Where you need to become an expert? If you are heading towards working as a Manager for ML, AI Technology

By ridhigrg |Email | May 6, 2019 | 6168 Views

So what all skills you exactly need for becoming a product manager at Google, Facebook or any other Big Company. And what all skills are required for it?

If you are planning to become an AI product manager you will be needing some critical skills and here are some: 

1) Identify problems solvable by AI/Spotting automation opportunities.
The AI product manager needs domain expertise and an understanding of supervised learning to identify solvable problems.

Today, 99% of economic value created by AI today is A to B (input-output) AI or in technical terms, Supervised Learning. Examples include image recognition, speech recognition, ad serving, self-driving car, etc.

There are other AI techniques such as unsupervised learning, deep learning, etc. But as a product manager, you should prioritize supervised learning. You can ask yourself these 3 questions.
  • Can we make money mapping inputs to outputs?
  • Is the problem appropriate for supervised learning?
  • Do we have the data we need? See next point

2) Strategic data acquisition
Defensible AI businesses are built on proprietary data that is difficult to replicate. This happens in two phases, bootstrapping and compounding.

In the bootstrap stage, you are building a unique set of training data by aggregating publicly available data and enriching it in some challenging way, running simulations to generate synthetic data, or doing BD deals to gather a set of internal company data. Once you have bootstrapped, you are building a data flywheel' into your products, so that you are capturing totally unique data over time from how your product is used, and that data capture is designed precisely to serve the needs of your models, which are designed to serve the needs of the product functionality, which is designed to meet the needs of the customer. This data value chain ensures that the customer's motivation is aligned with your motivation to compound the value of your proprietary dataset.

Programmers usually write code to manipulate data based requirements from customers or analysts. In supervised machine learning, the programmers teach algorithms on how to manipulate data by giving them thousands of examples.

The success or failure of your entire AI product - depends on your ability to get the best training data in your industry.

3) Designing Kaggle competitions.
Kaggle should be on the tips for AI product manager and he should know everything in relation to the competition. For example, the Instacart Market Basket Analysis.

These competitions look a lot like AI specifications. For completing this she must know: 
  • AI should be on tips for generating new ideas with the business units.
  • Business unit needs should be clear to you. 
  • For designing the data of training or managing a data scientist you need to have statistics skills.
  • Identify new data sources and develop the business case for buying or building them.

Lastly, don't forget you need to have these top product manager skills given below to become one of the top AI Product Manager.
  • Strategic thinking
  • Communication
  • Collaboration
  • Technicals
  • Details and quality
  • User science & Empathy and Management.

Source: HOB