President Biden signed a sweeping executive order yesterday covering numerous generative AI issues, and it’s comprehensive and thoughtful, as well as lengthy.

The EO contains eight goals along with specifics of how to implement them, which on the surface sounds good. However, it may turn out to be more inspirational than effective, and it has a series of intrinsic challenges that could be insurmountable to satisfy. Here are six of my top concerns in a post that I wrote for SiliconANGLE today.

All in all, the EO is still a good initial step toward understanding AI’s complexities and how the feds will find a niche that balances all these various — and sometimes seemingly contradictory — issues. If it can evolve as quickly as generative AI has done in the past year, it may succeed. If not, it will be a wasted opportunity to provide leadership and move the industry forward.

A new version of the smarter shopping cart will be coming to a nearby market this fall. Thanks to various partnerships and technological innovations of Instacart Inc., the latest embodiment of what the company calls Caper Carts will be able to track purchases while shoppers navigate through the aisles. The goal is to make it easier for shoppers to skip the checkout lines.

But it’s a tough reach, given the complexities of the retail channel and how the items will be scanned and tracked. If it works, it could be a major time saver. If it stumbles, it could be another example of bad user interface technology that is presently in most grocery and other retail chains: automated checkout scanning lanes. I write about it for SiliconANGLE today here.

Back in January, Andrej Karpathy, who now works for OpenAI LP and used to be the director of artificial intelligence for Tesla Inc., tweeted: “The hottest new programming language is English.” Karpathy was only semiserious, yet he has identified a new career path: AI chatbot prompt engineer. It could catch on.

The term describes the people who create and refine the text prompts that users type into the chatbot query windows — hence the use of English, or any other standard human language. These types of engineers don’t need to learn any code, but they do need to learn how the AI chatbots work, what they’re good at doing and what they’re not good at doing.

I interviewed several experts about whether the discipline will become its own career path in my post for SiliconANGLE here.

The growth of ChatGPT and other chatbots over the past year has also stimulated the growth of software that can be used to detect whether a text is most likely to originate from these automated tools. That market continues to evolve, but lately there is some mixed news that not all detector programs are accurate, and at least one has actually been discontinued.

I examine two different academic reviews of several of these detector tools, and how they have failed under varying circumstances, for my post for SiliconANGLE here.

A small Minneapolis mainframe computer software startup is poised to change the way enterprises use and share data across the cloud.

Virtual Z Computing Inc. claims to be the first and only women-founded and women-led mainframe systems integrator in history. That is a bold position, but perhaps more important is its pair of revolutionary software applications called Lozen and Zaac that connect native mainframe data with various third-party distributed, cloud-based applications.

I explain how the company’s products fit into the future of cloud computing in this story for SiliconANGLE here. 

The U.K.’s National Cyber Security Center last week posted a joint blog with the nation’s regulatory commissioner’s office about the need for better cybersecurity breach transparency. They’re concerned about the unreported incidents, in particular ransomware cases, which are getting more dangerous, more prevalent and more costly. The situation creates a vicious cycle: “If attacks are covered up, the criminals enjoy greater success, and more attacks take place,” they wrote in the post.

In this analysis for SiliconANGLE, I look at the implications for designing the next generation of customer support systems using AI enhanced tools.