CharonY

I am still not sure about that. The argument for AGI was that it will be able to improve itself almost infinitely. Perhaps this is a separate discussion, but I am unclear regarding limits and boundary conditions. There are, for example, already now hardware and energy limits. As the system works entirely different from how our (biological) mind works, I am not sure where the respective limits and differences are. But I think beyond that, our abilities to learn has already been changed (I would say degraded) by other things (including cellphones as portable dopamine delivery systems) and for a long time we really haven't found a teaching system that can address that.

My thinking has slightly shifted on that matter. Originally I was in the camp of teaching how to think rather than feed them info. But along the way it seemed that folks became incapable a) to find any information, despite increasing ease and b) have no idea how to handle information and c) do not benefit from training in problem solving as they used to. I think that at least some level of memorization and other boring routine exercises actually somehow strengthen mental capacity to due the trickier parts. And perhaps more importantly I think (I have no experiments to support it), it does counter the ubiquitous deterioration of attention span a bit. I am not joking when I say that I have students who by the end of the sentence do not remember the start of it anymore.

No doubt and higher education in general was traditionally geared towards understanding, not repetition. The commercialization of the process has made it harder to maintain. Depends a little bit. In the Chinese system there is still a lot of emphasis on memorization, yet they fare quite a bit better than their North American counterparts. One of the reason I think is the effort put in. I.e. emphasis of effort over efficiency. The former has the chance to train other cognitive abilities. The latter leaves more time for TikTok.

If there is access to LLMs somehow (say, smart glasses) then the answer is no. The other issue is that over the last decade or so, we typically always use a mix of memorization question to deeper question. An easy way to figure that out is to make an oral exam based on what they present, for example and try to figure out why they arrived at certain conclusions. The issue was always that (obviously) fewer get the reasoning part right, but even if folks fail, as long as they build a foundation (probed in part by memorization) over time they still can develop expertise to figure things out. I.e., it is a way to give students time to develop their thinking muscles without immediately failing them. As such, in higher classes the why questions traditionally were a higher proportion of the quizzes. Now, the issue, especially across NA is that high school (and probably already earlier) students learn exclusively what to put on a test without understanding the why. In fact, in their mind, the why is superfluous as it just adds baggage, after all the only thing you need is the right answer. And as there is a right answer for everything quite a few seem to think that trying to deduce it is wrong, you just need to know or find the answer (and weird as it is, before LLMs quite a few were turning to TikToks for answers). So, they do not even lack the skills, but even the awareness that reasoning skills are relevant. And they do get anxious and even angry when made aware as they feel the instructors are wasting the student's time by outlining the necessary background information. A common demand is: "just give us the correct answer and stop wasting our time." I.e. there is a lot going wrong especially in NA due issues with the education system (e.g. linked to tuition-based higher education), which, however, is part of a roughly global trend that indicates a general loss of reading, comprehension and overall competence. Papers are start to come out on this topic and they are a rather depressing read.

No, absolutely. However, in some forms of cheating (say, cheat sheets) they actually have to do some work. Being given the answer bypasses anything that could accidentally make you learn. I am more worried that not even starting to think but immediate turning to LLMs is increasingly becoming the norm.

Fair point. I just wanted to add that it is a bit scary how quickly also (or perhaps especially) young folks abandon their own learning and submit to the perceived superiority of AI answers. It has been a quite a few times when students were arguing about something and it turns out they were referencing ChatGPT, often not realizing that it runs counter to something that they were supposed to have learned. I found that whatever chat bot they are using, it is often hooked on what might be propagated as conventional wisdom with way more certainty that the lit actually allows. It is still very bad at figuring out biological nuances, but unfortunately we can already see how it erodes student abilities.

Apparently I have no idea how Langobardic art looks like.

My thinking goes a bit into a different direction, and I might be totally off. However, at least in my field, insights are rarely gained by extreme creative thinking about a problem. Instead, a lot is empirical, based on experiments you conduct, which provides unexpected outcomes. I.e. major breakthroughs happened often serendipitously, and are often based on new experiences. Now, once we give the systems a body to conduct experiments, it may mimic that. But as I see experiments and experiences as a limiting factor I am not sure how much robotic plus novel AI can accelerate discovery, say over an army of grad students, especially if the latter have access to robotic pipetting stations and other forms of automation. I am old, so I may have been repeating that though many times over already, but in an area such as biology, where the unknown far outweighs the known, ideas are less relevant than the resources to try out things. Edit: there are areas of exception in which computational approaches are are already heavily used, e.g. for big data analyses, and here the role of ML and other models are going to be highly relevant, of course. I think what I trying to express is how important experiences with reality (experiments, field observations, etc.) are for gaining novel insights.

I also saw a pre-print somewhere which suggested that some a significant proportion of information generated by AI chatbot originated from sources like Reddit. Findings such as these do make me question the claim that somehow an AI will be able to answer all questions we have.

I have seen terms like model collapse. For example Shumailov et al. published a paper on that (Nature 2025).

I got a biphasic distribution on geography, it seems. Either dead on (probably the easy bits) or half a continent away (but strangely, the precise time period).

Hmm a pin makes it harder. Otherwise I would have just blindly guessed "British Empire", Or perhaps "Mongol Empire". Edit: It is fun, though.

Tell that to the billionaires. Or perhaps it ain't cheating if you are making the rules.

I think that train has long sailed. The cows have left the station and the barn has been converted to a redneck data center. I might need more coffee.

Peas in a pod. In a way FIFA found out earlier that if give the masses what they want, you can be as corrupt as you like. Trump turns everything more to shit, as in addition to the utter lack of morals there is also staggering lack of basic competency.

My working hypothesis is that we all got sucked into the dumbest possible timeline where satire has become reality.

It depends on what the charges are, I presume. The claim seems to be that he deliberately ripped up the sealant causing damages in excess of $1,000 (threshold for felony charges, I assume). It passed a grand jury, so the substance has now to be demonstrated in court.

The thread is going exactly where I thought it would be going.

Chickadees might believe so. Well, specifically spatial cognition that is. https://doi.org/10.7554/eLife.110905.1.sa3 Branch et al. 2026 eLife

DNA and RNA both just encode the sequence of amino acids in a protein. During protein biosynthesis, the mRNA is introduced to the ribosome, where the assembly of the proteins happen (and includes also tRNA as the carriers of the amino acids, as well as a few other element). This whole process can nowadays be done cell-free using a mix that basically are lysates of bacterial or eukaryotic cells containing ribosomes, as well as polymerases (to transcribe RNA from DNA) and so on. So in essence, by adding the right vector (basically DNA) you can produce proteins in a vial. You can easily buy those as ready-to-use kits. The main difference here is that they are using a defined set of purified 30-something proteins rather than lysates, making it costlier, but also better defined. Edit: because of that limitations I think we can infer very little mechanistically about early life. However, it could be a way to explore certain aspects of it.

Protein biosynthesis is facilitated by putting in E. coli proteins (i.e. the whole machinery) into it. It is an extension of pure in vitro models (where the same reaction essentially happens in a vial), with some interesting elements of encapsulation. It is still not tackling the tricky bits, but it is more systematic as other approaches.

Or projection.

There are proteins that modify RNA at multiple levels, some arose with metazoans, others are way older. From memory, the oldest systems likely originated from defense against mobile genetic elements. The role has diversified than over the evolutionary history. No, in the broadest sense it is not much different to any other (homeostatic) regulatory mechanism and/or RNA machinery. On the molecular levels our cells have a massive amount of mechanism to react to environmental and intrinsic signals, RNA editing is not really different from that. These mechanisms are part of any organism's ability to respond to their environment. It is therefore important to acknowledge that each of our cells has a massive biochemical flexibility and adaptability and they are not simple machines that blindly run a fixed program. However, these adaptations have certain boundaries though they are often ill-defined (think of it as the whole theoretical capability of the system). On the evolutionary scene, what really matters is whether and how the mechanisms for any of these mechanisms are encoded in the genome. The most common form of metazoans (including cephalopods) is mediated by ADAR-family proteins, for example, which are encoded by their corresponding genes. I think the issue here is that OP's idea of evolution is not precisely mainstream and there is also a somewhat artificial distinction between humans and "wild" animals. So one could draw parallels, but I think they might be largely semantic. One could argue, for example that the ability to create eyeglasses is fundamentally present in the genome in the form of brain development, formation of eyes that work in a way where lens correction makes sense and perhaps arms and hands allowing us to build things. But it feels more like a philosophical than biological distinction. And one should probably also be very clear on the relationship of concepts such as selective pressure, stressors and stress adaptation. For example, heat is a stressor but let's say in a particular habitat, it is very easy to escape heat stress by behavioural changes (e.g., plenty of areas to cool down). The question is then whether those behaviours have a genetic basis (e.g. hard coded to find cool spots) or learned. The latter is complicated as learning behaviour of course does have a genetic basis (e.g. brain development) but finding a link to natural selection (e.g. did heat stress changed the likelihood of certain allele frequencies related to brain development) is very difficult to tease out. In another example, let's say a mechanism has developed over the evolutionary history and now all members of the species now have sweat glands. Let's assume for simplicity's sake that this is determined by a single allele and all members of this species carry that allele (i.e. it is fixed). This is a strong indicator that there was strong positive selection for that allele (as all other alleles got lost eventually). But now that they have adapted, the natural selection is not suddenly gone. If it was, the allele would no longer be fixed, i.e. selective forces maintain it. Not sure whether that makes sense but that is just what quickly comes to mind.

In short: no. RNA is not part of the genome. RNA is basically a transcript of DNA. Depending on the type of RNA they can be regulatory, structural or part of protein biosynthesis (in the form of mRNA). RNA editing happens a lot especially in eukaryotes as our genome contains introns and exons. The latter is part of mature RNA whereas the introns are spliced (removed). As it turns out, there is quite a bit of additional processing that can happen and a lot of it is regulatory in nature. E.g., mRNA can be produced, but modified so that it is rapidly eliminated if the coding proteins is actually not needed. Or they can modulate activity, changing overall RNA turnover, help the immune system to distinguish own RNA from viral ones etc. Often these modifications are in non-coding regions, but not exclusively so. So RNA editing is a somewhat common process in many eukaryotes. IIRC the study showed simply that cephalopods had a high level of modified RNA and I think the rate in coding regions was also higher. I.e., it is more a quantitative rather than a qualitative difference. And most importantly, RNA modifications are transient, they affect the current active RNA pool but they are not inherited. I.e. we are talking about adaptation to a change in environment in a very short time frame (e.g., reaction to heat stress), but not something that happens on evolutionary (or generational) scale.

I think here you are using your preconception to interpret what you observe. And unfortunately, I don't think your interpretation is accurate, regardless is one is on the spectrum or not. It seems to me that the key thing you are missing is that socialization is work and not an automatic process. If you observed folks carefully, you would notice some common elements like poking around on a variety of elements to find common ground to continue socializing. Depending on where you are on the spectrum, it can be very difficult to pick up on those cues, so for some it is harder than others. But in the end, it is a learnable skill. Hobbies, like any other interest, real or pretend, are means to to establish a communicative situation between otherwise strangers. Your ideal concept of "friendship" seems to be one that should arise without effort, just by being intelligent or altruistic somehow, folks should like you. I.e. it is a very self-centered view that the world has to react to your innate qualities, rather than the fact that one has to first make efforts in finding a common basis with other persons and spend efforts to interact. Again, it is a skill that can be learned and needs polishing. Depending on where you start it can be a lot of effort, but it is a necessary one. And that in itself is a rational process and importantly, it is a communal process. You do not make someone your friend, but it is a process requiring effort from both sides. As such, as part of ones own effort, it should become clear that the time investment is worth it. In that context, enjoying the same hobbies is a very easy pitch an again, very rational. If you enjoy your time with someone engaging in common activities (be it dancing, reciting poetry, geeking out on any topic) the effort to build friendship makes way more sense. Denigrating elements, such as dancing as irrational just makes you feel justified in your judgment, but it is actually easier just to acknowledge that it is something not for you and you need to look for something else to connect to people, rather than putting others down for their interest, even if they don't align with yours. As it turns out, people judge you for being judgemental.