Humans naturally learn by making connections between sight and sound. For instance, we can watch someone playing the cello and recognize that the cellist’s movements are generating the music we hear. A new approach developed by researchers from MIT and…
The Model Context Protocol (MCP) has rapidly become a cornerstone for integrating AI models with the broader software ecosystem. Developed by Anthropic, MCP standardizes how a language model or autonomous agent discovers and invokes external services, whether REST APIs, database…
Addressing Architectural Trade-offs in Language Models As language models scale, balancing expressivity, efficiency, and adaptability becomes increasingly challenging. Transformer architectures dominate due to their strong performance across a wide range of tasks, but they are computationally expensive—particularly for long-context scenarios—due…
Multimodal mathematical reasoning enables machines to solve problems involving textual information and visual components like diagrams and figures. This requires combining language understanding and visual interpretation to make sense of complex mathematical contexts. Such capabilities are vital in education, automated…
Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late 1960s, which showed that general matrix products could be computed with fewer…
Researchers are reimagining how models operate as demand skyrockets for faster, smarter, and more private AI on phones, tablets, and laptops. The next generation of AI isn’t just lighter and faster; it’s local. By embedding intelligence directly into devices, developers…
Over time, the pursuit of better performance of language models has pushed researchers to scale them up, which typically involves increasing the number of parameters or extending their computational capacity. As a result, the development and deployment of language models…
Marktechpost AI Media has unveiled its most comprehensive publication—The Agentic AI and AI Agents Report for 2025—delivering a technically rigorous exploration into the architectures, frameworks, and deployment strategies shaping the future of AI agents. The report spans the full agentic…
In this tutorial, we provide a practical guide for implementing LangGraph, a streamlined, graph-based AI orchestration framework, integrated seamlessly with Anthropic’s Claude API. Through detailed, executable code optimized for Google Colab, developers learn how to build and visualize AI workflows…
Large language models are now being used for evaluation and judgment tasks, extending beyond their traditional role of text generation. This has led to “LLM-as-a-Judge,” where models assess outputs from other language models. Such evaluations are essential in reinforcement learning…
