Why Model Ownership Is Critical for Enterprise AI ? Part 6 скачать в хорошем качестве

Why Model Ownership Is Critical for Enterprise AI ? Part 6

As enterprises experiment with large language models, a critical question emerges: who really owns the model — and the intelligence behind it? In this conversation, Medan Gabbay (CEO, Quod Financial) and Ivan from Boltzbit discuss one of the most important issues in enterprise AI adoption: model ownership, data privacy, and customization. While public LLMs such as OpenAI, Gemini, Claude, and others offer powerful capabilities, generic models are not designed for private enterprise workflows. Real competitive advantage comes from training and fine-tuning models on proprietary data — while retaining full control of the model weights and intellectual property. This discussion explores: – Why generic LLMs are not enough for enterprise use cases – The importance of model ownership and IP control – How private data transforms model performance – Why open-source models provide flexibility and independence – How enterprises can swap underlying models without losing customization – The true cost of pre-training and fine-tuning large models The future of AI in financial services is not about chasing the latest benchmark — it’s about building private, customizable intelligence layers aligned with your workflows, data, and regulatory constraints. — About Quod Financial Quod Financial delivers advanced multi-asset trading technology through Unity — a modular architecture layer that connects systems, normalizes data, and enables AI-driven automation across the trade lifecycle. 👉 Learn more: https://www.quodfinancial.com