Anthropic's Claude AI has been updated with a "styles" feature, allowing users to customise the AI's communication style by pre-selecting formal, concise, or explanatory modes, or by uploading custom examples. This personalisation approach differentiates Claude from competitors like ChatGPT and Gemini, who maintain a single conversational style. Anthropic highlights its commitment to data privacy, stating...
Author: Martin Treiber
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...
Five Useful and Fun NotebookLM Hacks
Google’s NotebookLM has taken the tech world by storm over the past few months. By simply uploading your sources, NotebookLM becomes an instant expert—grounding its responses in your material and offering powerful ways to transform information. Plus, since it’s your notebook, your personal data remains entirely private and isn’t used to train the AI. One...
Claude 3.5 Computer Use: The AI That Sees and Controls Your Computer
Imagine an AI that can navigate your computer just like you do, using only its "eyes" to understand and interact with the screen. That's exactly what Claude 3.5 Computer Use aims to achieve. It can tackle various tasks, from browsing the web to conquering challenges in video games, all without relying on traditional methods like...
From Boom to Bust: Is Generative AI Killing Freelance Work?
Generative AI is transforming industries, and the online freelance market is no exception. Recent research explores the immediate effects of tools like ChatGPT and AI-driven image generators on freelance job opportunities. By analyzing job postings on a major freelancing platform, the study reveals a striking decline in demand for roles in writing, software development, and...
Magentic-One by Microsoft – GUI Automation Ante Portas
Magentic-One by Microsoft, is an open-source, multi-agent system designed to solve complex tasks using artificial intelligence. Magentic-One utilises a team of specialised agents, each possessing unique skills like web browsing, file handling, and code execution, all coordinated by an Orchestrator agent. This modular design allows for flexibility and extensibility, enabling the system to adapt to...
The llms.txt Standard and the Rise of Human-AI Infrastructure
The World Wide Web stands at the threshold of a profound transformation. A new proposal called llms.txt signals the emergence of something remarkable: a web that serves not just human readers, but artificial intelligences as first-class citizens. This isn't merely another technical standard—it's the beginning of a fundamental shift in how we think about digital...
Test-Time Training: A Breakthrough in AI Problem-Solving
In a groundbreaking new paper from MIT researchers, artificial intelligence has taken a significant step forward in its ability to solve novel, complex problems. The research demonstrates that with a technique called "test-time training" (TTT), AI systems can dramatically improve their reasoning abilities—matching human-level performance on some challenging tasks. Let's dive into what this means...
Anthropic releases automatic Prompt Improver – Is Prompt Engineering over?
Anthropic has released new features in its developer console to improve the quality of prompts used with its language model, Claude. The prompt improver automates the refinement of existing prompts using techniques such as chain-of-thought reasoning and example standardization. The console also allows users to manage multi-shot examples in a structured format and provides a...
Test-Time Compute: The Next Frontier in AI Scaling
Major AI labs, including OpenAI, are shifting their focus away from building ever-larger language models (LLMs). Instead, they are exploring "test-time compute", where models receive extra processing time during execution to produce better results. This change stems from the limitations of traditional pre-training methods, which have reached a plateau in performance and are becoming too...
