Graphiti: A Python Library for Building Temporal Knowledge Graphs Using LLMs

Advancements in Deep Learning for Material Sciences Transforming Material Design Deep learning has greatly improved material sciences by predicting material properties and optimizing compositions. This technology speeds up material design and allows for exploration of new…

Generative AI is the next big technology trend that executives are preparing for, but it also comes with risks. The technology is challenging legal frameworks, creating cybersecurity threats, and causing workforce automation concerns. Organizations need to…

Large Language Models (LLMs) are poised to revolutionize coding tasks by serving as intelligent assistants, streamlining code generation and bug fixing. Effective integration into Integrated Development Environments (IDEs) is a key challenge, requiring fine-tuning for diverse…

Understanding Point Tracking in Video Point tracking is essential for video tasks like 3D reconstruction and editing. It requires accurate point approximation for high-quality results. Recent advancements in tracking technology use transformer and neural network designs…

Boston Dynamics’ robots, though appearing highly agile in videos, are still manually coded and struggle with new obstacles. However, researchers have used reinforcement learning to teach a robot, Cassie, dynamic movements without explicit training. This approach…

AQLM is a pioneering strategy for extreme compression of large language models, reducing the trade-off between model size and computational efficiency. Developed by researchers from various institutions, it employs additive quantization to optimize performance. AQLM demonstrates…

Introducing MambaVision: Advancing Vision Modeling Combining Strengths of CNNs and Transformers Computer vision enables machines to interpret visual information, and MambaVision enhances this capability by integrating CNN-based layers with Transformer blocks. This hybrid model effectively captures…

Language Model Aware Speech Tokenization (LAST): A Unique AI Method Integrates a Pre-Trained Text Language Model into the Speech Tokenization Process Speech tokenization is a fundamental process that underpins the functioning of speech-language models, enabling these…

Challenges in AI Reasoning Achieving expert-level performance in complex reasoning tasks is tough for artificial intelligence (AI). Models like OpenAI’s o1 show advanced reasoning similar to trained experts. However, creating such models involves overcoming significant challenges,…

NLP, or Natural Language Processing, is a field of AI focused on human-computer interaction through language. Recent research has explored improving few-shot learning (FSL) methods in NLP to overcome data limitations. A new data augmentation method…

Transforming AI with Insight-RAG Transforming AI with Insight-RAG Challenges of Traditional RAG Frameworks Retrieval-Augmented Generation (RAG) frameworks have gained popularity for enhancing Large Language Models (LLMs) by integrating external knowledge. However, traditional RAG methods often focus…

Revolutionizing Video and Image Understanding with AI Multi-modal Large Language Models (MLLMs) Multi-modal Large Language Models (MLLMs) have transformed image and video tasks like visual question answering, narrative creation, and interactive editing. However, understanding video content…

Researchers from Microsoft Azure and Microsoft Research have developed a framework for low-precision training using FP8, which can significantly reduce the costs associated with training large language models (LLMs). The framework offers fast processing, minimal memory…

Nvidia has announced the H200, a high-end chip designed for training AI models, with enhanced performance in inference. The chip is expected to be shipped in the second quarter of 2024 and will be compatible with…

The article discusses the concept of Transformer distillation in large language models (LLMs) and focuses on the development of a compressed version of BERT called TinyBERT. The distillation process involves teaching the student model to imitate…

ALERTA-Net is a deep neural network that forecasts stock prices and market volatility by integrating social media, economic indicators, and search data, surpassing conventional analytical approaches.

Practical Solutions for Snowflake Cost Optimization Meet Baselit: An AI-Powered Startup that Automatically Optimizes Snowflake Costs with Zero Human Effort Given the present state of the economy, data teams must ensure that they get the most…

Researchers from MIT investigated the scaling behavior of large chemical language models, including generative pre-trained transformers (GPT) for chemistry and graph neural network force fields (GNNs). They introduced the concept of neural scaling, examining the impact…