Stephen Downes

Miguel Guhlin shares this announcement on Perplexity Pages, touted as "a simple way to turn your research into visually appealing articles. With formatted images and sections, Pages lets you share in-depth knowledge on any topic...log into your Perplexity account, head to your Library to create a Page. Choose your topic, and let Pages guide you through the content creation process on desktop." Here's his can sample page.

Paul Wiltshire, we are told, "argues that we need a proper debate about student numbers." By this he means 'fewer'. His main argument is this: "it is obvious that the majority of the jobs that society needs performing (a high proportion of which are manual or administration based, low to medium skilled, or managerial – but not actually academic) don't actually need the incumbent to have spent their first three or four years of their adult life studying an academic course." He also argues against the idea that it is the academic education that explains graduates' higher pay: "the university cohort will be those who are not only on average more academic, but also more hard working and more conformist – so it is little wonder there is a career pay premium for this cohort." These are both stunningly bad arguments but not at all surprising in a post that argues against access to education.

I'll probably move on from this type of post in the future, but for now it remains relevant, especially for educators. Shannon Vallor writes, "the most ordinary human does vastly more than the most powerful AI system, which can only calculate optimally efficient paths through high-dimensional vector space and return the corresponding symbols, word tokens or pixels." Human intelligence, argues Vallor, is fundamentally different from AI. I think it's a bit of a straw man to point to the obviously limited capacities of today's AI. The argument is, "Why would a machine that works on silicon not be able to perform any of the computations that our brain does?" And what would the brain be doing other than computations?

I think there's a danger in speculating about biomechanical motives for actions. Such is the case here. Here, Mark William Johnson is responding to Michael Foot, who responds, "we are here to provide for all those who are weaker and hungrier, more battered and crippled than ourselves." Johnson, referencing epigenetics, suggests, "The uncomfortable fact may be that without the cruelty and selfishness, there can be no progress." That would be sad if true. But I am convinced that reality is rather more complex and subtle, at least to the extent that we can at least imagine doing away with cruelty, if not also selfishness.

This is from a few days ago but I want to make sure I don't forget it. Alan Levine, channeling some Mastodon discussion, points to a nice trick to get right of all the garbage in Google search engine results (by 'garbage' what I mean is all the stuff Google puts in the results page that isn't part of the search results). In particular, if you add '&udm=14' to the end of the URL on your results page, you can force it to display search results only. I do a similar thing with my personal Start Page, where I've created a small form to handle that for me. I also use '&tbs=qdr:y' to force it to return results only from the last year, so I'm not getting out-of-date results.

I've had discussions with people from time to time about the difference between networks and systems, and to me one of the main differentiators is this: a system has a purpose, and a network doesn't. Sometimes this difference can be difficult to parse, and this phrase, which originates with Stafford Beer, sits right along that dividing line. The idea that "The purpose of a system is what it does" (POSIWID) allows us to retroactively assign an intent to a system, even if it was not designed that way. A network, by contract, does not imbue cognitive properties; the structures and processes are purely physical, with no cognitive guidance whatsoever.