Prepare data from un-structured data sources to train your model for AI: Today data is the most important to train your AI models. More the data you train your model better the results you get. So, data is crucial for AI models. Huge data exists in the world but how do we prepare the data...
AI Model Comparison: IBM Granite, Meta LLaMA, and Mistral This blog provides a comparative overview of three prominent AI models: IBM Granite, Meta LLaMA , and Mistral. It highlights their key characteristics, architectural differences, training methodologies, strengths, and weaknesses,...
Applications based on LLMs are everywhere today. But in companies, many projects still struggle to go beyond the prototype stage. The reality of 2025 is that success in production no longer depends solely on the quality of the model, but on the ability to manage an ecosystem of intelligent...
Artificial intelligence in business analytics is not new. In fact, IDC’s North American Business Intelligence/Analytics Survey (August 2024) highlighted that nearly 80% of respondents were already using or integrating generative AI capabilities into their BI/analytics solutions. The aim? To make...
English version below: Während sich Künstliche Intelligenz von prädiktiven Modellen über generative Fähigkeiten bis hin zu intelligenten Assistenten weiterentwickelt, steht nun die nächste Evolutionsstufe bevor: Agentic AI – autonome Systeme, die nicht nur verstehen und antworten, sondern...
Authored By: @SHAILESH JAMLOKI and @HS Manoj Kumar Welcome to the final part of our Diff-Intel blog series! We've explored the motivation behind building an AI code reviewer in the Part1 and deep-dive into its hybrid architecture in the Part2 . Now it's time...