Tootfinder

A look at embedded and immersion chip-cooling tech; industry sources indicate Nvidia is mulling 6,000W to 9,000W TDP for its next-gen GPUs, up from ~1,200W now (Anton Shilov/Tom's Hardware)
https://www.

Attributes Shape the Embedding Space of Face Recognition Models
Pierrick Leroy, Antonio Mastropietro, Marco Nurisso, Francesco Vaccarino
https://arxiv.org/abs/2507.11372

Attributes Shape the Embedding Space of Face Recognition Models
Face Recognition (FR) tasks have made significant progress with the advent of Deep Neural Networks, particularly through margin-based triplet losses that embed facial images into high-dimensional feature spaces. During training, these contrastive losses focus exclusively on identity information as labels. However, we observe a multiscale geometric structure emerging in the embedding space, influenced by interpretable facial (e.g., hair color) and image attributes (e.g., contrast). We propose a …

Unsupervised Document and Template Clustering using Multimodal Embeddings
Phillipe R. Sampaio, Helene Maxcici
https://arxiv.org/abs/2506.12116 https://

Unsupervised Document and Template Clustering using Multimodal Embeddings
This paper investigates a novel approach to unsupervised document clustering by leveraging multimodal embeddings as input to traditional clustering algorithms such as $k$-Means and DBSCAN. Our method aims to achieve a finer-grained document understanding by not only grouping documents at the type level (e.g., invoices, purchase orders), but also distinguishing between different templates within the same document category. This is achieved by using embeddings that capture textual content, layout…

📉 Bitcoin's 'Mempool' Nearly Empty as Prices Trade Near Lifetime Highs
... although Bitcoin's price remains high, the evidence is the Bitcoin network is dying as transaction volume collapses and miners struggle
#bitcoin #crypto

BTC News: Bitcoin's 'Mempool' Nearly Empty as Prices Trade Near Lifetime Highs. What Next?
Almost all of Bitcoin's actual users have gone away, one observer said, warning of a major crisis.

Latent Action Diffusion for Cross-Embodiment Manipulation
Erik Bauer, Elvis Nava, Robert K. Katzschmann
https://arxiv.org/abs/2506.14608 https://

Latent Action Diffusion for Cross-Embodiment Manipulation
End-to-end learning approaches offer great potential for robotic manipulation, but their impact is constrained by data scarcity and heterogeneity across different embodiments. In particular, diverse action spaces across different end-effectors create barriers for cross-embodiment learning and skill transfer. We address this challenge through diffusion policies learned in a latent action space that unifies diverse end-effector actions. We first show that we can learn a semantically aligned laten…

Into the Unknown: Applying Inductive Spatial-Semantic Location Embeddings for Predicting Individuals' Mobility Beyond Visited Places
Xinglei Wang, Tao Cheng, Stephen Law, Zichao Zeng, Ilya Ilyankou, Junyuan Liu, Lu Yin, Weiming Huang, Natchapon Jongwiriyanurak
https://arxiv.org/abs/2506.14070…

Into the Unknown: Applying Inductive Spatial-Semantic Location Embeddings for Predicting Individuals' Mobility Beyond Visited Places
Predicting individuals' next locations is a core task in human mobility modelling, with wide-ranging implications for urban planning, transportation, public policy and personalised mobility services. Traditional approaches largely depend on location embeddings learned from historical mobility patterns, limiting their ability to encode explicit spatial information, integrate rich urban semantic context, and accommodate previously unseen locations. To address these challenges, we explore the appl…

Fractional Orlicz-Sobolev embeddings into Campanato type spaces
Angela Alberico, Andrea Cianchi, Lubo\v{s} Pick, Lenka Slav\'ikov\'a
https://arxiv.org/abs/2506.13669

Fractional Orlicz-Sobolev embeddings into Campanato type spaces
Optimal embeddings for fractional Orlicz-Sobolev spaces into (generalized) Campanato spaces on the Euclidean space are exhibited. Embeddings into vanishing Campanato spaces are also characterized. Sharp embeddings into $\operatorname{BMO}(\mathbb R^n)$ and $\operatorname{VMO}(\mathbb R^n)$ are derived as special instances. Dissimilarities to corresponding embeddings for classical fractional Sobolev spaces are pointed out.

everyonehateselon_ on Instagram: It would be such a shame for Donald if this photo of Trump with Jeffrey Epstein appeared absolutely EVERYWHERE on his tour of the UK. It would truly be such a huge shame if everyone donated to make that happen 👀 link in bio x
https://www.instagram.com/reel/DMNNZegI8qO/?utm_source=ig_embed&ig_rid=0825a374-d4be-4fd1-8965-53c68571a6a2

The Developments and Challenges towards Dexterous and Embodied Robotic Manipulation: A Survey
Gaofeng Li, Ruize Wang, Peisen Xu, Qi Ye, Jiming Chen
https://arxiv.org/abs/2507.11840

The Developments and Challenges towards Dexterous and Embodied Robotic Manipulation: A Survey
Achieving human-like dexterous robotic manipulation remains a central goal and a pivotal challenge in robotics. The development of Artificial Intelligence (AI) has allowed rapid progress in robotic manipulation. This survey summarizes the evolution of robotic manipulation from mechanical programming to embodied intelligence, alongside the transition from simple grippers to multi-fingered dexterous hands, outlining key characteristics and main challenges. Focusing on the current stage of embodie…

Can Pretrained Vision-Language Embeddings Alone Guide Robot Navigation?
Nitesh Subedi, Adam Haroon, Shreyan Ganguly, Samuel T. K. Tetteh, Prajwal Koirala, Cody Fleming, Soumik Sarkar
https://arxiv.org/abs/2506.14507

Can Pretrained Vision-Language Embeddings Alone Guide Robot Navigation?
Foundation models have revolutionized robotics by providing rich semantic representations without task-specific training. While many approaches integrate pretrained vision-language models (VLMs) with specialized navigation architectures, the fundamental question remains: can these pretrained embeddings alone successfully guide navigation without additional fine-tuning or specialized modules? We present a minimalist framework that decouples this question by training a behavior cloning policy dir…