The AI Hierarchy of Needs
Too Long; Didn't Read
As is usually the case with fast-advancing technologies, AI has inspired massive <a href="https://en.wikipedia.org/wiki/Fear_of_missing_out" target="_blank">FOMO</a> , <a href="https://en.wikipedia.org/wiki/Fear,_uncertainty_and_doubt" target="_blank">FUD</a> and <a href="https://techcrunch.com/2017/07/25/elon-musk-mark-zuckerberg-artificial-intelligence/" target="_blank">feuds</a>. Some of it is deserved, <a href="https://chatbotnewsdaily.com/machine-learning-ai-and-the-emperors-vest-32b7bdd99b58" target="_blank">some of it not</a> — but the industry is paying attention. From stealth hardware startups to fintech giants to public institutions, teams are feverishly working on their AI strategy. It all comes down to one crucial, high-stakes question: <strong><em>‘How do we use AI and machine learning to get better at what we do?’</em></strong>