12-03, 08:00–08:30 (UTC), Talk Track I
Why is the process of transforming research into a “real world” product so full of question marks? We often know where the research journey starts but have uncertainty about how and WHEN it ends.
In this talk, I will share my own experience leading algorithmic teams through the cycle of research into the production of live-streaming AI products. I will also share how to mitigate between agile incremental delivery and giant leaps forward that require longer research. How understanding the minimum viable product (MVP) way of thinking can help not only managers but every developer. Learn to outline MVP for new AI capabilities, and move forward with production in mind, while always raising the quality standards. At the end of this session, you will get the boost you need to take the data-driven experimental mindset to the next level, spiced with methodologies you can adapt to development as well as research.
This talk will cover the pain points in machine learning productization and ways to address them.
Topaz will share insights from her journey leading AI algorithmic groups: How to keep raising your ML quality standards?
From the data-driven aspect of ML through agility development and the minimum-viable-product (MVP) approach to enable it. This talk will cover how understanding the “MVP” way of thinking can help not only managers but every developer.
No previous knowledge expected
Topaz Gilad is an R&D manager specializing in AI, machine learning, and computer vision, leading production-oriented innovative research.
With experience in large companies as well as startups, in various industries, from space imaging and semiconductor microscopy to sports tech, wellness, beauty, and self-care industry, she has developed methodologies to scale up while improving quality, delivery, and teamwork.
Currently VP of AI and Algorithms at Voyage81, an innovation company that excels in computer vision deep learning algorithms in both RGB and hyper-spectral domains. Previously head of AI at Pixellot, a leading AI-automated sports production company.
Topaz is also an advocate for women in tech. When she is not building algorithmic teams, she enjoys painting.