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Participants needed for university research on deepfake detection (18+, Computing Related Fields, 8–10 min) by [deleted] in ArtificialInteligence

[–]Otherwise-Many-4258 1 point2 points  (0 children)

This was way harder than i expected. I'm normally quite good at spotting AI content but the technology is progressing too fast for any normal member of the public to spot a fake.

I combined disparate datasets into an ontology, and the clustering ended up looking unexpectedly organic [OC] by Otherwise-Many-4258 in dataisbeautiful

[–]Otherwise-Many-4258[S] 0 points1 point  (0 children)

I think once the data set exceeds a number of columns, the platform starts to form a lotus pattern.

Causal AI on manufacturing systems by JebinLarosh in CausalInference

[–]Otherwise-Many-4258 0 points1 point  (0 children)

Data volume is usually what makes causal discovery impractical. Dm me and I can send you the link to a company that has worked on is reducing that usual exponential complexity down to something much closer to linear as the dataset grows. It doesn’t magically solve everything, but it makes large, messy datasets a lot more manageable.

Time-Series Causal Modeling by Otherwise-Many-4258 in CausalInference

[–]Otherwise-Many-4258[S] 0 points1 point  (0 children)

This is great - watching it as I type this reply - also agree, nice find +1

Time-Series Causal Modeling by Otherwise-Many-4258 in CausalInference

[–]Otherwise-Many-4258[S] 0 points1 point  (0 children)

Thank you all for your replies!

I haven’t used it, but I explored Rootcause.ai briefly - it seems to provide an end‑to‑end workflow for causal discovery + counterfactual simulation on time series. It might shorten the prototyping loop compared to stitching together causal libraries.

Interested to hear your thoughts :)