In a recent discussion, we explored the intriguing capabilities and pitfalls of AI chatbots like ChatGPT and Google Bard, particularly in research contexts. These tools offer a wealth of creative responses but also underscore the importance of discernment, especially when accurate information is crucial.
By Amir Tabakovic Photo by Mak The original version of this article was published on Mobey Forum Blog Those who closely follow the digital trends impacting financial services will surely remember …
Moving fast and breaking things is extremely bad advice when it comes to privacy. The main reason why privacy turns out to be a killer of your data-driven innovation project lies in the fact that privacy is closely related to trust – the most valuable asset a financial institution has (to lose). But privacy protection stays tricky even if the banks don’t try to cut corners.
Three new privacy techniques finally allow banks to leverage the utility hidden in customer data while at the same time providing the highest level of privacy protection. Privacy protection can’t be used as an excuse to not innovate with data anymore. Innovations in privacy protection are the key to fixing data-driven innovation.
The original version of this article was published on Mostly AI’s blog Why Privacy Matters? “Knowledge is power” should be a familiar quote for most of us. But did you know …
Today’s barriers for adoption of state-of-the-art machine learning technology are no longer in technology but in our heads. ”We’ve always done it this way,” arises quickly even in machine learning projects..
