Tootfinder

I think we all knew a Melon Husk / Turnip meltdown was inevitable, but I didn't think it'd happen this soon, escalate this quickly, or blowup this spectacularly.
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#MelonHusk #POTUS47

Teknologiakritiikin ja -kriitikoiden tarpeesta. Taiteessa on kriitikoilla ja kritiikillä tärkeä rooli. (...) Teknologian maailmassa ei juurikaan ole tuollaista kritiikkiä, vaan arviointi on analyysiä jostain näkökulmasta (...) No niin, voisi miettiä olisiko teknologiakritiikissä ideaa. Se voisi kohdistua suoraan teknologiaan, kuten tekoäly, tai teknologiahypetykseen. Sellaisen sisältöjä jälkimmäisessä tapauksessa olisivat esim.
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Teknologiakritiikin ja -kriitikoiden tarpeesta. | Matti Vuori
Teknologiakritiikin ja -kriitikoiden tarpeesta. Taiteessa on kriitikoilla ja kritiikillä tärkeä rooli. Kaikkihan nykyään jo tietävät, että taidekritiikki ei ole negatiivista virheiden etsimistä, vaan prosessi ja tuotos, jolla etsitään teoksen olennaisuuksia, laatuja, erityisyyksiä liittämällä se taidelajin historiaan ja nykykenttään, genreihin jne., ymmärtäen taiteilijan pyrkimyksiä, teosten myötä paljastuvaa identiteettiä. Samalla kritiikki itsessään on kriitikon teos …

MoLink: Distributed and Efficient Serving Framework for Large Models
Lewei Jin, Yongqi Chen, Kui Zhang, Yifan Zhuo, Yi Gao, Bowei Yang, Zhengong Cai, Wei Dong
https://arxiv.org/abs/2507.05043

MoLink: Distributed and Efficient Serving Framework for Large Models
Large language models represent a groundbreaking shift in generative AI. Yet, these advances come with a significant challenge: the high cost of model serving. To mitigate these costs, consumer-grade GPUs emerge as a more affordable alternative. This presents an opportunity for more cost-efficient LLM serving by leveraging these GPUs. However, it is non-trivial to achieve high-efficiency LLM serving on consumer-grade GPUs, mainly due to two challenges: 1) these GPUs are often deployed in limi…

Hiding in Plain Sight: Query Obfuscation via Random Multilingual Searches
Anton Firc, Jan Klus\'a\v{c}ek, Kamil Malinka
https://arxiv.org/abs/2506.04963

Hiding in Plain Sight: Query Obfuscation via Random Multilingual Searches
Modern search engines extensively personalize results by building detailed user profiles based on query history and behaviour. While personalization can enhance relevance, it introduces privacy risks and can lead to filter bubbles. This paper proposes and evaluates a lightweight, client-side query obfuscation strategy using randomly generated multilingual search queries to disrupt user profiling. Through controlled experiments on the Seznam.cz search engine, we assess the impact of interleaving…

Daydream, which raised a $50M seed in June 2024 to build a generative AI shopping agent for fashion, launches in beta, with an app expected later this summer (Hilary Milnes/Vogue Business)
https://www.voguebusiness.com/story/techno

Is Daydream’s AI platform the answer to fashion’s discovery problem?
Founder Julie Bornstein raised $50 million last year to create the ultimate AI shopping experience. Today, it launches in beta.

I decided to share some of my observations that would benefit you if you are building applications: a deep dive session into the archetypes of attackers.
This session is for people who are developing software of any kind. It could be an API endpoint, a blog, or a complex application used by millions.
Join in or share with smart people.
Let me help you!