February 2026

Need advice!!! I had a very nice discussion with the founder of a well funded startup company. The problem mentioned to me got me excited and over the weekend I spend time just drafting the problem into the MDP as they would like to move to pure RL. The following week I had an interview with a guy who works as a consultant at the same company and the interview was okay. I gave good answers but got […]

Ver mais

Most self-supervised learning (SSL) methods learn continuous visual representations by aligning different views of the same input, offering limited control over how information is structured across representation dimensions. In this work, we frame visual self-supervised learning as a discrete communication process between a teacher and a student network, where semantic information is transmitted through a fixed-capacity binary channel. Rather than aligning continuous features, the student predicts multi-label binary messages produced by the teacher. Discrete agreement is enforced through […]

Ver mais

Data streams are rarely static in dynamic environments like Industry 4.0. Instead, they constantly change, making traditional offline models outdated unless they can quickly adjust to the new data. This need can be adequately addressed by continual learning (CL), which allows systems to gradually acquire knowledge without incurring the prohibitive costs of retraining them from scratch. Most research on continual learning focuses on classification problems, while very few studies address regression tasks. We propose the first prototype-based generative […]

Ver mais

Knowledge distillation (KD) is a tool to compress a larger system (teacher) into a smaller one (student). In machine translation, studies typically report only the translation quality of the student and omit the computational complexity of performing KD, making it difficult to select among the many available KD choices under compute-induced constraints. In this study, we evaluate representative KD methods by considering both translation quality and computational cost. We express computational cost as a carbon footprint using the […]

Ver mais

In today’s connected world, the generation of massive streaming data across diverse domains has become commonplace. In the presence of concept drift, class imbalance, label scarcity, and new class emergence, they jointly degrade representation stability, bias learning toward outdated distributions, and reduce the resilience and reliability of detection in dynamic environments. This paper proposes SCIL (Streaming Class-Incremental Learning) to address these challenges. The SCIL framework integrates an autoencoder (AE) with a multi-layer perceptron for multi-class prediction, uses a […]

Ver mais

Anthropic published a lawyer-related plugin on 30 January, and within four to five days, software stocks had lost billions of dollars. The pace of the collapse left everyone shocked, as the whole industry had been operating on a fundamental misperception of how the AI economy works. Why Everyone Thought They Were Safe The narrative that dominated the technological field held that AI companies would build baseline models, which would then serve as a foundation for software companies to […]

Ver mais

Domain Authority (DA) is one of the most discussed metrics in SEO. While Google has confirmed that it does not use Domain Authority as a direct ranking factor, many websites with higher authority scores tend to perform better in search results. This creates confusion for many SEO professionals. If Google does not use Domain Authority, why do high-authority websites often rank faster and show more stability? The explanation lies in what Domain Authority represents rather than the metric […]

Ver mais