Data Makers Fest 2026 Conference Interviews

About this episode

The episode features interviews from Data Makers Fest 2026, discussing the balance between GenAI hype and production realities in AI.

At Data Makers Fest, a recurring theme was the tension between GenAI hype and production reality. Speakers stressed that classical ML, MLOps, evaluation, data quality, and governance remain essential—especially in regulated sectors like fintech and healthcare. Another strong theme was inclusivity: building AI that serves smaller languages, diverse communities, and practitioners beyond the English-centric ecosystem. Ryan Chaves. Head of ML at a Dutch fintech, Ryan focused on the gap between AI demos and production systems. He argued that classical ML remains critical for fraud detection and risk scoring, while GenAI works best as an accelerator on top of existing systems. He also emphasized storytelling, stakeholder communication, and mentorship as core engineering skills. Alp Öktem. Computational linguist and researcher Alp explored the imbalance between AI progress in English and low-resource languages. Through Mozilla Data Collective, he highlighted how open datasets, speech corpora, and synthetic data can expand AI access to underrepresented communities. His broader warning: fluent AI can still fail culturally, linguistically, and ethically. Agnieszka Kamińska. Working in…

People in this episode

Guests: Ryan Chaves, Alp Öktem, Agnieszka Kamińska

Topics covered

• GenAI hype
• classical ML
• MLOps
• data quality
• inclusivity in AI
• low-resource languages
• knowledge graphs

Keywords

• GenAI
• MLOps
• data governance
• fraud detection
• low-resource languages
• AI inclusivity
• knowledge extraction

Mentioned in this episode

Organizations: Dutch fintech, Mozilla Data Collective, pharmaceutical ML engineering

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