Tootfinder

Things like this are not just a symbolic expression of discontent.
Fascism depends to a •very• large extent on anticipatory compliance. It needs people to feel like things are going that way, it’s already a done deal, better to just go along with it.
Every time dissent is visible, every way dissent feels ubiquitous, every time somebody feels like they’re not alone in opposition, every time somebody who’s tempted to comply fears there might be hell to pay if they do — that directly, concretely damages the fascists’ power.

DeSantis Orders Flags To Half-Staff For Dead Racist - Joe.My.God.
https://www.joemygod.com/2025/07/desantis-orders-flags-to-half-staff-for-dead-racist/

Abelianized Descent Obstruction for 0-Cycles
Hui Zhang
https://arxiv.org/abs/2506.22980 https://arxiv.org/pdf/2506.22980

Abelianized Descent Obstruction for 0-Cycles
Classical descent theory of Colliot-Thélène and Sansuc for rational points tells that, over a smooth variety $X$, the algebraic Brauer-Manin subset equals the descent obstruction subset defined by a universal torsor. Moreover, Harari shows that the Brauer-Manin subset equals the descent obstruction subset defined by torsors under connected linear groups. By using the abelian cohomology theory by Borovoi, we define abelianized descent obstructions by torsors under connected linear groups. As a…

Global Descent Method for Non-convex Multi-objective Optimization Problems
Bikram Adhikary, Md Abu Talhamainuddin Ansary, Savin Treanta
https://arxiv.org/abs/2507.22390 https://…

Global Descent Method for Non-convex Multi-objective Optimization Problems
In this paper, we develop a global descent method for non-convex multi-objective optimization problems. The proposed approach builds upon foundational concepts from single-objective global descent techniques while removing the need for predefined scalars or ordering information of objective functions. Initially, the proposed method identifies a local weak efficient solution using any suitable descent algorithm, then applies an auxiliary function termed the multi-objective global descent functio…

Using "AI" is no longer optional at Microsoft. Reminds me how when Meta had to force their engineers to use their "Metaverse" product.
If your product doesn't even gain traction internally, maybe it's just ... shit?
(Original title: ‘AI is no longer optional’ — Microsoft admits AI doesn’t help at work)

‘AI is no longer optional’ — Microsoft admits AI doesn’t help at work
An internal Microsoft memo has leaked. It was written by Julia Liuson, president of the Developer Division at Microsoft and GitHub. The memo tells managers to evaluate employees based on how much t…

From ⁨⁨⁨⁨⁨#AnnafromUkraine⁩⁩⁩⁩⁩ @AnnafromUkraine@youtube.com
VLADIVOSTOK ON FIRE: EXPLOSIONS NEAR DESANTNAYA BAY Vlog 1059: War in #Ukraine
Explosions near the "#Desantnaya" Bay …

Fediscovery explores the possibilities for better search and discovery on the Fediverse -- in the form of an optional, pluggable service.
This service should be decentralized, independent of any one specific Fediverse service and respect user choice and privacy.
Fediscovery @ FOSDEM 2025
We were very grateful to be able to present the Fediscovery project atFOSDEM 2025. The talk was recorded and you can download both the slides and the recorded video

Fediverse Discovery Providers
A project exploring better search and discovery on the Fediverse as an optional, decentralized and pluggable service.

Proof-of-Behavior: Behavior-Driven Consensus for Trustworthy Decentralized Finance
Ailiya Borjigin, Wei Zhou, Cong He
https://arxiv.org/abs/2506.22171 http…

Proof-of-Behavior: Behavior-Driven Consensus for Trustworthy Decentralized Finance
Current blockchain protocols (e.g., Proof-of-Work and Proof-of-Stake) secure the ledger yet cannot measure validator trustworthiness, allowing subtle misconduct that is especially damaging in decentralized-finance (DeFi) settings. We introduce Proof-of-Behavior (PoB), a consensus model that (i) gives each action a layered utility score -- covering motivation and outcome, (ii) adapts validator weights using recent scores, and (iii) applies decentralized verification with proportional slashing. T…

Adaptive Stepsize Selection in Decentralized Convex Optimization
Ilya Kuruzov, Xiaokai Chen, Gesualdo Scutari, Alexander Gasnikov
https://arxiv.org/abs/2507.23725 https://

Adaptive Stepsize Selection in Decentralized Convex Optimization
We study decentralized optimization where multiple agents minimize the average of their (strongly) convex, smooth losses over a communication graph. Convergence of the existing decentralized methods generally hinges on an apriori, proper selection of the stepsize. Choosing this value is notoriously delicate: (i) it demands global knowledge from all the agents of the graph's connectivity and every local smoothness/strong-convexity constants--information they rarely have; (ii) even with perfect i…

An Asynchronous Decentralised Optimisation Algorithm for Nonconvex Problems
Behnam Mafakheri, Jonathan H. Manton, Iman Shames
https://arxiv.org/abs/2507.22311 https://

An Asynchronous Decentralised Optimisation Algorithm for Nonconvex Problems
In this paper, we consider nonconvex decentralised optimisation and learning over a network of distributed agents. We develop an ADMM algorithm based on the Randomised Block Coordinate Douglas-Rachford splitting method which enables agents in the network to distributedly and asynchronously compute a set of first-order stationary solutions of the problem. To the best of our knowledge, this is the first decentralised and asynchronous algorithm for solving nonconvex optimisation problems with conv…