mdlincoln

Prolific | Senior Software Engineer | Hybrid ONSIDE 1-2 days/wk Bay Area | $200k-$250k

Prolific is not just another player in the AI space – we are the architects of the human data infrastructure that's reshaping the landscape of AI development. In a world where foundational AI technologies are increasingly commoditized, it's the quality and diversity of human-generated data that truly differentiates products and models.

We’re looking for impact-focused Software Generalists to join our specialized team focused on serving frontier model creators and enterprise AI application developers. As a full-stack engineer, you will work across Prolific’s domains to solve customer and product problems.

This is an exciting opportunity to work directly with frontier AI companies, making critical technical decisions that balance scrappy startup execution with scalable, reliable engineering, as Prolific revolutionizes research for the AI community. You'll will have regular in person collaboration with customers and our US team, as well as collaborate closely with our UK-based tech teams.

Unfortunately we don't sponsor US visas at this time.

Apply: https://job-boards.eu.greenhouse.io/prolific/jobs/4767348101

context-dependent, or "reified" assertions are a pain point for sure. I come from the perspective of cultural heritage data, where context is king. Which expert made this attribution for this painting? Who owned it _when_? According to which archival document? etc.

Almost all the engineering problems cited in the original post are still basically there, but graphical models are still the least painful way of doing this, particularly when trying to share data between institutions. Example: https://linked.art/model/assertion/

You may be interested in what Birkbeck has been developing: https://github.com/BirkbeckCTP/janeway

Just commenting to add this wonderfully succinct summary of the post by John Overholt:

It takes a tremendous amount of work to make the work that goes into photographing this goblet invisible.

https://twitter.com/john_overholt/status/991110369082068992

Several hundred publications from the Getty Museum (and the other research arms of the Getty) are available for free download as well: https://www.getty.edu/publications/virtuallibrary/

(I work at the Getty Research Institute)

I find that a fascinating reaction given how rapidly %>% have been taken up across a large segment of the R universe, to great excitement! Personally, I find it far MORE legible than endlessly-nested function calls.

It results in code that more closely resembles executed order of operations (e.g. filter -> mutate -> group -> summarize). Context is also key: it's most often used for data processing pipelines in specific analytical scripts or literate-code documents - less so used when defining generalizable/testable functions in packages (again, just a personal perspective - YMMV of course)

A related aside: while forgeries - deliberate imitations to mislead and deceive - are exciting, they only represent a very tiny portion of art attribution questions. In reality, these tend to deal more with discerning between artists working in the same period, rather than those attempting to fool the eye at several centuries' remove.

For example, the Rembrandt Research Project infamously set out to identify genuine vs. fake Rembrandt paintings in his corpus of known works under the false assumption that there would be a lot of 18th/19th/20th century forgeries. In fact, most of the "non-Rembrandt" cases they found were not later imitations, but instead works done by his own students or contemporaries - or works co-produced by Rembrandt and another. The result - deconstructing the project's original false assumption - proved revolutionary for our understanding of artistic studio practice from the period, but failed to locate many "forgeries" as such.

A review (paywalled, sorry!): http://www.sciencedirect.com/science/article/pii/02604779899...

And a Met exhibition: http://www.metmuseum.org/art/metpublications/Rembrandt_Not_R...

I'm working on pulling the images now, like I did for the Rijksmuseum CC0 dump. FWIW a good place to host that torrent is the Internet Archive - it's great for discoverability.

And if you want a TL;DR: http://neverworkintheory.org/2016/09/30/rethinking-git.html

The NYPL has posted metatdata about these collections on GitHub as well

https://github.com/NYPL-publicdomain/data-and-utilities

Oh, it wouldn't have to be that format in particular, I was just guessing how you might represent the worksheet in some useful, repurpose-able manner.

<3 this! Are there any plans for some type of export utility, e.g. some type of JSON serialization of a finished model?

It's not mentioned in this guide, but Hadley Wickham's tidyr is a more streamlined version of the reshape2 package for fitting your data into a "tidy" format necessary for ideal faceting.

Though it's probably not the largest sub-discipline, there are (and have been for some time: http://www.wiley.com/WileyCDA/WileyTitle/productCd-063122919...) a fair number of philosophers who are very interested in computing and (as you guessed) simulation as a way to approach their research questions.

Yes, I am guilty of writing the post for an audience already largely familiar with the context.

I should probably add that the types of "explanations" I put forward in this post are actually not of central concern to me - certainly not explanations derived solely from parsing quantitative results. I'm far more interested in the descriptive evidence this kind of measurement can provide. It can give wider context to what tends to be a very case-study-centric discipline (e.g. oh, this guy happened to work a lot with Italian publishers in this period? We didn't realize it before just looking at 5-10 artists per article/monograph, but actually that is quite exceptional/normal for this period...)

Then again, proposing these kinds of explanations is also something of a disciplinary norm, for better or worse.

blerg, sorry about that! Will fix when I'm done with the dissertation.

Author here, in case anyone had questions!

http://www.washingtonpost.com/news/the-intersect/wp/2015/03/...

A project apparently exploring how copyright claims result in selective censoring in the Street-View-esque images of museum collections produced by the Google Art Project.

The WaPo article actually conflates copyright and reproduction rights (I work in a museum curatorial dept. FYI) Copyright would apply to works where artists, or their estates, can still make copyright claims over their artworks (although the role of fair use in reproducing images of art is evolving: http://www.collegeart.org/fair-use/)

But why can older artworks that are now in the public domain still have their images blurred out? Although the museum may have agreed to openly release representations of the public domain works that they own, it is often the case that museums may temporarily hang works on loan from private collectors in their galleries. In cases like these, museums and the lenders work out loan terms that frequently include provisions about photography. These loan agreements supersede copyright issues. Whether or not museums should agree to such terms is, of course, a good question.