The field of video generation has seen remarkable progress with the advent of diffusion transformer (DiT) models, which have demonstrated superior quality compared to traditional convolutional neural network approaches. However, this improved quality comes at a significant cost in terms of computational resources and inference time, limiting the practical applications of these models. In response… →
Artificial intelligence (AI) planning involves creating a sequence of actions to achieve a specific goal in the development of autonomous systems that perform complex tasks, such as robotics and logistics. Furthermore, large language models (LLMs) have shown great promise in several areas focused on natural language processing and code generation. Nevertheless, if one has to… →
Tau is a logical AI engine that enables the creation of software and AI capable of fully mechanized reasoning, allowing software built with Tau to logically reason over formalized information, deduce new knowledge, and automatically implement it within the software, allowing AI to accurately act autonomously and evolve based on generic commands, greatly advancing software… →
Large language models (LLMs), characterized by their advanced text generation capabilities, have found applications in diverse areas such as education, healthcare, and legal services. LLMs facilitate the creation of coherent and contextually relevant content, allowing professionals to generate structured narratives with compelling arguments. Their adaptability across various tasks with minimal input has rendered them essential… →
Data discovery has become increasingly challenging due to the proliferation of easily accessible data analysis tools and low-cost cloud storage. While these advancements have democratized data access, they have also led to less structured data stores and a rapid expansion of derived artifacts in enterprise environments. The growing complexity of data landscapes has made it… →
Large Language Models (LLMs) have gained significant attention in recent times, but with them comes the problem of hallucinations, in which the models generate information that is fictitious, deceptive, or plain wrong. This is especially problematic in vital industries like healthcare, banking, and law, where inaccurate information can have grave repercussions. In response, numerous tools… →
The rapid advancement of AI has led to the development of powerful models for discrete and continuous data modalities, such as text and images, respectively. However, integrating these distinct modalities into a single model remains a significant challenge. Traditional approaches often require separate architectures or compromise on data fidelity by quantizing continuous data into discrete… →
Empowering LLMs to handle long contexts effectively is essential for many applications, but conventional transformers require substantial resources for extended context lengths. Long contexts enhance tasks like document summarization and question answering. Yet, several challenges arise: transformers’ quadratic complexity increases training costs, LLMs need help with longer sequences even after fine-tuning, and obtaining high-quality long-text… →