Sameer Soi @sameersoi
Dropping science like Galileo dropped the orange. VP DS & AI @AbaloneBio, ex-DS/ML @Atomwise @Zymergen, @grandroundsinc, PhD @UPennGCB sameersoi.com Bay Area, CA Joined October 2012-
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@pitdesi @Jason People forget that this was normalized (I heard this kind of casually racist banter in the open in western PA in the 90s and aughts). We might look back and see the 2010s were a blip.
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@FanBoyShi @vsbuffalo Definitely heard about its use at 10X
@thotmanifestor @InjeelJiday @SashaGusevPosts And for a more thorough edification on the matter: ncbi.nlm.nih.gov/pmc/articles/P…
@thotmanifestor @InjeelJiday @SashaGusevPosts Now tell me what % of variation is explained by those PCs. Not to mention sampling can produce patterns in PCA that can easily be over interpreted.
@Katie_Krause @CA_EDD @GovPressOffice @latimes No, never. I was able to figure out my issue by consulting my company’s HR provider as well as Internet forums. I never got through to a human even once.
I phone @CA_EDD all days of the week x hours of operation to ask about PFL. Each time the call queue is full. Instead of arranging a callback as one would expect in 2024, the call is unceremoniously dropped. Each time. @GovPressOffice is this the best CA can do for new parents?
@mnp_47 @vsbuffalo But you like the languages you like and those tastes change too! I used to love R the switched to Scala and then python. Now I look at R code and get a mild concussion.
@mnp_47 @vsbuffalo This functional style is employed by the popular dplyr syntax in R, which many people find readable. Ofc it wasn’t invented there (see OCaML, Scala, F# etc). The resulting code reads more like a narrative than typical procedural code.
@BauerKahan would appreciate knowing your thoughts on how new parents should be supported by @CA_EDD
@sanjaypartly You stink. Am I doing it right?
@Codie_Sanchez (Assuming they died due to aging and not randomly)
@Codie_Sanchez The exact same plot could be generated if people in the trades literally died (or retired) and no one replaced them. You would need to see if the number of people in trades were increasing at the same time.
@joe_pickrell A tardy April’s Fools’ Day?
@dhh @NZXT @AMD @PyTorch @lightning @Neovim @codeiumdev @humanscale Eco Sit, @audioengineusa P4 speakers, @hifimanofficial Sundara headphones and @HermanMiller chair are crucial to the full experience as well!
@dhh Custom built desktop @NZXT case @AMD Ryzen 12-cores, 96GB RAM running Ubuntu; python + @PyTorch + @lightning all edited through @Neovim with some help from @codeiumdev. Pure joy.
@dan_biderman @cherrvak @brianltrippe Fair. A lot of benchmarking in bio-ML is about out-of-domain generalization. Often we are interested in how predictions about proteins we don't know much about will fare. This could align with your result that LoRA is a good regularizer that helps with generalization.
@dan_biderman @cherrvak @brianltrippe Right from the abstract "On the PPI prediction task, we surprisingly find that PEFT models actually outperform traditional fine-tuning while using two orders of magnitude fewer parameters."
@dan_biderman @cherrvak @brianltrippe Here's a good ref: biorxiv.org/content/10.110… Similar in spirit to how we are doing it in our application area.
@dan_biderman @cherrvak @brianltrippe (I can't answer that but I use LoRA for finetuning antibody PLM's on activity signals)
Joshua G. Schraiber @jgschraiber
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