Latest blog posts by Krzysztof Kacprzak

Discover how customizing Large Language Models (LLMs) on proprietary data can enhance business operations, improve efficiency, and provide a competitive edge.

Dive into a detailed comparison of Cohere and GPT-4, exploring their architectures, capabilities, and real-world applications. Learn how these AI language models differ in their approach to natural language processing, their impact on various industries, and the ethical considerations surrounding their deployment. Essential reading for understanding the current state and future direction of AI language models.

Explore ChatGPT's impact on software engineering, from code generation to workflow optimization, highlighting strengths, challenges, and future possibilities.

Deploying LLMs in business requires careful planning, prototyping, testing, and ongoing optimisation. This article outlines a step-by-step approach to scale LLM solutions from concept to production, ensuring operational excellence and innovation.

Explore the key differences between RoBERTa and GPT-4, two leading NLP models. RoBERTa is optimised for deep contextual understanding, making it ideal for analysis and classification tasks, while GPT-4 excels in generating coherent, human-like text for creative and conversational applications. This article explains their architectures, training methods, and best use cases, helping you choose the right model for your NLP needs.

Explore the evolution from BERT to RoBERTa, highlighting their training differences, performance, applications, and advancements in NLP capabilities.

Explore the pros and cons of open and closed source LLMs, comparing flexibility, customization, resources, and transparency for AI project implementation.

LLMs present new privacy and data security risks, from data leakage to bias and explainability challenges. This article explains these issues and recommends advanced techniques—like tokenization, differential privacy, and secure handling—to protect sensitive information.