Welcome to our latest round-up of news from the technology and hosting world. Here’s what we’ve discovered this month.
Smaller Data Centres
While the UK currently has around 100 new hyperscale data centres in development, in the future, they may become much smaller. Compact data centres are already being installed in public buildings, with their recycled heat being used to warm swimming pools, offices and community facilities.
At the same time, universities are trialling small, on-site, GPU-powered systems to run their AI workloads, and several UK companies have even started installing small-scale data centres in residential homes. Besides providing a network of localised edge data centres, the latter also enables householders to ditch their boilers, cut energy bills and reduce their carbon emissions.
In addition, there are proposals to house data centres in vacant town centre shops, derelict buildings and even put them in orbit. While intensive AI workloads are likely to continue to be run in large facilities, in the future, we are likely to see smaller, distributed data centres used for local processing, to reduce latency and deliver more efficient energy use.
AI Flood Prevention
Northumberland County Council is trialling AI tools that could reduce administrative tasks and speed up decisions about flood risks. In a bid to improve how flood risk assessments are reviewed, the AI will assist council employees by extracting key information from planning documents, checking submissions against planning rules and spotting issues that need more attention.
Currently, the council receives thousands of applications every year, many of which are complicated, time-consuming and vary in quality. While decisions will continue to be made by humans, the AI should help streamline and accelerate the process for them.
The project, funded by the government’s Regulatory Innovation Office, will run until September. Its findings will be used to develop a governance framework that can be shared with other councils.
UK Robo-Taxi
Driverless taxis could be on UK roads this year, with Uber and Lyft sharing plans to test them in London. The trials will use Apollo Go driverless taxis, made by Chinese firm Baidu, which have already delivered millions of driverless rides in Chinese cities.
While the companies are still seeking approval from regulators, the UK government has shown support for limited trials as part of its aim to speed up the implementation of self-driving vehicles.
Self-driving systems still face a number of challenges. While they could reduce accidents caused by human error and improve transport efficiency, there remain concerns about safety, liability and how the services will operate in busy cities. Additionally, surveys show that most UK passengers are nervous about using driverless taxis and would prefer a human driver.
Vibe Coding Problems
Research from CodeRabbit has shown that while AI tools help developers work faster, they lead to more mistakes than code written solely by humans. From looking at hundreds of open-source pull requests on GitHub, the researchers discovered that submissions supported by AI were more likely to have serious problems, especially in areas like logic, code quality and security.
These results match earlier research from Cortex that showed that, despite improvements in developer productivity, AI-generated code was more likely to mishandle credentials or create insecure settings.
Researchers noted that risk can be reduced by ensuring that AI tools are given clear business context, coding standards and security rules. Businesses using these tools should also implement strong review processes and reliable development systems.
AI Jobs Outlook
A survey undertaken by SaaS company Monday.com shows that fewer bosses believe AI will start to replace jobs. Indeed, while the study found that 78% of UK directors do not think AI will lead to job cuts this year, almost a third of companies were planning to hire more people for new roles created by AI.
The survey noted that almost all directors used AI in their business, with more than half saying it will play a key role in their long-term goals, supported by teams focused on AI or innovation. For many businesses, the main focus was on making sure AI tools work well together, that the results are reliable, and that automation becomes part of everyday tasks.
While job losses were not a major worry, directors were concerned about data security, the accuracy of results, and the use of too many tools. Many companies also needed to establish clear rules for using AI responsibly.
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