Apache Airflow Document Ingestion Pipeline for RAG Systems
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Evidence of an Emergent “Self” in Continual Robot Learning
A key challenge to understanding self-awareness has been a principled way of quantifying whether an intelligent system has a concept of a "self," and if so how to differentiate the "self" from other cognitive structures. We propose that the "self" can be isolated by seeking the invariant portion of cognitive process that changes relatively little compared to more rapidly acquired cognitive knowledge and skills, because our self is the most persistent aspect of our experiences. We used this […]
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AI Model Develops Object Recognition Without Human Guidance
:::info Authors: Mathilde Caron, Facebook AI Research, Inria Hugo Touvron, Facebook AI Research, Sorbonne University Ishan Misra, Facebook AI Research Herve Jegou, Facebook AI Research Julien Mairal, Inria Piotr Bojanowski, Facebook AI Research Armand Joulin, Facebook AI Research ::: Abstract In this paper, we question if self-supervised learning provides new properties to Vision Transformer (ViT) [19] that stand out compared to convolutional networks (convnets). Beyond the fact that adapting self-supervised methods to this architecture works particularly well, we […]
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DySCo: Dynamic Semantic Compression for Effective Long-term Time Series Forecasting
arXiv:2604.01261v1 Announce Type: new Abstract: Time series forecasting (TSF) is critical across domains such as finance, meteorology, and energy. While extending the lookback window theoretically provides richer historical context, in practice, it often introduces irrelevant noise and computational redundancy, preventing models from effectively capturing complex long-term dependencies. To address these challenges, we propose a Dynamic Semantic Compression (DySCo) framework. Unlike traditional methods that rely on fixed heuristics, DySCo introduces an Entropy-Guided Dynamic Sampling (EGDS) mechanism to autonomously identify […]
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Writer denies it, but publisher pulls horror novel after multiple allegations of AI use
Shy Girl, a horror novel by Mia Ballard, was one of those buzzy books that leapt from self-published prominence into full-on trade publication. Until yesterday, that is, when publisher Hachette pulled the book from the UK market and canceled plans to bring it to the US. The move came after a New York Times investigation suggested that AI had been used in significant parts of the work. “If it isn’t AI, she’s a terrible writer” Shy Girl was […]
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Adversarial Batch Representation Augmentation for Batch Correction in High-Content Cellular Screening
arXiv:2603.05622v1 Announce Type: new Abstract: High-Content Screening routinely generates massive volumes of cell painting images for phenotypic profiling. However, technical variations across experimental executions inevitably induce biological batch (bio-batch) effects. These cause covariate shifts and degrade the generalization of deep learning models on unseen data. Existing batch correction methods typically rely on additional prior knowledge (e.g., treatment or cell culture information) or struggle to generalize to unseen bio-batches. In this work, we frame bio-batch mitigation as a Domain […]
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The Unique Relationship Between fMRI and MRI Scanner Vendors
One defining and often overlooked aspect of fMRI as a field is that it is has been riding on the back of and directly benefitting from the massive clinical MRI industry. Even though fMRI has not yet hit the clinical mainstream – as there are no widely used standard clinical practices that include fMRI, it has reaped many benefits from the clinical impact of “standard” MRI. Just about every clinical scanner can be used for fMRI with minimal […]
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Connecting LLMs to Your Data With Python MCP Servers
The Model Context Protocol (MCP) is a new open protocol that allows AI models to interact with external systems in a standardized, extensible way. In this video course, you’ll install MCP, explore its client-server architecture, and work with its core concepts: prompts, resources, and tools. You’ll then build and test a Python MCP server that queries e-commerce data and integrate it with an AI agent in Cursor to see real tool calls in action. By the end of […]
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What’s the right path for AI?
Who benefits from artificial intelligence? This basic question, which has been especially salient during the AI surge of the last few years, was front and center at a conference at MIT on Wednesday, as speakers and audience members grappled with the many dimensions of AI’s impact. In one of the conferences’s keynote talks, journalist Karen Hao ’15 called for an altered trajectory of AI development, including a move away from the massive scale-up of data use, data centers, […]
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Embedding-Aware Feature Discovery: Bridging Latent Representations and Interpretable Features in Event Sequences
arXiv:2603.15713v1 Announce Type: new Abstract: Industrial financial systems operate on temporal event sequences such as transactions, user actions, and system logs. While recent research emphasizes representation learning and large language models, production systems continue to rely heavily on handcrafted statistical features due to their interpretability, robustness under limited supervision, and strict latency constraints. This creates a persistent disconnect between learned embeddings and feature-based pipelines. We introduce Embedding-Aware Feature Discovery (EAFD), a unified framework that bridges this gap by […]
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