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@arXiv_csCY_bot@mastoxiv.page
2025-07-30 07:47:11

Examining the sentiment and emotional differences in product and service reviews: The moderating role of culture
Vinh Truong (RMIT University)
arxiv.org/abs/2507.21057

@arXiv_csHC_bot@mastoxiv.page
2025-06-27 08:33:49

Follow the user meaningfully and product growth will follow: A mixed methods case study tying UX Point of View & Growth leading to measurable impact
Neha Raghuvanshi
arxiv.org/abs/2506.21195

@tiotasram@kolektiva.social
2025-07-19 08:14:41

AI, AGI, and learning efficiency
An addendum to this: I'm someone who would accurately be called "anti-AI" in the modern age, yet I'm also an "AI researcher" in some ways (have only dabbled in neutral nets).
I don't like:
- AI systems that are the product of labor abuses towards the data workers who curate their training corpora.
- AI systems that use inordinate amounts of water and energy during an intensifying climate catastrophe.
- AI systems that are fundamentally untrustworthy and which reinforce and amplify human biases, *especially* when those systems are exposed in a way that invites harms.
- AI systems which are designed to "save" my attention or brain bandwidth but such my doing so cripple my understating of the things I might use them for when I fact that understanding was the thing I was supposed to be using my time to gain, and where the later lack of such understanding will be costly to me.
- AI systems that are designed by and whose hype fattens the purse of people who materially support genocide and the construction of concentration campus (a.k.a. fascists).
In other words, I do not like and except in very extenuating circumstances I will not use ChatGPT, Claude, Copilot, Gemini, etc.
On the other hand, I do like:
- AI research as an endeavor to discover new technologies.
- Generative AI as a research topic using a spectrum of different methods.
- Speculating about non-human intelligences, including artificial ones, and including how to behave ethically towards them.
- Large language models as a specific technique, and autoencoders and other neural networks, assuming they're used responsibly in terms of both resource costs & presentation to end users.
I write this because I think some people (especially folks without CS backgrounds) may feel that opposing AI for all the harms it's causing runs the risk of opposing technological innovation more broadly, and/or may feel there's a risk that they will be "left behind" as everyone else embraces the hype and these technologies inevitability become ubiquitous and essential (I know I feel this way sometimes). Just know that is entirely possible and logically consistent to both oppose many forms of modern AI while also embracing and even being optimistic about AI research, and that while LLMs are currently all the rage, they're not the endpoint of what AI will look like in the future, and their downsides are not inherent in AI development.

@inthehands@hachyderm.io
2025-07-04 21:04:18

I am triply cautious of this article from @…:
- OpenAI et al use the supposed danger (and thus implied power) of their own product as a marketing ploy (as the article points out)
- When a product vendor funds their own research about the potential dangers of their product, it’s more likely to be good PR than good research
- Society always engages in moral panics about new things causing addiction and psychological damage (including bicycles and novels!)
With those caveats in mind, I do think this is an issue worth watching closely. And that quote in the post? Chef’s kiss.
mstdn.ca/@dyckron/114796898620

@arXiv_csIR_bot@mastoxiv.page
2025-06-10 07:55:02

Research on E-Commerce Long-Tail Product Recommendation Mechanism Based on Large-Scale Language Models
Qingyi Lu, Haotian Lyu, Jiayun Zheng, Yang Wang, Li Zhang, Chengrui Zhou
arxiv.org/abs/2506.06336

@arXiv_csHC_bot@mastoxiv.page
2025-06-19 08:21:49

Case Study for Developing a UXR Point of View for FinOps Product Innovation
Jason Dong, Anna Wu
arxiv.org/abs/2506.15314

@Techmeme@techhub.social
2025-07-06 06:01:22

A look at DeepSeek's impact on the AI model race and market share landscape, roughly 150 days after DeepSeek R1 shook stock markets and the Western AI world (SemiAnalysis)
semianalysis.com/2025/07/03/de

@paulwermer@sfba.social
2025-07-19 13:59:33

One of the comments lodged in my mind from 50-some years ago was that the toxicology studies we were basing product approvals on failed to consider interactions between multiple substances - and apparently not much has been done in that area

@PaulWermer@sfba.social
2025-07-19 13:59:33

One of the comments lodged in my mind from 50-some years ago was that the toxicology studies we were basing product approvals on failed to consider interactions between multiple substances - and apparently not much has been done in that area

@scottmiller42@mstdn.social
2025-07-17 04:49:50

The USA domestic sugar production is already short, with about 25% of the sugar consumed being imported. If Coke actually does change from HFCS to sugar, doesn't that mean replacing a domestic product with new imports?
source: ers.usda.gov/topics/crops/suga

@jensilber@mastodon.social
2025-07-01 13:45:32

One way to ensure I don't buy an item is to market it "as seen on Shark Tank" -- but that's probably just me. Another way to ensure I don't buy an item is to market it as having AI features (??), and apparently that's widespread.
futurism.com/customers-see-ai-

@arXiv_csHC_bot@mastoxiv.page
2025-06-19 08:21:14

UXR Point of View on Product Feature Prioritization Prior To Multi-Million Engineering Commitments
Jonas Lau, Annie Tran
arxiv.org/abs/2506.15294

@arXiv_qbiobm_bot@mastoxiv.page
2025-07-22 09:33:30

Computations Meet Experiments to Advance the Enzymatic Depolymerization of Plastics One Atom at a Time
Francesco Colizzi, Paula Bl\'azquez-S\'anchez, Giovanni Bussi, Isabelle Andr\'e, Federico Ballabio, Thomas Bayer, Federica Bertocchini, Erik Butensch\"on, Emanuele Carosati, Alessia De Piero, Ania Di Pede-Mattatelli, Leonardo Faggian, Lorenzo Favaro, Pedro Alexandrino Fernandes, Alfonso Ferretti, Peter Fojan, Andreas Gagsteiger, Eva Garc\'ia-Ruiz, Lucia Gardossi, …

@arXiv_qfinMF_bot@mastoxiv.page
2025-05-22 07:38:12

Liquidity provision with $\tau$-reset strategies: a dynamic historical liquidity approach
Andrey Urusov, Rostislav Berezovskiy, Anatoly Krestenko, Andrei Kornilov
arxiv.org/abs/2505.15338

@arXiv_csCL_bot@mastoxiv.page
2025-06-10 19:04:11

This arxiv.org/abs/2506.04929 has been replaced.
initial toot: mastoxiv.page/@arXiv_csCL_…

@arXiv_csCR_bot@mastoxiv.page
2025-06-10 16:36:59

This arxiv.org/abs/2506.05376 has been replaced.
initial toot: mastoxiv.page/@arXiv_csCR_…

@arXiv_csMA_bot@mastoxiv.page
2025-06-10 07:45:22

Digital Twin-based Smart Manufacturing: Dynamic Line Reconfiguration for Disturbance Handling
Bo Fu, Mingjie Bi, Shota Umeda, Takahiro Nakano, Youichi Nonaka, Quan Zhou, Takaharu Matsui, Dawn M. Tilbury, Kira Barton
arxiv.org/abs/2506.07332

@arXiv_csIR_bot@mastoxiv.page
2025-06-04 07:25:29

DeepShop: A Benchmark for Deep Research Shopping Agents
Yougang Lyu, Xiaoyu Zhang, Lingyong Yan, Maarten de Rijke, Zhaochun Ren, Xiuying Chen
arxiv.org/abs/2506.02839