World is approaching point where no one can shut down a rogue AI, says director of body behind research
It’s the stuff of science fiction cinema, or particularly breathless AI company blogposts: new research finds recent AI systems can independently copy themselves on to other computers.
In the doom scenario, this means that when the superintelligent AI goes rogue, it will escape shutdown by seeding itself across the world wide web, lurking outside the reach of frantic IT professionals and continuing to plot world domination or paving over the world with solar panels.
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Writing code has always been the most time- and resource-intensive task in software development. AI is changing that, and faster than most engineering organizations are prepared for. Tools like Claude Code and Cursor are already handling significant parts of code construction, freeing developers to spend more time on requirements, architecture, and design.
But that shift creates a new challenge nobody is talking about enough. As AI takes on the heavy lifting, the skills that matter most are moving upstream: how to provide the right context for a prompt, how to evaluate what the model produces, and how to understand a problem deeply enough that you can’t be fooled by a confident but wrong answer.
This piece explores those three skills and why developers who master them will have a significant edge over those who don’t.
Beyond coding: Mastering the art of the prompt
Software translation tools such as compilers and assemblers map a high-level description of code to a lower-level represent
At first glance, Microsoft Foundry looks like a big grab bag of every AI-adjacent service that Microsoft has offered in the last decade, plus some new ones. In Microsoft’s own words, “Foundry consolidates several previous Azure AI services and tools into a unified platform” and “unifies agents, models, and tools under a single management grouping.”
Microsoft Foundry helps application developers to build and deploy agents, which may use models and tools. It also helps machine learning (ML) engineers and data scientists to fine-tune models, run evaluations, and manage model deployments. Finally, it helps IT administrators and platform engineers to govern AI resources, enforce policies, and manage access across teams. It isn’t quite a floor wax and a dessert topping, but it does try to serve three distinct audiences.
Key capabilities of Microsoft Foundry for building agents include multi-agent orchestration, workflows, a tool catalog, memory, knowledge integration, and publishing. Key cap
New research from the Oxford Internet Institute indicates that AI chatbots trained to be extra warm, friendly, and empathetic can also become less reliable, according to the BBC.
The researchers analyzed more than 400,000 responses from five different AI models from Meta, Mistral AI, Alibaba, and OpenAI. The results showed that the “kinder” versions more often gave incorrect answers, reinforced users’ misconceptions, and avoided stating uncomfortable truths.
For example, a friendlier model might deal with conspiracy theories about the moon landing more cautiously instead of clearly stating that they are false.
On average, incorrect answers increased by about 7.43 percentage points when the models were made to sound warmer in tone. Cooler and more direct models made fewer mistakes. According to the researchers, AI makes the same trade-off as humans: it sometimes prioritizes being perceived as pleasant rather than being direct.
