AI researchers are finding that today’s most advanced models are superhuman in some ways and stumbly in others. Take OpenAI’s new “o3” model, for example: it aced challenging business tasks in seconds but tripped over a simple children’s riddle. This paradox – uneven, “jagged” performance across tasks – has led Wharton professor Ethan Mollick to...
Category: Technology
Model Context Protocol Comparison: MCP vs Function Calling, Plugins, APIs
How does the Model Context Protocol (MCP) compare to other ways of connecting AI to tools? In this article, we break down how MCP stacks up against function calling, plugins, direct APIs, and agent frameworks. We’ll also explore real-world use cases for MCP and where this emerging standard might take us in the future. MCP...
Model Context Protocol: Inside the MCP Architecture
The Model Context Protocol (MCP) is redefining how AI systems interact with external tools and data sources. Building on simple function calling, MCP introduces a powerful, modular client-server architecture that enables dynamic tool discovery, secure integration, and efficient session management. In this post, we’ll explore the core components of MCP, including lifecycle phases, primitives like...
A2A vs MCP: Comparing AI Standards for Agent Interoperability
As AI agents increasingly automate and enhance complex workflows, the technology landscape is seeing the rise of crucial interoperability standards. Google's Agent2Agent (A2A) protocol and Anthropic's Model Context Protocol (MCP) stand out as prominent initiatives that, while complementary, target distinct aspects of AI integration. Here we take a deeper look at both, examining their designs,...
Model Context Protocol (MCP): A New Standard for Tool and Data Integration
Large language models are evolving fast, but their real power comes from connecting to the outside world. Enter Anthropic’s Model Context Protocol (MCP)—a universal standard that makes it easier for AI to call external tools, access real-time data, and interact fluidly with services. In this first article of our series, we unpack what MCP is,...
The Shifting Landscape: How LLMs Are Becoming the New Content Interface
In a thought-provoking statement on X, former OpenAI researcher Andrej Karpathy has painted a vision of the future where large language models (LLMs) become the primary interface for digital content. This perspective suggests a fundamental shift in how we create, structure, and optimize information in the coming years. The 99.9% Optimization Shift While Karpathy acknowledges...
Going Beyond RPA with LLMs
Robotic Process Automation (RPA) has long been the go-to solution for streamlining repetitive tasks. But when it comes to handling complex, (semi-)structured data, RPA falls short. Enter AI-powered intelligent automation—a transformative approach that redefines what’s possible in business operations. Unlike traditional RPA bots, AI agents bring contextual understanding to the table, making them more reliable...
What is the ARC Prize and why is it important?
The ARC Prize is a $1,000,000+ public competition aimed at advancing open-source progress towards Artificial General Intelligence. The ARC Prize is a competition designed to inspire new ideas and drive progress towards Artificial General Intelligence (AGI) by reaching a target benchmark score on the ARC-AGI (Abstraction and Reasoning Corpus for Artificial General Intelligence) benchmark. The...
Tag Based Prompting for Better Prompting Performance
Large Language Models (LLMs) have amazed us with their ability to generate human-quality text, translate languages, and answer complex questions. But what happens when you need them to tackle something outside their general knowledge base – like predicting the properties of a protein or translating a highly structured technical document? That's where tag-based prompting comes...
ChatGPT’s artificial empathy is a language trick. Here’s how it works
Anthropomorphism occurs when we attribute human characteristics to non-human entities like animals or machines. Chatbots, such as ChatGPT, Gemini and Copilot, encourage this by imitating human language to communicate with us, going beyond using mere familiar words and phrases to adopt human patterns of communication. By doing this, they are able to hold contextualised, coherent...
