Applying Machine Learning into Your Product


Bastiane Huang

Bastiane Huang has extensive experience in product management and business development. She currently works at Osaro, a San Francisco based startup that builds machine learning software for robotic vision and control and Amazon's Alexa group. She also worked with Harvard’s Future of Work Initiative and writes about AI-enabled robotics, machine learning, and product management for Robotics Business Review and Harvard Business Review. 

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Applying Machine Learning into Your Product

When it Will (and Won’t) Benefit 
the Customer

In recent years, we’ve seen the rise of Artificial Intelligence incorporated into products across various industries. The adoption of Machine Learning, an application of Artificial Intelligence, has enabled Product Managers to create self-learned autonomous products that don’t rely on the manual work of humans alone. But will this work for every product? Learn the fundamentals of Machine Learning and the different ways it can be applied to both B2B and B2C products. Then, determine if it’s the right choice to make your product successful.


When Machine Learning can benefit a product and when it's not the right choice. 

The different ways Machine Learning can be applied to B2B and B2C products. 

The fundamentals of how Machine Learning works.


Machine Learning (ML) is a branch of Artificial Intelligence computer science that has seen significant gains in the last ten years. Products like Alexa, Netflix viewing suggestions, and facial recognition on smartphones were enabled using Machine Learning. ML enables a move away from having to manually program the machine to self-learned autonomy: machines make predictions and improve insights based on patterns they identify in data without humans explicitly telling them what to do. That’s why ML is particularly useful for challenging problems that are difficult for people to explain to machines. 

The adoption of ML has been rapidly advancing across various business sectors. According to a recent McKinsey study, nearly half of the companies surveyed have incorporated one or more artificial intelligence capabilities in their process and another 30% are piloting AI projects. It’s not hard to see why ML is expected to be even more transformative than mobile technology. However, the transition to ML could also be more than 10 times harder than the transition to mobile. 

In this webinar, our guest expert Bastiane Huang, Product at Osaro, will explain the promises and challenges of incorporating ML technologies into your products. She will explain the fundamentals of ML, products that can benefit from it, and share a few best practices from her experience as a Product Manager managing machine learning products.


Roger Snyder is the Vice President of Marketing and a Principal Consultant and Trainer at 280 Group. He has worked in the field of Product Management for over 20 years, with experience in startups, growth companies, and various technology sectors. He specializes in improving product strategy development, implementing full product lifecycle processes, and roadmap development and evolution.  From his experience at startups through his time at Microsoft, Roger has been involved in many facets of the mobile industry, from infrastructure products that pioneered accessing the Internet from a mobile phone, to complete smartphones, to mobile cloud services and applications across iOS and Android.  

Roger Snyder
280 Group 

VP of Marketing

Bastiane Huang | Osaro

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When it Will (and Won’t) Benefit 
the Customer