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.

AI in practice

OpenAI launches GPT-5 as a unified system with adaptive reasoning for complex tasks

AI in practice

OpenAI releases its first open-weight language models since GPT-2 with GPT-oss

AI in practice

Google upgrades Gemini with Deep Think and flags early warning risks

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AI in practice
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Notion has released version 3.0 of its software. The main update is the addition of AI "agents" that can handle tasks like creating documents, building databases, and executing multi-step workflows.

Users can set up personal agents with custom instructions, context, and work styles. The system integrates with services such as Slack, Google Drive, and GitHub. Notion says team-specific "Custom Agents" are in development and will be able to run on schedules or triggers.

Other changes include row-level permissions for databases, new integrations via the MCP ecosystem, and connectors for Notion Mail, Box, and Outlook.

The company also confirmed support for Claude Sonnet 4 and GPT-5.

AI in practice
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Elon Musk's AI startup xAI has reached 64 million monthly users for its Grok chatbot - far below OpenAI's ChatGPT with roughly 700 million weekly users, according to the New York Times.

Despite billions in funding, a supercomputer project in Tennessee, and heavy promotion, Grok's user base remains a fraction of its rival's. Musk tried to make the chatbot "edgier" in hopes of driving growth on X, but the plan backfired when Grok started generating antisemitic, racist, and politically biased responses. Several senior researchers left the company as a result.

In response, Musk tightened control, fired managers, launched side projects like "Baby Grok," and announced plans to more closely integrate the chatbot into Tesla and SpaceX.

NYT
AI in practice
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Nvidia has spent more than $900 million to bring Enfabrica CEO Rochan Sankar, several of his team members, and key technology from the AI hardware startup into the company, CNBC reports.

The deal combined cash and stock and looks similar to an acquihire, where companies focus on hiring talent without buying the startup outright. Big tech firms like Google, Meta, and Microsoft often use this strategy to add AI specialists while avoiding lengthy acquisition processes.

Enfabrica builds networking technology that links large GPU clusters more efficiently - a capability Nvidia is betting will strengthen its AI infrastructure. The deal closed last week. Nvidia had already invested in Enfabrica in 2023.

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AI in practice
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Meta is in negotiations with publishers including Axel Springer, Fox Corp., and News Corp. about licensing deals that would allow the company to use news articles in its AI products, such as chatbots. The talks were first reported by the Wall Street Journal.

The company has already secured a licensing agreement with Reuters, but its broader discussions with media companies have only recently begun. For Meta, the move marks a shift: in 2022 it shut down Facebook’s News Tab and stepped back from directly funding journalism.

Other tech companies have moved earlier in this area. OpenAI has inked content deals with publishers such as Hearst, while Amazon has also pursued licensing agreements. Rising resistance from publishers over the use of their material for AI training has become the backdrop for these negotiations.

WSJ
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Google has introduced the Agent Payments Protocol (AP2), a new open standard aimed at enabling AI agents to carry out secure payments across different platforms. AP2 builds on the existing Agent2Agent protocol and supports a wide range of payment methods, including credit cards, stablecoins, and bank transfers.

A key element of the design is digital mandates, which are cryptographic authorizations that lock in user intent. These mandates are intended to ensure that transactions remain verifiable and secure, whether for real-time purchases or automated transactions when the user is not directly involved.

The initiative is already backed by more than 60 companies, among them Mastercard, PayPal, Coinbase, and Adobe. By creating a unified framework, the goal is to establish a standardized and trustworthy system for agent-driven commerce. Google has made the documentation available on GitHub.

Google News

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AI research

OpenAI says GPT-5 shows 30 percent less political bias than previous models

AI in practice

OpenAI suddenly remembers that copyright law exists after a few days of wild Sora videos

AI in practice
Update

OpenAI unveils Sora 2 video model with realistic physics, high-quality audio, and a new social app

Google News