Not to be combative, coming from genuine interest, I'd like to ask you why we should care? I study biology, and can think of a plethora of topics that we can study about human physiology that we don't understand and if we did would more directly lead to treatment of human diseases. That is not to say we need invest all resources towards this frontier but in the optimal scenario we must weight resource allocation to the potential usefulness of the discovery.

General knowledge is unpredictable. If you want to treat human diseases, explore the natural world, because a huge portion of the pharmacopea we have is in some way directly derived from general knowledge - the taxane family is derived from yew, sometimes when you explore easter island you find rapamycin, penicillin is a very old story of accidental primary research, it goes on and on. And many of the synthetics we have now are adaptations of an older drug with negative side effects to manage the side effects.

Hypothetically, in 100,000 years, if human activity has led to the death of everything not human on this planet and we ourselves are on the brink (effectively leading Earth to go back to square one) would you rather that, or humans end in 50,000 years but through conservation and study made way for other life on this planet that will eventually conquer space and some of the mysteries of the universe.

Obviously the timelines are insane but just as a thought experiment, I would suspect we would get different answers depending on who you ask, and thus the study, understanding and conservation of other life that shows a form of intelligence becomes much more important to some, whilst human preservation at the expense of all else is more important to others.

(I also recognise you aren't saying that by the way, but it's what came to mind when I read your comment. I personally think we have more than enough resources to do both. I'd also imagine we will learn more about ourselves and what's possible in medicine by studying other species.)

I don't think we have to understand the natural world to care about it. But I will go further haha: I think we _already_ prioritize human health and advancement above preserving anything about the natural world (unless we have identified that the preservation is advantageous for our own purposes.) And I reject this anthropocentric view, which is I suppose where we might differ :)

From a purely utilitariatic POV, understanding your environment helps avoiding mistakes that mess it up which then indirectly impacts you too since you depend on your environment. So, more understanding improves policy making.

Second, what people know is often valued more. If you can tell people about the environment then you can create a fascination and make them value their surroundings more, maybe causing them to think twice before dumping trash mindlessly in the forest or voting for the next guy who wants to expand fracking operations. And in order to tell them, you first need to understand it.

Third, it can give you material for creating useful tools or medicine which then improves lives, like vaccines or airplanes (which we wouldn't have without curiosity about birds).

Apart from that, it's empathy too. Animals can suffer and causing them suffering is usually against empathy people feel. More understanding helps with that. (It's not too long ago that the prevailing view of "that's just a fish, they don't feel anything, so I can eat them even though I'm vegetarian" was challenged and slowy overturned.)

And finally, beauty. Nature is just beautiful. Compared to a dead rock like mars, it's absolutely amazing what we have around us.

I hope these five reasons give you some perspective as a biology student.

I wonder, what made you choose that field of study?

Animals feel pain.

Let’s raise them humanely, kill them swiftly, and use they wholly letting nothing go to waste.

This is an entirely reasonable ethic.

"usefulness" being the keyword here. I agree that the investment of resources goes towards the "usefulness" as in, there is a profit to be made here "usefulness" ¯\_(ツ)_/¯

I believe their argument is weak but, I think it is a fair assumption that the average ride share driver is safer than the average driver. That is to say the average driver is unsafe due to the fact the average driver is the set of all people which includes the set of drunk drivers whereas we can generally assume that set of rideshare drivers don't, especially while on the clock.

I agree that these cases are ridiculous to blame on the waymo entirely, but to give logic to their reasoning here you're unsure if on average the 1.3 fatalities per 100 million miles (FPMM) may also be on average ridiculously not the drivers fault as well. Perhaps if you were to throw out all ridiculous cases you'd have an average of CDL's having a 0.3 FPMM vs Waymo's having 0 FPMM.

The nuance you describe at the end is the better interpretation: fatalities per mile driven is a useless metric since it's such a rare occurance and incredibly circumstantial that it cannot be used as a meaningful comparison metric for safety.

It also gets better depending on the medical services nearby and there competence. So having more competent medical services in cities, lowers murder statistics and car-fatalities. Thus the actual accident rate would only be visible in the countryside.

If we want to get closer to the "real" number, we would also need to account for mechanic failures of the car, wildlife, and suicide. We don't usually attribute people jumping in front of trains as the fault of the person driving the train. Fatalities per mile driven may very well be biased in favor of waymo that has nothing to do with safety of drivers, which in turn create uncertainty when trying to estimate the statistical result of making all cars Autonomous. For example, car owners can have a higher variance in maintenance than waymo, they can use the car in areas with more wildlife than city traffic, and they can commit suicide through other means than personal being behind the wheel (suicide statistics is itself quite complicated).

Um, in those two examples where it was ridiculously not waymo's fault it was still absolutely the fault of a human driver. I'm struggling to imagine a significant amount of cases where it's ridiculously not the fault of any human driver.

Thats why he specifically called out CDL drivers, or in another part of this thread they talked about rideshare drivers. Certain segments of humans likely approach the same rates as the driverless cars.

While it is a cool technical advance to see, its use case is probably niche. One of the biggest things people say about photography is lighting. In general, if you can get more photons onto your imaging plane, you will have a better picture. This is why phone cameras, despite advertising 100s of MPs, still fall short. For the same field of view and capture conditions, fewer photons are collected because phone sensor sizes are much smaller. This is a physical limitation that cannot be overcome.

Now given that they already have a lower photon budget, you now want to add aperture control, which when stopped down physically reduces the amount of light from the scene that reaches the sensor. Thus you need to compensate for these lost photons somehow, so gain will probably have to increase quite a bit, but then you get noisier, grainier photos. This then leads to the suspicion that you will need some sort of AI denoising or computational processing to recover some of that lost image quality. Though of course you can comp in other way such as exposure time (they can make big wins here with their stabilization) and tons of lighting.

Also a phone already starts with very deep depth of field because again smaller sensor size thus smaller focal length etc. Most images at their lower f stop is already in focus. So the ability to reduce aperture or simulate shallow DOF is trying to give users more of the creative control that larger sensor cameras naturally have (need to manipulate because of their larger sensor size) and doesn't make much sense to me.

What compact camera would you recommend to get to take pictures that look noticeably better than iPhone’s? I mean without running around with a bag of lenses.

>Also a phone already starts with very deep depth of field because again smaller sensor size thus smaller focal length etc. Most images at their lower f stop is already in focus. So the ability to reduce aperture or simulate shallow DOF is trying to give users more of the creative control that larger sensor cameras naturally have (need to manipulate because of their larger sensor size) and doesn't make much sense to me.

Totally agreed. I wonder if it will make 180-degree shutter angle video easier to achieve. The only way to achieve this on current iPhones during the day is using a pretty strong ND filter.

The iPhone 18 Pro main camera is f/1.48, which is half a stop wider than the f/1.78 main camera on the 17 Pro. An f/1.48 fixed aperture would probably not be ideal (less depth of field, more revealing of lens aberrations) so there is a real light gathering advantage to the variable aperture.

>Also a phone already starts with very deep depth of field

Fairly deep. You can easily see background blur on a modern iPhone camera if you focus on something close. The very fact that the cameras all have variable focus shows that depth of field isn't as deep as all that. The extra depth of field from a narrower aperture could certainly be useful in some cases, such as landscapes. Here's a question for your favorite LLM:

"If I am shooting an iPhone 17 Pro main camera, what aperture would I theoretically need to get perfect focus from 1.5 meters to infinity, assuming a CoC suitable for a 12MP shot?"

Answer: about f3.2 if you manage to focus at the optimum hyperfocal distance.

>which when stopped down physically reduces the amount of light from the scene that reaches the sensor

As you say, this is only the case if you can't increase the exposure time to compensate. In daylight you will often have plenty of latitude to do so, even without image stabilization. Typical daylight shutter speeds at f/1.78 can be around 1/1000 at base ISO, so there is plenty of room to increase exposure time by 2-3 stops in those conditions.

Am neurobiologist and I don't buy the "full" argument, its much more likely a brain aging thing.

The brain, before your born, in GW25 (gestational week 25) has finished growing all the neurons you're basically [we can talk about this later perhaps] going to have for the rest of your life. At GW25 current estimates say you have ~86 billion neurons. Now the timing for this next part is a bit unsure but your body doesn't need anywhere close to 86 billion neurons, so at some point as early as early adulthood you start to lose 85,000 neurons per day pretty steadily until you die. Now neurons are not the end all be all because connections are potentially what really matter but that is to say that the neurons that you have after GW25 are the neurons you basically have. Now going onto synaptic connections where things start to matter more. Now synapses form and then get pruned all the time its natural. But the rate of formation and the rate of pruning is not the same at all times of life. Now from a raw number of synapse scale we see a tipping point at around 16-26 years old (debated hence the big range) where the number of synapses start to go down, indicating that the rate of pruning is now outpacing the rate of formation. [It does seem however that the dysfunction of the rate of pruning i.e. not enough ends up with consequences like schizo or asd {autism}]. There is another factoid that the rate of decline seems to stay relatively stable until you hit ~60 and then synapse related decline becomes much more noticeable and we start to think of synapse loss as exponential.

Now about new neurons after GW25 is a whole topic in of itself... heavily debated but I won't get into that history, the most accepted viewpoint is that it does exist in the hippocampus [other regions as well] (really cool work with c14 carbon dating from atomic bomb {2010} and perhaps less cool new sequencing methods give evidence {2025/2026}). Note estimates of how many are born are comparatively low-ish, 500-1000 neurons per day.

That begs another question however which is why and what do they do? Final interesting part is that when you stop the mouse hippocampus neurons from dividing, [unethical to do in humans :( ] distinct representations of experiences start to look similar and overlap. I also know if you ablate neurogenesis in mouse nasal cortex I think mice lose the ability to form new sensory sensations all together.

Disclaimer, the evidence for function of new born neurons is actually pretty low only a few studies have tried this so its no where close to accepted and thus far far from textbook standard so take it as you will.

But couldn't, and wouldn't you expect, both things to be true?

Existing memories may be degrading as a result of ongoing neuron death and synapse pruning, but at the same time our "storage capacity" (neurons+synapses) is essentially fixed or decreasing, and new memories are going to increasingly be competing with existing ones.

Presumably there is at least some connection between our neuron + synapse counts and species longevity. If we had evolved to live longer then one might naively expect us to have more neurons/synapses to support life-long learning and memories, although you could also argue that, for example, episodic memories too far back are not useful to remember, so maybe there is a cap to how much episodic memory capacity we need, and the complexity of the evolutionary niche we inhabit also limits the amount of declarative knowledge we need to store.

It's been noted in birds that hippocampus size seems highly correlated with the species memory capacity - but specifically for memory of seasonal seed hiding locations, where the bird only needs memory capacity for the number of seeds (can be 10's of thousands) hidden in a single season - they presumably reuse this hippocampal memory capacity each season, and forget the last season.

Have there been any studies relating brain size / memory capacity to the need of a species for lifelong memory?

I'm in academia (biology but highly computational) and I would say opinions on AI are quite polarized. Some professors in the department equate not using AI as lost productivity. Contrarily some professors abhor the idea of even using AI at all. For us (biologists) it's less of an issue because we have no fear of openai or A/ publishing a biology paper. Though even people I known in physics, data science, or computer science still heavily use AI.

Our university has agreements that stipulate that our institutional accounts cannot be used to train AI models and certain research groups have differential model access.

Further from academic journal sense there is mixed feelings. I once was able to meet with a senior journal editor (general non-medical high IF journal > 50) who claimed that if they think something is written by AI they wouldn't consider it. Yet another high IF journal said it was completely fine if something was written by AI. About a month ago I reviewed a paper by yet a different high IF journal and in big bold red letters it said I was not allowed to feed any part of the paper through AI (even if it was locally ran) but you could ask it to rephrase text that you wrote.

Do you mind me asking why you have no fear of OpenAI etc publishing a biology paper? With increasing model capability and compatibility with lab hardware could we not be in a scenario soon(ish) where these agents are able to autonomously complete and publish experimental results?

I was debating this with a friend the other day and the consensus we came to was that a highly trained scientist would (or should) always review output like that described above, but that's starting to feel like a weakening argument!

Firstly the underlying worry here is about privacy which hinges on the fact that AI companies are stealing ideas in the first place. Stealing from your customers is an incredibly bad business model and I think if they were to steal IP (intellectual property) from researchers mathematicians or computer scientists would be first.

Now why I think biology is safer: 1) Producing novel biology still has to be done in a lab. It requires laboratories, equipment, experimental protocols, trained personnel, regulatory and safety infrastructure, and often substantial institutional organization all of which there is no indication they're heading for. Also I disagree that lab hardware is near a "soon state" where labs can be full autonomous, (liquid handlers are really good at niche tasks but lack any type of experimental general ability [not AI-bounded], especially for in vivo work where its footprint is non-existent). Even the most automated Labs I know where robots do 80% of experimental work, they still have grad students to carry out that last 20% and to oversee.

2) Even if AI could do the pipeline it's not worth it for AI LLM companies to dedicate capital to it currently. A lot of biology research itself doesn't produce a sellable product, in fact most of it never does. It seems currently and for at least the next couple years at least, AI capital is best spent growing compute to research better models, train better models, and sell inference.

The compatibility with the lab hardware part is going to take a little while, for now running experiments is problematic for LLMs

From a molecular neuroscience perspective, for both ADHD and ASD (autism) you're unlikely to find any pure biomarkers as clean as a disease like huntingtons disease whose mechanism is clearly understood as extra CAG repeats on the HTT gene (a clean mendelian disorder). ADHD is defined by behavior/cognitive symptoms and most all behavior/cognitive diseases are multifactoral, which ADHD is. WES/WGS and GWAS has been done and for familial ADHD and unlike ASD there is mostly no clear monogenic mutation (a single gene that would explain the phenotype) [note monogenic mutations are usually a very small subset of cases but give scientists a look into what pathway/mechanism is causing a multifactoral disease]. Thus it is not for a lack of looking classically, and deficit is speculated to likely manifest as a neural circuit organization or synaptic issue (though the latter is more closely linked to ASD). This is currently impossible (basically) to measure in alive human brain as it requires nanoscopic imaging, note how challenging the fly map was (incomplete IMO as well).

There’s a doctor who goes by Russell Barkley, PhD on his popular YouTube channel and claims to be able to brainscan for ADHD with certainty. Is his claim legitimate?

He's a legit researcher though I haven't seen his work on youtube. In terms of how accurate brain scans are at diagnosing adhd you can look at recent meta analyses (gold standard of evidence based medicine pyramid).

In a 2024 meta-analysis of MRI/fMRI machine-learning studies for ADHD, the average pooled sensitivity was 74% (the ability to correctly identify people who actually have ADHD) and the average pooled specificity was 75% (the ability to correctly identify people who do not have ADHD), that also means that there is a 26% false-negative rate (miss/Type II error) and a 25% false-positive rate (accidental diagnosis/Type I error) [https://doi.org/10.1016/j.jad.2024.03.111].

Though there is no set standards but under 80% is pretty low for a clinically useful test but can still be used in some conditions such as to supplement diagnosis. To give some numbers the rapid antigen covid tests had 72% sensitivity and 98.9% specificity. (note the lower sensitivity was acceptable at the time but the CDC guideline was for symptomatic people to retest 48 hours. Viral load and other staging factors could all confound.) [https://doi.org/10.1371/journal.pmed.1004011]

Russel Barkley is a pioneer in the field of ADHD research. I have heard of such a claim, but not from Russel Barkley. Could you provide a link of Russel Barkley making the claim please?

It's somewhere in this talk (broken down as a playlist). It's been a while since I've watched it but I do recall him saying that they can see physically differences in the brain of adhd folks

https://www.youtube.com/watch?v=BzhbAK1pdPM&list=PLzBixSjmbc...

Seeing physical differences in brain volume, connectivity or activity between groups of many adhd folks and non-adhd folks is one thing and that can be done. However, performing a clinical diagnosis of adhd in an individual, solely based on a brain scan, is a completely different thing.

If I remember correctly there are some paradigms in which you can show it in fMRI quite clearly but the trouble is of course MRIs are not accessible to a wide public. I will have to go dig through papers though, I have not read into MRI based diagnostics in a long while

ADHD also evolutionary advantages, so there is unlikely to be a single gene that encodes for it.

Evo-psych is impossible to falsify.

Practically all statement outside of mathematics is a soft statement.

IMO "Humans do this because [made up scenarios how it helped them survive]" is trash in its own rights, and not because it is not falsifiable. Not useful, not insightful, not anything.

I wish everyone would get this!

1. How is it advantageous?

2. Assuming it really is: Why would this make it unlikely to be encoded on a single gene? As a layman, the only condition I'm aware of with this "downside but also upside" quality is sickle cell anaemia (downside is anaemia, upside is increased resistance to malaria), which is decided by a single nucleotide change on chromosome 11.

> As a layman, the only condition I'm aware of with this "downside but also upside" quality is sickle cell anaemia

Essentially all traits that you might think of as "traits" and not "features of the species" have downsides and also upsides. Where there's any significant imbalance, the genes for that trait will be purged from the gene pool (if the trait is basically all negatives) or sweep to become universal (if all positives).

Am biologist and keeping genes that are "advantageous" is the most common trap that people fall into about evolution. Evolution isint actually about keep advantageous traits the real idea is about differences in reproductive success, not about evolution systematically preserving only traits that are beneficial to the individual.

In fact Darwin's theory of evolution is kind of outdated as well. We now understand genetic drift and things like the neutral theory of molecular evolution from moto kimura and the nearly neutral theory of evolution from tomoko ohta may give some sort of explanation to polygenic nature of adhd.

Sometimes the upside is just being different. I heard about a group of cattle, and one of them was ill, while the others feasted. The feed was tainted, and so only the sick one survived.

Though, with ADHD, I think it's definitely more than that. It doesn't just make it hard to focus, it makes it hard to focus on what you need to, until the moment that it is obviously now or never. Focus, though - there's tons of that, flitting about, and sometimes grabbing you up and running away with you - sometimes for months. I would imagine that there are a lot of novel discoveries attributable to it.

This isn't funny

> ADHD often comes with a high attention to detail

Per the DSM-5, one of the core symptoms of ADHD:

"often fails to give close attention to details or makes careless mistakes in schoolwork, work, or other activities

Yes, it's both a lack of attention to details in "boring" tasks and an exceptional attention to details in "interesting" tasks.

I think there is a conflation between attention and attention to details. I understand attention control can vary depending on the engagement value of a task. I have experienced the condition my entire life, I am well aware.

I am not aware of any data that supports being interested in a task lessens the likelihood of making mistakes. If you have any data, I will gladly read it.

What are they? Are there papers on this?

There are only papers which suggest this could be true, none that conclusively prove it. That I’m aware of.

There are some cool studies done where people with a without ADHD are tasked to forage berries. The people with ADHD do better and adhere to foraging patterns which existing theories suggest would be more optimal.

A lot of the studies like that indicate the individual with the condition might benefit more from ADHD than the group they’re in, but I’m not sure that studies have explored group benefits very much.

There’s an often cited paper in which nomadic men who carry a certain ADHD-related allele (DRD4-7R, a dopamine reception variant with ADHD traits and novelty seeking) tend to have better nutritional status. I can’t recall much about it or how high quality it is.

I’ve always thought, it’s not absurd to think there different development routes which the brain takes depending on the environment it develops in.

With your foraging example, it does make me think ADHD is a small group/individual optimisation. Prioritising high vigilance and individual productivity over social cohesion.

I speak with no authority. I don’t even know how such a theory could be tested.

> I’ve always thought, it’s not absurd to think there different development routes which the brain takes depending on the environment it develops in.

What do you think nutritional stunting means?

https://en.wikipedia.org/wiki/Stunted_growth

I don’t mean from a nutritional standpoint, but a behavioural perspective. Smaller groups would have an higher percentage of responsibility per individual to be vigilant and proactive.

It would make sense to me that evolutionary there would be different mental development paths depending on the requirements of their situation.

This is coming from my understanding that ADHD is more prevalent in stressful upbringings.

If adhd is heritable, then the stressful upbringing could be symptomatic of the parent's condition instead of causal.

I agree, stress during pregnancy could also be a signal shared with the developing brain.

> I don’t mean from a nutritional standpoint, but a behavioural perspective.

That would normally be called "learning". Also a pretty conventional idea.

With learning, though, you'd want to explain why something becomes immune to further learning at a certain point.

A psychiatrist told me that people with ADHD perform better under extreme pressure and chaos. No idea if that's true. Personally I don't even think of ADHD as a deficiency. It's just a trait that is not compatible with modern society and workplace.

A common meme you'll see on ADHD in online posts are about how people with it are perfectly calm during emergencies, but then when any inconsequential thing happens such as e.g. breaking a shoelace and they'll just unravel and/or take forever to deal with it.

There might be a correlation, but I doubt causation. I would argue people with ADHD, like myself, tend to end up in situations where extreme pressure and chaos is more common. Thus, we have more exposure than the average person. I imagine it can be a trainable trait in many people.

Yeah, I think this is the key point. I am better at handling chaos because I grew up around chaos (my mom has adhd and so do I) so I am much better at handling things falling apart.

I don't know about papers but I had a doctor tell me they are overrepresented among snipers in the military. ADD could be an advantage to hunting.

Or ADD just sucks there less than in other areas.

Like being physically weak is not an advantage in white collar jobs.