Nowadays researchers and scholars of all ages and specialization find themselves struggling with mailboxes pestered with invitations to conferences, invitations to submit papers to journals, invitations to participate in the editorial board of journals, invitations to receive prizes for this or that reason; and of course, 99% of the origin of these invitations are individuals running fake conferences, scam, or predatory journals. Spam filters are not extremely good at distinguishing good and bad invitations, so if one wants to avoid discarding prestigious opportunities the only option is a painful manual screening.

The 10th congress of the USERN organization was held on November 8-10 in Campinas, Brazil. Some time has gone by, so it is due time for me to report on the event. I could not attend in person for a cause of force majeure, but I was connected via zoom, and I also delivered two recorded speeches plus one talk in one of the parallel "virtual session" that were run via zoom in the evenings (CET) after the in-person program of the day was over. 

I am moving some baby steps in the direction of Reinforcement Learning (RL) these days. In machine learning, RL is a well-established and very promising avenue for the development of artificial intelligence, and the field is in rapid development. Unfortunately I have been left behind, as I never really needed to fiddle with those techniques for my research. Until recently.

Truth is under attack. It has always been, of course, because truth has always been a mortal enemy for those who attempt to seize or keep power in their hands. But the amplification of the phenomenon by today's information technology is extremely worrisome. AI today can generate fake videos and images that even experts have trouble flagging as such. This, combined with the different news value and propagation potential of false information with respect to typically less attention-grabbing true facts has created an explosive situation. What to do?

Today is November 1st, the day dedicated to the dead, and I am in northern Sweden where daylight is scarce this time of the year. The two things conjure to arise thoughts of a darkish nature. 


[Above, a lousy picture taken this evening in a cemetery in Gammelstad, close to Lulea, in Norrbotten, Sweden. Sorry for the bad quality... Yet the landscape with all those small lights was really inspiring.]

Having interacted for a few months with ChatGPT 5 now, both for work-related problems and for private / self-learning tasks, I feel I might share some thoughts here on what these large models can tell us about our own thought processes. 

The sentence above is basically giving away my bottomline from square one, but I suppose I can elaborate a bit more on the concept. LLMs have revolutionized a wide range of information-processing tasks in just three or four years. Looking back, the only comparable breakthrough I can recall is the advent of internet search engines in the early 1990s. But as exciting and awesome this breakthrough is, it inspires me still more to ponder on how this is even possible. Let me unpack this.