Tootfinder

'Accept that quality matters more than velocity.
Measure actual resource usage, not features shipped.
Make efficiency a promotion criterion. Reward engineers who reduce resource usage. Penalize those who increase it without a corresponding value.
Stop hiding behind abstractions.
Teach fundamental engineering principles again.'
From: @…

Deceptive Risk Minimization: Out-of-Distribution Generalization by Deceiving Distribution Shift Detectors
Anirudha Majumdar
https://arxiv.org/abs/2509.12081 https://

Deceptive Risk Minimization: Out-of-Distribution Generalization by Deceiving Distribution Shift Detectors
This paper proposes deception as a mechanism for out-of-distribution (OOD) generalization: by learning data representations that make training data appear independent and identically distributed (iid) to an observer, we can identify stable features that eliminate spurious correlations and generalize to unseen domains. We refer to this principle as deceptive risk minimization (DRM) and instantiate it with a practical differentiable objective that simultaneously learns features that eliminate dis…

MonochromeEvolutionaryBioDigitalCellularAutomataSimulation
Unlike the recently shared[1] multi-cellular struggles, these here are some selected research stills (handpicked from tens of thousands) of only single CA configurations (aka mono-cultures) which I found interesting/promising and which were then used as raw ingredients/candidates for my infinitely evolving C-SCAPE project[2]...
Each of these cellular automata is 1.5D, meaning each pixel row is one generation, but I allowe…

OpenLens AI: Fully Autonomous Research Agent for Health Infomatics
Yuxiao Cheng, Jinli Suo
https://arxiv.org/abs/2509.14778 https://arxiv.org/pdf/2509.1477…

OpenLens AI: Fully Autonomous Research Agent for Health Infomatics
Health informatics research is characterized by diverse data modalities, rapid knowledge expansion, and the need to integrate insights across biomedical science, data analytics, and clinical practice. These characteristics make it particularly well-suited for agent-based approaches that can automate knowledge exploration, manage complex workflows, and generate clinically meaningful outputs. Recent progress in large language model (LLM)-based agents has demonstrated promising capabilities in lit…

The Trump administration is promising to
block billions in
already-awarded
infrastructure bill broadband grants
to any states that enforce net neutrality
or try to impose any sort of meaningful oversight on the country’s unpopular, predatory broadband monopolies.
That was the promise of Commerce Department official Arielle Roth,
a former Ted Cruz staffer now in charge of the National Telecommunications and Information Administration (NTIA).
Ro…

Trump Admin Blocking Billions In Already Awarded Broadband Grants To States That Enforce Net Neutrality Or Engage In Telecom Oversight
The Trump administration is promising to block billions in already-awarded infrastructure bill broadband grants to any states that enforce net neutrality or try to impose any sort of meaningful ove…

Combinatorial Courant-Fischer-Weyl Minimax Principle on Cheeger $k$-constants of Weighted Forests
Zijun Meng, Dong Zhang
https://arxiv.org/abs/2510.06301 https://

Combinatorial Courant-Fischer-Weyl Minimax Principle on Cheeger $k$-constants of Weighted Forests
We establish novel max-min and minimax characterizations of Cheeger $k$-constants in weighted forests, thereby providing the first combinatorial analogue of the Courant-Fischer-Weyl minimax principle. As for applications, we prove that the forest 1-Laplacian variational eigenvalues are independent of the choice of typical indexes; we propose a refined higher order Cheeger inequality involving numbers of loops of graphs and $p$-Laplacian eigenvalues; and we present a combinatorial proof for the …

Source: Vanity Fair editor Mark Guiducci asked staff to stop covering Prince Andrew's daughters, as the magazine takes a deferential approach to celebrities (Max Tani/Semafor)
https://www.semafor.com/article/11/02/2025/the-new-vanity-fa…

Exclusive: The new Vanity Fair’s one rule: Leave the princesses alone!
Vanity Fair is trying to offer meaningful journalism that reveals inner workings of power — while also convincing the powerful to pose for its covers and attend its Hollywood events.

StageACT: Stage-Conditioned Imitation for Robust Humanoid Door Opening
Moonyoung Lee, Dong Ki Kim, Jai Krishna Bandi, Max Smith, Aileen Liao, Ali-akbar Agha-mohammadi, Shayegan Omidshafiei
https://arxiv.org/abs/2509.13200

StageACT: Stage-Conditioned Imitation for Robust Humanoid Door Opening
Humanoid robots promise to operate in everyday human environments without requiring modifications to the surroundings. Among the many skills needed, opening doors is essential, as doors are the most common gateways in built spaces and often limit where a robot can go. Door opening, however, poses unique challenges as it is a long-horizon task under partial observability, such as reasoning about the door's unobservable latch state that dictates whether the robot should rotate the handle or push …

I see the universe as an endless ocean of indifference. It does not care about my existence, nor will it ever. This void frees me. In knowing that life has no inherent meaning, I am no longer bound by others’ expectations or empty promises. My words, my actions, even my name will vanish in time, and that liberates me to live solely for the moments I choose.
Existential nihilism handed me a blank page. Life’s meaning is not given; it is mine to write. This truth healed my old anxieties …

What Data is Really Necessary? A Feasibility Study of Inference Data Minimization for Recommender Systems
Jens Leysen, Marco Favier, Bart Goethals
https://arxiv.org/abs/2508.21547

What Data is Really Necessary? A Feasibility Study of Inference Data Minimization for Recommender Systems
Data minimization is a legal principle requiring personal data processing to be limited to what is necessary for a specified purpose. Operationalizing this principle for recommender systems, which rely on extensive personal data, remains a significant challenge. This paper conducts a feasibility study on minimizing implicit feedback inference data for such systems. We propose a novel problem formulation, analyze various minimization techniques, and investigate key factors influencing their effe…