Stephen Downes

"Real-life learning ecosystems – networks that include classrooms, living rooms, libraries, museums, and more – may be the most promising approach for preparing learners for tomorrow," writes Gregg Behr. What's needed is "a collaborative ecosystem that sparks engaged, motivated learners by providing the tools, resources, and relationships that every young person deserves." I would say 'cooperative' rather than collaborative, and I would focus much more on public support for such an ecosystem (because private support would invariably commercialize it). Now for the other shoe to drop: "These ecosystems are not replacements for schools," writes Behr. But inevitably, they will be, as public education systems struggle with declining resources and increasingly complex societies.

As much as educational institutions may not want to talk about it, they to a degree depend on sales, in the form of student registrations. This article reconsiders the traditional 'sales funnel' which runs from awareness to consideration to action (it's called a funnel because the number of people gets narrower and narrower through each state). This article proposes a '4s' version of the funnel: streaming, which refers to the new 'always on' internet people have; scrolling, which refers to their browsing behaviour; search, which refers to their consideration of alternatives; and shopping, which refers to the actual purchase.

"The age of American Science is over, and it's not coming back any time soon," writes Alex Usher. "The opportunity exists, therefore, for ambitious universities to scoop up a fair bit of top new talent." He's speaking to a Canadian context, but of course the opportunity exists worldwide. And in Canada, since governments won't find new researchers, he suggests, universities should consider recruiting foundations to fill in the gap. The problem with this is that foundations have an agenda, and in a lot of cases that agenda lines up with the sort of thinking that led the U.S. into the position it's in now. There's a reason why we want public funds to support public education; it keeps the country from going off the rails.

George Siemens links to a couple new language models from China in his latest newsletter. First is Manus, "a general AI agent that turns your thoughts into actions" by deploying AI agents to do tasks for you. "Here's an example of a 'big tech stock performance' I requested," writes Siemens (noting it's hard to track how accurate the output is). Alsoi from China, Baidu launched its own "4.5-worthy LLM", Ernie. "Biggest difference between Ernie 4.5 and GPT-4.5? Ernie is 1% of the cost."

Molly White writes on the conundrum facing people who publish open access or free context: its use by companies in ways never intended by the authors: their content packaged into an ebook and sold on Amazon, or their code used to create a billion-dollar software company; or their art packaged into an NFT. Now (if I may say so) I have always expected this sort of thing, which is why I have always used and defended the use of the 'non-commercial' clause. White just sloughs off this response; "(and thus, non-free)". She says, instead, that we "we need to reframe the conversation to 'wait, not only like that' or 'wait, not in ways that threaten open access itself'." Well, yeah. But that's exactly what commercial use does. That's why I argue that 'non-commercial' is more free than the so-called 'free' licenses without restrictions. Image: Wikipedia.

If a human (ahem) can write a (sometimes opinionated) summary of an article they read online, then why can't an AI do it? I'm not sure, but that's the basis for this lawsuit between Brave (the web browser) which produces the summaries and News Corp (the evil media conglomerate run by Rupert Murdoch) which produces the stories. "Decades of legal precedent and practice confirm that it is not copyright infringement to index website content to maintain a search engine," Brave argues in its complaint to the federal district court. "Instead, it is fair use."