at the forecasted revenues of the AI market worldwide from 2018 to 2025 we see from $10 billion in 2018 to $126 billion in 2025. The business upside is significant, however with potential growth of this magnitude, risk and government regulation was inevitable. Governments around the world today see AI as a great enabler to […]

Contemporary machine learning systems are different from traditional rules-based systems. With these traditional systems a series of rules were written that matched up with the desired operation of the system. In machine learning, the system learns how to make decisions from the data that is presented to it. Whilst this has many advantages, a very […]

Explainability within Enterprise AI is critical, whether this is to comply with regulation such as the GDPR, for auditing your AI systems, for feeding back to customers, for getting buy-in from internal teams and boardrooms or actioning on the decisions made by the AI. This message is becoming very apparent, but how does this high-level […]

AI industry analysts state that AI projects and their real-world success metric is less than 8%. This is a staggeringly low number given the billions of investment and big bets being made. Unlike other traditional software implementations, AI has always been vague and it has been accepted that machines are correct in making their decisions. […]

Chatterbox Labs’ Explainable AI software works with any AI model in any AI system, which our enterprise customers use for: Validating continual AI model business relevance Auditing, tracing & explaining any AI model (text, image and mixed data) Exploiting & reinforcing existing AI assets Complying with global government AI regulation initiatives Conforming to a unified […]

With the plethora of AI Clouds, engines and platforms available to the enterprise everyone has an opinion on which is best to strategically lock into. AutoML still appears to still be the flavour of the day, however Chatterbox Labs see a different dimension to AI. Explainable AI by 2023 will be pivotal to any enterprise […]

Chatterbox Labs’ patented Explainable AI (XAI) product can explain any AI model. This is critical because it means that, rather than replacing all of your years of AI investments with a new explainable model (that may not achieve the performance that the existing system can), our XAI works hand in glove with your existing system […]