Hub AI in practice
Artificial Intelligence is present in everyday life – from “googling” to facial recognition to vacuum cleaner robots. AI tools are becoming more and more elaborate and support people and companies more effectively in their tasks, such as generating graphics, texting or coding, or interpreting large amounts of data.
What AI tools are there, how do they work, how do they help in our everyday world – and how do they change our lives? These are the questions we address in our Content Hub Artificial Intelligence in Practice.
Google is now letting utilities like Indiana Michigan Power (I&M) and the Tennessee Valley Authority (TVA) request a slowdown of non-essential AI workloads during periods of grid stress.
The company frames this not just as a way to help stabilize the power grid, but also as a strategic advantage: new data centers could be brought online more quickly, since energy providers would have fewer concerns about peak demand. The move represents a shift in thinking, treating AI not only as a potential strain on the grid but also as a possible buffer. It's still unclear which workloads count as non-essential, but Google says that core services like Search, Maps, and cloud operations for key industries, including healthcare, won't be affected. As an example, Google points to YouTube video encoding as a task that could be scaled back during power shortages.
ChatGPT is set to reach 700 million weekly users this week, according to Nick Turley, App Product Manager at OpenAI. That's up from 500 million at the end of March and four times higher than last year. In addition, OpenAI now counts 5 million paying business users, up from 3 million in June, as more enterprises and educators turn to AI tools. The company recently raised $8.3 million in funding and is preparing to launch GPT-5.

Apple is working on its own AI-powered search engine, marking a shift away from its previous anti-chatbot stance.
Despite years of skepticism toward ChatGPT-style systems, Apple is now developing an internal generative search feature designed to answer user questions based on context, according to Bloomberg's Mark Gurman. The new AI team, called "Answers, Knowledge and Information" (AKI) and led by Robby Walker, is building a system that scans the web and consolidates results into a planned "Answer Engine" product. The team is also working on a standalone app, along with new backend infrastructure for Siri, Spotlight, and Safari.
This change in direction signals that Apple now sees generative search as strategically important in the AI race, and is moving to regain lost ground against Google and OpenAI.
Google's AI infrastructure is under strain as demand for its latest models increases. Product manager Logan Kilpatrick responded to complaints about the limited availability of Gemini 2.5 Pro Deep Think, explaining, "the release is constrained because this is a big model and takes a boat load of compute to run, when our TPU's are already burning to keep up with massive growth on Veo, Gemini 2.5 pro, AI mode rollout to hundreds of millions, etc."
Kilpatrick addressed criticism after users pointed out that, despite strong benchmark scores, Gemini 2.5 Pro Deep Think is difficult to use to use due to access restrictions. Even Ultra subscribers can only make a handful of requests per day as the system struggles to keep up with demand.

Wan2.2 A14B now tops the rankings for open source video models, according to Artificial Analysis. It ranks seventh for text-to-video and fourteenth for image-to-video, with the lower placement in the latter likely due to its 16 frames per second output compared to 24 fps in some competitors. Among open models, Wan2.2 A14B leads the field, but it still trails behind closed models like Veo 3 and Seedance 1.0 in overall performance. Pricing, however, is often much lower depending on the provider.
