What’s the difference between training an LLM from scratch and fine-tuning one that already exists?
In this episode, we unpack the full story: the data, the GPUs, the cost, the workflows, and the practical reasons why most companies choose fine-tuning over full training. We also explain how fine-tuned models can adapt to new styles, languages, and business needs.

A simple and direct conversation about how modern AI models are actually built and shaped.

Data-driven transformation isn’t just about analytics dashboards. It’s about mindset, culture, clarity, and the ability to evolve with technology.

In this episode, Andredi Mauro and Michele Pacifico dive into the insights behind their book The Financial Times Guide to Data-Driven Transformation. We explore how executives can rethink business models with data, the role of AI and generative AI in shaping the future, and why clarity of goals matters more than ever.

We also discuss the common pitfalls companies face, why FOMO leads to bad decisions, and how data professionals can act as genuine change agents in their organizations.

If you're working in data, leading digital transformation, or preparing for the AI-driven future, you’ll find tons of practical wisdom here.

What you’ll learn
• What true data-driven transformation looks like
• Why clarity beats hype in data initiatives
• The changing role of data professionals
• How generative AI is reshaping analytics and strategy
• How to build governance and culture that scale
• Why the journey is iterative, not a one-time project

Key quotes
"The book can be your compass."
"Value clarity is your north star."
"Stay consistent in your journey."

AI isn’t just a technology play. It is a readiness game.In this episode, Vijay Krishnam breaks down what it really takes for enterprises to succeed with AI… and why so many still struggle to turn AI investments into business value. From regulated industries like banking and healthcare to fast-moving tech environments, we explore the five pillars of AI readiness: infrastructure, data quality, talent, governance, and culture.We talk about real-world AI challenges, ethical pressures, data governance realities, KPIs that matter, and why cultural alignment is often the deciding factor between flashy POCs and actual impact.If your company is exploring AI, scaling it, or you want to understand the truth behind enterprise AI success, this episode is a must watch.What you’ll learn• What AI readiness really means• Why culture and governance matter more than models• How regulated industries approach AI adoption• Where companies go wrong with AI investments• A practical mindset for long-term AI successKey quotes"Cultural alignment is very important.""Garbage in, garbage out is still true for AI.""Start with a business problem, not technology."Connect🎧 Subscribe to the podcast📰 Join the newsletter on Substack💬 Tell us your thoughts in the comments