What is the way from prove of concept to big production solutions for GenAI application? How to make it scalable and make one release by 7 sprints?
AI fundamentals, Programming, Azure fundamentals, AWS fundamentals
We talk about different GenAI Accenture cases in production and preproduction studies, how to implement new technologies and what advantages and disadvantages we can discover during such projects. How often client really know what they want? GenAI "magic" tricks or 99% accuracy? Let's talk about LLM, stable diffusion and similarity search.
Daria Lashkevich has more 15 years experience in computer vision and machine learning programming of applications in such areas as Automotive, Welding systems, Medical systems, Robotics Daria has Master’s degree in Computer science (Artificial Intelligence) with honors , Moscow State Technical University by Bauman. Join Accenture in 2017 Daria start working in Riga Liquid studio as Computer Vision Engineer to develop Innovative PoC and client project as Water color analyzer, Virtual Therapist and Migration chat-bot. From 2021 Daria working as AI Architect in long-term client project in Automotive, Media Entertaiment, Health area to develop GenAI solutions based on LLM, RAG, AI Agents and Computer vision.