This post explores how DeepEval helps systematically assess the effectiveness of both retrieval and generation components, ensuring more reliable machine-generated insights.
Research on artificial intelligence (AI) began with the desire to understand whether and to what extent computers can solve problems in a way similar to the human mind. Many of the early works related to AI focused on creating mathematical models and algorithms capable of performing tasks requiring intelligence, such…
The development of broadly understood artificial intelligence is gaining momentum. This is evidenced by the widespread interest in this topic and an increasing number of media articles and publications. What draws particular attention are the data illustrating how much financial resources are allocated to investments in semiconductor technologies, i.e.,…
GitHub anticipates that in the coming years, 80% of the world’s code will be generated by AI [1]. Although it is difficult to find exact information on the number of sold GitHub Copilot licenses, it is undeniable that we are observing a change in the way organizations and programmers themselves…
Optimization of Data Collection Process Thanks to AI Algorithms In an era of progress and numerous achievements in natural language processing, we see increasing possibilities in the analysis and inference based on data collected in unstructured textual archives and documents. Therefore, streamlining business operations and implementing NLP (Natural Language…
GPT – A DIFFERENT POINT OF VIEW In the previous post, we looked at the possibilities of the GPT model in terms of supporting the work of a programmer. But that’s not the only thing this technology can do. GPT is a language model that utilizes a deep learning technique…
