In this tutorial, we demonstrated how Microsoft’s AutoGen framework empowers developers to orchestrate complex, multi-agent workflows with minimal code. By leveraging AutoGen’s RoundRobinGroupChat and TeamTool abstractions, you can seamlessly assemble specialist assistants, such as Researchers, FactCheckers, Critics, Summarizers, and Editors,…
The effectiveness of language models relies on their ability to simulate human-like step-by-step deduction. However, these reasoning sequences are resource-intensive and can be wasteful for simple questions that do not require elaborate computation. This lack of awareness regarding the complexity…
Recent advances in long-context (LC) modeling have unlocked new capabilities for LLMs and large vision-language models (LVLMs). Long-context vision–language models (LCVLMs) show an important step forward by enabling LVLMs to process hundreds of images and thousands of interleaved text tokens…
Modern web usage spans many digital interactions, from filling out forms and managing accounts to executing data queries and navigating complex dashboards. Despite the web being deeply intertwined with productivity and work processes, many of these actions still demand repetitive…
Anthropic has announced the release of its next-generation language models: Claude Opus 4 and Claude Sonnet 4. The update marks a significant technical refinement in the Claude model family, particularly in areas involving structured reasoning, software engineering, and autonomous agent…
Large Reasoning Models (LRMs) like OpenAI’s o1 and o3, DeepSeek-R1, Grok 3.5, and Gemini 2.5 Pro have shown strong capabilities in long CoT reasoning, often displaying advanced behaviors such as self-correction, backtracking, and verification—collectively known as “aha moments.” These behaviors…
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…
