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,...
Category: Technology
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...
The Long Context
In "You Exist In The Long Context," Steven Johnson explores the advancements in large language models (LLMs), particularly the significant impact of long context windows. Johnson illustrates this progress by creating an interactive game based on his book, showcasing the LLM's ability to handle complex narratives and maintain factual accuracy. He draws a parallel between...
The Model Context Protocol
Anthropic's Model Context Protocol (MCP) is an open-source standard for connecting AI assistants to various data sources. MCP employs a client-server architecture, enabling two-way communication between AI applications (clients) and data providers (servers) via different transports like stdio and HTTP with SSE. The protocol facilitates access to resources, tools, and prompts, enhancing AI response relevance...
TinyTroupe: Simulating Human Behaviour with AI
Microsoft has released TinyTroupe, an open-source Python library that uses large language models to simulate human behaviour in virtual environments. This allows for testing digital advertising, software, and generating synthetic data for machine learning. The library enables the simulation of multiple AI agents ("TinyPersons") with individual personalities interacting within a simulated world ("TinyWorld"), facilitating virtual...
