Stephen Downes

You'd think, with newsletters being "all the rage now", that I'd be seeing an increase in subscriptions. Why, early adopters "blogged here two years ago about the idea of writing a solo newsletter." But it's not so simple. What's actually happening is that a few platforms (most notably Substack) with some good marketing popularized the idea of bloggers and columnist using a 'newsletter platform' to write. There would be monetization, of course. You could also use WordPress (use the Noptin plugin) or Ghost but you'll have to set up or find a mail transport service (I use MailGun; I wrote my own client for it, but the WordPress plugin will do this for you). But hey - if you do think email newsletters are all the rage, you can still subscribe to OLDaily some 23 years after the first email left the server. Just saying.

"Online doctoral candidates constitute an ultraperipheral population in the academic landscape," argue the authors. "Online delivery was viewed as both a blessing for the accessibility it enabled and a curse due to pervasive feelings of isolation and virtually non-existent peer networks." I would suggest that these peer networks exist - just look at GO-GN - but the students' "strong drive for participation, sometimes matched by the supervisor but rarely supported by the institution" renders them invisible. In any case, it would take a study of more than 24 part-time online students to reveal anything in the way of trends (you can't say, as these authors do, that "they often feel invisible and neglected by the institution" - you don't know that and you haven't shown that). But to the extent that graduate students are sometimes not able to find online support networks, that is indeed something that should be addressed.

The actual news here (because we've covered similar work in the past) is that the researchers probed "the supramarginal gyrus, a region of the brain never before tested with brain–computer interface (BCI) technology." The accuracy of the six-word test wasn't great - in one patient, barely above what would be accomplished by chance (23%, as compared to the one-in-six (15.5%) a 50-50 coin flip would produce). This part of the brain, also known as Brodmann area 40, and (per Wikipedia) "interprets tactile sensory data." Here's the full study by Sarah K. Wandelt and colleagues. Implications: first, that computers could (potentially) read thoughts; and second, what they 'read' is the words as they are 'spoken' in one's inner voice (which, I would suspect, more or less clearly articulated in different people).

"It's amazing," writes Kevin Purdy, "and a little sad, to think that something created in 1989 that changed how people used and viewed the then-nascent Internet had nearly vanished by 2024." The think in question was a search engine that allowed users to find documents made available through anonymous FTP services. But it has been rescued. "Not only did The Serial Port rescue the last working version of Archie (seemingly a 3.5 beta), but they posted its docs and now run an actual Archie server on an emulated Sun SPARCstation 5." Takes me back.

Donald Clark has already gotten a couple posts out of Google's EdAI announcements. This paper (86 page PDF) presents Google's efforts to "translate high level principles from learning science into a pragmatic set of seven diverse educational benchmarks" and to "develop a new set of fine-tuning datasets to improve the pedagogical capabilities of Gemini." To develop, in other words, a generative AI tutor. It deserves a careful reading, and your impressions of the 35 page main text and 50 pages of supplementary material may vary from mine. While the paper is very up-to-date with respect to AI, it reveals (to me) a dated and psychology-heavy understanding of 'learning science' that seems limited to work on intelligent tutoring systems - but you can view their 'Pedagogy rubrics' in section 4.3.1. Saying, "the gen AI models that power most of the latest EdTech systems are not explicitly optimised for pedagogy" the authors state that they "focus on conversational tutoring because we believe that it is one of the most impactful and general use cases." This forms the basis for their LearnLM-Tutor, introduced in this paper. There's a ton of information in this paper, but a lot that is not said - the model was "trained on an offline dataset," whatever that means (they say they tried several), and no stats are reported.

This is another effort to find some human skill or capacity that is at least different, if not better, than AI. "There are compelling reasons why human curiosity is needed more than ever in the age of AI," writes Anne-Laure Le Cunff, "and they stem from the fundamental differences between human and AI curiosity." The post offers a framework that identifies three key aspects of curiosity - processing, perspective, purpose - and tries to show how different they are for humans as compared to AI (not that people would really think of AI as 'curious' in the first place). I don't think it works because the descriptions are too surface-level. How do we know 'hunches and instincts to produce serendipitous discoveries' are actually different from 'processes vast amounts of data to uncover patterns'? The same mechanism could produce both results.