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

Oct 31, 2025Oct 31, 2025

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

AI in practice

Aug 7, 2025Aug 7, 2025

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

AI in practice

Aug 5, 2025Aug 5, 2025

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

AI in practice

Jul 13, 2023Jul 13, 2023

Meta's new AI model aims to break the dominance of OpenAI and GPT-4

AI in practice

Jul 12, 2023Jul 12, 2023

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AI tool RFdiffusion, a neural network developed by the University of Washington, can rapidly design custom proteins with potential applications in vaccines, therapeutics, and biomaterials. The tool borrows principles from neural networks that generate realistic images, such as Stable Diffusion, DALL-E, or Midjourney, creating complex and diverse protein shapes when it "denoises" a random assortment of amino acids.

Although the designs show promise in early experimental tests, researchers are still working to improve the AI's ability to design proteins with more complex active sites and specific reactions. RFdiffusion is available on GitHub.

Nature

AI in practice

Jul 12, 2023

Adobe Firefly offers new features and supports over 100 languages

AI in practice

Jul 12, 2023Jul 15, 2023

Elon Musk's new AI company xAI - what we know so far

AI in practice

Jul 11, 2023Jul 11, 2023

ChatGPT alternative: OpenAI competitor Anthropic's "Claude 2" chatbot is live

AI in practice

Jul 11, 2023Jul 11, 2023

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Researchers have released a preview of LongLLaMA, a large language model capable of handling long contexts up to 256.000 tokens or more. Built on the open-source OpenLLaMA and fine-tuned using the Focused Transformer (FoT) method, it permits some attention layers to access a memory cache of key-value pairs to extend their context length.

According to the researchers, the model retains performance on tasks that don't require long contexts, and can be used as a drop-in replacement for shorter context LLaMA implementations. The team has released their smaller 3B variant under the Apache 2.0 license, with inference code supporting longer contexts on Hugging Face. More information and examples of LongLLaMA can be found on their GitHub repository.

GitHub

AI in practice

Jul 10, 2023

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Axel Springer has formed a global Generative AI team to consolidate efforts and drive innovation in Generative AI.

The initiative, led by Niddal Salah-Eldin and Samir Fadlallah, will support Axel Springer and its brands in harnessing and leveraging Generative AI in their processes and products. The team will focus on product and market research, in-depth analysis of potential M&A opportunities and partnerships, prototyping disruptive scenarios and developing strategic partnerships with AI-driven tech companies and startups. The plans were previously announced in an internal podcast and then leaked.

Axel Springer

AI in practice

Jul 10, 2023Jul 10, 2023

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GPT Researcher is an AI-based autonomous agent for conducting comprehensive online research on a variety of tasks. The tool, inspired by AutoGPT and the "Plan-and-Solve" prompting, seeks to improve on speed and determinism issues found in current language models, "offering a more stable performance and increased speed through parallelized agent work, as opposed to synchronous operations."

According to the team, GPT Researcher facilitates research by generating relevant research questions, aggregating data from over 20 web sources, and leveraging both GPT3.5-turbo-16k and GPT-4 to create comprehensive research reports. The project aims to address the time-consuming nature of manual research tasks and the biases that result from limited resource usage in alternative approaches such as ChatGPT + WebPlugin. It includes a web interface and provides an export function for research reports in various formats.