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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The SlashNext State of Phishing Report 2023 has revealed a 1265% increase in malicious phishing emails since Q4 2022, "signaling a new era of cybercrime fueled by generative AI." The SlashNext Threat Labs report links this increase to the growing use of tools like ChatGPT in crafting sophisticated phishing messages. The study also found an average of 31,000 phishing attacks per day, with 68% identified as text-based Business Email Compromise (BEC). The analysis looked at threads delivered through email, mobile, and browser channels for the 12-month period from Q4 2022 to Q3 2023.

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AI in practice
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Meta's Llama 2 Model Guide provides detailed instructions on how to set up and use the AI model. The guide covers prerequisites, obtaining the models, hosting options, fine-tuning, prompting, inferencing, and validation. It also provides information on community support and resources. Hosting options include Amazon Web Services, Cloudflare, Google Cloud Platform, Hugging Face, Kaggle, Microsoft Azure & Windows, and ONNX for Windows. The guide also provides detailed instructions on how to integrate the model with Code Llama and LangChain. The guide is available on Meta's website.

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AI in practice
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Google is expanding its Vulnerability Rewards Program (VRP) to include generative AI-specific attack scenarios to incentivize AI security research. The company is also expanding its open-source security work to make AI supply chain security information universally discoverable and verifiable. As part of the VRP expansion, Google is revising its bug categorization and reporting policies to address new concerns raised by generative AI. In addition, Google is launching the Secure AI Framework (SAIF) to help the industry build trustworthy applications and is working with the Open Source Security Foundation to protect the integrity of AI supply chains.

Generative AI raises new and different concerns than traditional digital security, such as the potential for unfair bias, model manipulation or misinterpretations of data (hallucinations).

Google

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AI research

Gemini 3 Pro tops new AI reliability benchmark, but hallucination rates remain high

AI research

Researchers push "Context Engineering 2.0" as the road to lifelong AI memory

AI and society

German court deepens the split on AI and copyright with its latest ruling

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