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

Google leans on token metrics, not revenue, adding to bubble talk about AI growth

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

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AI in practice
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Google Labs Creative Director Henry Daubrez says the new Veo 3.1 update is being overhyped. Though it adds helpful features like image-to-image animation, he sees the changes as minor. Daubrez blames financial pressure in the AI industry for turning small updates into big marketing moments. Veo is part of Flow by Google.

"The bigger issue is that the enormous financial stakes around AI are turning timelines into marketing noise, with rumors inflated to the point where every incremental update gets treated like a paradigm shift."

Henry Daubrez

AI in practice
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Apple's new M5 chip is aimed at speeding up AI features on the MacBook Pro, iPad Pro, and Apple Vision Pro. Apple says the M5 delivers more than four times the GPU performance for AI tasks compared to the previous M4 chip. Each of the ten GPU cores includes a built-in "Neural Accelerator." The 16-core Neural Engine can process up to 38 trillion operations per second, making it 60 percent faster than the Neural Engine in the M4. The CPU is also up to 15 percent quicker at multi-threaded processing.

The chip uses a third-generation 3 nm manufacturing process, offers 153 GB/s of shared memory bandwidth (about 30 percent more than before), and supports up to 32 GB of unified memory. This allows larger AI models to run directly on the device. Apple expects that existing AI apps and tools like Apple Intelligence will see faster performance. Developers can access the AI hardware using Core ML, Metal 4, and Tensor APIs.

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AI in practice
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Salesforce is deepening its AI collaborations with both OpenAI and Anthropic. OpenAI's models, including GPT‑5, are being integrated into Agentforce 360 and made accessible through ChatGPT. This setup will let Salesforce customers retrieve sales data, review conversations, and generate Tableau analyses directly within ChatGPT.

At the same time, Anthropic is expanding its partnership with Salesforce to serve regulated industries. Its Claude model will be embedded into Agentforce and Slack, operating under Salesforce's trust layer for data security. Salesforce also announced the global rollout of Agentforce 360, a unified platform designed to connect people, AI agents, and data in one environment.

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Amazon has officially launched AgentCore, its platform for running AI agents, making it generally available as part of Amazon Bedrock. AgentCore is designed to help companies quickly integrate AI agents into real-world applications, with support for models and frameworks like OpenAI, Gemini, and LangGraph. The platform offers runtime environments, access to web apps, API integration, and built-in storage and monitoring through CloudWatch.

Image: AWS

Amazon says companies including Sony, Ericsson, and Cohere Health are already using AgentCore for manufacturing, telecom, and healthcare. AgentCore is now available in nine AWS regions.

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Walmart is partnering with OpenAI to introduce "agentic commerce" to ChatGPT, making it possible for customers to shop and buy products directly through chat. Based on OpenAI's new Instant Checkout feature, users will "soon" be able to search for items in a conversation and purchase them immediately, skipping traditional search results and shopping carts. Walmart says the goal is to create an AI-powered shopping experience that understands personal preferences and offers predictive recommendations.

"For many years now, eCommerce shopping experiences have consisted of a search bar and a long list of item responses. That is about to change. There is a native AI experience coming that is multi-media, personalized and contextual."

Walmart CEO Doug McMillon

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Microsoft has introduced its first in-house image generation model, MAI-Image-1. The model currently ranks ninth among text-to-image systems on LMArena. According to Microsoft AI, MAI-Image-1 was designed to avoid repetitive or overly generic results. The team incorporated feedback from creative industry professionals to fine-tune the model. It performs especially well at producing photorealistic images, capturing details like lighting effects and landscapes, and runs faster than many larger models.

Image: Microsoft

The model is available for testing on LMArena and will soon be integrated into Copilot and Bing Image Creator. Microsoft emphasizes its focus on safe and responsible outputs. MAI-Image-1 expands the company’s own AI lineup, which also includes the speech generation model MAI-Voice-1 and the chatbot MAI-1-preview.

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AI and society
Comment

OpenAI and Microsoft call AGI pointless, then make it the linchpin of billion-dollar deals

AI in practice

Google leans on token metrics, not revenue, adding to bubble talk about AI growth

AI and society

OpenAI restructures under new foundation, Microsoft takes 27 percent stake

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