Heh, for a second there this read like some of the Portiid adventures with Bianca and Fabian from Adrian Tchaikovsky's book "Children of time". If you find this kind of thing interesting and are a fan of sci-fi, I highly recommend the book.
It is truly fascinating, I wonder how it evolved like that.
Before becoming a spring as it is today how was it hunting in the past? What constraints made it need such a mechanism instead of a typical web?
Amazing specialization. I was wondering the same thing. Cave glow worms cast a "fishing line," and this is similar-ish. I wonder if N million years ago, a couple of fishing-line-like spiders started anchoring their lines, and the ones with a more conic shape anchor may led to more success over time. And the anchor may have only worked on territorial prey. Fun stuff to imagine.
Me too! I was visiting my parents’ farm and walking around in pitch black while looking at the stars when I saw a bright green glow out of the corner of my eye. Ended up tracking it down to a California pink glow worm that had perched itself on a rock.
Injured Himenoptera are known to send pheromones that trigger a vicious defensive response from other members of the colony. On a typical web the companion ants would do what the ants do. Go to war and flood the place surrounding the danger until eventually killing it. The spider does not have neither the stamina, nor the venom amount to deal with that. This web is designed to extract just one ant, while cutting the path that the ant rescuers could follow.
This is the first spider web known designed to catch only one species of prey. That alone would make the finding extraordinary. The trap can lure only green ants and serve the food exactly were the spider wants it; granting access to a common source of food that is everywhere, but also that is very dangerous to hunt (as much big as the spider, with powerful jaws, and much stronger).
The video shows one most interesting thing: Notice that the spider is carefully moving out of the way, just a second before the ant is launched. The spider knows in advance that its current location is about to be hit by a bungee jumping ant, and acts accordingly just in time to avoid the "bullet". We can easily imagine the spider thinking 5,4,3... This means that spider brains can predict the future outcome of a complex movement of objects in the physical system of its trap, and also calculate how much time the fibers will resist the jaw of the ant.
The smart spider is portia, a jumping spider. A quick search uncovers zounds of videos, articles, and scientific publications on them.
They specialize is hunting spiders, changing hunting tactics based on type and number of prey. Yes, they count. They strategize. They make multi-step plans that take them out of sight of prey. And some people keep them as pets.
I can personally vouch for them being great pets. They're active during the day, hunt prey, don't need much food or water, and tend to "hide" in silk cases they build along the top of their terrariums so you can always see them. They like to get water from inside flowers, and probably can differentiate between many colors, so adding bright flowers not only makes things prettier, it provides a watering hole and possible hunting advantage over color-blind insects trying to hide.
Of course, if you don't want to set up a terrarium and personally sentence crickets to death, just look at the screens in your windows. Odds are, a jumping spider is already living there and will stay as long as you let it. They're territorial.
I once watched a spider spinning a very crude "parachute" and catching wind to leap between two parked cars about 6 feet apart. Spiders definitely have great spatial reckoning and a level ingenuity in silk use that is pretty shocking for such small creatures.
> Notice that the spider is carefully moving out of the way, just a second before the ant is launched.
It's not moving before the ant is launched. It's moving as soon as the tension in the web is gone, ie. there's movement in their web. Most spiders react to movement in their web.
There are many such mysterious mysteries in evolution. Some wasps paralyse a caterpillar of a particular species by stinging it very precisely in its nervous centres, then carries the caterpillar into the nest it previously dug out, lay its egg on the caterpillar then close the hole to never come back.
This is a completely automatic, unintelligent behaviour; if you remove the paralysed caterpillar at any point in the process the wasp simply goes on with its business (it will close its nest without any caterpillar inside, where the larva will die out from lack of food).
In the late 19th century, Jean-Henri Fabre studied these wasps (and many other strange insects) and had a copious correspondence with Charles Darwin on this very matter. His books are absolutely fascinating (ditto the letters Darwin and him exchanged).
The weirdest insects I've seen in real life are these ones called Burying Beetles - they have chemoreceptors that allow them to detect the odor of a dead mouse from as far away as two miles. Then a male and female fly to it, dig a big hole, strip all the fur off of it to line the hole, then drag it down in there and raise their young together. They are also unusual in that outside of bees and ants, very few insects raise their young together from infancy to adulthood.
2° it paralyses a caterpillar (some other species use different worms, or beetles, as their victims; but each species of wasp targets one precise species of caterpillar or bug and cannot use any other food source for its larvae than the one it's genetically programmed to catch).
3° it carries the caterpillar into the hole
4° it lays its egg on the caterpillar, far from the head
5° it closes the hole with dirt
6° the egg hatches in the dark, and the larva feasts on the paralysed caterpillar, eating it alive.
If you pull out the caterpillar while the wasp turns around to lay its egg, it doesn't interrupt itself. IIRC even if you take the caterpillar while it's flying to the hole, it still proceeds to the end, without the caterpillar (which makes no sense at all, showing it's a purely reflex activity, without any intelligence).
I'm from where these spiders were found. The ants they're predating are an equally fascinating and super aggressive species of green weaver ants (that have other cool predators like "mimic" jumping spiders).
I wonder why biological organisms are capable of such absurdly high accelerations. Article reminded me of cnidocytes which apparently produce anywhere between 40,000 and 5,410,000 g. Is it because of the small masses involved?
If they would prove that the trap also breaks the ant neck, saving venom, or stunning the prey for easy kill, that would be incredible. Somebody needs to include this thing in the script of a science fiction film.
As a general rule of dynamical systems, specialization is essentially the exploitation of regularity within your environment.
A highly regular environment can allow for extreme specialization because a system can predict and "expect" certain situations. This leads to much less energy expended, since maintaining stability requires energy that scales with the turbulence of a system.
If gravity is always down, you don't need to spend energy on organs that overcome gravity in other directions. Your circulatory system can use gravity to its advantage; that's why you can't just remain upside down, there's no effective mechanism to pump blood out of your brain.
If a car passes a street exactly every 2 minutes, you don't need to spend lots of time and energy figuring out when to cross. You know once a car crosses, you're good for 2 minutes. If you know the sun comes up around the same time every day, you can allow yourself a deep sleep during the night if you're in a safe place, or bloom only during the day.
Nature exploits such regularities in order to reduce the energy needed to maintain an organism or group, which creates specialization, whether on the scale of the group, on the scale of the individual, etc. This is hierarchical; your cells specialize, your organs specialize, you get training or education to specialize your skills, etc. For example, you might specialize as a software engineer, depending on the regularity of people willing to pay money for you to solve their problems, but AI comes around and suddenly you're out of a job.
The danger is that the more regularities you depend on, the less free energy your body needs to keep around and the less free energy you have to suddenly react and adapt to a new environment. If tomorrow, gravity started being up and not down, most of us would have a bad time. If those regularities are interdependent, as geological/biological cycles tend to be, a few bad conditions could unravel the entire ecosystem.
I should add that another way to consider this constraint is the good regulator theorem: every good regulator of a system must be a model of that system.
Through this lens, you can view an organism as an hierarchical collection of various models of its environment at different scales. As the organism specializes further, its model of the world can simplify, and it is free to explore simplification of some internal structures so that others can become more optimized for the more dynamic parts of the model which may need realtime updates, such as recognizing and tracking fast-moving prey. Various positive feedback loops result, and drive evolution.
It all comes back to the amount of free energy needed to predict the next state. In the information-theoretic sense, regularity lowers the uncertainty of the next relevant state given the system’s model. Specialization is what occurs when the system transforms that lower uncertainty into structure. This saves energy because the system has less ambiguity to resolve in realtime. But in the case of most biological organisms, it takes tens to millions of years for an organism's structure to react to its environment, so the cost of these "cheap reads" (metabolically speaking) on the model is an extraordinarily long, expensive and nondeterministic write process to update the model.
If an organism specifically allocates enough free energy to allowing rapid mutation while still constraining bad evolutionary paths, while metabolically expensive it can lead to organic evolution on the span of literally just decades:
> The new habitat once had its own healthy population of lizards, which were less aggressive than the new implants, Irschick said. The new species wiped out the indigenous lizard populations
> Researchers found that the lizards developed cecal valves—muscles between the large and small intestine—that slowed down food digestion in fermenting chambers, which allowed their bodies to process the vegetation's cellulose into volatile fatty acids.
> The rapid physical evolution also sparked changes in the lizard's social and behavioral structure, he said. For one, the plentiful food sources allowed for easier reproduction and a denser population.
> The lizard also dropped some of its territorial defenses
The lizard not only developed a new organ to help it eat the local vegetation, but it exploited the regularity of dominion to reduce metabolic energy which was previously allocated for modelling an environment exhibiting territorial pressure from competing species.
fascinating and thank you for the great explanation. I was actually going to followup and ask with regards to AI but your response covered it aswell :)
I just expanded more in a reply to my own comment if you're interested!
To technically expand a bit on AI:
Any regularity in an environment which an embedded system can detect but fails to exploit represents an amount of excess free energy in the organism, distributed over itself, its group, its species, etc. depending on what types of systems and scales you choose to model.
There are parallels in information theory: any recognizable patterns/relationships within a compressed message represents excess entropy (the average uncertainty of future states), since that regularity was not exploited during compression and remained in the compressed structure. This means that a perfectly compressed message is functionally indistinguishable from random noise.
You can view weights in an AI model through the same lens: The weights represent "knowledge" of the environment the model has been exposed to. The model is designed to correctly predict future states, and thus "learning" is effectively the compression of a full model of the environment, which is more efficient to traverse than the uncompressed model. A perfectly learned environment minimizes uncertainty and should translate to weights that have no discernible patterns and thus are also functionally indistinguishable from random noise, void of any regularity.
Some level of "compression" of the local environment is required for any stable embedded system, or else the energy required to continually stabilize the system would require an equal amount of energy present as that in all of the universe, because the system would become a perfect copy of the very environment it is embedded within. This is obviously thermodynamically prohibitive.
Hopefully this helps make the relationship between structure, knowledge, information and uncertainty a lot more intuitive.
As a bonus, consider Fabrice Bellard's ts_zip, a great showcase on how knowledge and compression are related.
ts_zip compresses text at record efficiency (at the cost of magnitudes more memory and compute, nothing is free)
Previous attempts at text compression all purely relied on character-level patterns and semantics, syntactical structure, etc., maybe with some heuristic tweaking here and there.
That got us far, but LLMs do something never achieved before, which is to incorporate relationships beyond the surface: not just placement of characters, n-grams or words, but the actual meaning behind them, and large-scale correlations with other words or tokens across vast context windows.
The LLM actually becomes a world model with enough size and training, and thus we are able to use every fact we know about everything to compress text. If we're speaking about biology for example, that constrains the probabilities of what the most likely word might be after a given prefix. Or if the context is constrained to a specific historical period.
All of these regularities can be leveraged, at the cost of a lot of energy, in order to create compressed text that gets arbitrarily close to looking like completely random noise (actually verifying this would require infinite energy though, per Kolmogorov).
The catch is, such systems are specialized and depend on the regularity of cheap, widely-available energy networks and consumer access to cheap compute. Take that away, and it becomes ill-suited vs just using bzip. I mean, even now, bzip is a better choice when considering energy tradeoffs. And ts_zip in particular is specialized to the point of only working with text and not arbitrary byte streams.
The part from the paper which is so interesting is why the ant bites the trap in the first place. The paper suggests that the spider puts out a pheromone that attracts the ant and triggers the ant to aggressively bite the snare, but the pheromone only does this for the spider's target species, the green tree ant. The researchers watched three other ant species check out the snare, go "meh", and move on, unharmed, without showing any aggression towards the snare.
that's a good question -- the paper describes it triggering aggression in the ant within milliseconds of it probing the snare with its antenna. I don't know the basis for it, but that's some down-to-the-metal ant programming right there
It is the year 2038. A new brand of slingshot is almost immediately removed from store shelves after multiple children receive through-and-through wounds.
The notion of a species only really exists in the human world; it's a human concept. So the discovery of a new species is the discovery of a new classification need. It is new to science.
(At a first approximation, essentially all existing species are new on an evolutionary level — isn't it the case that something like 99.9% of all life on earth is newer than a million years old?)
Not seeing the "problem." To humans, it's new. It's a new addition to the list of "species we know about." It's a new spider species. This is how language has been used for a long time.
Heh, for a second there this read like some of the Portiid adventures with Bianca and Fabian from Adrian Tchaikovsky's book "Children of time". If you find this kind of thing interesting and are a fan of sci-fi, I highly recommend the book.
And the Underhill spiderlings in A Deepness in the Sky by Vernor Vinge too!
Another great book that I usually reread right before rereading Children of Time because the whole spider civilization angle is so fun.
Children of Time is fantastic! I ended up totally rooting for the spiders in the end.
Children of Time is one of the best books I've ever read, it's honestly amazing. It might be my all-time favorite. Seconding this recommendation!
Thirding it! This is your sign, go read it
I don't think I've been disappointed by anything from Adrian Tchaikovsky, tbh. Alien Clay and Service Model are also great.
I read Alien Clay and another book by him, which it turned out is basically the same book, which I found disappointing.
It is truly fascinating, I wonder how it evolved like that. Before becoming a spring as it is today how was it hunting in the past? What constraints made it need such a mechanism instead of a typical web?
Amazing specialization. I was wondering the same thing. Cave glow worms cast a "fishing line," and this is similar-ish. I wonder if N million years ago, a couple of fishing-line-like spiders started anchoring their lines, and the ones with a more conic shape anchor may led to more success over time. And the anchor may have only worked on territorial prey. Fun stuff to imagine.
Just saw glow worms for the first time last month. Very cool critters. Not sure I even knew they existed before that.
Me too! I was visiting my parents’ farm and walking around in pitch black while looking at the stars when I saw a bright green glow out of the corner of my eye. Ended up tracking it down to a California pink glow worm that had perched itself on a rock.
Injured Himenoptera are known to send pheromones that trigger a vicious defensive response from other members of the colony. On a typical web the companion ants would do what the ants do. Go to war and flood the place surrounding the danger until eventually killing it. The spider does not have neither the stamina, nor the venom amount to deal with that. This web is designed to extract just one ant, while cutting the path that the ant rescuers could follow.
This is the first spider web known designed to catch only one species of prey. That alone would make the finding extraordinary. The trap can lure only green ants and serve the food exactly were the spider wants it; granting access to a common source of food that is everywhere, but also that is very dangerous to hunt (as much big as the spider, with powerful jaws, and much stronger).
The video shows one most interesting thing: Notice that the spider is carefully moving out of the way, just a second before the ant is launched. The spider knows in advance that its current location is about to be hit by a bungee jumping ant, and acts accordingly just in time to avoid the "bullet". We can easily imagine the spider thinking 5,4,3... This means that spider brains can predict the future outcome of a complex movement of objects in the physical system of its trap, and also calculate how much time the fibers will resist the jaw of the ant.
The smart spider is portia, a jumping spider. A quick search uncovers zounds of videos, articles, and scientific publications on them.
They specialize is hunting spiders, changing hunting tactics based on type and number of prey. Yes, they count. They strategize. They make multi-step plans that take them out of sight of prey. And some people keep them as pets.
>And some people keep them as pets.
I can personally vouch for them being great pets. They're active during the day, hunt prey, don't need much food or water, and tend to "hide" in silk cases they build along the top of their terrariums so you can always see them. They like to get water from inside flowers, and probably can differentiate between many colors, so adding bright flowers not only makes things prettier, it provides a watering hole and possible hunting advantage over color-blind insects trying to hide.
Of course, if you don't want to set up a terrarium and personally sentence crickets to death, just look at the screens in your windows. Odds are, a jumping spider is already living there and will stay as long as you let it. They're territorial.
Yes! I learned about them reading Adrian Tchaikovsky's excellent scifi book "Children of Time".
I once watched a spider spinning a very crude "parachute" and catching wind to leap between two parked cars about 6 feet apart. Spiders definitely have great spatial reckoning and a level ingenuity in silk use that is pretty shocking for such small creatures.
> Notice that the spider is carefully moving out of the way, just a second before the ant is launched.
It's not moving before the ant is launched. It's moving as soon as the tension in the web is gone, ie. there's movement in their web. Most spiders react to movement in their web.
May be an effect of the video being show in slow motion. Good point. Then this spider is ultra-fast.
Of course, the problem with such a high amount of specialization is that if the green ant disappears, so does this spider.
There are many such mysterious mysteries in evolution. Some wasps paralyse a caterpillar of a particular species by stinging it very precisely in its nervous centres, then carries the caterpillar into the nest it previously dug out, lay its egg on the caterpillar then close the hole to never come back.
This is a completely automatic, unintelligent behaviour; if you remove the paralysed caterpillar at any point in the process the wasp simply goes on with its business (it will close its nest without any caterpillar inside, where the larva will die out from lack of food).
In the late 19th century, Jean-Henri Fabre studied these wasps (and many other strange insects) and had a copious correspondence with Charles Darwin on this very matter. His books are absolutely fascinating (ditto the letters Darwin and him exchanged).
The weirdest insects I've seen in real life are these ones called Burying Beetles - they have chemoreceptors that allow them to detect the odor of a dead mouse from as far away as two miles. Then a male and female fly to it, dig a big hole, strip all the fur off of it to line the hole, then drag it down in there and raise their young together. They are also unusual in that outside of bees and ants, very few insects raise their young together from infancy to adulthood.
> lay its egg on the caterpillar
> it will close its nest without any caterpillar inside, where the larva will die out from lack of food
...wouldn't the larva be with the caterpillar? You said that's where it lays the eggs.
The process is as follows :
1° the wasp digs a hole in soft ground
2° it paralyses a caterpillar (some other species use different worms, or beetles, as their victims; but each species of wasp targets one precise species of caterpillar or bug and cannot use any other food source for its larvae than the one it's genetically programmed to catch).
3° it carries the caterpillar into the hole
4° it lays its egg on the caterpillar, far from the head
5° it closes the hole with dirt
6° the egg hatches in the dark, and the larva feasts on the paralysed caterpillar, eating it alive.
If you pull out the caterpillar while the wasp turns around to lay its egg, it doesn't interrupt itself. IIRC even if you take the caterpillar while it's flying to the hole, it still proceeds to the end, without the caterpillar (which makes no sense at all, showing it's a purely reflex activity, without any intelligence).
Se for instance https://www.gutenberg.org/ebooks/3462
(Jean-Henri Fabre was a marvellous writer, and the English translation is very good).
I'm from where these spiders were found. The ants they're predating are an equally fascinating and super aggressive species of green weaver ants (that have other cool predators like "mimic" jumping spiders).
https://en.wikipedia.org/wiki/Weaver_ant
I wonder why biological organisms are capable of such absurdly high accelerations. Article reminded me of cnidocytes which apparently produce anywhere between 40,000 and 5,410,000 g. Is it because of the small masses involved?
Strength of fibers scales with crossection area, mass scales with volume.
If they would prove that the trap also breaks the ant neck, saving venom, or stunning the prey for easy kill, that would be incredible. Somebody needs to include this thing in the script of a science fiction film.
> Somebody needs to include this thing in the script of a science fiction film.
"The Fly" is ready for a quick rewrite.
The videos are amazing. Sadly I think theses types of adaptations make it easier for the species to go extinct since its so highly specialized.
>theses types of adaptations make it easier for the species to go extinct since its so highly specialized.
super interesting. I'm guessing because being highly dependent on a single tactic can make it difficult to adapt or course change ?
As a general rule of dynamical systems, specialization is essentially the exploitation of regularity within your environment.
A highly regular environment can allow for extreme specialization because a system can predict and "expect" certain situations. This leads to much less energy expended, since maintaining stability requires energy that scales with the turbulence of a system.
If gravity is always down, you don't need to spend energy on organs that overcome gravity in other directions. Your circulatory system can use gravity to its advantage; that's why you can't just remain upside down, there's no effective mechanism to pump blood out of your brain.
If a car passes a street exactly every 2 minutes, you don't need to spend lots of time and energy figuring out when to cross. You know once a car crosses, you're good for 2 minutes. If you know the sun comes up around the same time every day, you can allow yourself a deep sleep during the night if you're in a safe place, or bloom only during the day.
Nature exploits such regularities in order to reduce the energy needed to maintain an organism or group, which creates specialization, whether on the scale of the group, on the scale of the individual, etc. This is hierarchical; your cells specialize, your organs specialize, you get training or education to specialize your skills, etc. For example, you might specialize as a software engineer, depending on the regularity of people willing to pay money for you to solve their problems, but AI comes around and suddenly you're out of a job.
The danger is that the more regularities you depend on, the less free energy your body needs to keep around and the less free energy you have to suddenly react and adapt to a new environment. If tomorrow, gravity started being up and not down, most of us would have a bad time. If those regularities are interdependent, as geological/biological cycles tend to be, a few bad conditions could unravel the entire ecosystem.
I should add that another way to consider this constraint is the good regulator theorem: every good regulator of a system must be a model of that system.
Through this lens, you can view an organism as an hierarchical collection of various models of its environment at different scales. As the organism specializes further, its model of the world can simplify, and it is free to explore simplification of some internal structures so that others can become more optimized for the more dynamic parts of the model which may need realtime updates, such as recognizing and tracking fast-moving prey. Various positive feedback loops result, and drive evolution.
It all comes back to the amount of free energy needed to predict the next state. In the information-theoretic sense, regularity lowers the uncertainty of the next relevant state given the system’s model. Specialization is what occurs when the system transforms that lower uncertainty into structure. This saves energy because the system has less ambiguity to resolve in realtime. But in the case of most biological organisms, it takes tens to millions of years for an organism's structure to react to its environment, so the cost of these "cheap reads" (metabolically speaking) on the model is an extraordinarily long, expensive and nondeterministic write process to update the model.
If an organism specifically allocates enough free energy to allowing rapid mutation while still constraining bad evolutionary paths, while metabolically expensive it can lead to organic evolution on the span of literally just decades:
https://www.nationalgeographic.com/animals/article/lizard-ev...
> The new habitat once had its own healthy population of lizards, which were less aggressive than the new implants, Irschick said. The new species wiped out the indigenous lizard populations
> Researchers found that the lizards developed cecal valves—muscles between the large and small intestine—that slowed down food digestion in fermenting chambers, which allowed their bodies to process the vegetation's cellulose into volatile fatty acids.
> The rapid physical evolution also sparked changes in the lizard's social and behavioral structure, he said. For one, the plentiful food sources allowed for easier reproduction and a denser population.
> The lizard also dropped some of its territorial defenses
The lizard not only developed a new organ to help it eat the local vegetation, but it exploited the regularity of dominion to reduce metabolic energy which was previously allocated for modelling an environment exhibiting territorial pressure from competing species.
fascinating and thank you for the great explanation. I was actually going to followup and ask with regards to AI but your response covered it aswell :)
I just expanded more in a reply to my own comment if you're interested!
To technically expand a bit on AI:
Any regularity in an environment which an embedded system can detect but fails to exploit represents an amount of excess free energy in the organism, distributed over itself, its group, its species, etc. depending on what types of systems and scales you choose to model.
There are parallels in information theory: any recognizable patterns/relationships within a compressed message represents excess entropy (the average uncertainty of future states), since that regularity was not exploited during compression and remained in the compressed structure. This means that a perfectly compressed message is functionally indistinguishable from random noise.
You can view weights in an AI model through the same lens: The weights represent "knowledge" of the environment the model has been exposed to. The model is designed to correctly predict future states, and thus "learning" is effectively the compression of a full model of the environment, which is more efficient to traverse than the uncompressed model. A perfectly learned environment minimizes uncertainty and should translate to weights that have no discernible patterns and thus are also functionally indistinguishable from random noise, void of any regularity.
Some level of "compression" of the local environment is required for any stable embedded system, or else the energy required to continually stabilize the system would require an equal amount of energy present as that in all of the universe, because the system would become a perfect copy of the very environment it is embedded within. This is obviously thermodynamically prohibitive.
Hopefully this helps make the relationship between structure, knowledge, information and uncertainty a lot more intuitive.
As a bonus, consider Fabrice Bellard's ts_zip, a great showcase on how knowledge and compression are related.
https://bellard.org/ts_zip/
ts_zip compresses text at record efficiency (at the cost of magnitudes more memory and compute, nothing is free)
Previous attempts at text compression all purely relied on character-level patterns and semantics, syntactical structure, etc., maybe with some heuristic tweaking here and there.
That got us far, but LLMs do something never achieved before, which is to incorporate relationships beyond the surface: not just placement of characters, n-grams or words, but the actual meaning behind them, and large-scale correlations with other words or tokens across vast context windows.
The LLM actually becomes a world model with enough size and training, and thus we are able to use every fact we know about everything to compress text. If we're speaking about biology for example, that constrains the probabilities of what the most likely word might be after a given prefix. Or if the context is constrained to a specific historical period.
All of these regularities can be leveraged, at the cost of a lot of energy, in order to create compressed text that gets arbitrarily close to looking like completely random noise (actually verifying this would require infinite energy though, per Kolmogorov).
The catch is, such systems are specialized and depend on the regularity of cheap, widely-available energy networks and consumer access to cheap compute. Take that away, and it becomes ill-suited vs just using bzip. I mean, even now, bzip is a better choice when considering energy tradeoffs. And ts_zip in particular is specialized to the point of only working with text and not arbitrary byte streams.
The part from the paper which is so interesting is why the ant bites the trap in the first place. The paper suggests that the spider puts out a pheromone that attracts the ant and triggers the ant to aggressively bite the snare, but the pheromone only does this for the spider's target species, the green tree ant. The researchers watched three other ant species check out the snare, go "meh", and move on, unharmed, without showing any aggression towards the snare.
Yeah, that is pretty crazy. I wonder what it smells like? Has to be an enemy specific to that ant species right?
that's a good question -- the paper describes it triggering aggression in the ant within milliseconds of it probing the snare with its antenna. I don't know the basis for it, but that's some down-to-the-metal ant programming right there
Of course it’s an Australian spider
this gives me children of time vibes
link to the paper here: https://news.ycombinator.com/item?id=48635929
It is the year 2038. A new brand of slingshot is almost immediately removed from store shelves after multiple children receive through-and-through wounds.
HN pedantry time:
>discovered a remarkable new spider species...
Recently evolved then?
Or perhaps...
"An international team of researchers has recently discovered a remarkable spider species..."
The notion of a species only really exists in the human world; it's a human concept. So the discovery of a new species is the discovery of a new classification need. It is new to science.
(At a first approximation, essentially all existing species are new on an evolutionary level — isn't it the case that something like 99.9% of all life on earth is newer than a million years old?)
It’s a new discovery for humans.
that's precisely their point
Not seeing the "problem." To humans, it's new. It's a new addition to the list of "species we know about." It's a new spider species. This is how language has been used for a long time.