Chatbots, now omnipresent, face a crisis of accuracy and security highlighted by recent public blunders at Air Canada and Chevrolet, where bots made unintended promises. Air Canada's attempt to deflect blame onto its bot was rejected by authorities, underscoring a harsh reality: companies are indeed responsible for their bots' actions. Despite the prowess of language models like ChatGPT, their inherent nature to occasionally fabricate with confidence poses unique challenges. Drawing lessons from cybersecurity, this article explores four advanced red team testing strategies aimed at reining in bot misstatements and significantly bolstering chatbot security.
How to Spot Great AI Opportunities in Your Business
You probably suspect AI can dramatically improve your business, but perhaps you are not sure exactly how -- perhaps you are even worried that a start up or tech company is gunning for your business. Ask yourself two questions: 1. what are the high level business problems that could be transformational if solved and 2. which business problems are feasible to solve with AI to some meaningful degree.
10 Reasons Why AI Innovation Fails According to an AI Consultant
As an AI Consultant, I get a front row seat to AI and innovation; I repeatedly see when it succeeds, and when it fails. I’ve been building AI and machine learning based systems for over 20 years, in many different companies, cultures, and problem domains. During this time, I’ve noticed a number of patterns that cause the deployment of AI systems and AI powered features to fail.
Predicting Covid-19 like the Weather, Using AI to Harness a Network of Health Sensors
The national weather service operates a massive sensor array including sensors located on weather balloons, in airplanes, on land, in sea buoys, and from satellites. Just like a confluence of variables can indicate a hurricane is on the way, we believe an infectious disease forecasting service powered by AI can predict the likelihood of a new wave of C19 and other infectious diseases.
Understanding Conversations in Depth through Synergistic Human/Machine Interaction
Every day, billions of people communicate via email, chat, text, social media, and more. Understanding the conversation begins with understanding one document. Once we can teach a machine to understand everything in a single document, we can project this understanding up to a collection, thread or larger corpus of documents to understand the broader conversation.