Tootfinder

Elizabeth May is and always has been a voice of reason and thoughtfulness in Parliament.
I also think this is a not-too-subtle dig at the current leader of the Conservative Party of Canada who distinguishes himself as the only leader *choosing* not to get top-secret clearance.
Being any part of the Government of a country should be taken seriously and these leaders should sit down and talk.

#VfL Stadion Sanierungsfinanzierung (in der Fantasie ~69Mio €) fast in trocknen Tüchern.
Nach Einsparungen bei der Erweiterung der Radinfrastruktur hat es nun auch die Vorstandsetage der Stadt #Osnabrück getroffen.
€

Sen. Warren warns Powell against weakening banking regulations: 'Do your job' (Hugh Son/CNBC)
https://www.cnbc.com/2024/06/18/sen-elizabeth-warren-powell-basel-iii-endgame.html
http://www.memeorandum.com/240618/p49#a240618p49

Mike Walker on X: "The window for Robert F. Kennedy Jr. to qualify for the first presidential debate is closing rapidly. https://t.co/QZehbsDyJN" / X

Debate window is closing fast for RFK Jr.
CNN said that Kennedy is only eligible for 89 electoral votes, well short of the debate requirement.

🔊 #NowPlaying on #BBCRadio3:
#Unclassified
- A Date with Dublin
For Bloomsday, the great celebration of Dublin as portrayed in Joyce’s Ulysses, Elizabeth Alker offers the best ambient and neo-classical music being made in the city today.
Relisten now 👇
https://www.bbc.co.uk/programmes/m00202zk

Tänkvärt om DCA avtalet. Det jag blir fundersam över är varför Sverje-vännerna så gärna ger bort svensk mark till USA #sv #svpol #dca

On the long time behaviour of solutions to the Navier-Stokes-Fourier system on unbounded domains
Elisabetta Chiodaroli, Eduard Feireisl
https://arxiv.org/abs/2406.09587

On the long time behaviour of solutions to the Navier-Stokes-Fourier system on unbounded domains
We consider the Navier-Stokes-Fourier system on an unbounded domain in the Euclidean space $R^3$, supplemented by the far field conditions for the phase variables, specifically: $ρ\to 0,\ \vartheta \to \vartheta_\infty, \ u \to 0$ as $\ |x| \to \infty$. We study the long time behaviour of solutions and we prove that any global-in-time weak solution to the NSF system approaches the equilibrium $ρ_s = 0,\ \vartheta_s = \vartheta_\infty,\ u_s = 0$ in the sense of ergodic averages for t…

You are what you eat? Feeding foundation models a regionally diverse food dataset of World Wide Dishes
Jabez Magomere, Shu Ishida, Tejumade Afonja, Aya Salama, Daniel Kochin, Foutse Yuehgoh, Imane Hamzaoui, Raesetje Sefala, Aisha Alaagib, Elizaveta Semenova, Lauren Crais, Siobhan Mackenzie Hall
https://arxiv.org/abs/2406.09496 https://arxiv.org/pdf/2406.09496
arXiv:2406.09496v1 Announce Type: new
Abstract: Foundation models are increasingly ubiquitous in our daily lives, used in everyday tasks such as text-image searches, interactions with chatbots, and content generation. As use increases, so does concern over the disparities in performance and fairness of these models for different people in different parts of the world. To assess these growing regional disparities, we present World Wide Dishes, a mixed text and image dataset consisting of 765 dishes, with dish names collected in 131 local languages. World Wide Dishes has been collected purely through human contribution and decentralised means, by creating a website widely distributed through social networks. Using the dataset, we demonstrate a novel means of operationalising capability and representational biases in foundation models such as language models and text-to-image generative models. We enrich these studies with a pilot community review to understand, from a first-person perspective, how these models generate images for people in five African countries and the United States.
We find that these models generally do not produce quality text and image outputs of dishes specific to different regions. This is true even for the US, which is typically considered to be more well-resourced in training data - though the generation of US dishes does outperform that of the investigated African countries. The models demonstrate a propensity to produce outputs that are inaccurate as well as culturally misrepresentative, flattening, and insensitive. These failures in capability and representational bias have the potential to further reinforce stereotypes and disproportionately contribute to erasure based on region. The dataset and code are available at https://github.com/oxai/world-wide-dishes/.

On the long time behaviour of solutions to the Navier-Stokes-Fourier system on unbounded domains
Elisabetta Chiodaroli, Eduard Feireisl
https://arxiv.org/abs/2406.09587

On the long time behaviour of solutions to the Navier-Stokes-Fourier system on unbounded domains
We consider the Navier-Stokes-Fourier system on an unbounded domain in the Euclidean space $R^3$, supplemented by the far field conditions for the phase variables, specifically: $ρ\to 0,\ \vartheta \to \vartheta_\infty, \ u \to 0$ as $\ |x| \to \infty$. We study the long time behaviour of solutions and we prove that any global-in-time weak solution to the NSF system approaches the equilibrium $ρ_s = 0,\ \vartheta_s = \vartheta_\infty,\ u_s = 0$ in the sense of ergodic averages for t…

You are what you eat? Feeding foundation models a regionally diverse food dataset of World Wide Dishes
Jabez Magomere, Shu Ishida, Tejumade Afonja, Aya Salama, Daniel Kochin, Foutse Yuehgoh, Imane Hamzaoui, Raesetje Sefala, Aisha Alaagib, Elizaveta Semenova, Lauren Crais, Siobhan Mackenzie Hall
https://arxiv.org/abs/2406.09496 https://arxiv.org/pdf/2406.09496
arXiv:2406.09496v1 Announce Type: new
Abstract: Foundation models are increasingly ubiquitous in our daily lives, used in everyday tasks such as text-image searches, interactions with chatbots, and content generation. As use increases, so does concern over the disparities in performance and fairness of these models for different people in different parts of the world. To assess these growing regional disparities, we present World Wide Dishes, a mixed text and image dataset consisting of 765 dishes, with dish names collected in 131 local languages. World Wide Dishes has been collected purely through human contribution and decentralised means, by creating a website widely distributed through social networks. Using the dataset, we demonstrate a novel means of operationalising capability and representational biases in foundation models such as language models and text-to-image generative models. We enrich these studies with a pilot community review to understand, from a first-person perspective, how these models generate images for people in five African countries and the United States.
We find that these models generally do not produce quality text and image outputs of dishes specific to different regions. This is true even for the US, which is typically considered to be more well-resourced in training data - though the generation of US dishes does outperform that of the investigated African countries. The models demonstrate a propensity to produce outputs that are inaccurate as well as culturally misrepresentative, flattening, and insensitive. These failures in capability and representational bias have the potential to further reinforce stereotypes and disproportionately contribute to erasure based on region. The dataset and code are available at https://github.com/oxai/world-wide-dishes/.