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’s text embedding model "gemini-embedding-001" is now generally available via the Gemini API and Vertex AI. It costs $0.15 per one million input tokens.
The model supports over 100 languages, handles inputs of up to 2048 tokens, and uses Matryoshka Representation Learning (MRL) to reduce output size, which helps cut memory use and computing costs. Google says the model performs better than its earlier models and external alternatives in several tasks. Since its experimental launch in March, Google states the model has held a top position on the MTEB Multilingual Leaderboard.
Mistral AI and All Hands AI have introduced two new models designed for AI-powered programming agents: Devstral Small 1.1 and Devstral Medium. Devstral Small 1.1 2507 is open source and can run locally on an RTX 4090 or a Mac with 32 GB of RAM. It achieved a 53.6% score on the SWE-Bench Verified benchmark and supports XML along with other formats.
Devstral Medium scored 61.6% on the same benchmark. According to Mistral, it offers more power and a lower price than Gemini 2.5 Pro and GPT-4.1. The model is available via API, supports fine-tuning, and will soon be integrated into Mistral Code.
