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14 results for dl.acm.org:

Fantastic-Climate-84 t1_it3gsnv wrote on October 20, 2022 at 5:34 PM

Reply to The End of Moore’s Law: Silicon computer chips are nearing the limit of their processing capacity. But is this necessarily an issue? Copenhagen Institute for Futures Studies by CPHfuturesstudies

state buildings and legal battles ensued. Can’t find anything in two minutes here. 2003 - https://dl.acm.org/doi/10.1109/MC.2003.1250885 2002 - https://spectrum.ieee.org/the-death-of-moores-law-will-spur-innovation This is a long way of saying “is it that time if year

chrisdh79 OP t1_itx3u90 wrote on October 26, 2022 at 11:00 PM

Reply to Facebook Segments Ads by Race and Age Based on Photos | Ads with teenage girls are mostly directed at men over 55, while white people see fewer ads with Black faces, a new study finds. by chrisdh79

Meta, Facebook’s parent company. But outside research sometimes offers a glimpse. A new [study](https://dl.acm.org/doi/10.1145/3517745.3561450) published Tuesday in the Association for Computer Machinery’s Digital Library journal finds that Facebook uses image

idrajitsc t1_iy8hyiv wrote on November 29, 2022 at 3:26 PM

Reply to comment by Ingvariuss in [P] Speaking with Plato - A Deep Learning Approach to Philosophy by Ingvariuss

question!" Which lends it a credibility it doesn't deserve. You should read [this paper](https://dl.acm.org/doi/10.1145/3442188.3445922) and particularly section 5 and its citations. edit: sorry I meant section

No_Cryptographer9806 t1_j5ufip4 wrote on January 25, 2023 at 5:22 PM

Reply to [D] Self-Supervised Contrastive Approaches that don’t use large batch size. by shingekichan1996

FastSiam: SimSiam that fit on one GPU small batch size (down to 32 smth) https://dl.acm.org/doi/abs/10.1007/978-3-031-16788-1_4

ImZanga t1_j8gh6ci wrote on February 14, 2023 at 3:05 AM

Reply to [R] What are some papers that describe TikTok's algorithm? by Thin-Shirt6688

/ffe8/77e4093a8f879d5543c71cf294488effb0a7.pdf) * [Trick and Please. A Mixed-Method Study On User Assumptions About the TikTok Algorithm (2021)](https://dl.acm.org/doi/pdf/10.1145/3447535.3462512) * [Leveraging Rights of Data Subjects for Social Media Analysis: Studying TikTok via Data Donations

alexiuss t1_jar5i61 wrote on March 3, 2023 at 1:41 PM

Reply to comment by Slow-Schedule-7725 in Really interesting article on LLM and humanity as a whole by [deleted]

lost their jobs as co-leads of Google’s Ethical AI team." Link to the paper: https://dl.acm.org/doi/epdf/10.1145/3442188.3445922 I can see why they go fired, thats a really bad paper with lots of assumptions

ACH-S t1_jawnajq wrote on March 4, 2023 at 5:21 PM

Reply to [D] Are Genetic Algorithms Dead? by TobusFire

would recommend that you have a look at the proceedings from the GECCO conference (*e.g.* [*https://dl.acm.org/doi/proceedings/10.1145/3512290*](https://dl.acm.org/doi/proceedings/10.1145/3512290) , the conference is much smaller than neurips/ICML/etc, and the research quality tends to be a bit more

currentscurrents t1_jc03yjr wrote on March 13, 2023 at 1:31 AM

Reply to comment by Dendriform1491 in [P] Discord Chatbot for LLaMA 4-bit quantized that runs 13b in <9 GiB VRAM by Amazing_Painter_7692

could pack more bits in your bit with [in-memory compression.](https://dl.acm.org/doi/10.1145/3394885.3439194) You'd need hardware support for decompression inside the processor core

U03B1Q t1_je4xekj wrote on March 29, 2023 at 1:20 PM

Reply to Variance in reported results on ImageNet between papers [D] by kaphed

dl.acm.org/doi/10.1145/3324884.3416545 There was an ASE paper that found that even under identical hyperparameter seed settings networks had a variance of about 2% due to non-determinism in the parallel computing workflow. If they chose

elections. **Ask me anything!** **More Info:** Read the TechBrief on Election Security: Risk-limiting Audits [https://dl.acm.org/doi/pdf/10.1145/3568005](https://dl.acm.org/doi/pdf/10.1145/3568005) ACM TechBriefs is a series of technical bulletins by ACM’s Technology Policy Council that present scientifically

there's another way that I can score popularity. I've currently found papers like this: https://dl.acm.org/doi/abs/10.1145/2661714.2661722 but they're rather old. Wondering if there's a better way to go about this

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14 results for dl.acm.org:

People who post stories marked false by Snopes on Reddit fall into five groups: Reason to Disagree, Changed Belief, Steadfast Non-Standard Belief, Sharing to Debunk, and Sharing for Humor. Reducing misinformation requires different approaches for each group.

Using AI to combat human trafficking raises ethical concerns including bias endemic in datasets, privacy risks stemming from data collection and reporting, and issues concerning potential misuse

One in twenty Reddit comments violates subreddits’ own moderation rules, e.g., no misogyny, bigotry, personal attacks