Following a link from Adviso I came across another article that explains how changing a button can increase revenues by $300 million. The form used was the simplest possible with the strict minimum. The general opinion and mine too until reading the article is that it is so simple they can't have issues with the form:
We were wrong about the first-time shoppers. They did mind registering. They resented having to register when they encountered the page. As one shopper told us, "I'm not here to enter into a relationship. I just want to buy something."
The designers fixed the problem simply. They took away the Register button. In its place, they put a Continue button with a simple message: "You do not need to create an account to make purchases on our site. Simply click Continue to proceed to checkout. To make your future purchases even faster, you can create an account during checkout."
Not exactly the same, but it reminds me of sites that offer PayPal as a means to pay in France. Via PayPal you can use your Amex whereas these sites that allow you to use PayPal don't offer you the ability to pay using your Amex. Furthermore when you choose PayPal and look at creating an account via the PayPal for France version there is no option to use Amex (well there wasn't last time I tried).
I question the reliability and accuracy of Generative AI (GenAI) in enterprise scenarios, particularly when faced with adversarial questions, highlighting that current Large Language Models (LLMs) may be data-rich but lack in reasoning and causality. I would call for a more balanced approach to AI adoption in cases of assisting users, requiring supervision, and the need for better LLM models that can be trusted, learn, and reason.
I discuss my experience with chatbots, contrasting older rules-based systems with newer GenAI (General Artificial Intelligence) chatbots. We cannot dismiss the creative capabilities of GenAI-based chatbots, but these systems lack reliability, especially in customer-facing applications, and improvements in the way AI is structured could lead to a "software renaissance," potentially reducing society's technical debt.
The article discusses the contrasting debate on how AI safety is and should be managed, its impact on technical debt, and its societal implications.
It notes the Center for AI Safety's call for a worldwide focus on the risks of AI, and Meredith Whittaker's criticism that such warnings preserve the status quo, strengthening tech giants' dominance. The piece also highlights AI's potential to decrease societal and technical debt by making software production cheaper, simpler, and resulting in far more innovation. It provides examples of cost-effective open-source models that perform well and emphasizes the rapid pace of AI innovation. Last, the article emphasises the need for adaptive legislation to match the pace of AI innovation, empowering suitable government entities for oversight, defining appropriate scopes for legislation and regulation, addressing ethical issues and biases in AI, and promoting public engagement in AI regulatory decisions.
Japan has made its ruling on the situation between Content creators and Businesses. Japanese companies that use AI have the freedom to use content for training purposes without the burden of copyright laws. This news about the copyright laws in Japan reported over at Technomancers is seen as Businesses: 1 / Content Creators: 0 The […]