technocracy

TL;DR I don’t know what I believe about AI anymore. Some days I’m excited. Some days I’m scared. Some days I’m just tired of the shouting. And honestly? That’s okay. We don’t need to pick a team. The useful thing isn’t being “for AI” or “against AI.” The useful thing is staying honest about how complicated this feels—and letting myself sit with the discomfort long enough to understand what’s actually at stake. Also, heavy metal got there before […]

Ver mais

arXiv:2604.08609v1 Announce Type: new Abstract: Digital forensic investigations increasingly rely on heterogeneous evidence such as images, scanned documents, and contextual reports. These artifacts may contain explicit or implicit expressions of harm, hate, threat, violence, or intimidation, yet existing automated approaches often assume clean text input or apply vision models without forensic justification. This paper presents a case-driven multimodal approach for hate and threat detection in forensic analysis. The proposed framework explicitly determines the presence and source of textual […]

Ver mais

Accurate assessment of spheno-occipital synchondrosis (SOS) maturation is a key indicator of craniofacial growth and a critical determinant for orthodontic and surgical timing. However, SOS staging from cone-beam CT (CBCT) relies on subtle, continuously evolving morphological cues, leading to high inter-observer variability and poor reproducibility, especially at transitional fusion stages. We frame SOS assessment as a fine-grained visual recognition problem and propose a progressive representation-learning framework that explicitly mirrors how expert clinicians reason about synchondral fusion: from coarse […]

Ver mais

During my childhood I was highly passionate about biology, and especially genetics. I liked to solve inheritance genetics problems and understand mechanisms of molecular biology. Later I started to learn programming and with time I became a Data Scientist, partially forgetting about my childhood passion. During my Master I re-found my passion in biology, understanding that I can combine my passion to biology and my experience in Data Science by pursuing the Bioinformatics field. The National Human Genome […]

Ver mais

What separates a cryptocurrency that endures for over a decade from the thousands that vanish within their first year? January 18, 2025 marks twelve years since Dash launched as a fork of Bitcoin, making it one of the oldest active blockchain networks still operating with its original vision intact. While data from CoinGecko shows that over 90% of cryptocurrencies launched since 2017 no longer maintain active development or trading volume, Dash continues processing transactions daily across 158 countries. […]

Ver mais

arXiv:2601.07944v1 Announce Type: new Abstract: Since the turn of the century, approximate Bayesian inference has steadily evolved as new computational techniques have been incorporated to handle increasingly complex and large-scale predictive problems. The recent success of deep neural networks and foundation models has now given rise to a new paradigm in statistical modeling, in which Bayesian inference can be amortized through large-scale learned predictors. In amortized inference, substantial computation is invested upfront to train a neural network that […]

Ver mais

I just published Multiverse, an open-source reinforcement learning framework for training agents across many custom environments with memory recall, safety layers, transfer learning, and transformer-based generalist experiments. It’s built for people who want more than a single-task RL demo and need a system for experimentation across different worlds and agent types. Repo: https://github.com/Wilker00/Multiverse submitted by /u/Specialist_Cap_2551 [link] [comments]

Ver mais

Concrete is the most widely used construction material worldwide; however, reliable prediction of compressive strength remains challenging due to material heterogeneity, variable mix proportions, and sensitivity to field and environmental conditions. Recent advances in artificial intelligence enable data-driven modeling frameworks capable of supporting automated decision-making in construction quality control. This study leverages an industry-scale dataset consisting of approximately 70,000 compressive strength test records to evaluate and compare multiple predictive approaches, including linear regression, decision trees, random forests, transformer-based […]

Ver mais