Artificial Intelligence Machine Learning Data Science

The GenAI Revolution Reaches RecSys

When we talk about the generative AI revolution, the conversation usually stays close to chatbots, image generation, and code assistants. But the same architectures that powered that wave (transformers, autoregressive modeling, scaling laws) are quietly reshaping fields most people don't associate with GenAI at all. Recommender systems are one of the most interesting examples. Meta, Netflix, Google, Spotify and others are replacing decades-old recsys pipelines with transformer-based foundation models, and the results are hard to ignore. This talk is a practical tour of that shift from a Python engineer's seat.

Speaker

Carlos Andrés Osorio Alcalde

Sr Machine Learning Engineer @ Factored

Mathematician (Summa Cum Laude) and MSc in mathematics. Machine Learning Engineer and Data Scientist with 6+ years of experience delivering Data Science and AI solutions across industries like retail, finance, education, and social enterprises. Skilled in developing and deploying advanced models for tasks such as recommendation systems, customer clustering, churn prediction, transactional risk, LLM-powered chatbots, Gen-AI applications and search engines using tools like Python, PyTorch, PySpark, FastAPI, PydanticAI, Qdrant, LangChain and cloud platforms (AWS, GCP and Azure). Passionate about leveraging math and AI to drive meaningful change.

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