For those of you who follow the series 'Mad Men', you may have heard about the twitter story around it where characters from the series appeared on Twitter. After having been closed down by the company AMC behind the series as they were not endorsed, they were then reinstated after the following outcry from fans.
The fans behind the twittering 'Mad Men' discuss in an article on CNet their experience and the lessons that can be learnt from it. Two interesting quotes from the article:
First, she [Carri Bugbee] said, producers should strive to reserve the Twitter accounts for all the characters in whatever show or film they're making. "I can't believe that any of us would have to say that," Bugbee said, adding that for fans, "if you have a favorite TV show, you could probably go reserve (any character's) name on Twitter" even now.
"Ross said there are further lessons producers and marketers need to draw from the "Mad Men" Twitter experience. Perhaps most important, she suggested, advertisers need to "stop siloing." In other words, they need to understand that to get their message out, it is necessary to spread it across a wide variety of platforms"
Update: take a look at an interview of Carri Bugbee's interview on Ad Age
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 […]