5 ms·

>The AI identified 20,515 signals of interest, which the researchers had to inspect manually. Of those, eight had the characteristics of technosignatures and co

by zh3 4y ago

>The AI identified 20,515 signals of interest, which the researchers had to inspect manually. Of those, eight had the characteristics of technosignatures and couldn’t be attributed to radio interference. The obvious question being, if the AI is so smart why was it necessary to use humans to check 20,515 signals to find the eight with the "characteristics of technosignatures"?

junon 4y ago
Presumably, because it filtered through orders of magnitude more than that.
m3kw9 4y ago
Because it’s not so smart, it just try to recognize a set of patterns that was trained to look at
- detrites 4y ago
  Which is what we do. The rest of what we believe makes us special is simply emergent, and arbitrarily defined in terms of just being further useful pattern recognition, rather than any fundamental property of "intelligence".
readyplayeremma 4y ago
AI is not a well-defined term. This is more likely a specific machine learning technique that is designed to identify all the boring "normal stuff" and ignore it, and then do that at very large scale. By doing that, you can find the interesting parts so that humans with more limited resources can determine if those newly flagged things need to be added to the boring list, or if they do represent something truly interesting. edit: After reading the article a bit more, it is using a random forest classifier. This is almost certainly not meeting the definition of what many here are thinking when the term "AI" is being used in the title. The term is clearly used here for marketing purposes.
- haupt 4y ago
  >The term is clearly used here for marketing purposes. I think most uses are for sensationalistic purposes. I'd wager almost nobody in the general public really understands what AI is or can pin it down. It doesn't help when so many different media outlets abuse the terminology by using it to refer to different things. What's even worse is that whatever ideas people have about AI tend to come from Hollywood.
- nyrikki 4y ago
  They are talking about ML, which is statistical pattern matching and finding. Gödel ruined the fun of automated theorem testing a century ago unless we make significant discoveries in math. Type inference is an accessable example of SOTA automated reasoning if you want a more realistic idea of what our current constraints are. We will be restricted to Human assisted Turing machines for the foreseeable future unless there is a major development in pure math. Remember we can't even build a logically consistent model of arithmetic due to Gödel.
  - uncletaco 4y ago
    Nitpicky and probably universalist or whatever but the fact that we can't build a logically consistent model was always the case, Gödel just discovered it.
    - nyrikki 4y ago
      No, you are most likely correct, I personally haven't found anything that even gives a reason to hope. But as reductionism and Laplacian Determinism are taught as cannon and not as the best option I sugar coated it. The Wada property arising in simple models like predator/prey models with simple added factors like fear/cover probably also suggests that even simple models may be indeterminate at least with binary operations like modern algebra is based on. Three attractors or exit basins can make this unintuitive topological feature pop up. Note that that fractal behavior is topological and not scale invariant noise like is typically studied with topics like fractal scattering. Indecomposable continua like the Wada property aren't solvable with probabilistic models using automata like in the standard model, which is lucky enough to have less than three exit basins. Here is one fairly accessable paper on the Wada property. Hopefully some n-ary algebras may come forward to deal with restricted problems, but even if we could create a logically consistent model of arithmetic, binary operations will still be indeterminate with feature like the Wada property even with perfect knowledge of initial conditions. https://www.researchgate.net/publication/365233050_Organized_periodic_structures_and_coexistence_of_triple_attractors_in_a_predator-prey_model_with_fear_and_refuge https://www.researchgate.net/publication/365233050_Organized...
buddhistan 4y ago
No one claimed the AI "is so smart" - it's another tool in their kit. The article clearly conveys that the potential is a useful way to augment human-led research by providing a way of quickly processing large datasets i.e. the 20k signals are filtering down 150 terabytes of data which is much more manageable for human analysis. It's not like we have definitive parameters of what constitutes an "alien signal," so we can't exactly create an absolute model for detecting such telemetry. Instead the goal of the article is to simply demonstrate exciting new ways to leverage machine learning methods in different contexts
HdS84 4y ago
Trying to filter noise from data also follows the 80,/20 principle. The rules for the easy cases is written easily but then you have one-offs, maybes and special cases. Trying to filter one of these does not cover anything else. So doing it manually takes the same time. Case study: had to clean a list of German addresses once. Excluding obviously invalid addresses like some Chinese address was easy. But some addresses had errors which needed a human eye to fix and correct.
remarkEon 4y ago
I'm assuming that the 20,515 signals of interest come from a pool that's one or several orders of magnitude larger than 20,515.
- zh3 4y ago
  I understand. Still, the point remains that the AI is, in this case, clearly inferior to humans (I would have been impressed if the humans found 20,515 signatures and the AI only - verifably - found eight of them to be worth following up).
  - groestl 4y ago
    > clearly inferior to humans But maybe we are just proto-AI, running on a different platform
  - gowld 4y ago
    "inferior" is a funny word for "doesn't perfectly impersonate us".
jacobsenscott 4y ago
Because it isn't AI. It is just statistical models. AI is for marketing.
tshaddox 4y ago
How do you judge whether 20,515 is a large number or a small number? If the AI provided 2 candidates is that still too high?
- flangola7 4y ago
  SETI@home sorted through I think trillions of data points.
- ad404b8a372f2b9 4y ago
  Any 10000s of something is a large number when it involves human work.
  - fnordpiglet 4y ago
    Imagine that tax returns for millions of people were all processed by hand not but a few decades ago.
    - umeshunni 4y ago
      And that required 1000s of people
      - fnordpiglet 4y ago
        And the results here were three orders of magnitude less, so they require single digits people.
        Retric 4y ago
        Assuming the task was of similar difficulty and the deadline was equally short. I doubt those assumptions hold.
        fnordpiglet 4y ago
        True. I bet the tax returns were harder and had a bounded deadline, unlike an academic research paper.
naasking 4y ago
Because the statistical models powering AI don't have the depth of understanding of a PhD in this field, and so it casts a wide net to ensure nothing gets missed and then a more refined search by human heuristics is needed.
nl 4y ago
The others were "intelligent" signals but from human interference. There's a lot of this so the unique patterns don't occur often enough to automate. The paper is actually worth reading about this part[1]. They have a moderately complex pipeline that you can think of as a filter: it tries to find anomalous signals. The stage-1 autoregressor filtered 115M signals to 3M. Then they perform signal processing techniques to remove things like GPS signal contamination ("t can be seen that certain observing frequencies contain a much higher number of events compared with the others—for example, the region around 1,600 MHz. This overlaps with known RFI at the GBT site specifically from persistent GPS signals."). After this second stage they are left with 20,515 potential signals which were visually inspected. The issue here is that we don't know what a alien signal looks like so we can't just use a classifier. The pipeline can only find things it has never seen before, but it takes human judgement to decide if these signals are "alien" or more likely contamination from human sources that weren't filtered ("Regarding the nature of the rest of the events, most of them look like false positives associated with RFI signals.") [1] https://www.nature.com/articles/s41550-022-01872-z.epdf?sharing_token=t6jjoqbFXFLJH8B5_RNzEtRgN0jAjWel9jnR3ZoTv0Mkq1U55F4UpwCyo9pvCV4lj--uzspzi_o3Nto3GrgPPPK7bN8GhKil2WvNSdFgUJmpmWo-kBOlWGQDS8nBDmrm5jSNwB_Db9767cFT2RRBBvupuVMql4JeV3b9Nn2FjQw%3D https://www.nature.com/articles/s41550-022-01872-z.epdf?shar...
nanidin 4y ago
I think it's useful to replace "AI" with "app" any time you encounter it in the wild. AI is a set of computational techniques that is very broad. The problem with considering "the AI" or "an AI" is that people have in mind some kind of AI agent and that isn't really the case. AI is also not well defined - day one of my AI course in university opened with "What is AI?" Generally once we figure out how to do something using a computer, we decide that's not really intelligent anymore so the implementation isn't AI. An example of that is the minimax algorithm - it's featured "AI: A Modern Approach"[0] but it isn't really something people think of when they hear "an AI". [0] https://aima.cs.berkeley.edu/contents.html https://aima.cs.berkeley.edu/contents.html
ETH_start 4y ago
The AI is fast, not smart.

by zh3 4y ago

junon 4y ago

Presumably, because it filtered through orders of magnitude more than that.

m3kw9 4y ago

Because it’s not so smart, it just try to recognize a set of patterns that was trained to look at

detrites 4y ago
Which is what we do. The rest of what we believe makes us special is simply emergent, and arbitrarily defined in terms of just being further useful pattern recognition, rather than any fundamental property of "intelligence".

readyplayeremma 4y ago

AI is not a well-defined term. This is more likely a specific machine learning technique that is designed to identify all the boring "normal stuff" and ignore it, and then do that at very large scale. By doing that, you can find the interesting parts so that humans with more limited resources can determine if those newly flagged things need to be added to the boring list, or if they do represent something truly interesting. edit: After reading the article a bit more, it is using a random forest classifier. This is almost certainly not meeting the definition of what many here are thinking when the term "AI" is being used in the title. The term is clearly used here for marketing purposes.

haupt 4y ago
>The term is clearly used here for marketing purposes. I think most uses are for sensationalistic purposes. I'd wager almost nobody in the general public really understands what AI is or can pin it down. It doesn't help when so many different media outlets abuse the terminology by using it to refer to different things. What's even worse is that whatever ideas people have about AI tend to come from Hollywood.
nyrikki 4y ago
They are talking about ML, which is statistical pattern matching and finding. Gödel ruined the fun of automated theorem testing a century ago unless we make significant discoveries in math. Type inference is an accessable example of SOTA automated reasoning if you want a more realistic idea of what our current constraints are. We will be restricted to Human assisted Turing machines for the foreseeable future unless there is a major development in pure math. Remember we can't even build a logically consistent model of arithmetic due to Gödel.
- uncletaco 4y ago
  Nitpicky and probably universalist or whatever but the fact that we can't build a logically consistent model was always the case, Gödel just discovered it.
  - nyrikki 4y ago
    No, you are most likely correct, I personally haven't found anything that even gives a reason to hope. But as reductionism and Laplacian Determinism are taught as cannon and not as the best option I sugar coated it. The Wada property arising in simple models like predator/prey models with simple added factors like fear/cover probably also suggests that even simple models may be indeterminate at least with binary operations like modern algebra is based on. Three attractors or exit basins can make this unintuitive topological feature pop up. Note that that fractal behavior is topological and not scale invariant noise like is typically studied with topics like fractal scattering. Indecomposable continua like the Wada property aren't solvable with probabilistic models using automata like in the standard model, which is lucky enough to have less than three exit basins. Here is one fairly accessable paper on the Wada property. Hopefully some n-ary algebras may come forward to deal with restricted problems, but even if we could create a logically consistent model of arithmetic, binary operations will still be indeterminate with feature like the Wada property even with perfect knowledge of initial conditions. https://www.researchgate.net/publication/365233050_Organized_periodic_structures_and_coexistence_of_triple_attractors_in_a_predator-prey_model_with_fear_and_refuge https://www.researchgate.net/publication/365233050_Organized...

buddhistan 4y ago

No one claimed the AI "is so smart" - it's another tool in their kit. The article clearly conveys that the potential is a useful way to augment human-led research by providing a way of quickly processing large datasets i.e. the 20k signals are filtering down 150 terabytes of data which is much more manageable for human analysis. It's not like we have definitive parameters of what constitutes an "alien signal," so we can't exactly create an absolute model for detecting such telemetry. Instead the goal of the article is to simply demonstrate exciting new ways to leverage machine learning methods in different contexts

HdS84 4y ago

Trying to filter noise from data also follows the 80,/20 principle. The rules for the easy cases is written easily but then you have one-offs, maybes and special cases. Trying to filter one of these does not cover anything else. So doing it manually takes the same time. Case study: had to clean a list of German addresses once. Excluding obviously invalid addresses like some Chinese address was easy. But some addresses had errors which needed a human eye to fix and correct.

remarkEon 4y ago

I'm assuming that the 20,515 signals of interest come from a pool that's one or several orders of magnitude larger than 20,515.

zh3 4y ago
I understand. Still, the point remains that the AI is, in this case, clearly inferior to humans (I would have been impressed if the humans found 20,515 signatures and the AI only - verifably - found eight of them to be worth following up).
- groestl 4y ago
  > clearly inferior to humans But maybe we are just proto-AI, running on a different platform
- gowld 4y ago
  "inferior" is a funny word for "doesn't perfectly impersonate us".

jacobsenscott 4y ago

Because it isn't AI. It is just statistical models. AI is for marketing.

tshaddox 4y ago

How do you judge whether 20,515 is a large number or a small number? If the AI provided 2 candidates is that still too high?

flangola7 4y ago
SETI@home sorted through I think trillions of data points.
ad404b8a372f2b9 4y ago
Any 10000s of something is a large number when it involves human work.
- fnordpiglet 4y ago
  Imagine that tax returns for millions of people were all processed by hand not but a few decades ago.
  - umeshunni 4y ago
    And that required 1000s of people
    - fnordpiglet 4y ago
      And the results here were three orders of magnitude less, so they require single digits people.
      - Retric 4y ago
        Assuming the task was of similar difficulty and the deadline was equally short. I doubt those assumptions hold.
        fnordpiglet 4y ago
        True. I bet the tax returns were harder and had a bounded deadline, unlike an academic research paper.

naasking 4y ago

Because the statistical models powering AI don't have the depth of understanding of a PhD in this field, and so it casts a wide net to ensure nothing gets missed and then a more refined search by human heuristics is needed.

nl 4y ago

The others were "intelligent" signals but from human interference. There's a lot of this so the unique patterns don't occur often enough to automate. The paper is actually worth reading about this part[1]. They have a moderately complex pipeline that you can think of as a filter: it tries to find anomalous signals. The stage-1 autoregressor filtered 115M signals to 3M. Then they perform signal processing techniques to remove things like GPS signal contamination ("t can be seen that certain observing frequencies contain a much higher number of events compared with the others—for example, the region around 1,600 MHz. This overlaps with known RFI at the GBT site specifically from persistent GPS signals."). After this second stage they are left with 20,515 potential signals which were visually inspected. The issue here is that we don't know what a alien signal looks like so we can't just use a classifier. The pipeline can only find things it has never seen before, but it takes human judgement to decide if these signals are "alien" or more likely contamination from human sources that weren't filtered ("Regarding the nature of the rest of the events, most of them look like false positives associated with RFI signals.") [1] https://www.nature.com/articles/s41550-022-01872-z.epdf?sharing_token=t6jjoqbFXFLJH8B5_RNzEtRgN0jAjWel9jnR3ZoTv0Mkq1U55F4UpwCyo9pvCV4lj--uzspzi_o3Nto3GrgPPPK7bN8GhKil2WvNSdFgUJmpmWo-kBOlWGQDS8nBDmrm5jSNwB_Db9767cFT2RRBBvupuVMql4JeV3b9Nn2FjQw%3D https://www.nature.com/articles/s41550-022-01872-z.epdf?shar...

nanidin 4y ago

I think it's useful to replace "AI" with "app" any time you encounter it in the wild. AI is a set of computational techniques that is very broad. The problem with considering "the AI" or "an AI" is that people have in mind some kind of AI agent and that isn't really the case. AI is also not well defined - day one of my AI course in university opened with "What is AI?" Generally once we figure out how to do something using a computer, we decide that's not really intelligent anymore so the implementation isn't AI. An example of that is the minimax algorithm - it's featured "AI: A Modern Approach"[0] but it isn't really something people think of when they hear "an AI". [0] https://aima.cs.berkeley.edu/contents.html https://aima.cs.berkeley.edu/contents.html

ETH_start 4y ago

The AI is fast, not smart.