pks016

I had tried astro for my personal website when it was released. It was a mess for me. I couldn't keep with so many components. I keep breaking things, one way or the other. I might have to try again to see what things have changed.

Yes. Kind of. They showed that birds can do function/meaning of calls (e.g., contact call group) using the meaning not other cues (e.g. duration, acoustic similarity of calls etc.).

Generally, you test birds in a series of discrimination experiments. So for this example, the discrimination task would be distance calls vs contact calls. Let's say, birds learn to discriminate between 20 distance calls vs 20 contact calls. They can learn this quickly (reward and punishment). After birds learned this rule (say 75% accuracy), we ask to generalize this by adding more calls. Now, birds have to discriminate 30 distance calls vs 30 contact calls (10 new for each). We can check now, for which new calls they are more likely to correct and incorrect response.

In this research field, we often perform this types of experiments (not this exact one). So, this is not that surprising to some of us. Birds also prioritize duration a lot when telling apart calls.

Yeah, the paper is indeed difficult to read (even for me). I read it a while back. I'll try to explain.

So, there are few things to know before and see what we're trying to prove. main thing: Categorical perception: (in short) brain perceive similar sounding sounds (say A and B) in a continuous manner, and in the continuum of two sound, there would be a point where one sound (A) will switch and sound like the other sound (B).

In zebra finches, let's take an example: distance call and tet call. Both these calls are contact calls, birds use them to keep in contact with other birds. Now, we need to extract the acoustic similarity between these two calls, and test birds in a experiment where we ask them to discriminate between these two call types (and get a learning curve; say trials vs probability of correct choice). Then, we can fit a theoretical model of categorical perception to see how well they fit both in acoustic and perceptual dimensions.

This is for one function (contact call), we can do this within other call types and between other call types. At the end, we can see how much of birds' performance is explained by acoustic dissimilarity, function of acoustic calls etc.

This is what the authors have done. They first performed LDA based classification on call type to obtain distance between call types, misclassification etc. (acoustic dimension). Birds went through a series of discrimination experiments based on call types (similar to what wrote above). Then, they compared/matched acoustic and perceptual dimension.

I work in the field. The main takeaway is zebra finches (maybe other songbirds) can discriminate vocalizations based on function, even if they sound similar.

Generally, birds can tell apart categories of sounds e.g. vocalizations from different individual birds, male vs female, call vs song, conspecific vs heterospecific etc. The question is if birds can do it for specific function e.g. agonistic calls vs non-agonistic calls. Simple question but way harder to test because of associated contextual info. with vocalizations.

The paper is culmination of last decade of work (includes many of the past works) but this is the new result.

I get google scholar alerts according to authors.

Interesting. Btw I agree with some of the comments. The framing/language of the question is a bit weird.

I can relate. I remember my most used syntax, but I have to search once in a while.

I would be in minority. But, I don't like tidyverse ecosystem. I prefer data.table for most of my uses.

Another alternative is raincloud plot (depending on data).

There are story ads now.

If the Claude team care for feedback for the free model.

I'm using the free model via chat from the beginning. This is the first time, I'm seriously considering moving away from Claude. Before last month, Claude's Sonnet model was consistent in quality. But, now the responses are all over the place. It's hard to replicate the issue as it happens once in a while. I rarely encountered hallucinations from Claude models with questions from my domain however since last month I have observed abundance of them.

That would be something. Definitely more exciting. But, from I have seen so far, the models are not there yet.

It's a tricky situation for people who might want to work on hard problems like this. Is it worth spending time and money fiddling around the models?

In research, you can't show your progress by showing how many ways you have failed (which I don't like). The universities, grant agency etc. require you to work on solvable problems.

Relatable. Motivation is crucial for any task and most of time they are not motivated to do what you want.

I mean regarding the domains of intelligence and how to test them.

With humans, performance in one cognitive test correlates with another and so on, generally. So, intelligence across domains.

Researchers test the same with animals. The issue being animals' intelligence being tied to their ecology. The dilemma being what is it worth for an animal solving a task that has no significance in its life. The other argument being if the animals' intelligence is closer/similar to human intelligence, we will find similar results in both.

I work on some aspects of intelligence in birds, primarily in songbirds. There have been some effort finding general intelligence ("g" cognitive factor) in birds since last 15-20 years. The results have been mixed as you would expect. Animals' intelligence have evolved for survival and designing experiments to test those are quite hard.

Research has shown brain size matters but not that much, we should look at relative brain size.

That's true. I was much younger back then to notice about privacy.

Yeah, it was pretty bad incorporating G+ account to everything. The way the G+ worked (at least in my friend circle), normal people had less business there. It was very hobby focused.

Ghost town was the best part, for users like me. I didn't want another fb or insta. The circles and community were great.

I think Google closed Google+ because it worked as social media and they couldn't find better ways to exploit users.

Interesting but not surprising to me. Once a field expert guides the models, they most likely will reach a solution. The models are good at lazy work for experts. For hard or complicated questions, many a time the models have blind spots.

I was saying generally. I don't work in maths. PhD students do lots of other things than research. If we ask a PhD student to just solve these kinds of problems and nothing else, the student would do it without much difficulty.

I guess it's different in somewhere like Europe. But in Canada, most of the PhD students are paid for doing TAships, not primarily through grant. Average salary is 25k/year. Take 6-10k out for tuition, that's 15-19k/year. You get a student doing so many things for less pay. I guess, if your job only requires research then you can do it.

I don't think so. I went through the output of Opus 4.6 vs GPT 5.4 pro. Both are given different directions/prompts. Opus 4.6 was asked to test and verify many things. Opus 4.6 tried in many different ways and the chain of thoughts are more interesting to me.

Funding a few PhDs for a year costs orders of magnitude more than it did to solve this problem in inference costs.

I don't think PhD students are sitting around and solving one problem for a year. Also PhD students are way cheaper

Bayesian methods are not better than frequentist methods and vice versa. I use both, but mostly Bayesian.

Bayesian approaches take a long time thinking, making models, choosing priors, simulations etc. but they provide a better estimate and understanding the parameters. I hate point estimates and decision based arbitrary p-value. Whenever possible I use Bayesian methods.

There are few. I use zoteroGPT to extract things(e.g. methods, sample size, species etc.) from a bunch of papers/collection. I don't use it for summary.

I tried with some my domain specific question. Claude generated the visuals but they were rough and not as helpful.

Not as cool as robotics but we use Pi zero for audio playback for songbird research.

Goodluck in North America!

Most people are in headphones and give weird looks if you try doing small talks. I find it's easier to talk with older people.

I was active on FB, Insta, Goggle +, and Orkut during their early days. My brother and I were the first few people from our circle to have these social media account.

Looking back, the incentives have changed. Back then, there was some openness, rawness, and genuine curiosity about people and things. And of course, the signal-noise ratio was much higher.

Influencer culture ruined everything, consciously or subconsciously. I still use Insta for photography. But, it's a sinking ship. Insta could have made a different app for reels.

One can dream. Capitalist society would never reduce their PhD slaves. Saying this as someone who's closer to finishing PhD.