Shaping the Future of Education: Advancing Personalized AI Learning Companion™ Every day, 1.5 billion students encounter challenges with their homework, and Brainly is here to assist them. One of the platform’s primary goals is to provide widespread access to personalized […]
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts State Space Models (SSMs) have become serious contenders in the field of sequential modeling, challenging the dominance of Transformers. At the same time, Mixture of Experts (MoE) has significantly improved […]
AI Agent framework for robotics The talk introduces RAI, a novel open-source framework bridging state-of-art robotics with generative AI agents, and discusses challenges and solutions for embodied agents operating in the real world. The audience will learn from experiments and […]
Practical Low Rank Decomposition for Large Language Models The huge number of parameters in modern Large Language Models makes them hard to deploy as they require a lot of memory and compute resources. Many solutions for reducing the number of […]
Dense Retrieval for Allegro Search Engine Modern system designs for e-commerce search are complex, multi-layered systems that must adhere to various online and offline performance requirements. Retrieval is a key component of search engines. In the face of today’s dominance […]
Practical Low Rank Decomposition for Large Language Models The huge number of parameters in modern Large Language Models makes them hard to deploy as they require a lot of memory and compute resources. Many solutions for reducing the number of […]
Scaling Laws for Fine-Grained Mixture of Experts Mixture of Experts (MoE) models have emerged as a primary solution for reducing the computational cost of Large Language Models. In this work, we analyze their scaling properties, incorporating an expanded range of […]
Polite Teacher In construction site segmentation, like in many pixel-wise computer vision tasks, it is (relatively) easy to get the data. However, providing the labels is much more cumbersome. In this case not only because of the volume, but also […]
Polite Teacher In construction site segmentation, like in many pixel-wise computer vision tasks, it is (relatively) easy to get the data. However, providing the labels is much more cumbersome. In this case not only because of the volume, but also […]
Synerise BaseModel: A Foundation Model for Behavioral Event Data The complexity of industry-grade event-based datalakes grows dynamically each passing hour. Companies actively gather behavioral information on their customers, recording multiple types of events, such as clicks, likes, page views, card […]
