Author: Sana Hassan

Sana Hassan
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Sana Hassan, a consulting intern at Marktechpost and dual-degree student at IIT Madras, is passionate about applying technology and AI to address real-world challenges. With a keen interest in solving practical problems, he brings a fresh perspective to the intersection of AI and real-life solutions.

8 Comprehensive Open-Source and Hosted Solutions to Seamlessly Convert Any API into AI-Ready MCP Servers

Agentic AI
The Model Communication Protocol (MCP) is an emerging open standard that allows AI agents to interact with external services through a uniform interface. Instead...

How the Model Context Protocol (MCP) Standardizes, Simplifies, and Future-Proofs AI Agent Tool Calling Across Models for Scalable, Secure, Interoperable Workflows Traditional Approaches to...

Agentic AI
Before MCP, LLMs relied on ad-hoc, model-specific integrations to access external tools. Approaches like ReAct interleave chain-of-thought reasoning with explicit function calls, while Toolformer...

Multimodal Queries Require Multimodal RAG: Researchers from KAIST and DeepAuto.ai Propose UniversalRAG—A New Framework That Dynamically Routes Across Modalities and Granularities for Accurate and...

AI Paper Summary
RAG has proven effective in enhancing the factual accuracy of LLMs by grounding their outputs in external, relevant information. However, most existing RAG implementations...

Google Researchers Advance Diagnostic AI: AMIE Now Matches or Outperforms Primary Care Physicians Using Multimodal Reasoning with Gemini 2.0 Flash

AI Paper Summary
LLMs have shown impressive promise in conducting diagnostic conversations, particularly through text-based interactions. However, their evaluation and application have largely ignored the multimodal nature...

LLMs Can Learn Complex Math from Just One Example: Researchers from University of Washington, Microsoft, and USC Unlock the Power of 1-Shot Reinforcement Learning...

AI Paper Summary
Recent advancements in LLMs such as OpenAI-o1, DeepSeek-R1, and Kimi-1.5 have significantly improved their performance on complex mathematical reasoning tasks. Reinforcement Learning with Verifiable...

Building the Internet of Agents: A Technical Dive into AI Agent Protocols and Their Role in Scalable Intelligence Systems

Agentic AI
As large language model (LLM) agents gain traction across enterprise and research ecosystems, a foundational gap has emerged: communication. While agents today can autonomously...

Meta AI Introduces First Version of Its Llama 4-Powered AI App: A Standalone AI Assistant to Rival ChatGPT

AI Agents
Meta has officially entered the standalone AI assistant arena with the launch of its new Meta AI app, unveiled at the inaugural LlamaCon developer...

Exploring the Sparse Frontier: How Researchers from Edinburgh, Cohere, and Meta Are Rethinking Attention Mechanisms for Long-Context LLMs

AI Paper Summary
Sparse attention is emerging as a compelling approach to improve the ability of Transformer-based LLMs to handle long sequences. This is particularly important because...

Can Coding Agents Improve Themselves? Researchers from University of Bristol and iGent AI Propose SICA (Self-Improving Coding Agent) that Iteratively Enhances Its Own Code...

Agentic AI
The development of agentic systems—LLMs embedded within scaffolds capable of tool use and autonomous decision-making—has made significant progress. Yet, most implementations today rely on...

UniME: A Two-Stage Framework for Enhancing Multimodal Representation Learning with MLLMs

AI Paper Summary
The CLIP framework has become foundational in multimodal representation learning, particularly for tasks such as image-text retrieval. However, it faces several limitations: a strict...

ViSMaP: Unsupervised Summarization of Hour-Long Videos Using Meta-Prompting and Short-Form Datasets

AI Paper Summary
Video captioning models are typically trained on datasets consisting of short videos, usually under three minutes in length, paired with corresponding captions. While this...

Tiny Models, Big Reasoning Gains: USC Researchers Introduce Tina for Cost-Effective Reinforcement Learning with LoRA

AI Paper Summary
Achieving strong, multi-step reasoning in LMs remains a major challenge, despite notable progress in general task performance. Such reasoning is crucial for complex problem-solving...
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